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Journal of Management & Development Economics April 2015

Vol. 4

Issue No. 1

ISSN 2392-4551

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(Tribhuvan University Affiliate) Mid- Baneshwor, Kathmandu, Nepal Tel: 977-1-4488312 | 4475254 | Fax: 977-1-4472083 Email: [email protected] | URL: www.globalcollege.edu.np


Vol. 4

Issue No. 1

Chief Editor Prof. Radhe S. Pradhan Managing Editor Dr. Khagendra P. Ojha Executive Editor Mr. Dev Raj Paneru Editors Mr. Achyut Gyawali Mr. Damaru Poudel Mr. Santosh Poudel Advisory Board Prof. Dr. Prem Raj Pant Prof. Dr. Puskar Bajracharya Dr. Tilak Rawal Prof. Dr. Ajaya Bikram Sthapit Dr. Manish Thapa Dr. Nar Bahadur Bista Peer Reviewed by Prof. Dr. Prem. R. Pant Prof. Dr. Radheshyam Pradhan Mr. Dev Raj Paneru Mr. Santosh Poudel Publishing Team Mr. Nabraj Bhandari Mr. Tulashi Ram Shrestha Mr. Baburam Subedi Design & Layout Dev Nandan Chaudhary

ISSN 2392-4551


Vol. 4

Issue No. 1

ISSN 2392-4551

Editorial Journal of management and development economics is purely an official publication of Global College of Management, Tribhuvan University Affiliate, located at Mid Baenshwor Kathmandu. The journal is published annually as a regular research publication in April or May. It is not -for profit- publication of the college aimed to promote research and learning activities among the college faculties, researchers, university professors and graduate and undergraduate students and personnel in administrative positions involved jointly or individually in research ventures; academic or professional, though academic researchers are prioritized. As obvious from the title of the journal, mainly the research based; primary and secondary data based articles; qualitative or quantitative but exclusively from the field of management and economics are accepted for publication. The journal is the institutional property of Global College of Management and hence, publishing of the journal is solely in the responsibility of the research committee working as the steering committee for the College's Quality Assurance and Accreditation (QAA) department formed in response to the college's commitment as an applicant institution to the QAA indictors assigned by the University Grants Commission Nepal (The college has entered into the formal process for QAA from UGC, Nepal starting from 2013). The articles published in this journal in all its issues are from economics, finance, and general management areas and some of the articles are secondary data based whereas others primary. The articles were assigned for peer review to the professors and practitioners in their respective field, amendments were recommended followed by editing corrections ensured before they were processed in this journal as far as possible. However, the editorial team does not bear responsibility for any incongruences in contents and patterns presented in the articles as they are purely the products of their authors and hence, the authors are subject to ethical interrogations in the circumstances that are marked to violate ethical parameters applicable in the field of academics and research. The articles have been arranged in alphabetical order of the authors' name. Concisely the purpose of each article has been attached briefed here: The first article by Achyut Gyanwali titled Influence of Corporate Income Tax on DebtFinancing: Evidence from Nepalese Manufacturing Companies aims at assessing the relationship between corporate income tax and debt-equity mix, and estimate the influence of corporate income tax on debt financing of the manufacturing companies of Nepal. The purpose of the article titled An Analysis of Electricity Consumption in Industrial Sector of Nepal by Bhola Nath Ghimire is to derive and estimate a consumption function for Nepalese indus trial electricity use, and to investigate changes in consumption pattern over the time period


Vol. 4

Issue No. 1

ISSN 2392-4551

1980-1912. Does development of commercial banks spur economic growth? By Dr. Dipak Bahadur Bhandari and Keshab Acharya examines the degree of relationship and direction of causality between the development of commercial banks and economic growth of Nepal. The article titled Teacher Management and Development in Higher Secondary Education: A Case of Higher Secondary Education Board of Nepal by Dev Raj Paneru qualitatively examines human resource management and development practices undertaken to manage and develop teachers serving in the schools under HSEB, Nepal. Globalization: A Trozan Horse: Globalization is a buzzword that has no precise definition by Prof. Dr. Kanhaiya Ram Bhakta Mathema examines how Globalization brings in interconnectedness in economic, cultural, and technological domains via expansion in unrestricted trade. An Analysis of Foreign Employment and Inflow of Remittance in Nepal by Mr. Mani Ratna Lamsal examines the migration and inflow of remittance in Nepal. It deals with literature review on remittance, the inflow of remittance from various countries, the contribution of remittance to GDP, consumption and expenditure pattern. Non-financial Performance Measurement Practices in Nepalese Commercial Banks, by Naba Raj Adhikari, examines the non-financial performance measurement practices in Nepalese commercial banks. Dividend Policy, Performance, and the Sock Price in Nepal by Dr. Nabaraj Adhikari, aims at investigating the dividend policy, performance, and the stock price in the pre-emerging capital market of Nepal employing descriptive cum analytical research. The Cross-Section of Expected Stock Returns in Nepal by Prof. Dr. Radhe S. Pradhan aims at examining the ability of beta and other company specific factors such as firm size, book to market ratio, sales to price ratio, dividend yield and earning price ratio to explain cross section of stock returns in Nepal and finally, An Empirical Study on Stock Market, Bank and Economic Growth by Santosh Poudel, examines the relation between economic growth with financial growth. The editorial team and research committee of the college welcomes all the academic and research endeavors to the standard applicable in research and studies in higher education.

Dev Raj Paneru Executive Editor Journal of Management and Development Economics A peer reviewed journal of Global College of Management Mid- Baneshwor Kathmandu, Nepal.


Vol. 4

Issue No. 1

ISSN 2392-4551

Notes Articles are subject to editorial review by referees from the community of management and economics experts. Comments or notes regarding articles are welcome and will be considered for publication to the extent possible. The opinions and the interpretations expressed in the articles are the personal opinions of the authors and reviewers and do not necessarily reflect the views of the publisher and editors, or of any institution with the information with which the author may be associated. The editorial board does not guarantee the accuracy of the data and the information included in the articles and accepts no responsibility, whatsoever, for any consequences of their use.

Subscription information Journal of Management and Development Economics (JMDE) is a journal published annually by Global College of Management. The publication is for the benefit of the management experts, economists, planners, professionals as well as those interested in the field of management and development. Copies of the journal may be subscribed/purchased from Global College of Management. The subscription rates are as follows: Individuals Per copy

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Journal of Management & Development Economics Vol. 4

April 2015

Issue No. 1

ISSN 2392-4551

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Vol. 4

Issue No. 1

ISSN 2392-4551

Contents INFLUENCE OF CORPORATE INCOME TAX ON DEBT FINANCING: EVIDENCE FROM NEPALESE MANUFACTURING COMPANIES .................

1-10

Achyut Gyawali (PhD Scholar)

AN ANALYSIS OF ELECTRICITY CONSUMPTION IN INDUSTRIAL SECTOR OF NEPAL ..............................................................................................

11-18

Bhola Nath Ghimire

TEACHER MANAGEMENT AND DEVELOPMENT IN HIGHER SECONDARY EDUCATION ..................................................................................

19-30

A Case of Higher Secondary Education Board of Nepal Dev Raj Paneru

DOES DEVELOPMENT OF COMMERCIAL BANKS SPUR ECONOMIC GROWTH .................................................................................................................

31-52

Dr. Dipak Bahadur Bhandari & Keshab Acharya

GLOBALIZATION: A TROZAN HORSE "GLOBALIZATION IS A BUZZWORD THAT HAS NO PRECISE DEFINITION." ............................................................. 53-60 Dr. Kanhaiya Ram Bhakta Mathema

AN ANALYSIS OF EMPLOYMENT AND INFLOW OF REMITTANCE IN NEPAL .................................................................................................................

61-70

Mani Ratna Lamsal

NON-FINANCIAL PERFORMANCE MEASUREMENT PRACTICES IN NEPALESE COMMERCIAL BANKS ................................................................

71-76

Naba Raj Adhikari, M. Phil

DIVIDEND POLICY PERFORMANCE, AND THE STOCK PRICE IN NEPAL .... 77-90 Nabaraj Adhikari, PhD

THE CROSS-SECTION OF EXPECTED STOCK RETURNS IN NEPAL .............

91-99

Prof. Dr. Radhe S. Pradhan

AN EMPIRICAL STUDY ON STOCK MARKET, BANK AND ECONOMIC GROWTH ................................................................................................................. 100-112 Mr. Santosh Poudel

of] k]h vfnL /fVg]

Influence of corporate income tax on debt-financing: Evidence from Nepalese manufacturing companies

1

INFLUENCE OF CORPORATE INCOME TAX ON DEBT-FINANCING: EVIDENCE FROM NEPALESE MANUFACTURING COMPANIES ...? Achyut Gyawali (PhD Scholar) Abstract The main purpose of this paper is to assess the relationship between corporate income tax and debt-equity mix and estimate the influence of corporate income tax on debt financing of the manufacturing companies of Nepal. Debt-equity mix has been taken as the dependent variable to represent the debt financing and effective tax rate has been used as independent variable to represent the corporate income tax. The secondary data have been utilized to estimate the relationship between the variables and simple regression equation as used in Alessi (1965) study has been employed to infer the relationship. The results of the analysis suggest that debt financing is influenced by corporate income tax positively, but such influence is not much significant in shaping specific mix of debt and equity capital of the manufacturing companies. However, the nature of influence is different across the profitability status of the companies. Keyword: Corporate tax, Manufacturing companies, Debt-equity mix, profitability, Income tax

Background A firm seeking to maximize welfare of its shareholders should take tax factors into elucidation while involving in the process of making financing decisions. It is because; the imposition of income tax on corporate business profit reduces the residual amount of income available for distribution of returns as dividends to the shareholders (Altman and Subrahmanyam, 1985: 181). For corporate income tax purpose, the expenses made on the payment of interest to the bondholders of the company are allowed as a deduction, but the expenses made on disbursement of dividends to the shareholders are not allowed as a deduction. Income tax provision regarding with eligibility of interest deduction from taxable income is favorable for the firms as it equally adds benefit to generate valuable tax shield. The debt financing significantly helps increase firm's cash-flow ancillary in the course of generating operation funds available for return distribution to the shareholders through its tax shields (Pringle and Harris, 1987: 495). Hence, a resonance proportion of debt in financing mix also increases the market value of the manufacturing firms (Ross, et al., 2013:368). As a result, interest-bearing debts are attractive to the manufacturing firms for financing their investments (King, 2012: 158). Therefore, the Mr. Gyawali is the Lecturer of Management at Tribhuvan University. He is the PhD Scholar at T.U.

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Achyut Gyawali

difference in tax treatment of interest and dividend affect financing choice between debt and equity (Chua, 1995). Corporate income tax is potentially an important consideration in a firm's financing decision (Fama and French, 1998: 819). It has an effect on the ways of project financing. If it is financed with the debt capital, tax relief is available on the interest payment (Hutchinson, et al., 1994:296). Therefore, financial managers remain constantly aware of tax consideration in their day-to-day decisions and spend a considerable part of their managerial effort to reduce the incidence of income tax through an appropriate financing mix. Thus, corporate income tax is an influential factor in the choice of sources to raise required funds. Funds to finance an investment proposal can be obtained either by borrowing from banks, by selling marketable securities, by selling non-business assets or parts of its business assets, by issuing additional securities or by utilizing the savings generated from business operations. Hence, an investment proposal is either financed by a composite capital mix or by any one of the sources of funds. Composite capital mix depends on various factors and no uniform standard can be laid down for all investments of a corporation (Saynyal, 1971: 817). When the corporation uses debt, it must pay interest, on the other hand when it uses equity; it is expected to distribute dividends to the equity investors. In case the debt is used, the interest expenses paid by a corporation on it are allowed to deduct from operating income to obtain its taxable income. But the dividends paid to equity holders are not deductible. For this reason, corporate tax system favors debt financing over equity financing. However, it is not always possible to finance an investment exclusively with debt capital, and the risk of doing so setbacks the benefits of the higher expected income (Brigham, et al., 1999: 56-57). Thus, the problem of financial manager is to choose proper level of debt to arrive at appropriate financing mix that results into tax benefits. The major issue in corporate financing is to determine the appropriate mix between debt and equity. Extensive controversial views have come up on this issue. Regardless of the controversial views, the tax law has given debt financing a definite cost advantage over preferred stock and common stock (Martin, et. al. 1991: 48). Taxes tend to place a premium on one form of financing as compared to the other. For instance, income tax law allows deduction of all interests paid before arriving at taxable income. This deductible interest makes debt capital cheaper for corporations to use it for financing the investments (Keown, et. al., and 2001: 425). Thus, the financial managers need to know how taxes influence financing decision of the firms. Due to the attractiveness of debt, there would be a tendency for additional investment to be debt financed (Arditti and Pinkerton, 1978: 65). To the contrary, Fama and Miller (1972), Jensen and Meckling (1976) suggested that debt is not much attractive to maximize the combined wealth of security holders because it has a tendency to make risky investments. Similarly, Myers (1977) suggested that use of debt in financing mix causes firms to make less investment of funds because the returns are to be shared with debt holders. In Nepalese corporate income tax system also the interest paid on debt capital is a deductible expense whereas dividend paid for equity capital is not deductible for income tax purpose. It means, interest paid on debt reduces the amount of tax to be paid to the government. In


3

contrast, the dividend is not the deductible expense and it does not save corporate tax. The corporate taxpayers using equity as the source of capital should pay more tax than those using debt as the source of capital. Because of this provision, it can be stated that Nepalese corporate tax system provides favoritism to debt capital over the equity capital of the companies, which is reflected in the process of financing decision. Because of such discrimination between the debt and equity capitals, there is a scope of favoring the debt financing by the manufacturing companies in the context of Nepal (Kandel, 2009:165). A company may reduce its tax liability substantially if it finances its capital requirement through loans due to the deductibility of interest that results into lower tax burden. This is the reason why debt financing is more attractive than equity financing and Nepalese companies may be thinly capitalized in order to reduce income tax liability (Khadka, 2001: 46). In this context, the influence of corporate income tax on debt financing is emerging as an important aspect to investigate empirically. In Nepalese context, however, the influence of corporate income taxes on debt financing of manufacturing firms is a matter of study. There is absence of adequate studies especially on the relationship between corporate income taxes and debt financing of Nepalese manufacturing companies. Most of the Nepalese studies, in this regard, concentrate macro level analysis, and administrative aspect of the income taxes. It is therefore difficult to generalize specific Nepalese case by applying the findings of international studies. In other words, the applicability of the findings of previous international studies in the area of corporate income taxes and their influence to debt financing of Nepalese companies remains questionable. Thus, this study has dealt with the following issues: 1. 2. 3.

Does corporate income tax influence debt-equity mix of manufacturing listed companies? What kind of relationship does exist between corporate income tax and debt-equity mix of manufacturing companies? Is there any difference in the nature of relationship between corporate income tax and debt-equity mix across profit-making and loss-making companies?

Objectives of the study The purpose of this paper is to assess the relationship between corporate income tax and debtequity mix and estimate the influence of corporate income tax on debt financing of the manufacturing companies of Nepal. It also analyses on relationship does exist between corporate income tax and debt-equity mix of manufacturing companies and the nature of relationship between corporate income tax and debt-equity mix across profit-making and lossmaking companies.

Methodology In this study an attempt has been made to assess the relationship between corporate income tax and debt-financing of manufacturing companies which are enlisted in Nepal Security Exchange Limited. Altogether eight companies were selected by considering reported profit and loss. The manufacturing companies which have reported operating loss in any year out of the last five years (2006/07 to 2011/12) have been taken as loss-making companies. And

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Achyut Gyawali

obviously, those companies which have reported profit for all last five years of study period have been taken as profit-making companies. In this study only secondary data have been utilized for analysis. The financial accounting data for the period of ten years (2001/02 to 2011/12) were collected from the annual and periodic publications of Nepal Stock Exchange Limited (NEPSE), and Securities Board, Nepal (SEBO/N). The publications of NEPSE like: Financial Statements of Listed Companies, Trading Report, and Monthly Bulletin were utilized as data sources. Similarly, the publications of SEBO/N like: Securities Board Nepal: Annual Report, Securities Market Review, and Securities Board Nepal: Journal, were essentially taken as the sources for secondary data. The data that were collected in these ways have been analyzed with regression equations for each group of profit-making and loss-making companies and for total sample. Alessi (1965) incorporated corporate income tax rate as a single independent variable to investigate the effect of corporate income tax on debt-equity mix. In that study, he concluded that the corporate income tax rate should be considered as a major independent variable in any model intended to explain variations in debt-equity mix. He considered the effect of other non-tax variables on debt-equity mix to be somewhat less critical and confined to a simple linear equation having the tax rate as the only independent variable. Rao and Rao (1975) employed three measures of dependent variable debt-equity mix. Spencer (1969) argued that in an unconstrained reduced form equation the variables included are important only in their ability to represent a spectrum of variables which will remove the nontax influences while isolating the tax influence. In another study, Wang (1991) employed three alternative measures of explanatory variable effective tax rate, computed as: the ratio of tax expenses to gross profit, the ratio of tax expenses to pre-tax profit and the ratio of tax expenses to earning before interest and tax, in investigating the relationship between firm size and effective tax rate. Myers and Brealey (2000) pointed out that the debt equity ratio for corporations as a whole depends on the corporate tax rate. If corporate tax rate is increased, migration starts again, leading to a higher debt to equity ratio for companies as a whole. For better result, dependent as well as explanatory variables can be used alternatively to estimate the relationship between debt-equity mix and corporate income tax. Thus, in this study different measures of debt-equity mix such as debt to networth ratio, debt to total assets ratio, and total debt to total assets ratio have been employed as dependent variables. In the same way, two measures of corporate income tax rates like: statutory corporate tax rate and effective tax rate have been employed as explanatory variables alternatively. In the present study, the following equation has been taken as base to specify the equations showing linear relationship between debt-equity mix (measure of debt financing) and corporate income tax rates. Yt = a0 + a1 Zt-1 + u. …. … … … … (1) Y = measures of debt-equity mix, Z = effective tax rate, u = error term, a = parameter to be estimated, t = current fiscal year under consideration (Rao and Rao, 1975: 11). Previous empirical studies have suggested that dependent as well as explanatory variables could be used alternatively to estimate the relationship between debt-equity mix and corporate


5

income tax rates (Rao and Rao, 1975:15). Thus, in this study, different measures of debtequity mix such as debt to networth ratio; debt to total assets ratio, and total debt to total assets ratio were employed as dependent variables. Therefore, equation (1) has been adjusted with alternative measures of dependent variable (debt-equity mix) and the following specified linear regression equations were employed to estimate the relationship between debt-equity mix and effective tax rate in the present study: (D/NW)i, t = a0 + a1 Zi, t-1 + ui. …. …. (2) (D/TA)i, t = a0 + a1 Zi, t-1 + ui. …. …. . (3) (TD/TA)i, t = a0 + a1 Zi, t-1 + ui. …. …. (4) D = long term and short term borrowings, NW = net worth, TA = total assets, TD = total debt, Z = effective corporate tax rate, t = current fiscal year under consideration; a0, a1 = parameters to be estimated, i = states of nature of the sample companies like: big, medium, small, profit-making, loss-making, and total sample; u = error term.

Debt-Equity Mix Debt-equity mix is the financing mix. It is the proportion of debt and equity capitals used to finance investments. The optimal debt-equity mix of a company normally depends on the nature of the business. There are different motives for borrowing by the firms. Among them, capturing the tax benefits of deductibility of interest is the one (Pringle and Harris, 1987: 493, 506). In this context it is to be noted that the empirical results are sensitive to the ways of measurement of variables. The usefulness of a model, hence, has to be tested with possible alternative measures of the variables. Thus, the ratio of debt to net worth, the ratio of debt to total assets, the ratio of total debt to total assets etc. could be the alternative measures to test the debt-equity mix (Rao and Rao, 1975:15). In the present study, debt-equity mix has been taken as the measure of debt financing. Three alternative measures of debt-equity mix were employed to examine the relationship between debt financing and corporate taxes. These measures were: debt to networth ratio, debt to total assets ratio, and total debt to total assets ratio. Further, these measures of debt-equity mix were computed by applying following formulas: Long term borrowings + Short term borrowings D/NW = --------------------------------------------------------------- … … (5) Total assets - Total liabilities

D/TA =

Long term borrowings + Short term borrowings -------------------------------------------------------------- … … (6) Total assets

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Achyut Gyawali Long term liabilities + Current liabilities TD/TA = -------------------------------------------------------------- … … (7) Total assets

Total assets = current assets, and fixed assets. Current assets = cash and bank balance, sundry debtors, inventory and misc.current assets. Fixed assets = plant and machinery, land and buildings, vehicles, furniture and fixture, office equipment and other fixed assets. Total liabilities = long term liabilities, and current liabilities. Long term liabilities = long term loans, and miscellaneous deferred liabilities. Current liabilities = short term loans and advances, sundry creditors, and misc. current liabilities.

Effective Tax Rate The relation between the income tax accrual and the pre tax income is referred to the effective tax rate (Bernstein, et al., 2000: 587). The measurement of effective tax rate depends upon the method of accounting used to report financial activities. It also depends upon the purpose of enquiry to which effective tax rate is essential. Effective tax rate can be measured as the ratio of tax provisions to profits before tax (Gandhi, 1968: 39). Alternatively, effective tax rate can be measured as the ratio of income tax expense to pre tax income (Sondhi, et al., 1994: 539). Further, effective tax rate can be measured as the ratio of income tax expenses to profit before tax or gross profit (Wang, 1991:162). Where, a positive relationship between effective tax rate and debt-equity mix is expected. In the present study effective tax rate has been computed by applying the following formula:

Effective Tax Rate =

Income tax provision ------------------------------- … … … (8) Profits before tax

Relation of Effective Tax Rate to Debt-Equity Mix Effective tax rate is a true tax rate applicable to a firm. This rate is usually less than statutory corporate tax rate. The financing mix of a business firm is affected by an effective tax rate. In order to examine the relationship between debt financing and effective tax rate, the debtequity mix measures have been regressed on effective tax rate. In addition to this, the same regression equations have been used to estimate the relationship of debt financing and effective tax rate separately for profitability-wise states of nature of the selected companies. The regression results of the measures of debt-equity mix on effective tax rate for profitabilitybased states of nature of selected companies have been presented in Table 5.6.


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Table:1 Results of the Regression of Debt-equity Mix on Effective Tax Rate S.N

1

2

3

Dependent Variables

(D/NW)t Profit-making

Constant

Explanatory Variable (Z)t-1

r2

F

N

0.458* (4.041)

0.0736 (0.676)

0.011

0.457

43

Loss-making

2.250* (6.865)

-0.269 (-0.548)

0.009

0.300

34

Total

1.257* (6.504)

-0.023 (-0.193)

0.001

0.037

77

0.151* (5.433)

0.0361*** (1.407)

0.045

1.979

44

Loss-making

0.554* (15.889)

-0.0541 (-1.033)

0.032

1.068

34

Total

0.322* (9.612)

0.031 (0.259)

0.011

0.67

78

0.430* (14.158)

0.0216 (0.684)

0.009

0.467

51

Loss-making

0.717* (21.051)

0.0137 (0.267)

0.002

0.071

34

Total

0.542* (18.304)

0.046 (0.410)

0.012

0.168

85

(D/TA)t Profit-making

(TD/TA)t Profit-making

Notes: Figures in parenthesis are t-values. * Significant at 1 percent, ** Significant at 5 percent, ***Significant at 10 percent,

The Table: 1 depicts regression results of debt-equity mix measures on effective tax rate for profit-making and loss-making companies. The coefficient of explanatory variable effective tax rate for profit-making companies is statistically significant at 10 percent level, with the dependent variable (D/TA)t. The sign associated with the coefficient indicates a positive relationship between (D/TA) and effective tax rate. However, this coefficient (0.0381) is followed by weak r2 showing only about 5 percent variation in debt to total assets ratio is explained by effective tax rate. Moreover, the 'F' value is observed statistically insignificant, which indicates that there is absence of statistical evidence about the good fitness of regression equation. On the other hand, the coefficients of this explanatory variable with dependent variables (D/NW)t and (TD/TA)t have showed positive signs, but these coefficients are statistically insignificant.

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Achyut Gyawali

For loss-making companies, it is observed that the coefficients of explanatory variable, effective tax rate, showed negative signs pertaining to dependent variables (D/NW)t, and (D/TA)t. But, the observed coefficients are not statistically significant at 10 percent level. Thus, the negative association of effective tax rate and debt-equity mix lacks considerable statistical justifications in the context of loss-making companies. The coefficient of explanatory variable, in relation to the dependent variable (TD/TA)t, is appeared with positive sign, suggesting positive association of effective tax rate with total debt to total assets ratio. However, this coefficient is not statistically significant, reflecting negligible association between these variables. For total sample, Table: 1 shows regression coefficients of effective tax rate having positive sign for two measures of dependent variable and negative sign for one measure of dependent variable. The explanatory coefficients are statistically insignificant. Due to this, it can be concluded that debt-equity mix and effective tax rate are related positively, but their relationship is not statistically significant.

Conclusion The regression coefficient of explanatory variable (effective tax rate) for profit-making companies is observed significant with the dependent variable (D/TA)t. The sign associated with this coefficient has indicated a positive relationship between (D/TA) and effective tax rate. Likewise, the coefficients of effective tax rate with dependent variables (D/NW)t and (TD/TA)t have positive signs, however these coefficients are observed insignificant. Thus, an insignificant positive relationship has been found between effective tax rate and debt-equity mix of profit-making companies. For loss-making companies, the regression coefficients of explanatory variable (effective tax rate) with dependent variables (D/NW)t, and (D/TA)t are observed with negative signs. But, the observed coefficients are not significant. Again, the coefficient of this explanatory variable in relation to the dependent variable (TD/TA)t has been observed with positive sign, suggesting positive relationship of effective tax rate with debt-equity mix. However, this coefficient of the effective tax rate is also not significant. Thus, there is an insignificant negative relationship between effective tax rate and debt-equity mix of loss-making companies. The results, depending upon the measures of dependent variable used, are consistent with the findings of Rao and Rao (1971) and Rao and Rao (1975) studies that the relationships of effective tax rate with debt-equity mix vary across the measures of dependent variable tested in the model. Moreover, the relationship of effective tax rate and debt-equity mix varies according to profitability status of the companies. For total sample, the regression coefficients of effective tax rate with debt-equity mix are positive. Thus, an insignificant positive relationship has been found between effective tax rate and debt-equity mix. This observed relationship has indicated that the corporate income tax rate does not influence debt financing of manufacturing companies significantly. This finding has implication on financing behavior of the companies that the Nepalese manufacturing companies do not consider the effects of corporate income tax on debt financing while making decision about the appropriate mix of debt and equity capital.


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References Agrawal, R.P. (1969-July). Financing company expansion The chartered accountant, The Institute of Chartered Accountants of India, P.19. Alam, Kazi Firoz, (1994). Taxation and investment policy: A survey report on the New Zealand manufacturing industry. Accounting forum, School of Accounting, University of South Australia, Vol.17, No.4, PP.121-143. Alessi, Louis De (1965 -Spring). The corporate income tax and debt to equity ratio. Wester economic journal, PP. 195-199. Altman, Edward I. and Subrahamanyam, Marit G. (1985). Recent advances in corporate finance" NewYork: Irwin Homewood Illinois Arditti, F. D. and Pinkerton, J.M. (1978-March). The valuation and cost of capital of the levered firm with growth opportunities. The journal of finance, Vol. 33, PP. 65-73. Bernstein, Leopold A. and Wild John J., (2000). Financial statement analysis, theory, application and interpretation. Seventh Edition, California:Mc Gray Hill. Brigham, Eugene F., Gapenski Louis C. and Ehrhardt Michael C. (1999). Financial management, theory and practice. Florida: The Dryden Press, Har Court Brace College Publishers. Chua, Dale (1995). The concept of cost of capital: Marginal effective tax rate on investment. In Parthasarathi Some (Ed.) "Tax policy" Washington: IMF. Fama, Eugene F. and French Kenneth R. (1998). Taxes, financing decisions, and firm value. The journal of finance, Vol. 53, No. 3, PP. 819-843. Fama, Eugene F. And Miller Merton H.(1972). The theory of finance. Hinsdale: Dryden Press. Gandhi, Ved, P. (1968-April). Company tax incidence- industry studies. The indian economic review, Vol. 3, No. 1, PP. 33-47. Hutchinson, Patrick, Alison Stewart, Gregory Warwick and Lumby Stephen (1994). Financial management decisions, principles and practices. Sydney: Thomas Nelson. Jensen, Michael C. (1986). Agency costs of free cashflow, corporate finance and takeovers. American economic review, Vol. 76, PP. 323-329. Jensen, Michael C. And Meckling, William H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of financial economics, Vol. 3, PP. 305-360. Keown, Arthur J., Martin John D., Petty J. William and Scott JR. David F. (2001). Foundations of finance, the logic and practice of financial management. Third Edition. New Jersey: Prentice Hall International. Khadka, Rup (1994). Nepalese taxation, a path for reform. Merburg: Merburg Consult for Self Help Promotion. P.119.

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Khadka, Rup (2001). Income taxation in Nepal: Retrospect and prospect. Kathmandu: Ratna Pustak Bhandar. Kandel, Puspa (2009). Tax laws and tax planning in Nepal. Katmandu: Buddha Academic Enterprises Pvt.Ltd. King, John R. (2013). Debt and equity financing. In Parthasarathi Some (Ed.) "Tax policy", Washington: IMF. P.158. Martin, John D., Petty J. William, Keown Arthur J. and Scott David F. (1991). Basic financial management. New Jersey: Prentice Hall International. Myers, Stewart C. (1977). Determinants of corporate borrowing. Journal of financial economics, Vol. 13, No. 2, PP. 147-175. Myers, Stewart C. And Brealey, Richard A. (2000). Principles of corporate finance. Sixth Edition, New York: McGraw Hill. Pringle, John J. and Harris, Robert S. (1987). Essentials of managerial finance. Sydney: Scott Foresman and Company. Rao, S. C. Humananta and Rao, V. Ganapathi, (1971-Dec.). The effects of taxation on corporate capital structure. "Indian journal of commerce. Vol. 26, No. 90, PP. 239-248. Rao, V. G. and Rao K. S. H., (1975-April). The corporate income tax and corporate debt policy. Indian economic review, Vol, 10.New Series, No. 1. PP. 7-25. Ross, Jordan, Bradford D. and Westerfield, Randolph W. (2013). Essential of corporate finance. Third Edition, New York: McGraw Hill. Saynyal, S. K. (1971-May). Trading on the equity: A tool in the hands of the financial manager. The chartered accountant, The Institute of Chartered Accountants of India, P. 817. Sondhi, C. Ashwinpaul, White I. Gerald, and Fried Dov, (1994). The analysis and use of financial statements. New York: John Wiley & Sons, Inc. Spencer, Byron G. (1969-Feb). The shifting of the corporate income tax in Canada. The Canadian journal of economics, PP. 21-34. Wang, Shiing Wu (1991). The relation between firm size and effective tax rates: A test of firms' political success." The accounting review, American accounting association, Vol. 66, No.1, PP. 158169.

An Analysis of Electricity Consumption in Industrial Sector of Nepal

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AN ANALYSIS OF ELECTRICITY CONSUMPTION IN INDUSTRIAL SECTOR OF NEPAL ...?

Bhola Nath Ghimire

Abstract Nepal has a huge hydropower potential. In fact, the perennial nature of Nepali rivers and the steep gradient of the country's topography provide ideal conditions for the development of some of the world's largest hydroelectric projects in Nepal. The purpose of this article is to derive and estimate a consumption function for Nepalese industrial electricity use, and to investigate changes in consumption pattern over the time period 1980-1912. The article employs data on the industrial electricity use, electricity and oil prices and data on the value of production, and specifies a log liner function, which is used running OLS regression. The data are divided in to two time periods 1980-1995 (before conflict) and 1996-2012 (conflict and then) in order to test for structural change and the Chow test used in the research for testing structural change in consumption. The consumption for electricity in second period is higher than that of first period. The own price electricity consumption and cross price elasticity of consumption have gone by statistically significant in both periods., and the Chow test also shown that there is structural break in consumption for hydroelectricity by Nepalese industries. Keyword: Electricity, consumption, elasticity, Chow test, structural break

Introduction The use of electricity and fossil fuels over the last decade seems to be accelerating as evidenced by an empirical research carried out recently in Nepal (Dahal, 2004). Nepal has a huge hydropower potential. In fact, the perennial nature of Nepali rivers and the steep gradient of the country's topography provide ideal conditions for the development of some of the world's largest hydroelectric projects in Nepal. The average annual precipitation is approximately 1700 mm (80% of which occurs during the monsoon season - June to September). The total annual average run-off from the nation's 600 perennial rivers is over 200 billion m3 Current estimates are that Nepal has approximately 42,000 MW of economically feasible hydropower potential. However, the present situation is that Nepal has developed only approximately 705MW of hydropower. Therefore, bulk of the economically feasible generation has not been realized yet. By the end of FY 20012/13 from all projects across the country, 705 MW of electricity has been generated. Of the total electricity generated, 697 MW has been connected to the national grid, while for the rest; the stand-alone micro hydro-electricity centers have been supplying them at the local level. Likewise, including the thermal electricity centres' production of 53.4 MW and solar centres' production of 100 KW, the total electricity production has reached 758 MW (Source: 13th periodic plan). Mr. Ghimire is the Lecturer of Economics at Global College of Management

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Cross Price Elasticity of Consumption The cross price elasticity of electricity consumption shows the change in consumption for electricity when the price of the substitute, oil, changes. This cross price elasticity is defined as:

If the cross price elasticity of electricity consumption is positive the goods are said to be gross substitutes, implying that the consumption for electricity will increase as the price of the substitute increases. To test for a structural break, Chow test used in the model, which is defined as:

Where RSSR is restricted residual sum of square and RSSUR is called unrestricted residual sum of square and RSSUR is the sum of RSS1 and RSS2. Result is obtained through use of software stata and all the diagnostic checks such including Autocorrelation, Hetroskedasticity and Multicollenearity done and the model modified as needed and result interpreted accordingly.

Analysis for Elasticity and Structural Break of Electricity Consumption by Industrial Sector of Nepal Nepalese industries have been using coal, Hydroelectricity, Petroleum product and other recycling solid and liquid materials simultaneously. However according to research topic for simplicity of the analysis I have used only Petroleum product as substitute source of energy

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along with electricity in my research. Its main reason is the price of coal and recycling material are not found as collective form, from the authentic sources therefore I have avoided the feasible happing of destruction in my model. The model is, free from autocorrelation and heteroskedasticity problem.

Price and Cross Price Elasticity of Electricity Consumption Elasticity of consumption refers to change in quantity of goods and services by certain percentage due to change in determinants of consumption by a one percentage. The Estimated elasticity consumption of price and cross price based on model, 1 are shown in table 4.1. Table 1: Estimation of the price elasticity and cross price elasticity of consumption Dependent variable = lnEL Time period

1980 – 2012(n = 28) prob.

Coeffi.

lnPEL

-0.10

0.004

-21.25

0.00

-0.19

0.008

-23

0.00

-0.07

0.004

-19.68

0.00

lnPOIL

0.70

0.03

23.03

0.00

0.52

0.57

9.10

0.00

0.35

0.015

24.5

0.00

Variables

Coeffi. std.error t-value

1996 – 2012(n = 17)

1980 – 1995(n = 11) std.error t-value

Prob.

prob.

DW Test

1.54

LM Test

0.185

0.67

0.007

0.93

0.887

0.35

Heterosked.Test

12.24

0.20

7.08

0.215

11.20

0.26

R2 F

1.34

Coeffi. std.error t-value

0.99 1030.39

0.00

1.89

0.95 53.98

0.00

0.98 408.19

0.00

Level of significance = 5%

Note: where EL = Electricity consumption, PEL = Price of electricity, POIL = Price of Petroleum product, ln = Natural logarithm and Coeffi. = Coefficient.

Own Price Elasticity of Electricity Consumption The elasticity table 4.1 shows that the own price elasticity of electricity consumption is significant at a five percentage level for the time- period 1980-2012 , 1980-1995 and 1996-2012 as well. Where the coefficient for all periods are negative which implies that one percentage change in price of electricity would lead to a decrease in industry's total consumption of electricity by 0.10 percentage, 0.19 percentage and 0.07 percentage at1980-2012, 1980-1995 and1996 -2012 periods respectively, ( when other things remain constant). It shows that negative relationship between electricity consumption and price of electricity. The consumption is less elastic in the period 1996-2012 than 1980-1995. It could be happened at second period due to high consumption of electricity for industry, consumers were standing by to purchase electricity even though price is in increasing order. After signing the consensus of carbon- business agreement, just to reduce carbon mono-dioxide and for environment friendly sustainable development, people choose electricity as a first source of energy. Various explanations can be raised for this lower elasticity; first, the price of electricity remained very low and almost constant during the period 1980-2012. Second, industries were not run properly before privatization programme and in this prospect, government's interest just could be the cost of producing and transmitting electricity to the industry. Third, government made several policy statements (such as hydropower development policy, rural energy policy, climate change policy etc.). It would keep the price of electricity as low as possible to attract investment in industrial sector.


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Cross Price Elasticity of Electricity Consumption The elasticity table 4.1 shows that the cross price elasticity of electricity consumption is significant at a five-percentage level for the period 1980-2012, 1980-1995 and1996-2012 as well. The coefficient for all periods are positive which implies that one percentage change in price of petroleum product would lead to a increase in industry's total consumption of electricity by 0.70 percentage , 0.52 percentage and 0.35 at 1980-2012 , 1980-1995 and 1996-2012 periods respectively (when other things remain constant). It shows that cross elasticity of consumption for electricity the overall period is more elastic than samples. Therefore, we can say that when increased the price of petroleum product, consumers bought more units of electricity at overall period, it gives that petroleum product becomes perfect substitute goods for electricity. However, industries were not ready to consume more units of electricity after 1995 as comparison that of before, when the price of petroleum product increased by certain percentage. Industry bought more units of electricity before 1995 comparatively after that of period. It could be happened due to high load shedding problems, consumer used their private plant, but previously consumer used energy run by diesel pumped and when price of petroleum product increased definitely increased in the consumption (consumption) of electricity. At the beginning there were not enough policies regarding to electricity can be one caused for more elastic. Although diesel has shown its potential as a substitute for electricity, yet its escalating prices and strict environmental regulation in Nepal may reduce the substitutability.

Chow Test Analysis Model 1 assumes that there is no difference, consumption for electricity between the two time periods and therefore estimates the relationship between consumption for electricity in industry and price of electricity with its substitute goods price for the entire time period consisting 28 observations. If the value of the test statistics is greater than the critical value from the Fdistribution, which is an F (k, n1+n2-2k), then reject the null hypothesis that the parameters are stable over time. Here we have restricted residual sum of square (RSSR) = 0.0870 with df 23 and Unrestricted residual sum of square (RSSUR) is given by sum of RSS1 and RSS2 i.e. RSSUR = RSS1 + RSS2 = 0.073. Table 2: Chow test estimation Period

Residual sum square Coefficient

1980–2012

RSSR

0.870

1980–1995

RSS1

0.057

1996–2012

RSS2

0.016

Calculated value Tabulated value

10.54(0.00)

3.05

Level of significance 5%

From the F tables, we find that for 4 and 22 df the 5 percent critical F value is 3.05, which is smaller than calculated value (10.54). Therefore, we reject the null hypothesis that the coefficients are the same in the two periods. The chow test shows that the consumption of electricity- price of electricity and price of oil relation has undergone a structural change in Nepalese industries over the period 1980-2012 has been tested. As above chow test could be easily generalized to handle cases of more than one structural break in the model.

Bhola Nath Ghimire

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Electricity consumption / Income 6 8 10

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1980

1990

2000 2010 Year – Electricity consumption – Income of energy sector

Figure 1: Electricity consumption and Income of energy sector Note: Electricity consumption is in GWh and Income is in ten millions Rs. The figure 4.1 shows that the structure of change in consumption and income (Gross Domestic Product from energy sectors) of electricity as changing period of time in Nepalese industries before conflict period since 1980AD and after and then conflict 1996 AD separately. The income and electricity consumption by Nepalese industries both are increasing initially however, they are fluctuated in time-to-time (sometimes increasing with increasing rate, increasing with decreasing rate and decreasing). At the target period of time 1996AD, slightly decreased in electricity consumption and its impact of income seemed in 1997 AD as a result the income curve slightly bended (it can be shown in figure 4.1) in 1996/97 AD. Civil war, internal and external disturbance in Nepalese industries, increasingly appeared political instability disturbed in industrial sector as a result the measureable fluctuations came in to notice of electricity consumption for industry of Nepal. In the period of 1956-2012 the income elasticity, price elasticity and cross elasticity were greater than previous period. It shows that due to political recovery phase after a decade civil war, industrialization become a milestone for future economic activities so consumption for electricity become more elastic in this period. The consumption for electricity slightly increased as increased in size of population or consumers in various fiscal years. Nevertheless, the drastically have not changed in consumption pattern as per possible potentiality of energy, its main cause can be lack of investment environment, political instability (mainly civil war) along with defective laws and policies. Almost seven years after the end of a 10-year internal conflict, Nepal remains one of the poorest countries worldwide, ranking 145th out of the187 countries on the Human Development Index and enhancing almost 3.5% (in average) of Economic growth per annum. These values are less than south Asian average values. Harnessing hydroelectric potential along the Himalayas will not only provide Nepal with a more reliable source of electricity, it would also address the costs currently borne by the population. Rural electrification could mitigate national inequalities by ringing health and economic well-being to millions of Nepalese.


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Nepal's energy forecast to 2028 indicates the national electricity shortage will only become more severe in the future. In 2028, Nepal will face an energy output of 17404 GWh and the system peak load is furcated to reach about 3679 MW under a medium growth (NEA).

Conclusion The purpose of this thesis has been to derive and estimate a consumption function for the Nepalese industrial electricity use, this in order to investigate changes in consumption patterns over the time period 1980-2012. By using yearly data on total industrial electricity use, electricity and oil prices and the value of production, conducting OLS regressions on a log linear consumption function on the entire time period, and , in order to test the model for a structural break, on the two time periods 1980-1995 and 1996-2012 elasticities of consumption were obtained. The coefficients for the own price elasticity of consumption and the cross price elasticity of consumption in the first time period as well as second time period were statistically significant respectively. Whereas own price elasticity and cross price elasticity of consumption both are more elastic in first and second period than in second and first period respectively. This implies that the industries consumption for electricity has gone from being entirely price insensitive to a situation where electricity use responds to changes in the own price also in the short run. One possible explanation for this is that the electricity price incorporates a higher uncertainly ever since the electricity market has been deregulated. This induces firms to expand their flexibility in energy use, and thus make substitution between these inputs easier. It is always spell out using electricity is less economic than using alternative sources. Even the price of electricity is high; industries are ready to consume more units of electricity. It could be main attraction to the investors in electricity production field. The examination on the industrial electricity consumption presented in this report by using regression analysis and Chow test shown the structural break in hydroelectricity consumption. It means there is changed in consumption for electricity by Nepalese industries in various time periods. These result point out some important conclusions, electricity is today being used more efficiently in production process than earlier, implying that the value of production is higher per used unit of electricity today. The industrial electricity consumption seems today to be more influenced by environmental factors such as policy regulations on a more efficient energy use and environmental policy regulations. Since the environmental awareness and the work on a more efficient energy, use is in an early phase it can be expected that these results will be strengthened over time.

References Altrnative energy promotion center/ energy sector assistant programme (AEPC/ESAP). (2001). Microhydro data of Nepal: Kathmandu, Nepal. Bhusal, T.P. (2009). Basic econometrics. Ayam Publication Pvt. Ltd., Kathmandu, Nepal. CBS.(2010). Statistical year book of Nepal 2010. Central Bureau of Statistics, Nepal. Chama, Y.(2012). An econometric analysis of zambian industrial electricity consumption. An unpublished M.Phil. dissertation submitted to University of Oslo, Norway.

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Chaudhry, A. (2010,September). A panel data analysis of electricity consumption in Pakistan. The labour journal of economics, Vol.3,pp. 75-106. Dahal, M.K. (2004). Nepalese economy. Central department of economics and New Hira Books Enterprises, Kathmandu, Nepal. Dhungel, K. R. (2007). Trends and patterns of energy consumption in Nepal. An unpublished Ph.D. dissertation submitted to Tribhuvan University, Kathmandu, Nepal. Dougherty, C. (2007). Introduction to econometrics. Oxford University Press, Newyork. Enders, W. (2010). Applied econometric time series. Wiley India Pvt. Ltd., New Delhi, India. Gujarati, D.N. (2006). Basic econometrics. Tata Mc Graw Hill companies. Http://www.ippan.org.np/Hp in Nepal.html (3/13/2012) Https://energypedia.info/index.php/Nepal-Country- Situation. (3/13/2012) Https://trn.gorkhapatraonline.com/index.php/op-ed/11095. (10/10/ 2014). Hunt, L.,& Judge, G.(2005). Estimating underlying energy demand trends using UK annual data. Applied economics letters, 12(4), 239-244. IEA.(2013). IEA electricity information. OECD electricity and heat supply and consumption. Koutsoyiannis, A.(1977). Theory of econometrics. Palgrave, New York, U.S.A. Lundberg, L. (2009). An econometric analysis of the Swedish industrial electricity consumption. An unpublished master thesis submitted to Lulea University of Technology, Sweden. Maddala, G.S.,& Lahiri, K.(2009). Introduction to econometrics. Wiley India Pvt. Ltd., New Delhi, India. Madnani,G.M.(2005). Introduction to econometrics, principles and applications. Oxford & IBH publishing Co.Pvt.Ltd., New Delhi, India. MOF. (2001). Economic survey fiscal year 2000/2001. Ministry of Finance, Kathmandu, Nepal. MOF. (2014). Economic survey fiscal year 2013/2014. Ministry of Finance, Kathmandu, Nepal. National Planning Commission. (2013). The thirteenth plan (2013-2016). National Planning Commission Secretariat, Kathmandu, Nepal. NEA. (2013). Nepal electricity authority FY 2012/2013 a year in review. Nepal Electricity Authority, Kathmandu, Nepal. Nicholson, W.(2005). Microeconomic theory basic principles and extension. South Western, Thomson, Mason, Ohio. NOC.(2014). Price survey of petroleum product in Nepal. FY2013/14, Nepal Oil Corporation, Kathmandu, Nepal. NRB.(2010). Quarterly economic bulletin FY 2010/11. Nepal Rastra Bank, Nepal. Parajuli,R.(2013). Energy consumption projection of Nepal: An econometric approach, www.elsevier.com/locate/renene. Sharma, P.N.(2000). Further Nepal and use water resource. The true market, Year 3, No.5. Water and Energy Commission. (2012). Review of consumption of energy in Nepal FY 2011/12. Water and Energy Commission Secretariat/Government of Nepal, Kathmandu, Nepal.

Teacher Management and Development in Higher Secondary Education 19

TEACHER MANAGEMENT AND DEVELOPMENT IN HIGHER SECONDARY EDUCATION A Case of Higher Secondary Education Board of Nepal ...?

Dev Raj Paneru

Abstract This case study on higher secondary education board of Nepal examines qualitatively human resource management and development practices undertaken to manage and develop teachers serving in the schools under HSEB in reference and against the stated vision, mission and objectives of higher secondary education board of Nepal. An assessment of HSEB goals, HRM practices undertaken by the board and universally accepted significance of HRM perspectives were used as main research strategies to address the research question stated here: How does HSEB Nepal address teaching faculty management and development issues in an endeavor to address quality educational outcomes as envisioned in its policy documents? The analysis of statistical data from the HSEB office publications, electronic media, and qualitative information, and research participants' opinions showed that integrating sustainable HRM practices in line with other functions of HSEB was crucial for attaining academic objectives measurably. Key words: management, development, enculturation, globalization, post -secondary, commissions, entrepreneurship, human resource management, efficient, effective.

Education in Nepal Nepalese education system seems to have endured uneven changes from the time of its inception. Both internal and external factors are taken accountable for changes in the field of education till the date which have been unpredictable. The main stream political systems such as authoritarian governments under Rana oligarchy followed by dictatorial monarchies, then in the 21st century multiparty democracy and currently federal republic system yet to be institutionalized are major internal factors and UNO guidelines, donor support for education along with internationalized mindset leading to English enculturation through globalization, are the external factors (Sharma &Sharma, 2066BS), taken accountable to have set Nepal's education into today's formal structures generallydivisible in three hierarchical layers. The levels are; 1. School level education ;1-5 primary, 6-8 lower secondary, and 9-10 secondary. 2. Higher secondary; 11-12 grades and 3. Higher education; bachelors and masters level as university programs, all administered, planed, budgeted, supervised and monitored by ministry of education as the apex body (Wikipedia, 2014). Mr. Paneru is the Lecturer of managerial communication at Global College of Management. He is the PhD Scholar at Kathmandu University and also an exchange student of Masaryla University Gech Republic under Erasmus Mundus Action II

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Dev Raj Paneru

Turns and bounds that education has so far travelled through are required to be reviewed in order to gain some insight into the entire system. In this connection, prior to modern education, there was the system of imparting Sanskrit education based on Hinduism that is alleged to have permitted Brahmins to study Vedas, Upanishada, Jyotish (Astronomy) and science of rituals (KarmaKanda) and the Chhetris to learn administration and art of warfare. Hence, education was confined to these groups to support the kings in their administration and courts. Buddhist monks imparted education based on their religion during the Malla regime (Http://www.geocities, 2014). Latterly, Prime Minister Jung Bahadur Rana, on returning home from Europe established an English school in Thapathali Palace on 7th Ashoj 1910 BS to teach his children only and thus, is regarded to have been the founder of modern education. Subsequently, in 1915 BS, Education Department was established that founded Darbar high school which later shifted to Rani Pokhari and was named Bhanu Madhmik Vidhyalaya. Ranas as well gave place to Sanskrit and Language schools called Bhasa Pathsalas. On closing some of the language schools, Chandra Samser established Tri-Chandra College in 1916 that obviously paved foundation of higher education first time in Nepal (Edusanjal.com, 2014). On demolition of Rana oligarchy, democracy in 2007 BS merely competed to establish political system but faced a sack in 2017 overtaken by King Mahendra who established Panchayat system. However, he is regarded for introducing modern education system by giving place to new educational system plan in 2028 (Bhattarai, 2014). Ever since, education in Nepal is traceable clearly in the structures as school, and higher education which was further demarcated as school education, proficiency level and university level. Following this development, education planning was embedded with development planning and ever since several commissions have come into frame in endeavors to reform and modify education to make it time relevant and contextually beneficial. Bhattarai (2014) observed, The National Education Planning Commission, which was the first of its kind, was formed in 1954 after the dawn of democracy in 1950 in the country. After this, six other commissions and committees have been made and they are: The National Education Committee in 1961, The National Education SystemPlan 1971, The Royal Commission on Higher Education 1983, The National Education Commission 1993, The High Level Education commission 1992; and The Higher Education Task Force, 1999. Nevertheless, it is often observed that though education has been named modern, it has not left its past legacy of traditional approach and segregating values even till the date. Proficiency Level was operated in TU whereas CTEVT administered technical courses for the same level simultaneously. But as proficiency level comprising 11 and 12 grades was becoming burdensome and difficult to operate along with increasing volume of undergraduate and graduate level education in TU, higher secondary education act was drafted in 1989 to segregate higher secondary level from university education. In the same context, Higher Secondary Education Assembly was constituted under the chairmanship of the Minister of Education that introduced Higher Secondary Education Board (HSEB) in 1989 under the same act. Ever since, the board is involved in running the 10+2 system in the country which was also recommended as being important toward specialization by Nepal National Commission of Education 1992. This is alleged to have been an initiation for incorporating extra two years in school education as a change in the existing educational structure. The development aimed at meeting the middle level human resource and imparting

Teacher Management and Development in Higher Secondary Education 21 necessary knowledge and skills to the students pursuing further education, need invited by globalization (www.hseb.edu.np/introduction). There are approximately 3600 higher secondary schools run in private and community efforts having Nepali and English medium at present. Nearly, entire higher secondary level population is accommodated in the schools under HSEBas there is no other entity in Nepal that taken responsible to educate this age group populace except Cambridge A level run privately in meager number of institutions with meager number of students and a few technical schools running CTEVT programs (Ghimire, 2014).

Higher Secondary Education Board Formation of Higher Secondary Board is often linked with a common realization in the education stakeholders that higher secondary level is far more important in extending the nurturing period of school age children from 10 years to 12 years by integrating grade 11 and 12 grades deemed essential in shaping and preparing them for university education with quality and skills (http://www.hseb.edu.np/introduction, 2014). At this turn of the time, higher secondary education board is one of the largest educational administrative bodies like SLC board and is entitled to planning, organizing, leading and controlling the entire higher secondary education system for general education that includes administrating educational and evaluation activities, as well as activities relating issuance of credentials. Producing middle level human resources as well as preparing students for university education is the key objective that HSEB has adopted since its inception in 1992 as an option to currently running proficiency level in Tribhuvan University which eventually was phased out in the year 2010. Understandably, increasing volume of students that a single university was not able to accommodate on one hand and liberalized education policy that opened the horizon for public as well as private sectors to contribute in the field of educational entrepreneurship more freely on the other hand are supposed to have resulted into formation of HSEB. Apart from its key objective that of developing middle level manpower, HSEB aims at promoting marginal populace for higher secondary education; produce capable and competent scholars and contribute as a feeder level for university education. The higher secondary education council is responsible to forward policy and recommend strategy to the cabinet of ministers so as to address mission, vision and objectives of the board apart from taking the responsibilities such as granting affiliation to schools , managing teachers, developing infrastructure, developing curriculum, & controlling quality(ibid). Presently, there are approximately 36oo higher secondary schools and some of them are new affiliates in2071 with approximately more than 300000 students taking admissions and appearing in grade 11 exams every year and thus, the entire institution is believed to be accommodating about 1000000 students in total (Gurung, 2013 in Sampreshana, 2013; Sampreshana, 2014). Owing to ever increasing size of higher secondary level population and growing number of schools and institutions, the council of higher secondary education is alleged to be holding a huge national responsibility of educating almost entire learning population of post secondary level. The fact is that along with the increased volume of consumer groups such as schools and their students, HSEB is expected to have been preoccupied with policy, management and administration related functions at centre, region, and local level far more extensively now than it used to be prior to 2010, before PCL was phased out from TU (Sharma, 2013 in Sampreshana, 2013). As stated in its office website (2014), the specific objectives of Higher

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Dev Raj Paneru


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at providing introductory remarks only, it does not seem to be adequate in addressing a large number of crucial areas without which management is alleged to remain incomplete. Olum (2004) has examined modern management theories and practices stressing on the growing importance of managerial skills for managing complex organizations indicating complexity in managing human resources in the emerging cross cultural contexts. The paper concludes utmost importance of human resource over other kinds of resources or conditions and thus, it shows that organizations either prosper or fail excessively depends on capable human resource and this in turn is possible only if HRM is effective and efficient. Despite powerful advocacy on importance of human resource management, the paper does not seem to specify internal components of human resource management nor does it speak about how to address human resource development issues. A profile of higher secondary education: Statistics books (2071 BS) is a book of statistics and it presents information on entire national result of the board in seven different methods. The divisions of result presentation are 1. Group wise result status of grade XI and XII 2. Higher Secondary School type wise result status 3. Development region wise result status 4. Sectoral office wise result status 5. Eco-development wise result status 6. District wise result status and 7. School wise result status (Statistics Book, 2071 BS). The presented data in the book showed that HSEB result in the national level in the year 2065 BS remained below 46%, it was nearly 47% in the year 2066 BS, the result in the year 2067 deteriorated and went down to 44%, it again rose up to 48% in the year 2068 BS but in the year 2069 the HSEB result went far further down to 42 %, it again progressed a little and reached 44% in gross in the year 2071. From the tabulated data in the book it becomes clear that HSEB result has remained highest in all categories in the year 2068 and it sustained least percentage in the year 2069. Although result status presented in the book may be very significant in getting some insights on how HSEB has been functioning, in getting to know about students' academic performance which can as well be treated as an indicator of letting some insight upon performance of teaching faculties and schools as exam results are pretty good indicators for educating process and personnel competence (Gurung, 2014). However, as there is no other area of information appended in the book, it can't be taken useful if recordable data are required in other areas as curriculum, school, teacher, staff management etc.. Besides, the book contains foreword by member secretary and vice-chairman who claimed that the purpose of the book is to identify changes that have occurred since 2064BS till the date and stated that it contains information on different activities of higher secondary education board. But in fact, it merely limits to presenting information on result status in seven different heads including students and schools, regions etc. and hence, it does not speak anything regarding management, development and status of teaching faculty under HSEB. Sampreshan (2014) a latest publication of HSEB in the form of bulletin stated vision, mission, and objectives that its vision is to develop the youth of 21st century Nepal as able citizens who would be able to deal with forth coming challenges. The objectives are to develop middle level work force and to prepare capable scholars eligible to join university education. The publication presents some glimpses on teachers and head teachers training and other administration related information but does not seem to provide information about policy and practices regarding management and development of higher secondary level teaching faculties. It presents the list of schools with their result of XI (2069) and XII (2070) and has only 3266 schools listed appeared XI and XII examination in 2069 and 2070 respectively. The result of XII seems to have been progressive in the year 2070 as it is 52% in gross. Despite ample

Teacher Management and Development in Higher Secondary Education 25 information on various areas, the bulletin does not seem to have given any space for information about HRM and HRD to link teaching faculty status. SSRP MOE (2009), in full form school sector reform project is a national project that is aimed to redesign the school level education including higher secondary education which initially had been a university proficiency level latterly handled by higher secondary board after its establishment in 1992. The document speaks in detail on the modalities e.g. structure, curriculum, administration and supervision and monitoring and over all frame of action. The document proposes teaching faculty management as well as development as the key responsibilities of department of education which till the date seems to be providing two teachers to a school on relief quota and the rest to be managed by the school management committee itself for higher secondary level. Nevertheless, the SSRP does not seem to have worked in details about modality of faculty management so far. Reform in higher secondary education : Connecting education with the world bank by Sharma, T.( 211). is an argumentative feature journal paper aiming to discuss various aspects of integration of curricula to bring transformation on higher secondary education in Nepal. The paper is useful as it supports the idea of teacher collaboration while exercising the collaboration of curricula but as it is limited to addressing its key concern i.e. to discuss and advocate on various modalities of curricula integration, the paper speaks very little about teacher management issue. It rather speaks about collaborating teachers as a means to collaborate curricula. There is no further detail on how teaching resources under HSEB are being managed and developed.

Review in Conclusion The above reviewed journals, documents and books can be categorized as office documents of HSEB, theory journal papers and information documents. The theoretical works show that human resource management and development is a very crucial area of concern for management of any organization in any size and it has been more crucial in the today's changed contexts i.e. cross cultures as the external factors in organizations. In this regard, for HSEB as it aims to develop youth in 21st century Nepal who would be able to tackle with the any kind of challenges in their professional life, effective and efficient management and development of teaching personnel and resources in all its faculties would be essential. But the documents show that there are still no clear landmarks nor any frames to deal with this issue as the schools are left to manage and develop their teachers on their own except provision of only 2 teaching personnel provided to a school in all.

Study Context The present study is an exploratory study. Its field is Higher Secondary Education Board. The head office of the board is located at Sanothimi- Bhaktapur Nepal. Since the teaching faculty management and development issue is supposed to be one of the concerns of HSEB in the light of the fact that education is centrally controlled phenomenon in the country, head office was selected over other sectoral, regional and district offices for data generation purpose. Along with Kathmandu district office was contacted for a telephone conversation and the chief of the office was interviewed to learn whether the district offices coordinated the schools for human resource management and development purposes or not. The study was conducted using a qualitative case study approach in higher secondary board head office and one district office as stated above. The chief of the Kathmandu district

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office, the director of planning section in the HSEB head quarter, the under secretary of the planning section, and the section officer of the computer section of HSEB head quarter were the participants of this case who volunteered information spontaneously as interacted in person and telephone conversation both. All the mentioned participants were purposively selected due to the fact that the planning section and computer section were supposed to handle the faculty related issues e.g. training and development activities. The computer section head was interviewed as the section had to responsibility to maintain data related to HSEB profile, section wise activities and programs and achievements. Under secretary was approached with a view to get the details on activities under planning section.

Data collection Having collected and analyzed data about result status, and faculty related programs being handled by HSEB from secondary sources i.e. statistics book of HSEB, primary data were collected in two different periods from headquarter of HSEB and also from the district office once in January first week and secondly in the third week of January 2015. Semi structured questionnaire and interview guide lines were used to generate information from the research participants. One participant from Kathmandu district office was interviewed on phone whereas other participants including the chief of planning section, undersecretary and chief of the computer section were interviewed in person for which pre- consent was obtained through phone call two days prior to face to face interview of the participants. The participants were conversantly interviewed and for this, the researcher performed two duties simultaneously i.e. interviewing the participants and note taking on their information so as to keep anonymity of the information (Skene, 2007). Note taking was carried out in electronic device i.e. laptop computer.

Data Analysis The data recorded in the soft form were used for sorting and analysis in accordance with the research questions and objectives i.e. to find out about the volume of teaching resources under HSEB, to examine the HRM practices of HSEB, to assess human resource development practices, and evaluate relevance and effectiveness of the HSEB practices in relation with its objectives, and then reflection and interpretation of their meaning qualitatively. The data contained guiding questions that were designed to address all the above stated objectives and research questions which I first sorted in their category so as to help interpretation with clarity. The guiding questions were used to sort out the answers and information derived from the research participants while analyzing them. A qualitative model of data analysis suggested by Seidel (1998) who invented the ideas as 'noticing, collecting, and thinking about interesting thing' was practically applied in this study in the form of noticing by identifying the suggested meanings from the participants in their interviews, reviewing on the noticed meanings, collecting special information out of the data gathered and then reflecting on the types of data and their denotative as well as connotative meanings.

Primary Findings This section presents findings of this study in the light of significance HRM and HRD practices in general hold, in the view of objectives of HSEB and significance that teaching faculty management and development would have to achieve the pronounced objectives in the policy document of HSEB.


Financing for Higher Secondary Education Teacher Management and Development Financing for teaching faculties is a supply side of financing of education and it entails funding inputs on human and material resources e.g. remuneration, compensation and development of the faculties for their skills and career promotion on one hand and development and accessibility of physical as well as technological devices on the other hand that the planners, government bodies or managers need to ensure (Heakal, 2014). Neither HSEB nor the department of education is clear about the number of teaching faculties involved in the schools as the authorities pointed out that they were responsible to support schools with only relief quota whereas the rest had to be done by the concerned school management committees. In this regard, the HSEB under secretary informed that the HSEB has financed 4000 teachers of higher secondary level through relief quota in coordination with the department of education and recently the board has decided to make the number 2000. The number of schools under HSEB is about 3600 among which approximately 1000 schools are privately managed institutions. In this connection, 6000 teachers with recently added quota, the ratio in all the community schools turns out to be 2 teachers per school. From the information as sited here, it is obvious that the financing on higher secondary schools is a poor sight and has obviously affected the funding inputs on teaching faculties and thus, it is worth stating that the higher secondary education is in common facing the issue of insufficient supply of teachers as compared to its student volume. Besides, the contribution of local people and their resources is the only support through which the entire system seems to be under operation. Regarding how far faculty management and development issues are adequate, it can be concluded that it is not as all school committees in all areas of the country cannot be asserted to be equally equipped to supply competent teaching resources in the number required.

Planning, Recruitment, Selection, Compensation, and Faculty Development Human resource planning, recruitment, selection and compensation are key tools of human resource management whereas, development of employees comprises the activities such as training, assessment of training, reward and motivation and promotion (Agrawal, 2012). Regarding HRM and HRD in higher secondary education, the chief of the planning section maintained, HSEB is stuffed with exam, curriculum and school affiliation related work load more than the capacity of its staff already and so, including the issues planning, recruitment, selection, compensation and faculty development would be impossible along with. I can't suggest that it should be endorsed in HSEB, rather, department of education should be assigned teaching resource management and development responsibilities. The opinions as such clearly indicated that teaching faculty management and development was treated as a secondary issue or no issue at all. The focus laid by the board was on how to conduct the exams, develop curriculum and affiliate schools particularly. Thus, it can be stated that despite advent of advance management practices imported by a number of Nepalese organizations through multinational and cross cultural companies and organizations, teaching faculty management at HSEB as a mainstream organization of national and international value was still limited to traditional HRM concepts like in many government organizations treating the issue as personnel administration and labour relations functions (Agrawal, 2012, p. 41). The under secretary along with the district office chief informed regarding faculty compensation and development that all the teaching faculties even the one srecruited through government

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funding were temporary, though the planning chief informed that nominal training packages were handled by HSEB every year but that was in no respect sufficient as compared to demand of the giant size of the faculties under the board. No provision with HSEB till the study time to make the teachers permanent, plan demand and supply sides, compensate and develop the faculties is simply an indication that despite large volume of faculties' involvement in educating nearly 1000000 students throughout the nation in higher secondary education, the organization has failed in addressing the key issue which is no other than faculty management and development issue and therefore, it is worth making out that the vision of HSEB, 'develop capable youth of Nepal to deal with the challenges of 21st century successfully' (Sampreshan, 2014), is still far behind from being achieved. Faculty Performance Management System in Higher Secondary Education Performance management is a practice of performance appraisal that must apply job standard oriented, comparison oriented and objective oriented methods to ensure validity and reliability in the appraisal of teachers' performance (Fancy, 1999 in Sharma Poudyal, 2013). The chief of the planning section of HSEB opined, "department of education" was accountable for monitoring and supervision of higher secondary schools and therefore, even teachers' performance was embedded within the task of school supervision." He further added, When schools recruited their faculties observing the criteria and qualifications prescribed by HSEB, this fairly worked as appraisal of faculties' performance and thus sufficed in performance management." The opinions as expressed by the HSEB authority clearly indicate that there was no systematic nor any scientific performance management system developed in HSEB though the volume of the faculties was too huge to be imagined in any ordinary set up or organization of any kind. In the situation as such claiming for successful attainment of the stated goals or vision is likely to end in debates and doubts.

Module of Teacher Management and Development under HSEB Faculty management and development are purely two determinant actions of human resource management and development deemed highly crucial for organizational goal achievement as these components deal with human skills and performance for quality and productivity of the organization. All the HRM and HRD oriented activities such as collaborative goal setting, performance review and evaluation, discipline, reward, organizational citizenship behavior, training, job design, job evaluation, employee benefits, retrenchment, and retention are some of the major concerns that the human resource department of an organization must deal with so as to manage the whole organization effectively and efficiently (Robbins & DeCenzo, 2005). All the research participants of this study agreed that HRM/D should not remain ignored area from the mainstream concerns because all of them thought that success or failure of an organization in achieving its vision, mission and objectives at large is determined by how competent, dedicated and reliable its human resources tend to be and how proficiently the resources are managed by its HRM/D department. In the light of their expressed opinions, it seemed reasonable to suggest that either HSEB or department of education was required to establish a separate human resource management and development section for higher secondary level so that the faculties would get recruited, controlled , managed and developed to make the entire program sustainable like the SLC or junior school level programs for which public

Teacher Management and Development in Higher Secondary Education 29 financing has been handled directly by the government for teaching resources in Nepal. There might be various models of operating human resource department for higher secondary level but before all, the concerned stakeholders, planners and managers of the board and the entire organizational entities needed to build a consensus on the need of sustainable mechanism that would eventually take the responsibility in hand. The chief of the planning said, Department of education need to be expanded from its currently practiced partial intervention and responsibility of providing relief quota teachers to schools to handling overall responsibility of managing and developing the entire teaching faculties in the schools under HSEB nationwide. Further it was suggested after some discussions on complicacies likely to be faced by department of education in the light of the fact that it was already stuffed with national level responsibility of managing and developing exceptionally large volume of teaching faculties for school level that the issue of HRM and HRD for higher secondary level could be made far more accountable, sustainable, efficient, and effective in handling all HRM/D related matters such as planning, job design and analysis , recruitment and selection, training and development, performance appraisal, motivation, reward, compensation, discipline and labour relations and grievances, occupational safety and health if a separate Higher Secondary Education Teacher Service Commission could be incepted. The participants pointed out that internal resources of HSEB as well as external resources could be brought into use for this purpose and besides, it was concluded that HSEB would become more accountable and enriched if it could be integrated directly through a subsidiary unit like TSC as HR department.

Conclusion HSEB envisions catering the nation with quality education to prepare middle level manpower and prepare capable scholars who would sustain university education positively. Its vision is undoubtedly super and commendable. The board accordingly has been undertaking very crucial areas of action oriented to achieving its vision, mission and objectives. Planning, management and development of curriculum and evaluation system for the entire HSEB level population along with management of the technical and conceptual level staff are the key functions that HSEB has been performing from its inception. Nevertheless, the study findings showed that the board has considerably ignored extensively in policy and in practice the most critical area called HRM/D under which an organization or its allocated department must carry out the functions e.g. planning, management and development of human resources(Agrawal, 2012) as had to be the areas of concern for the board as a national organization. This seems to have forced the schools to address the issue of HRM/D on their own to a large extent and thus, anomalies, inefficiencies and obstacles in teaching human resource management for higher secondary education are often heard of as strong issues challenging HSEB and department of education against their estimated outcomes. Even in a country like Bangladesh, laden with poverty fiercer than Nepal, the higher secondary education is publically financed and teaching faculties are paid by the central government (Budget_Paper_2012), Nepali state needs to be prepared to incorporate HRM/D for faculty and staff for sustainability in its present performance and future goals as well. Thus, further need survey researches or researches that aim at fixing human resource management and resource development modalities are recommendable so that HSEB not only persists its programs in conventional manner but can come as a time fitting and a modernized national organization with ever multiplied responsibilities, skills, technologies and attainments as envisioned in its policy.

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References Bhattarai, K. P. (2014). Higher education in Nepal: Truth and challenges. Retrieved from http://www.telegraphnepal.com/national/2007-08-22/higher-education-in-nepal;-truth-andchallenges. Robbins, S. P. & DeCenzo, D. A. (2005). Fundamentals of human resource management. India: Sanat Printers. Gurung, G. M. (2014). Seven problems of higher education. Kantipur national daily. Kathmandu: Kantipur Publications Ltd. September 19, 2014. Legacy analytics(2015). Schaumburg, IL60173. Retrieved from www.legacyanalytics.net, January13. Http://edusanjal.com/college/details/tri-chandra-multiple-campus retrieved from www.google.com (2014). http://en.wikipedia.org/wiki/Education_in_Nepal retrieved on Nov. 12, 2014. Http://www.geocities.ws/gknepaleyn/data/data/history.html, retrieved on 12- 26- 2014. http://www.hseb.edu.np/introduction, retrieved from www.google.com/nepal, on January 19, 2015. http://www.unicef.org/bangladesh/Education_Budget_Paper_2012_Dec_3.pdf retrieved from www.google.com/nepal on January 19, 2015. Heakal, R.(2014). Economics basics: Supply and demand: http://www.investopedia.com/university/economics/economics3.asp Kafle, B. D.(2060 BS). Education planning. Kathmandu : Bhudi Prakashan. Koirala, N. P. (2014). Mission education: An interview with Narayan Prasad Koirala, the HSEB speaker. Sagarmatha television live, retrieved on Nov 9, 2014 6: 30 PM. Olum, Y. (2004). Modern management theories and practices. Uganda: Makerere University Faculty of Social Sciences Department of Political Science and Public Administration. Sampreshana (2013). Ucha madhyamik sikshya parishad ka gatibidhi sambandhi prakasan. Nepal: Higher Secondary Education Council. Sampreshana (2014). Ucha madhyamik sikshya parishad ka gatibidhi sambandhi prakasan. Nepal: Higher Secondary Education Council. School sector reform project (2009). Ministry of Education. Nepal Sharma, C. & Sharma, N. (2066). Foundations of education. Kathmandu: M. K. Publishers and Distributors. Sharma Poudyal, Ch. (2013). Private schooling and Fayol's principles of management: A Case from Nepal. Journal of education and research, Vol. 3, No. 3, pp.6-23. Sharma, T.(2011). Reform in higher secondary education: Connecting education with the world of work. Higher secondary education journal, Vol 1, No. 1, Dec. Nepal. Skene, C. (2007). Interviewing women: Using reflection to improve practice. Nurse researcher, 14(4), 53-63.

Does Development of Commercial Banks Spur Economic Growth

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DOES DEVELOPMENT OF COMMERCIAL BANKS SPUR ECONOMIC GROWTH ...?


Abstract This paper examines the degree of relationship and direction of causality between the development of commercial banks and economic growth of Nepal. The impact of one on another is critically important for policy makers too, and it is for this reason the researchers believe that the above issues must be investigated through an empirical study. The motivation for this study therefore, arises from a number of shortcomings, various gaps and unresolved issues in the literature on the linkages between commercial banks and economic growth. It is anticipated that the approach and methods adopted in this research will help to bridge this gap. The main aim of this research is to make a contribution towards the understanding of the relationship between the development of commercial banks and economic growth of Nepal. Granger causality test provides the mixed result. There is the bidirectional causality between per capita real GDP and domestic assets of commercial banks to the total domestic assets. Similarly, there is no causality between per capita real GDP and private sector credit to total credit of commercial banks. Granger causality test also shows the unidirectional causality as per capita real GDP Granger causes private sector credit of commercial banks to GDP but causality in the opposite direction is not supported statistically.

Introduction The financial sector is a lifeline of all economic activities. The performance of financial system determines economic growth through successful channeling of resources to the productive areas, which is prerequisite for economic growth. Banks are among the most important financial institutions in the economy. They are the principal source of credit for millions of individuals and families and for many unit of government. Banking sector in Nepal is facing a rapidly changing market. Nepalese banking industry has significant changes over past decades as a result of liberalization, deregulation, advances in information technology and globalization. The financial sector liberalization resulted into entry of new firms in the market; deregulation widened the scope of activities and delimited the banking activities; advancement in technology resulted into new ways and tools to perform banking activities; and globalization added more pressure on competitiveness of individual banks. Nepal has a reasonably diversified financial sector as evidenced by the number and variety of institutions that play an active role in the society. Relative to Nepal's small and underdeveloped economic Dr. Bhandari is the Registrar of Pokhara University. Mr. Acharya is the Lecturer of Management & Finance at Uniglobe College, Pokhara University Affiliate.

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base over the past 20 years, Nepal's financial sector has become deeper, and the number and type of financial intermediation has grown rapidly with in this period. The Nepalese financial sector has grown significantly both in terms of business volume and size of assets and market capitalization (Shrestha & Bhandari, 2008). A well functioning financial sector plays a crucial role in the process of economic development by efficiently mobilizing resources and allocating capital for productive investment projects. After the introduction of financial sector reforms, the number of banks and other financial institutions with variegated types of financial instruments has emerged up. As a first step of initiation to liberalize the financial sector since mid-1980s, entry barriers were removed. Three joint venture banks were established in the three subsequent years from 1985. Following it, interest rates were liberalized gradually. Then, especially after the restoration of democracy in 1990, popularly elected government gave a major thrust on economic and financial liberalization in Nepal. The institutional network and volume of operations of the financial system has expanded and diversified. The number of other financial institutions has likewise seen a quantum jump. Realizing the significance of the financial system in the economic development, the government formulated and implemented various policies and processes during the past one and a half decade. They are, permission to establish joint venture banks, autonomy in the determination of the interest rate, scrapping of statutory liquidity ratio, implementation of the prudential guidelines, removal of credit ceilings, and introduction of open market operations and other indirect instruments of monetary policy. This has resulted significant improvements in quantitative as well as qualitative dimensions of the financial system (Bhetuwal, 2005). Over the past decade, Nepal has made serious efforts to transform itself into a market-based economic system and adopted the policy of financial sector reforms. The financial sector reform aimed at enhancing savings mobilization and credit allocation to the private sector. However, growth experienced less than expectation, which also affected the performance of its financial sector. Nepal formulated a comprehensive financial sector reform to deregulate the financial markets from decades of government intervention, mainly, by late 1980s and 1990s. Despite of the efforts on financial sector reform, critics argue that the reform has had little impact on mobilization of financial savings. Instead, the reform led to high nominal interest rates on lending (rather than deposit) and continuous devaluation of its currency. Improvements so far achieved after the introduction of reforms, mainly in the banking sector are not satisfactory. Mainly the performances of public sector banks have been observed to be poor. So, Nepalese banking sector is in the process of broad and comprehensive reforms. Still there are some loopholes making reform efforts less effective. It is, therefore, critical to examine the causal relationship between the development of commercial banks and economic growth of Nepal (Shrestha, 2005).

Literature Review Conceptual Review Economists hold the view that the development of the financial sector is a crucial element for spurring economic growth. Through their role of allocating capital, monitoring managers, mobilizing savings and promoting technological changes among others, financial intermediaries play a significant role in economic growth. Finance has for a long time been a neglected area in development literature, but a number of recent writings have helped to redress this imbalance.


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This neglect of finance as regards economic development is somewhat surprising, considering key role that savings and investments play in the theory of economic growth as described by Harrod (1939), Domar (1946), Solow(1956) and the importance ascribed to it by Schumpeter (1911) in his theory of economic development, McKinnon (1973) and Shaw (1973) and proponents of their views. Whether or not they have provided definitive guidelines for financial policies, or even an understanding of the role of finance in economic growth, is another question.

Role of Financial Institutions in Economic Growth Financial development can be defined as the ability of a financial sector to acquire information, enforce contracts, facilitate transactions and create incentives for the emergence of particular types of financial contracts, markets and intermediaries, and all this at a low cost (Rajan and Zingales, 2003; Levine, 1999). Financial development occurs when financial instruments, markets and intermediaries ameliorate - though not necessarily eliminate - the effects of information, enforcement and transaction costs, and therefore better provide financial services. Thus, financial development involves improvements in the (i) production of ex-ante information about possible investments, (ii) monitoring of investments and implementation of corporate governance, (iii) trading, diversification, and management of risks, (iv) mobilization and pooling of savings, and (v) exchange of goods and services. Each of these financial functions/services may influence saving and investment decisions and hence economic growth. Since many market frictions exist, and laws, regulations and policies differ remarkably across economies and over time, the impact of financial development on growth may have different implications for resource allocation and welfare in the economy. There are two distinct views of the finance-growth nexus in the traditional development economics. The first view was first proposed by Schumpeter (1911) who contends that services provided by financial intermediaries are essential drivers of innovation and growth. Thus, well-developed financial systems channel financial resources to their most productive use. Schumpeter's view was later formalised by Goldsmith (1969); McKinnon (1973); Shaw (1973); King and Levine (1993 a,b); Fry (1995) and Pagano (1993), to name just a few, who all believed that financial development is a catalyst for economic growth. The second view suggests that the increase in the demand for financial services resulting from economic growth is the major driving force behind the development of the financial sector. This mechanism is stressed in the work of Robinson (1952). According to the latter as an economy grows, more financial institutions, financial products and services emerge in markets in response to a higher and for financial services. Although plausible, the importance and correlation between financial sector development and economic growth is not the only possible description of reality, since growth can also be good for finance. Indeed, many well-known scholars, including Robinson (1952) and Ireland (1994), have long rejected this hypothesis on purely theoretical grounds. In their view, a lack of financial development is simply the manifestation of a lack of and for financial services. As the real sector of the economy expands, the various financial services increases, and will thus be met by the financial sector. Robinson (1952) argued that financial development follows growth, and articulated this causality argument by suggesting that "where enterprise leads finance follows". Even though conclusions must be drawn with caution, the preponderance of theoretical reasoning and empirical evidence suggests a positive, first-order relationship

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between financial development and economic growth (i.e. finance is related with and leads to economic growth). If these opposing theories are a correct representation of reality, then policy efforts to promote financial development will be premature, and will in fact amount to a waste of scarce resources. However, if the opposite theory is not correct, policy-makers should focus attention on the creation and promotion of modern financial institutions, including banks, non-banks and stock markets, in order to promote genuine and enduring economic growth.

Empirical Review Greenwood and Jovanovic (1990) and Bencivenga and Smith (1992) have given a new impetus to the relationship between financial development and growth as these models postulate that savings behavior directly influences not only equilibrium income levels but also growth rates. Thus, financial markets can have a strong impact on real economic activity. On the other hand, Luintel and Khan (1999) have used endogenous growth models to show a two-way relationship between financial development and economic growth. However, despite the emergence of new growth theories, the debate on the direction of causality between financial development and economic growth remains apparent yet. Greenwood and Jovanovic (1990) have addressed the context of financial structure and economic development to show causal relationship between financial development and economic growth in Pareto-optimal competitive model. Economic growth provides the development of financial structure and, in turn, allows for higher growth through efficiency in investment. Assuming that many entrepreneurs solicit capital and that capital is scarce, financial intermediaries produce better information on firms, thereby fund firms to more promising and induce a more efficient allocation of capital. King and Levine (1993a, 1993b) have found that besides identifying the best production technologies, financial intermediaries may also boost the rate of technological innovation by identifying those entrepreneurs with the best chances of successfully initiating new goods and production processes. King and Levine (1993a) have examined the capital accumulation and productivity growth channels of 77 countries over the period 1960-1989, by systematically controlling for other factors affecting long-run growth, they construct additional measures of the level of financial development, and analyze whether the level of financial development predicts long-run economic growth, capital accumulation, and productivity growth. They found very consistent results across the different financial development indicators. They however, simply found the potentially large long-term growth effects from changes in financial development. Levine (1997) has assessed theoretical and empirical evidences on finance growth nexus that the financial system that active role in the economic growth. Development of financial institutions and markets are crucial for the long run growth process. The development in the non-financial (i.e. real) sector, information and technological changes, innovations of computer, financial and monetary and other economic policy, legal and political system and institutions etc have a direct influence in the development of the financial system Further, Levine (2004) has suggested that the countries with better functioning financial system (whether bank-based or market-based), grow faster and it eases constrains on external finance. He has stressed on co-evolution of finance and growth. Technological innovation may foster growth in the presence of a well functioning financial system. It also affects the operation of financial systems by transforming the acquisition, processing, and dissemination


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of information. Importantly, the financial system may provide different services at different stages of economic development, so that the financial system promotes growth. Calderon and Liu (2003) have examined pooled data of 109 countries to examine the direction of causality between financial development and economic growth by employing Gewke Decomposition test. They found the five distinct results as; financial development generally leads economic growth; bi-directional causality between financial development and economic growth; in developing countries, financial deepening causes more to growth than industrial countries (supply leading supportive);financial development has larger effect on economic growth in long run; financial deepening contributes economic growth through more rapid capital accumulation and productivity growth. Jalil and Ma (2008) studied that the impact on the financial development and economic growth in China and Pakistan. Their hypothesis were "financial development leads to growth" under the ARDL framework by using the deposit liability ratio and credit to private sector as the indicators of financial development. They found that a positive and significant relationship between financial development and economic growth exists in the case of Pakistan. But, in the case of China, their analysis showed that a positive and significant relationship for credit liability ratio and a positive, yet insignificant, relationship with credit to private sector. Fadare (2010) empirically identifies the effect of banking sector reforms on economic growth in Nigeria from 1999-2009 by using credit to the private sector and other variables as well. He found negative relationship however the result was insignificant. In a similar kind of study conducted by Eslamloueyan and Sakhaei (2011) in Middle East suggest that there is bidirectional causality between financial development and economic growth in both the short- and long run. Hassan, Sanchez and Suk Yu (2011) found a positive relationship between financial development and economic growth in developing countries. Moreover, they have shown a two-way causality relationship between finance and growth for most regions and one-way causality from growth to finance for the two poorest regions using short-term multivariate analysis .They argued that a well-functioning financial system is a necessary but not sufficient condition to reach steady economic growth in developing countries.

Nepalese Perspective Demetriades and Luintel (1996) have examined the effects of banking sector policies on the process of financial development and economic growth of Nepal over the period of 19601992 by using unrestricted error correction model (UECM). The dynamics between financial development and economic growth are examined by exogeneity tests. They have also constructed the index of financial repression by using principal component method to quantify the influences of banking sector policies on financial development, independently of the interest rate. They could not find support for real interest rate as determinant of financial development. They have jointly determined financial development and economic growth. In other words, policies determining financial depth also influence economic growth and vice-versa. Khanal (2003) has criticized economic reforms in Nepal for an abrupt initiation. Critics are for accepting conditions of donor agencies, even if they were impossible to implement. Externally dictated reforms could not generate national consensus among working political parties as well. Reforms are criticized for no assessments of the existing domestic conditions, absence of participatory process to enlist cooperation of the stakeholders. As a result of reforms, there was a massive devaluation of domestic currency, tariff rates at the lowest in

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The study used the natural logarithms of different variables under consideration. Real GDP per capita is used as the proxy of economic growth. Real GDP is measured at basic price of a particular year and real GDP per capita is calculated by dividing the real GDP by total population of the country in a particular year. Likewise, different three variables are used as the proxy for development of commercial banks. Ratio of domestic assets of commercial banks to the sum of domestic assets of Nepal Rastra Bank and commercial banks (CBDATOTDA) is one of major indicators to measure the development of commercial banks. This ratio measures the size of commercial banks as the financial intermediaries. Similarly, ratio of private sector credit to total loans and advances of commercial banks (PRIVTOCRE) is used to measure the availability of total assets of commercial banks' in the economy because banking system extends credit to the private sector as well as government and public enterprises simultaneously. It gauzes to what extent the credit is available to the private sector out of total assets of the commercial banks. Furthermore, ratio of credit to private sector to GDP (PRIVTOGDP) is taken as another variable to measure financial development. It is the ratio of total credit available to the private sector by commercial banks to nominal GDP. It depicts the size of private sector credit in terms of the size of the economy. Out of three variables CBDATOTDA measures the size of commercial banks as the financial intermediaries. PRIVTOCRE and PRIVTOGDP measure to whom the commercial banks allocates the resources.

Empirical Results For the research purpose, among different financial institutions of Nepal; commercial banks are chosen. The research has considered the last 37 years data (from 1975/1976 to 2011/2012) for the development of commercial banks and the economic growth of the country.

Unit Root Test Unit Root Test in Level Augmented Dickey-Fuller Test is applied to test the presence of unit root in the data. The test is performed in level including no intercept in test equation with lagged difference one. Even though the sample includes the data from 1975/1976 to 2011/2012; adjusted sample considered the data from 1977/1978 to 2011/2012 after adjusting endpoints i.e.35 observations. The result of this test is summarized in the table below. Table 1: Unit root test in level F test statistic Variables LOG (PRGDP)

ADF test statistic 1.407590

LOG (CBDATOTDA)

-1.409066

LOG(PRIVTOCRE)

-1.342696

LOG(PRIVTOGDP)

-1.403766

40


MacKinnon critical values Level of significance

Critical values*

1%

-3.6289

5%

-2.9472

10%

-2.6118

*MacKinnon critical values for rejection of hypothesis of a unit root. In case of LOG (PRGDP), the computed values of ADF statistic 1.407590 which is less than the absolute MacKinnon critical value at all the level of significance under consideration. Likewise, the computed values of ADF statistic for LOG (CBDATOTDA), LOG (PRIVTOCRE), and LOG (PRIVTOGDP) are -1.409066, -1.342696, and -1.403766 respectively. However the MacKinnon critical values at 1%, 5% and 10% level of significance are -3.6289, -2.9472 and -2.6118 respectively. Comparing these values in there absolute form, the computed values of ADF statistic of all the variables are less than the MacKinnon critical values at 1%, 5% and 10% level of significance. This implies that the null hypothesis of non-stationarity in log of PRGDP, log of CBDATOTDA, log of PRIVTOCRE and log of PRIVTOGDP cannot be rejected in level test.

Unit Root Test in First Difference Most of the time series data are expected to be found first difference stationary. In order to confirm the validity of the argument, ADF test statistics have been derived from the first difference. In order to test the first difference in time series data, the null hypothesis of unit root problem in first difference in time series data is equal to zero, that is, there is unit root problem in first difference against the alternative hypothesis of zero, i.e., there is no unit root problem in such data. Testing of non-stationarity from ADF test is to take the first difference including no intercept in test equation with lagged difference one. The adjusted sample included the data from 1978/1979 to 2011/2012 after adjusting endpoints i.e.34 observations. The result of this test is summarized in the table below. Table 2: Unit root test in first difference ADF test statistic Variables

ADF test statistic

LOG (PRGDP)

-4.357927

LOG (CBDATOTDA)

-4.707436

LOG(PRIVTOCRE)

-3.957937

LOG(PRIVTOGDP)

-4.242505


41

MacKinnon critical values Level of significance

Critical values*

1%

-3.6353

5%

-2.9499

10%

-2.6133

*MacKinnon critical values for rejection of hypothesis of a unit root. The computed values of ADF statistic for LOG (PRGDP) is -4.357927 which is greater than the absolute MacKinnon critical value at all the level of significance under consideration. Likewise, the computed values of ADF statistic for LOG (CBDATOTDA), LOG (PRIVTOCRE), and LOG (PRIVTOGDP) are -4.707436, -3.957937, and -4.242505 respectively. However the MacKinnon critical values at 1%, 5% and 10% level of significance are -3.6353, -2.9499, and -2.6133 respectively. Comparing these values in there absolute form, the computed values of ADF statistic of all the variables are greater than the MacKinnon critical values at 1%, 5% and 10% level of significance. This implies that the null hypothesis of non-stationarity in log of PRGDP, log of CBDATOTDA, log of PRIVTOCRE and log of PRIVTOGDP are rejected in first difference. In summing up, all the variables which are not stationary in level form data are shown stationary in their first difference. The ADF statistics of all the four variables in their absolute form are greater than MacKinnon critical value at 1%, 5% and 10% level of significance. Therefore, the first difference data are stationary or they are integrated of order 1 or I (1).

Co-integration Test In order to derive the stable long-run relationship between economic growth and financial development' explanatory variables of Nepal, the Johansen co-integration tests have been performed to validate the variables whether they are co-integrated in same order. The test assumption is the linear deterministic trend in the data.

Co-integration Test between LOG (PRGDP) and LOG (CBDATOTDA) The Johansen co-integration test has been performed in the series LOG (PRGDP) and LOG (CBDATOTDA). The included number of observation in between 1977/1978 to 2011/2012 is 35. Furthermore, the test allowed for the linear deterministic trend in the data and there is no trend assumed in the co-integrating equation and test VAR. The assumed lag interval (pairs) in VAR is 1 to 1. The test results are presented in table below: Table 3: Co-integration test between LOG (PRGDP) & LOG (CBDATOTDA) Lags interval: 1 to 1 Eigen value Likelihood ratio 5% critical value 1% critical value Hypothesized no. of CE(s)

0.326356

15.40158

15.41

20.04

None

0.043994

1.574698

3.76

6.65

At most 1

*(**) denotes rejection of the 5% (1%) significance level L.R. rejects any co-integration at 5% significance level

42


The values of likelihood ratio between these two variables are 15.40158 and 1.574698 considering 'no hypothesized co-integrating equations' and 'at most one co-integrating equation'. However, critical values for 1% and 5% level of significance in the first case are 20.04 and 15.41 respectively and that of second case are 6.65 and 3.76 respectively. As the likelihood ratio in both the cases is less than the critical value, there is no co-integration presence at 1% and 5% level of significance. Similarly, test has been performed in the series LOG (PRGDP) and LOG (CBDATOTDA) assuming 1 to 2 lag interval (pairs) in vector auto regression variables (VAR). The included number of observation in between 1978/1979 to 2011/2012 is 34. The test results are given in the following Table: Table 4: Co-integration test between LOG (PRGDP) & LOG (CBDATOTDA) Lags interval: 1 to 2 Eigen value Likelihood ratio 5% critical value 1% critical value Hypothesized no. of CE(s)

0.470431

22.04219

15.41

20.04

None **

0.012529

0.428667

3.76

6.65

At most 1

*(**) denotes rejection of the 5% (1%) significance level L.R. test indicates 1 co-integrating equation(s) at 5% significance level Normalized co-integrating coefficients: 1 co-integrating equation(s) LOG (PRGDP)

LOG (CBDATOTDA)

C

1.000000

-1.679785

-9.987995

(0.13398) Log likelihood

148.4208

The values of likelihood ratio between these two variables are 22.04219 and 0.428667 considering 'no hypothesized co-integrating equations' and 'at most one co-integrating equation'. However, critical values for 1% and 5% level of significance in the first case are 20.04 and 15.41respectively and that of second case are 6.65 and 3.76 respectively. As the likelihood ratio the first case is greater than the critical value, there is the presence of one co-integrating equation at 1% and 5% level of significance. Furthermore, the co-integrating equation between LOG of PRGDP and LOG of CBDATOTDA with normalized co-integrating coefficients has also shown in the above table. The presence of co-integrating equation indicates that there exists the long run relationship between LOG (PRGDP) and LOG (CBDATOTDA).

Co-integration Test between LOG (PRGDP) and LOG (PRIVTOCRE) The Johansen co-integration test has been performed in the series LOG (PRGDP) & LOG (PRIVTOCRE). The test allowed for the linear deterministic trend in the data and there is no trend assumed in co-integrating equation and test VAR. Furthermore, the assumed lag interval (pairs) in vector auto regression variables (VAR) is 1 to 1. The included number of observation in between 1977/1978 to 2011/2012 is 35. The test results are given in the table below:


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Table 5: Co-integration test between LOG (PRGDP) & LOG (PRIVTOCRE) Lags interval: 1 to 1 Eigen value Likelihood ratio 5% critical value 1% critical value Hypothesized no. of CE(s)

0.212681

8.910216

15.41

20.04

None

0.015337

0.540952

3.76

6.65

At most 1

*(**) denotes rejection of the 5% (1%) significance level L.R. rejects any co-integration at 5% significance level The values of likelihood ratio between these two variables are 8.910216and 0.540952 considering 'no hypothesized co-integrating equations' and 'at most one co-integrating equation'. However, critical values for 1% and 5% level of significance in the first case are 20.04 and 15.41 respectively and that of second case are 6.65 and 3.76 respectively. As the likelihood ratio in both the cases is less than the critical value, there is no co-integration presence at 1% and 5% level of significance. Similarly, test has been performed in the series LOG (PRGDP) and LOG (PRIVTOCRE) assuming 1 to 2 lag interval (pairs) in vector auto regression variables (VAR). The included number of observation in between 1978/1979 to 2011/2012 is 34. The test results are given in the following Table: Table 6: Co-integration test between LOG (PRGDP) & LOG (PRIVTOCRE) Lags interval: 1 to 2 Eigen value Likelihood ratio 5% critical value 1% critical value Hypothesized no. of CE(s)

0.202945

8.616186

15.41

20.04

None

0.026235

0.903907

3.76

6.65

At most 1

The values of likelihood ratio between these two variables are 8.616186 and 0.903907 considering 'no hypothesized co-integrating equations' and 'at most one co-integrating equation'. However, critical values for 1% and 5% level of significance in the first case are 20.04 and 15.41 respectively and that of second case are 6.65 and 3.76 respectively. As the likelihood ratio in both the cases is less than the critical value, there is no co-integration presence at 1% and 5% level of significance.

Co-integration Test between LOG (PRGDP) and LOG (PRIVTOGDP) The Johansen co-integration test has been performed in the series LOG (PRGDP) and LOG (PRIVTOGDP). The test allowed for the linear deterministic trend in the data and there is no trend assumed in co-integrating equation and test VAR. Furthermore, the assumed lag interval (pairs) in vector auto regression variables (VAR) is 1 to 1. The included number of observation in between 1977/1978 to 2011/2012 is 35. The test results are given in the following Table: Table 7: Co-integration test between LOG (PRGDP) & LOG (PRIVTOGDP) Lags interval: 1 to 1 Eigen value Likelihood ratio 5% critical value 1% critical value Hypothesized no. of CE(s)

0.408527

19.48066

15.41

20.04

None *

0.030962

1.100784

3.76

6.65

At most 1

*(**) denotes rejection of the 5% (1%) significance level L.R. test indicates 1 co-integrating equation(s) at 5% significance level

44


Normalized co-integrating coefficients: 1 co-integrating equation(s) LOG (PRGDP)

LOG (CBDATOTDA)

C

1.000000

-0.387648

-10.35390

(0.02542) Log likelihood

120.7601

The values of likelihood ratio between these two variables are 19.48066and 1.100784 considering 'no hypothesized co-integrating equations' and 'at most one co-integrating equation'. However, critical values for 1% and 5% level of significance in the first case are 20.04 and 15.41respectively and that of second case are 6.65 and 3.76 respectively. As the likelihood ratio the first case is greater than the critical value, there is the presence of one co-integrating equation at 5% level of significance. Furthermore, the co-integrating equation between LOG of PRGDP and LOG (PRIVTOGDP) with normalized co-integrating coefficients has also shown in the above table. The presence of co-integrating equation indicates that there exists the long run relationship between LOG (PRGDP) and LOG (PRIVTOGDP). Similarly, test has been performed in the series LOG (PRGDP) and LOG (PRIVTOGDP) assuming 1 to 2 lag interval (pairs) in vector auto regression variables (VAR). The included number of observation in between 1978/1979 to 2011/2012 is 34. The test results are given in the following Table: Table 8: Co-integration test between LOG (PRGDP) & LOG (PRIVTOGDP) Lags interval: 1 to 2 Eigen value Likelihood ratio 5% critical value 1% critical value Hypothesized no. of CE(s)

0.296217

13.06768

15.41

20.04

None

0.032518

1.124004

3.76

6.65

At most 1

*(**) denotes rejection of the 5% (1%) significance level L.R. rejects any co-integration at 5% significance level The values of likelihood ratio between these two variables are 13.06768 and 1.124004 considering 'no hypothesized co-integrating equations' and 'at most one co-integrating equation'. However, critical values for 1% and 5% level of significance in the first case are 20.04 and 15.41 respectively and that of second case are 6.65 and 3.76 respectively. As the likelihood ratio in both the cases is less than the critical value, there is no co-integration presence at 1% and 5% level of significance. The Johansen co-integration test indicated that there exists one co-integrating equation between log of real GDP per capita and log of commercial bank assets to total domestic assets at 1% and 5% level of significance. Similarly, one co-integrating relationship is confirmed in between log of per capita GDP and log of total credit available to the private sector through commercial banks to GDP at 5% level of significance. The existence of co-integration implies that there is long-run relationship between those variables during the review period. However, no cointegrating relationship is found between log of real GDP per capita and log of commercial banks' credit to private sector to total credit.


45

Vector Error Correction Model As LOG (PRGDP) is co-integrated with LOG (CBDATOTDA) and LOG (PRIVTOGDP), the short-run "disequilibrium" relationship between the same can always be represented by an Error Correction Model (ECM). This model states that changes in y depend on changes in x and one period lag residual term which is derived from co-integrating equation as the disequilibrium error in the previous period, that is, Dyt = a0 + a1 Dxt + ut–1 + et. If no equilibrium relationship exists, short-run behavior should not be represented by ECM. According to the ECM argument both the level form data (long-run relationship) and their first differences (short-run relationship) are required in a single regression equation. Among co-integrated variables both the short run as well as long-run relationship can be represented in Error Correction Model (ECM). Therefore, ECM reconciles the short-run behavior of an economic variable with its long-run behavior.

VECM in between LOG (PRGDP) and LOG (CBDATOTDA) Vector Error Correction Model (VECM) has been applied in the co-integrating equation between LOG (PRGDP) and LOG (CBDATOTDA). VAR assumes intercept but no trend in co-integrating equations. The sample includes 35 observations from 1977/1978 to 2011/2012 after adjusting end points. Table 9: VECM in between LOG (PRGDP) and LOG (CBDATOTDA) Error correction: CointEq1

D(LOG(PRGDP))

D(LOG(CBDATOTDA))

0.129875 (3.32610) (0.09000)

(0.03905) 0.377445 (4.19392)

D(LOG(PRGDP(-1)))

-0.472274 (-2.52895) (0.43042)

(0.18675) -0.877827 (-2.03945)

D(LOG(PRGDP(-2)))

-0.293673 (-1.60005) (0.42303)

(0.18354) -1.065833 (-2.51952)

D(LOG(CBDATOTDA(-1)))

0.061846 (0.88644) (0.16081)

(0.06977) 0.238892 (1.48559)

D(LOG(CBDATOTDA(-2)))

0.028085 (0.43575) (0.14855)

(0.06445) 0.275036 (1.85143)

C

0.034843 (5.34994) (0.01501)

(0.00651) 0.035705 (2.37857)

46


The vector error correction model has shown that about 12.98% of disequilibrium is 'corrected' each year by changes in economic growth indexes 'log of per capita real GDP' i.e. LOG (PRGDP). Similarly, about 37.74% of disequilibrium is 'corrected' each year by changes in one of the commercial banks' development index 'log of domestic assets of commercial banks to total domestic assets' i.e. LOG (CBDATOTDA). All other error correction in the variables has been reported in the above table. Furthermore, Standard errors & t-statistics are reported in parentheses.

VECM in between LOG (PRGDP) and LOG (PRIVTOGDP) As another co-integrating equation exists between LOG (PRGDP) and LOG (PRIVTOGDP), the vector error correction model is also applied in the equation between them. In this case also VAR assumes intercept but no trend in co-integrating equations. The sample includes 35 observations from 1977/1978 to 2011/2012 after adjusting end points.

Table 10: VECM in between LOG (PRGDP) and LOG (PRIVTOGDP) Error Correction:

D(LOG(PRGDP))

D(LOG(PRIVTOGDP))

CointEq1

-0.105988 (0.05838) (-1.81553)

0.985220 (0.22874) (4.30709)

D(LOG(PRGDP(-1)))

-0.095556 (0.17280) (-0.55298)

0.466226 (0.67709) (0.68858)

D(LOG(PRIVTOGDP(-1)))

-0.010892 (0.03605) (-0.30215)

0.418546 (0.14125) (2.96312)

0.022087 (0.00579) (3.81270)

0.029462 (0.02270) (1.29800)

C

The vector error correction model has shown that about -10.59 % of disequilibrium is 'corrected' each year by changes in economic growth index 'log of per capita real GDP' i.e. LOG (PRGDP). Similarly, about 98.52% of disequilibrium is 'corrected' each year by changes in one of the commercial banks' development indexes 'log of private sector credit by commercial banks to GDP' i.e. LOG(PRIVTOGDP). All other error correction in the variables has been reported in the above table. Furthermore, Standard errors & t-statistics are reported in parentheses.

Granger Causality Test From the above Johansen co-integration test, it has been found that there exists the long term relationship between log of real GDP per capita and log of commercial bank assets to total domestic assets at 1% and 5% level of significance. Similarly, the long term is relationship is also confirmed in between log of per capita GDP and log of total credit available to the


47

private sector through commercial banks to GDP at 5% level of significance. According to the Engle and Granger (1987) representation theorem, if two variables are co-integrated and each is individually I (1), that is, integrated of order 1 (i.e., each is individually non-stationary), then first variable may Granger-cause second variable, second variable may Granger-cause first variable or each other. Granger causality test has been performed as follows:

Granger Causality Test between LOG (PRGDP) & LOG (CBDATOTDA) Table 11: Granger causality test between LOG (PRGDP) & LOG (CBDATOTDA) Null hypothesis

Obs Lags F-statistic

Prob

LOG(PRGDP) does not Granger cause LOG(CBDATOTDA)

36

1

5.41109

0.02630

LOG(CBDATOTDA) does not Granger cause LOG(PRGDP)

36

1

4.45370

0.04249


35

2

3.08689

0.06038


35

2

3.52423

0.04220


34

3

5.38914

0.00488


34

3

3.83626

0.02076


33

4

4.11155

0.01120


33

4

2.22561

0.09635

Granger causality test has been performed between LOG (PRGDP) and LOG (CBDATOTDA) considering the different lag length. In case of null hypothesis 'LOG (PRGDP) does not Granger cause LOG (CBDATOTDA)' the F-statistics are 5.41109, 3.08689, 5.38914 and 4.11155 for the lag length 1, 2, 3 and 4 respectively. In the meantime, the values of probability for the lag length 1, 2, 3 and 4 are 0.02630, 0.06038, 0.00488, and 0.01120 respectively. The above table shows that values the F-statistics is significant at 2.63% level of significance for the lag length 1. In case of lag length 2, it is significant at 6.03% level of significance. When lag length is considered as 3, F-statistics is significant at 0.5% level of significance. Similarly, in case of lag length 4, it is significant at 1.12% level of significance. That means the null hypothesis 'LOG (PRGDP) does not Granger cause LOG (CBDATOTDA)' has been rejected at 5% level of significance considering the lag length 1, 3 and 4 whereas for the lag length 2, it has been rejected at 6% level of significance. Similarly, In case of null hypothesis 'LOG (CBDATOTDA) does not Granger Cause LOG (PRGDP)' the F-statistics are 4.45370, 3.52423, 3.83626, and 2.22561 for the lag length 1, 2, 3 and 4 respectively. Similarly, the values of probability for the lag length 1, 2, 3 and 4 are 0.04249, 0.04220, 0.02076, and 0.09635 respectively. Analyzing the value of F-statistics and probability, it can be concluded that the F-statistics is significant at 4.2 % level of significance for the lag length 1. In case of lag length 2, it is significant at 4.2 % level of significance. When lag length is considered as 3, F-statistics is significant at 2 % level of significance. However, in case of lag length 4, it is significant at 9.6% level of significance. That means the null hypothesis 'LOG (CBDATOTDA) does not Granger Cause LOG (PRGDP)' has been rejected at 5% level of significance considering the lag length 1, 2 and 3 whereas for the lag length 4, it has been rejected at 10% level of significance.

48


From the above analysis it can be concluded that there is bidirectional causality between log of per capita real GDP [LOG (PRGDP)] and log of domestic assets of commercial banks to the total domestic assets [LOG (CBDATOTDA)]. That means LOG (CBDATOTDA) Granger causes LOG (PRGDP) and LOG (PRGDP) Granger causes LOG (CBDATOTDA).

Granger Causality Test between LOG (PRGDP) & LOG (PRIVTOCRE) Table 12: Granger causality test between LOG (PRGDP) & LOG (PRIVTOCRE) Null hypothesis


Prob

LOG(PRGDP) does not Granger cause LOG(PRIVTOCRE)

36

1

1.85439

0.18250

LOG(PRIVTOCRE) does not Granger cause LOG(PRGDP)

36

1

0.37396

0.54504


35

2

2.84082

0.07416


35

2

0.17588

0.83958

LOG(PRGDP) does not Granger Cause LOG(PRIVTOCRE)

34

3

2.17972

0.11355

LOG(PRIVTOCRE) does not Granger Cause LOG(PRGDP)

34

3

0.40578

0.75005


33

4

1.41571

0.25900


33

4

0.03438

0.99757

Although there is no co-integrating relationship between LOG (PRGDP) and LOG (PRIVTOCRE), Granger causality test has been performed between them considering the different lag length. In case of null hypothesis 'LOG (PRGDP) does not Granger Cause LOG (PRIVTOCRE)' the F-statistics are 1.85439, 2.84082, 2.17972, and 1.41571 for the lag length 1, 2, 3 and 4 respectively. In the meantime, the values of probability for the lag length 1, 2, 3 and 4 are 0.18250, 0.07416, 0.11355, and 0.25900 respectively. The above table shows that the values of F-statistics are insignificant at 5% level of significance for all the lag lengths under consideration. Only in the case of lag length 2, it is significant at 7.4% level of significance. That means the null hypothesis 'LOG (PRGDP) does not Granger Cause LOG (PRIVTOCRE)' can't be rejected at 5% level of significance. Similarly, in case of null hypothesis 'LOG (PRIVTOCRE) does not Granger Cause LOG (PRGDP)' the F-statistics are 0.37396, 0.17588, 0.40578, and 0.03438 for the lag length 1, 2, 3 and 4 respectively. Also, the values of probability for the lag length 1, 2, 3 and 4 are 0.54504, 0.83958, 0.75005, and 0.99757 respectively. Analyzing the value of F-statistics and probability, it can be concluded that the F-statistics are insignificant at 5% level of significance for all the lag length under consideration. That means the null hypothesis 'LOG (PRIVTOCRE) does not Granger Cause LOG (PRGDP)' can't be rejected at 5% level of significance. From the above analysis it can be concluded that there is no causality between log of per capita real GDP [LOG (PRGDP)] and log of private sector credit to total credit of commercial banks [LOG (PRIVTOCRE)]. That means LOG (PRGDP) does not Granger cause LOG (PRIVTOCRE) and LOG (PRIVTOCRE) does not Granger cause LOG (PRGDP).


49

Granger Causality Test between LOG (PRGDP) & LOG (PRIVTOGDP) Table 13: Granger causality test between LOG (PRGDP) & LOG (PRIVTOGDP) Null hypothesis


Prob

LOG(PRGDP) does not Granger cause LOG(PRIVTOGDP)

36

1

4.79680

0.03569

LOG(PRIVTOGDP) does not Granger cause LOG(PRGDP)

36

1

2.53809

0.12066


35

2

8.11699

0.00152


35

2

1.07791

0.35312


34

3

4.07156

0.01652


34

3

0.39794

0.75555


33

4

3.87350

0.01448


33

4

0.66784

0.62057

Granger causality test has also been performed between LOG (PRGDP) and LOG (PRIVTOGDP). In case of null hypothesis 'LOG (PRGDP) does not Granger cause LOG (PRIVTOGDP)' the F-statistics are 4.79680, 8.11699, 4.07156 and 3.87350 for the lag length 1, 2, 3 and 4 respectively. Similarly, the values of probability for the lag length 1, 2, 3 and 4 are 0.03569, 0.00152, 0.01652, and 0.01448 respectively. The above table shows that values the F-statistics are significant at 3.5% level of significance for the lag length 1. In case of lag length 2, it is significant at 0.15% level of significance. For the lag length 3, F-statistics is significant at 1.65% level of significance. Similarly, in case of lag length 4, it is significant at 1.4% level of significance. That means the null hypothesis 'LOG (PRGDP) does not Granger cause LOG (PRIVTOGDP)' has been rejected at 5% level of significance for all the lag length under consideration. Similarly, in case of null hypothesis 'LOG (PRIVTOGDP) does not Granger Cause LOG (PRGDP)' the F-statistics are 2.53809, 1.07791, 0.39794, and 0.66784 for the lag length 1, 2, 3 and 4 respectively. Meanwhile, the values of probability for the lag length 1, 2, 3 and 4 are 0.12066, 0.35312, 0.75555, and 0.62057 respectively. Analyzing the value of F-statistics and probability, it can be concluded that the F-statistics are insignificant at 5% level of significance for all the lag length under consideration. That means the null hypothesis 'LOG (PRIVTOGDP) does not Granger cause LOG (PRGDP)' can't be rejected at 5% level of significance. This analysis shows that there is unidirectional causality between log of per capita real GDP [LOG (PRGDP)] and log of private sector credit of commercial banks to GDP [LOG (PRIVTOGDP)]. The test suggests that LOG (PRGDP) Granger causes LOG (PRIVTOGDP) whereas LOG (PRIVTOGDP) does not Granger causes LOG (PRGDP). In summing up, the result of Granger causality test provides the mixed result. Considering the first Granger causality test, the statistically significant F-statistic confirms the fact that there is the bidirectional causality between log of per capita real GDP and log of domestic assets of commercial banks to the total domestic assets. Similarly, in the second Granger causality test, the insignificant F-statistic suggests that there is no causality between log of per capita real GDP and log of private sector credit to total credit of commercial banks. Finally, the third Granger causality test shows the unidirectional causality as log of per capita real

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GDP Granger causes log of private sector credit of commercial banks to GDP but causality in the opposite direction is not supported statistically. The results of present study partially resembles with the findings of King and Levine (1993a) as they found the strong positive relationship between each of the financial development indicators and the three growth indicators, long-run real per capita growth rates, capital accumulation and productivity growth. Furthermore, the study of Calderon and Liu (2003) revealed that the financial development generally leads economic growth but there is the bidirectional causality between financial development and economic growth. Levine (2004) stressed on co-evolution of finance and growth. Present study also supports these findings as there is the bidirectional causality between log of per capita real GDP and log of domestic assets of commercial banks to the total domestic assets. Jalil &Ma (2008) found that a positive and significant relationship between financial development and economic growth exists in the case of Pakistan. But, in the case of China, a positive and significant relationship for credit liability ratio and a positive, yet insignificant, relationship with credit to private sector were found. However, in this study there is no causality between log of per capita real GDP & log of private sector credit to total credit of commercial banks. Also, there is the unidirectional causality as log of per capita real GDP Granger causes log of private sector credit of commercial banks to GDP but there is no causality in the opposite direction. Bhetuwal (2007) and Poudel (2005) found that financial development contributes positively to domestic economic growth. On the other hand, Shrestha (2005) did not find any significant relationship between economic growth and financial development. The present study suggests the co-integration between development of commercial banks and economic growth although there is bidirectional causality between log of per capita real GDP and log of domestic assets of commercial banks to the total domestic assets; and unidirectional causality between log of per capita real GDP and log of private sector credit of commercial banks to GDP. In this context of mixed results, the appropriate development of Nepalese financial sector is essential so that it can play a critical and positive role in the economic growth of the nation.

Conclusions The analysis has clearly depicted the real picture of development of Nepalese commercial banks. Until 1984, Nepalese financial system was suffering from several problems. It was not proliferated until 1984, although there were couples of banks and financial institutions. The initiation in financial sector reforms and introduction of market oriented economic policies led a rapid expansion of financial institutions and instruments. It has resulted for diversification of financial system during a short span of time. Additionally, the development of new financial instruments and services, introduction of regulatory framework and institutionalization of savings has created new scene for economic growth and development. The existence of co-integration implies that there is long-run relationship between log of real GDP per capita and log of commercial bank assets to total domestic assets; also between log of per capita GDP and log of total credit available to the private sector through commercial banks to GDP. However, no co-integrating relationship is found between log of real GDP per capita and log of commercial banks' credit to private sector to total credit. Granger causality test provides the mixed result. The statistically significant F-statistic confirms the fact that


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there is the bidirectional causality between log of per capita real GDP and log of domestic assets of commercial banks to the total domestic assets. Similarly, the insignificant F-statistic suggests that there is no causality between log of per capita real GDP and log of private sector credit to total credit of commercial banks. Granger causality test also shows the unidirectional causality as log of per capita real GDP Granger causes log of private sector credit of commercial banks to GDP but causality in the opposite direction is not supported statistically. Economy of the country cannot reach to its growth potential and develop at an adequate pace without an active contribution of the financial sector. A well functioning financial system efficiently mobilizes resources and allocates capital for productive investment projects. Commercial banks are the largest financial institutions dominant in the financial system occupying the major portion of the total financial assets. The development of commercial banks' is important to the speed and direction of economic growth, by mobilizing idle financial resources for productive investment. To link up commercial banks' development and economic growth, the economic activities in the private sector must go simultaneously to strengthen the growth and reducing mass poverty.

References Bencivenga,V.R., & Smith, B. D. (1992). Deficits, inflation and the banking system in developing countries: The Optimal Degree of Financial Repression. Oxford economic papers 44: 767 - 790 Bhetuwal, K. R. (2005). Assessing the effectiveness of financial reforms. Doctoral thesis, Maharaja Sayajirao University of Baroda, Department of Economics, Vadodara. Bhetuwal, K. R. (2007). Financial liberalization and financial development in Nepal. Economic review, Nepal rastra bank, 23-41 Calderon, C., & Liu, L. (2003). The direction of causality between financial development and economic growth. Journal of development economics 72: 321-324 Demetriades, P.O., & Luintel, K.B. (1996). Banking sector policies and financial development in Nepal. Oxford bulletin of economics and statistics, 58(2): 355 - 372 Domar, E. (1946). Capital expansion, rate of growth and employment. Econometrica, 14: 137-147. (46), 61-76. Engle, R.F., & Granger, C.W.J. (1987). Cointegration and error correction: Representation, estimation and testing, econometrica, 55: 251-826. Eslamloueyan, K., & Sakhaei, A. E. (2011). The short run and long run causality between financial development and economic growth in the middle east. Iranian journal of economic research, 16 Fadare, S. O. (2010). Recent banking sector reforms and economic growth in Nigeria. Middle eastern finance and economics 8: 1450-2889. Fry, M. (1995). Money, interest and banking in economic development. The John Hopkins Studies in Development, Baltimore, John Hopkins University Press. Goldsmith, R. W. (1969). Financial structure and development. New Haven, CT: Yale University Press. Granger, C.W.J. (1969). Investigating causal relations by econometric models and cross- spectral methods. Econometrica, July 1969, pp. 424-438. Granger, C., & Newbold, P. (1974). Spurious regression in econometrics. Journal of econometrics 2. Greenwood, J., & Jovanovic, B. (1989). Financial development, growth and the distribution of income. NBER working paper series no. 3189. Greenwood, J., & Jovanovic, B. (1990). Financial development, growth and the distribution of income. Journal of political economy Vol. 98 No. 5, pp 1076-1107

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Gujarati, D.N. (2004). Basic econometric. Tata McGraw-Hill Publishing Company Limited, New Delhi, (Fourth Edition). Harrod, R.F. (1939). An Essay in dynamic theory. Economic journal, 48 (192) .14-33. Hassan, K., Sanchez, B., & Yu, J. (2011). Financial development and economic growth: New evidence from panel data. The quarterly review of economics and finance, 51, pp.88-104. Ireland, P. (1994). Money and Growth: An alternative approach. American economic review, March, 47-65. Jalil, A., & Ma, Y. (2008). Financial development and economic growth: Time series evidence from Pakistan and China. Journal of economic cooperation, November, 29(2). pp. 29-68 Khanal, D. R. (2003). Why economic reform failed in Nepal: 9 Reasons. New business age, March Kharel, R.S., & Pokhrel, R.D. (2012). Does Nepal? Financial structure matter for economic growth? NRB working paper series, 31-46. King, R., & Levine, R. (1993a). Finance and growth: Schumpeter might be right. Quarterly journal of economics Vol. 108(3). 717-737. King, R. G., & Levine, R. (1993b). Finance, entrepreneurship, and growth: Theory and evidence, Journal of monetary economics 32, 513-42. Levine, R. (1997). Financial development and economic growth: Views and agenda. Journal of economic literature 35, 688-726. Levine, R. (1999). Financial development and economics growth: view and agenda. World bank policy research working paper, No 1678. Levine, R. (2004). Finance and growth: Theory and evidence. National bureau of economic research working paper No.10766 Luintel, K.B., & Khan, M. (1999). A Quantitative reassessment of the finance-growth nexus: Evidence from a multivariate VAR. Journal of development economics 60, 381-405. McKinnon, R. (1973). Money and capital in economic development. Brookings Institution. Washington, DC, USA. Nepal Rastra Bank. Various Issues. Quarterly economic bulletin. Kathmandu: Nepal Rastra Bank. NRB Economic Review: Occasional Paper (2003- 2010) Pagano, M. (1993). Financial markets and growth: An overview. European economic review 39, 613-622. Paudel, N. P. (2005). Financial system and economic development. In NRB, Nepal rastra bank in fifty years. Kathmandu: NRB Quarterly economic bulletin: Nepal Rastra Bank, July 2011, Vol. 45, No. 4 Rajan, R. G., & Zingales, L. (1998). Financial dependence and growth. American economic review Vol. 88(3), pp. 559 - 586. Rajan, R. G., & Zingales, L. (2003). The great reversals: the politics of financial development in the twentieth century. Journal of financial economics, 69, 5-50. Robinson, J. (1952). The generalization of the general theory in the rate of interest and other essays. MacMillan, London. Roubini, N., & Martin, S. (1992). Financial repression and economic growth. Journal of development economics. 1992, 39(1), 5-30. Schumpeter, J. A. (1911). The theory of economic development, An inquiry into profits, capital, credit, interest, and the business cycle, Translation 1934, Cambridge MA, Harvard University Press. Second Printing 1936; third printing 1949. Shaw, E. S. (1973). Financial deepening in economic development. Oxford University Press, New York. Shrestha, M. B. (2005). Financial Liberalization in Nepal. Ph.D. dissertation submitted to university of Wollongon, Australia. Shrestha, M.K., & Bhandari, D.B. (2008). Financial markets & institutions. Asmita Publication 3rd edition Solow, R.M. (1956). A contribution to the theory of economic growth. Quarterly journal of economics, 70 (1). 65-94.

Globalization: A Trozan Horse "Globalization is a Buzzword That Has No Precise Definition 53

GLOBALIZATION: A TROZAN HORSE "GLOBALIZATION IS A

BUZZWORD THAT HAS NO PRECISE DEFINITION." ...?

Dr. Kanhaiya Ram Bhakta Mathema

Abstract Globalization brings in interconnectedness in economic, cultural, and technological domains via expansion in unrestricted trade. It is based on "one-size-fits-all" policies of IMF and the World Bank that does not click in all circumstances. A very large patch of cloud has appeared in most of the developing countries mired by the parallax of borderless market where goods and services as well as capital are supposed to flow unrestricted benefiting the countries on trade. A very large patch of cloud has appeared in most of the developing countries mired by the parallax of borderless market where goods and services as well as capital are supposed to flow unrestricted benefiting the countries on trade. The state of bailing out in Greek economy can be taken as an example. It more than hurts countries such as Nepal that are economically nascent. The current balance of trade scenario of Nepal embedded with successive deficits rightly presents globalization in countries with nascent economies as a Trozan Horse. To avoid its Trozan Horse image there is the need for concerted efforts in the production frontiers keeping in mind that every dog has its day when it is recognized that there is the possibility of product internationalization, increased capital mobility and knowledge growth provided globalization is perceived to its spirit. Otherwise it simply gives rise to a dilemma whereby someone attempts to be in love simultaneously with two beautiful women. Key Words: Trozan Horse, Globalization, Nepal, Developing Countries, Consensus, Loss and sufferings

Background The dynamics of globalization, though is in motion, is rather engulfed by the red-herrings. Accordingly, it is not that successful towards the sedentary configuration of much coveted economic volatility in many parts of the world. The state of bailing out in Greek economy can be taken as an example. It more than hurts countries such as Nepal that are economically nascent. This article is based on the reviews of some of the published works highlighting the pros and cons of globalization supported by some empirical evidences from the current status of Nepal's state in international trade. The thrust of the same is to present an eye opener to economically nascent countries like Nepal in the contest of globalization that is circumscribed by misapprehension of pareidolia. Dr. Mathema is the Retired Professor of Economics from Tribhuvan University.

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Encyclopedia of Business (2015) defines globalization as a "process by which the economies of countries around the world become increasingly integrated over time. This integration occurs as technological advances expedite the trade of goods and services, the flow of capital, and the migration of people across international borders. The term has been used in this context since the 1980s, when computer technology first began making it easier and faster to conduct business internationally. Globalization can also refer to the efforts of businesses to expand their operations to new countries and markets". The important attribute of globalization is nothing but in simple term means global interconnectedness in economic, cultural, and technological domains. No doubt, globalization has unleashed hosts of meritorious effects in countries irrespective of their economic standings. Nevertheless, the arrays of antagonistic waves against it all over have cast doubt about its benevolence particularly to the developing nations. People who are organizing against globalization are on the rise. "The plain truth is that market liberalization by itself does not lift all boats, and in some cases, it has caused severe damage to poor nations…what's more, there's no point denying that multinationals have contributed to labor, environmental, and human rights abuses as they pursue profit around the globe" (Encyclopedia of Business 2015). "Globalization could be frightening, stimulating, overwhelming, destructive or creative, depending on one's point of view". Actually, it is "one-size-fits-all" policies of IMF and the World Bank that does not click in all circumstances.

Tenet, Upshot and Debate One of the tenets of globalization is no other than lowering of tariffs in trade between the nations to enlarge the trade volume depending upon each other's comparative advantage in the production of goods. The hub has been World Bank promoted trickle down theory that has predominated the thoughts of the bureaucrats and development economists alike up until the decades of the 1980s and early 1990s. Centripetalling the hub among others is Washington Consensus as well along the principles of GATT, actually, globalization was taken with fanfare, however, under the illusion that "what is good for a goose is good for a gander". The ongoing convection is wrapped up within the concept of trickle down theory of growth. Looking at the discrepancies brought about by globalization, it is always better to judge it under the following premise of 2014 Human Development Report ". According to income-based measures of poverty, 1.2 billion people live with $1.25 or less a day. However, according to the UNDP Multidimensional Poverty Index, almost 1.5 billion people in 91 developing countries are living in poverty with overlapping deprivations in health, education and living standards. And although poverty is declining overall, almost 800 million people are at risk of falling back into poverty if setbacks occur. Many people face either structural or life-cycle vulnerabilities. The open secret of the Report mirrors the fact that globalization and by the same token open border economy flattens the globe easing out for the interplay of the multinationals. This is an upshot of globalization no one can bypass at present. Trickle-down economics has become a myth whereby enriching multinationals does not necessarily benefit those who are at the bottom of the road to development (Stiglitz 2014). Stiglitz claims that globalization has not brought the promised economic benefits to some of the poorest nations in the world evidenced by the fact that during the last decade of the twentieth century the number of people living in poverty increased by almost 100 million.


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The west, in general, has greatly benefited from the globalization. The production was moved to cheaper countries, companies started to make more profit, people started to make more money and we are all happy. However, some people in the west lost their job due to that reason. Many miners, for example, were made redundant, because it is cheaper to import coal from China, than to exploit it in "expensive" UK or Germany, where labour cost are high. A lot of companies and manufactures had to quit, because they simply couldn't compete with big corporations, that significantly lowered the process. The developing countries also suffered from the globalization. The foreign industry highly affected their eco-system. People, who frequently work two times longer than in Europe, have very low salaries. In addition, the workers cannot even demand better conditions, because they are under the constant threat of loosing job. After all, the corporations can move wherever they want. So we can say, that corporations have grown in power so much, that they can virtually blackmail the entire governments. "You want to raise the minimal wage in India? Ok, so we are moving to Bangladesh," for example. As everything, the globalization has its plusses and minuses. Unfortunately, the wealth it brought is not distributed equally. it's the richer who gained most of that phenomenon, whereas the poor actually lost. Globalization bears fruit provided it could instill dynamism to Schumpeter's gale in the developing world. Otherwise it just eludes those countries as if they were buying hope. In the process, the in-swing of "beggar thy neighbor" in these countries by no means should be permitted. In the words of James R. Rogers Department Head at Texas A&M University "… the opposition to globalization seen in movements like "Occupy Wall Street" isn't simply about protecting what Americans already have, it also means continuing the poverty of less-developed countries. This doesn't mean that we should accept globalization uncritically, but it does mean that domestic responses will need to be as complicated as its effects". Recent popular titles on globalization, "Lexus and the Olive Tree" Friedman, Thomas (1999) and "Jihad Vs. McWorld (Benjamin R. Barber, 1992)", attest to the seemingly contradictory unifying and divisive forces inherent in globalization. The true spectrum of globalization can be seen from the prism of World Economic Forum Agenda Councils, 2015. The top 10 trends visualized by the Forum can be taken as the externalities diffused by globalization, particularly in the context of developing countries. They are: deeping income inequality, persistent jobless growth, lack of leadership, rising geostrategic competition, weakening of representative democracy, rising pollution in the developing world, increasing occurrence of severe weather events, intensifying nationalism, increasing water stress and growing importance og health in the economy. Reference here is made only those directly connected with economic and financial globalization. Amina Mohammed's reflections on Outlook on the Global Agenda 2015 goes like this," Deepening income inequality: De inequality is one of the key challenges of our time. Income inequality specifically is one of the most visible aspects of a broader and more complex issue, one that entails inequality of opportunity and extends to gender, ethnicity, disability, and age, among others. It was identified as the most significant trend of 2015 by our Network experts. This affects all countries around the world. In developed and developing countries alike, the poorest half of the population often controls less than 10% of its wealth. This is a universal challenge that the whole world must address. While it is true that around the world economic growth is picking up pace, deep challenges remain, including poverty, environmental degradation, persistent unemployment, political instability, violence and conflict. These problems, which are reflected in many parts of this report, are often closely related to inequality.

Globalization: A Trozan Horse "Globalization is a Buzzword That Has No Precise Definition 59 The inherent dangers of neglecting inequality are obvious. People, especially young people, excluded from the mainstream end up feeling disenfranchised and become easy fodder of conflict. This, in turn, reduces the sustainability Inequality is one of the key challenges of our time. Income inequality specifically is one of the most visible aspects of a broader and more complex issue, one that entails inequality of opportunity and extends to gender, ethnicity, disability, and age, among others. Ranking second in last year's Outlook, it was identified as the most significant trend of 2015 by our Network's experts. This affects all countries around the world. In developed and developing countries alike, the poorest half of the population often controls less than 10% of its wealth. This is a universal challenge that the whole world must address. While it is true that around the world economic growth is picking up pace, deep challenges remain, including poverty, environmental degradation, persistent unemployment, political instability, violence and conflict. These problems, which are reflected in many parts of this report, are often closely related to inequality (Mohammed 2015).

Refutation of the Claim Mander et al (2001) evidentially refute the claims made by the proponents of globalization that the period (1970-2000) of economic globalization's most rapid ascendancy - shows that it is bringing exactly the opposite outcome that its advocates claim. The evidence now comes nearly as much from the proponents of globalization as its opposition. Probably the most traumatic impacts of globalization policies - both in terms of poverty-creation, and environmental devastation - have come with the forced shift of local economies away from small-scale diversified agricultural models to the industrial export model, directed by global corporations. They go on to add that economic globalization has only proved to be successful in making global corporations and a few elites wildly wealthy. For example, of the largest 100 economies in the world, 52 are now corporations. In what the UN describes as the "staggering concentration of wealth among the ultra-wealthy," total wealth controlled by people with assets of at least $1 million nearly quadrupled from 1986 to 2000, from $7.2 trillion to $27 trillion. Even with the dot-com crash and the current global financial slump, Merrill Lynch predicts that wealth controlled by millionaires will continue to increase by 8 percent a year, reaching $40 trillion by 2005.

Reality and Lesson Considering the above one has to be cautious to blindly second the versions of the proponents of globalization in countries like Nepal that most of the time suffer from huge deficit in balance of trade lacking euphoria for product and productions. The challenges of globalization in Nepal could be perceived from the fact that there is substantial rise in imports while export has deteriorated right from the 1990s when the image of globalization has started to protrude. In the FY2013 imports surged by 24 percent to Rs 316.21 billion while exports stood at just Rs 44.98 billion. As a result, the country's trade deficit also surged by 27.2 percent to Rs 271.22 billion. It has its adverse implication even in the country's overall balance of payment situation. The country's balance of payments (BoP) surplus declined by Rs 4.51 billion in the seventh month (Nepal Rastra Bank Macro-economic Report, 2013-03-17). The BoP surplus fell to Rs 1.59 billion in the seventh month from Rs 6.1 billion in the sixth, according to the Nepal Rastra Bank (NRB)'s latest Macro-economic Report. The country's foreign exchange reserves also decreased to Rs 437.85 billion as of the seventh month, compared to Rs 439.46 billion in the same period last fiscal year. In the 5 months of 2070, the trade deficit occurred by 20.32 billion (2 kharba 32 arba) higher by 21 per cent that of the previous year. Trade deficit with India is 1 kharba 53 arba 79 caroad and oversees trade deficit at the vicinity of 79 arba 19 corod (The Kathmandu Post , 16 March 2013). According to The Kantipur Daily (2015), the scenario in the present fiscal year is all the more frightening.

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In the first half of the current FY, trade deficit has amounted to Rs.314.00 billion. The import of goods and services during that period has registered at Rs 357.56 billion while the export figure stood at Rs 43.43billion. Citing Nepal Rastra Bank, the Daily says that the deficit has jumped to a staggering mark of Rs 600.19 billion in the last fiscal year. In the last fiscal year, the amount of import was Rs.3333.00billion against the export of Rs.45.14billion. It has actually distorted the overall balance of payment situation of Nepal. The above picture has clearly presented globalization in Nepal as a Trozan Horse. Reaping benefits from globalization is a dilemma whereby someone is attempting to be in love simultaneously with two beautiful women. Nevertheless, the reality is that we should take on the challenges of globalization head on to be besmeared with glimmer of hope and avoid its Trozan Horse image with dynamic efforts in the production frontiers keeping in mind that every dog has its day when it is recognized that there is the possibility of product internationalization, increased capital mobility and knowledge growth provided globalization is perceived to its spirit with a view to penetrating into the international markets.

References Barber, Benjamin R.(1992). Jihad Vs. McWorld, Nelson, Canada Development Research Group (2004) Challenges for developing countries, Development research group, World Bank, June 2004 Encyclopedia of Business (2015). Globalization, Encyclopedia of business 2nd ed. Friedman, Thomas (1999). The lexus and the olive tree, Farrar, Straus & Giroux , New York Jerry Mander, Debi Baker and David Korten (2001). Does globalization help the poor international forum on globalization? IFG bulletin, 2001, Volume 1, Issue 3, Kilgour, David (2000). Globalization for the benefit of all notes for an address by Hon. David Kilgour to the closing session of the 7th World Summit of Young Entrepreneurs September 1, 2000 World Trade Centre, New York Kohut, Andrew and Richard Wike (2008). Assessing globalization benefits and drawbacks of trade and integration Pew research global attitudes project, Washington Mohammed, Amina (2015). Outlook on the global agenda 2015 top 10 trends of 2015 World economic forum Agenda Councils, USA Panel on High-Level Panel on Globalization and the State (2001) Report on 56th session of the United Nations general assembly, second committee, November 2001, New York Patrickbatemaneconomics.blogspot.com Globalization: Who benefits / who loses? Economics, Saturday, 10 September 2011 Schmukle,r Sergio L. and Richard Wike, (2004). Benefits and risks of financial globalization: Pew research global attitudes project Stiglitz, Joseph E. (2002). Globalization and its discontents W.W. Norton & Company Stiglitz, Joseph E. ( 2014). On the wrong side of globalization, The opinionator the opinion page, the great divide, March 15, 2014 The Kantipur Daily (2015). Trade deficit in six months amounted to Rs. 314.00 billion (Translated), 29 January, 2015 The Kathmandu Post (2013). Nepal rastra bank macro-economic report 2013-03-17, The Kathmandu Post, 16 March 2013 UNDP (2014). The 2014 human development report - Sustaining human progress: Reducing vulnerabilities and building resilience Human development report 2014, UNDP

An Analysis of Foreign Employment and Inflow of Remittance in Nepal

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AN ANALYSIS OF FOREIGN EMPLOYMENT AND INFLOW OF REMITTANCE IN NEPAL ...?

Mani Ratna Lamsal

Abstract The percentage of migrants from developing countries to developed and industrialized nations is ever increasing. Because of this increasing tendencies of migrants in worldwide, the inflow of remittance in Nepal after 1990s is increasing significantly. According to World Bank report, some 2-3 millions new migrants leave their homeland each year. Of them, about half goes to industrial nations. Nepalese economy is becoming remittance economy in these days. This paper examines the migration and inflow of remittance in Nepal. It deals with literature review on remittance, the inflow of remittance from various countries, the contribution of remittance to GDP, consumption and expenditure pattern. Keyword: Labour migration, Remittance, Money transfer channels, Destination.

Introduction Migration of people from one place to another has become a common phenomenon since the beginning of human civilization. The migration in the beginning was for the sake of food and exploring new places for security purposes. But, gradually, migration took the shape in diverse forms and now has become a very common around the world. Millions of people from around the world (especially from the developing countries) are migrating (i.e. leaving their homeland) for seeking better employment opportunities, education facilities and for many other purposes. Labour migration for overseas countries has particularly increased after globalization. In Nepal, the migration in overseas countries has rapidly increased especially after the restoration of multi-party democratic system and implementation of liberlization policy since 1990s. Remittance is money transferred from workers abroad (which are called remitters) to their home country. According to IMF, total remittances include three items: workers remittance, compensation of employees and migrant transfers. The proportion of migrants from poorer countries has become increasingly significant. The flow of migrants to industrial countries has also risen. The World Bank (1995) suggests that some 2-3 million new migrants now leave developing countries each year; about half of them go to industrial nations. India has placed itself in first position to inflow remittance receiving $45 billion in 2008 followed by China receiving $34 billion. Mexico, Philippines and Poland have received $26 billion, $18 billion and $11 billion respectively in 2008. Bangladesh and Nepal are other major remittance earning countries in the world (Ratha, et al, 2007). Mr. Lamsal is the Lecturer of Economics at Global College of Management.

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Mani Ratna Lamsal

Nepalese economy is passing through poverty and stagnation and suffers from inherent structural constraints (Dahal, 2004). The master-bottlenecks of Nepalese economy are: landlockedness, rugged topography with limited croplands, lack of basic infrastructures, high extent of poverty, lack of commercial exploitation of natural resources and optimal utilization of human resources, rampant corruption, absence of good governance, etc. The average GDP growth rate is around 3.5 percent p.a., which is too low in SAARC region. In such situation, remittance is becoming a crucial component/ base to rescue Nepalese economy from the lowlevel equilibrium trap, which could provide a new and sustainable life for Nepalese economy. Acceleration in overseas migration and remittances has been instrumental for survival, poverty alleviation and improvement in living standard of the people (Seddon, et al, 1999). Remittance has been the single most dynamic factor to deal with dismal scenario of the Nepalese economy. International migration for foreign employment has become strategy for survival of the rural subsistence household,(Shrestha, 2004). Foreign employment has increased the foreign exchange reserve, BOP is surplus, increased the liquidity in banking sector.

Research Methodology The main goal of this study is to analyze the role of foreign employment and remittance in Nepal. The required data for this study has been taken from secondary sources- various issues of economic survey, publications of Nepal Rastra Bank, published and unpublished research articles, books, etc. A descriptive, analytical and quantitative research design has been used for this study.

Foreign Employment: Historical Perspectives Labour migration from the developing countries has been one of the major sources to fill up the labour shortage in developed and industrialized countries. A large number of Turks migrated to Germany, Pakistanis to Saudi Arabia and the Mexicans to the United States. Before world war- II, the purpose of migration was settlement in North America, Latin America and the Western Europe. However, since the world war - II, the settlement migration has changed in the form of temporary migration of the labour - as seasonal or contract workers. After the oil boom in the Gulf, the destination of migrants from Asian developing country becomes Gulf countries due to rapid increase in demand for labour. Every year on average 6 to 7 million people migrate from one country to another country particularly from developing to developed countries in search of foreign employment (Shrestha, 2004). The migration of Nepalese people for employment abroad has a long history. Nepalese started foreign employment by travelling to Lahore in early 19th century to join the Sikh ruler Ranjit Singh. Labour migration started after Anglo-Nepal Treaty of peace and Friendship of 1816. It has recruited 3000 Nepalese soldiers in Brithish Gorkha. Signing of peace and friendship Treaty between India and Nepal in 1950 has granted Nepalese workers to move in India without work permit (Kayestha, 2002). Nepalese workers started to migrate beyond India with the enactment of Foreign Employment Act 1985. The major destinations for Nepalese workers are: Malaysia, Gulf nation, Hong Kong, Singapore, South Korea, Macao, European nations, Japan, etc. Remittance has become one of the major companies of Nepal's GDP since 1990s.


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Literature Review on Remittances In the comparison of international studies, very few studies have been done related to foreign employment and remittance in Nepal. Different studies have shown different findings about remittance in Nepal. Some of the past studies have been reviewed to gain some theoretical knowledge about foreign employment and remittances. Highlighting the role of remittance, Sigdel (2010) suggested that remittance plays a central role in the economies of many labour sending countries including Nepal. The flow of remittance does it only determine the level of economic growth but its meaningful utilization develops the remote areas, boosts up the economic activities, uplifts the living standard of people, increases the employment and output and GDP in long-run. Neupane (2010) in his study 'An Analysis of Impact of Remittance on Nepalese Economy' said that remittance is one of the important avenues of national economy not only to minimize the problem of unemployment but to minimize the level of poverty and foreign exchange constraints. He further writes that Nepalese economy will face serious economic downturn if there is reduction in flow of remittance. Pant (2006) in his study ' Remittance inflow in Nepal: Economic impact and policy option' argued that remittance can generate a positive effect on the economy through various channels such as consumption, saving, investment, economic growth, reduction in poverty and inequality. A paper 'Remittance in the Pacific Region' presented in IMF by Browne and Mineshima (2007) claimed that Asian countries that receive more remittance include China, India, Nepal, Bangladesh, Srilanka and Philippines. Their aim is to increase saving and investment when remittance is deposited in financial institution, it provides easy credit for various purpose which promotes development in remittance recipient countries. Are there any costs of remittance with a number of benefits? To answer the question, Robert (2004) has presented following costs and benefits of remittance. Benefits 1.

4.

As a stable source of foreign exchange that eases foreign exchange constraints and helps finance external deficits. Is a potential source of saving and investment for capital formation and development. Facilitates investment in children's education and human capital formation. Raise the standard of living of recipients.

5.

Reduces poverty and income inequalities

2.

3.

Costs 1.

Eases pressure on govt. to implement reforms and reduce external imbalances (moral hazard) 2. Reduces saving of recipient families and thus negative impact on growth and development. 3. Reduces labour effort of recipient families and thus negatively impact on growth. 4. Migration leads to brain drain and negative impact on the economy that are not fully compensated by remittances transfer. 5. Increases income inequalities.

64

Mani Ratna Lamsal

Factors Affecting Labour Movement and Foreign Employment According to the report of Population Census 2011 A.D. published by CBS, the annual population growth rate of Nepal is 1.35% p.a. Every year 4,50,000 labour force enter into Nepalese Job market in search of job (Economic Survey, 2012/13). Hardly, one third of it can get some jobs in Nepal. It shows higher rate of unemployment. Globalization should be associated with an increase in relative demand for worker in industrial economies. Wage and opportunity gaps, political instabilities, unemployment, low salary structures, are other causes of labour migration. Likewise, decrease in share of young people in developed countries and increase in Asia, Africa and other country is another important cause of labour migration. Developed countries and getting cheaper labour force while poor countries gain from comparatively higher wages and remittances.

Foreign Employment and flow of Remittances Migration from developing to developed countries has increased in the recent days. It's importance and impact has been felt in every aspects of the life of the country. Migration and foreign employment has become a way of life to many youth of the country. In Nepal about 4,50,000 productive youths enter the labour market annually. The three year interim plan has set an objective of reducing country's unemployment situation there by reducing poverty level; enhancing contribution of foreign employment in strengthening of country's economy and managing safe and dignified foreign employment. The total number of workers gone for foreign employment during the period between FY 1994/95 and FY 2011/12 has reached 24,37,111. Various reports show that large numbers of Nepalese workers also have gone abroad for foreign employment without government permit. Based on official and unofficial records, more than 3 million Nepalese citizens gone abroad for foreign employment (Economic Survey, 2013). Likewise, recent reports show that in an average, more than 1500 Nepalese people are going abroad in search of job. The workers remittances for some selected countries are presented in Table 1 and Table 2. Table 1: Workers Remittances for selected countries(Amount in US$ Million) Country

1996

2000

Albania

500

531

Bangladesh

1345

1958

Brazil

1866

1113

Columbia

635

1128

Croatia

603

531

India

8453

9054

Mexico

4224

6573

Sudan

220

638

Source: Sigdel, Bamadev (2010), Table 1, P-113


65

Table 2: Remittances inflow in Selected SAARC Countries (US $ million) Country

1997/98

1998/99

1999/00

2000/01

2001/02

2002/03

Bangladesh

1525.4

1705.7

1949.3

1882.1

2501.1

3062.0

India

11875.0

11830.0

12290.0

12125.0

14807.0

15170.0

Pakistan

1490.0

1060.0

983.0

1086.5

2389.0

4236.8

Sri lanka

817.7

867.5

930.5

979.0

1040.5

NA

Source: Sigdel, Bana Dev (2010), Table 2, P-114 Table 1 and Table 2 show the inflow of remittances in selected countries. As shown in Table -1, India received the largest amount of remittance i.e. US$ 8453 and US$9034 million in 1996 and 2000 respectively. Likewise, Table 2 shows that India, Pakistan, Srilanka and Bangaladesh are largest recipient of remittance in South Asia. The world wide flow of remittances in all over the world has been presented in Table 3. Table 3: Global flows of International Migrant Remittances ($ million) 2000

2001

2002

2003

2004

2005

All developing countries

85,231

96,348

116,697

145,016

163,176

188170

Low income countries

21,792

25,897

32,048

39,572

40,534

45815

Middle income

63,439

70,451

84,649

105444

122642

142355

Lower MICS

43263

48079

61485

75319

86076

95325

Upper MICS

20176

22372

23164

30125

36566

47030

East Asia and pacific

16682

20105

29476

35309

38774

43934

Europe and central Asia

13383

12980

14386

17299

22691

30812

Latin America and Caribbean

20127

24381

28097

34856

41103

47556

Middle east and North Africa

13202

15082

15595

20702

23419

23542

South Asia

17212

19185

24155

31094

29787

34883

Sub-sahara africa

4625

4615

4988

5756

7403

7443

131786

147015

169688

204671

230495

257496

World

Source: International monetary fund, 2007 Table 3 represents the global flows of remittances from international migrants. It shows the data between 2000 to 2005 A.D. The first destination for maximum remittances inflow are all developing countries because of maximum availablity of labour force, which is followed by lower middle income countries (MICS), Latin America and caribbean, upper middle income countries (MICS), Low income countries, South Asia. In 2000, total flow of remittances in world was $131,786 million while it has reached to $257496 in 2005. Which country of the world sends maximum remittances to stood at top first position? It is United States followed by Saudi Arabia, switzerland, Germany, etc. The list of top remittances sending countries with their ranks (for 2005) is presented in Table - 4.

66

Mani Ratna Lamsal

Table-4: Top Remittances Sending Countries (US $ milion) Rank

Country

1995

2000

2001

2002

2003

2004

2005

1

United States

22181

30961

34592

36126

36545

39305

41072

2

Saudi Arabia

16594

15390

15120

15854

14783

13555

14318

3

Switzerland

10114

7591

8380

9223

11411

12839

13200

4

Germany

11270

7761

7609

9572

11172

11983

12519

5.

Spain

868

2059

2470

2914

4012

6977

7733

6.

Russia

3939

1101

1823

2226

3233

5534

7651

7.

Luxemborg

2215

2720

3138

4011

5077

6009

6599

8.

Italy

1824

2582

2710

3579

4369

4745

5815

9.

Netherlands

2802

3122

2850

2889

4238

5153

5686

10.

Malaysia

1329

599

634

3826

3464

4991

4991

11.

France

4935

3791

3960

3804

4391

4883

4867

12.

Lebanon

-

-

-

2521

4081

4233

4233

13.

Korea Rep.

634

972

1014

1474

1852

2497

3336

14.

United Kingdom

2581

2044

3342

2439

2624

2957

3060

15.

Belgium

3252

3588

3958

1446

2329

2618

2756

16.

China

2602

17.

Austria

2543

18.

Kuwait

19.

Isreal

2287

20.

Oman

2257

~

2402

Source: IMF Remittance Statistics, 2007 Based on Table 4, the top remittance sending countries are United States, Europe and the middle east. When we compare the data of United States in 1995 and 2005, the remitted amount has almost doubled from US$22181 to US$41072. Based on the data for 2005, the top remittance sending countries are ranked from 1 to 20 i.e. to 20 countries and listed in Table-4. It has been already mentioned that more than 1500 Nepalese workers leave Nepal in search of job. The number of migrant workers is ever increasing year after year. The detail of number of Nepalese workers abroad is given in Table 5.


67

Table-5: Number of Nepalese Workers Abroad Fiscal Year

No. of Workers

2002/03

347062

2003/04

452792

2004/05

591695

2005/06

756039

2006/07

959985

2007/08

1203657

2008/09

1413500

2009/10

1702239

2010/11

2055685

2011/12

2437111

2012/13*

2713898

Source: Department of Foreign Employment * First eight months Table 5 shows the total number of Nepalese workers working abroad up to different years. Up to FY 2002/03, total number of working abroad was 347062 while it has been reached 2437111 until the end of FY 2011/12. The major destinations of Nepalese workers are Malaysia, Saudi Arabia, Qatar, UAE, Kuwait, South Korea, etc. The main destinations have been presented in Table 6. Table-6: Destination of Nepalese Migrant workers in FY 2012/13 S.N. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.

Country Qatar Malaysia Saudi Arab UAE Kuwait Bahrain Oman South Korea Lebanon Israel Afghanistan Japan Others Total

Male 54639 97543 60576 32399 6150 2318 2127 1613 184 30 211 650 1634 260074

Female 582 4697 283 5686 3408 565 683 151 158 29 2 101 368 16713

Source: Department of Foreign Employment. Note: Percentage values are calculated by researcher.

Total 55221 102240 60859 38085 9558 2883 2810 1764 342 59 213 751 2002 276787

Percent 19.96 36.94 21.99 13.76 3.46 1.05 1.01 0.60 0.12 0.02 0.08 0.28 0.73 100

68

Mani Ratna Lamsal

Table No. 5 shows that the total number of Nepalese people who have gone for foreign employment in FY. 2012/13 is 276787 (2713898-2437111=276787). Of this number, 16,713 are women while 260074 are men. Regarding to their destination, Table No. 6 clarifies that Malaysia is the first destination with 36.94 percent labour for followed by Saudi Arab (21.99%), Qatar (19.96%), UAE (13.76%) and Kuwait (3.46%) respectively.

Inflow of Remittances in Nepal Employment in foreign countries provides opportunity to work in other countries. Those people working abroad send money in the home country. The proportions of households that receive remittances are 56 percent in Nepal. The average income transfer in the form of remittance is Rs. 80,436 (in nominal terms) per recipient household (NLSS-III, 2010/11). Of the total remittances, 77% of remittances are transferred by person, 19 percent via financial institution, 2 percent via hundi and 2 percent from other means. According to NLSS-III, 79 percent of the total remittance received by the household is used for daily consumption, 7 percent is used for loans repayment, 4 percent for education, 2% for capital formation, 4 percent for household property, etc. Out of the total inflow of remittances, 85 percent remittances come only from five countries (Malaysia, Qatar, Saudi Arab, Japan, and America). The largest among of remittances i.e. 36 percent of total comes only from Malaysia (Kantipur Daily, May 6, 2014). The summary statistics of remittance inflow as prepared by Nepal living stndard summar-III is presented in Table 7. Table 7: Summary Statistics of Remittances 1995/96 to 2010/11

Source: Nepal Living Standard Survey, 2010/11


69

The year-wise inflow of remittances has been presented in Table No.8 Table-8: Year wise inflow of Remittances (RS Billion) Fiscal year 1990/91 1991/92 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/2000 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10 2010/11 2011/12

Remittance income (Rs. billion) 0.550 0.423 0.550 0.223 2.906 2.660 2.938 4.084 6.520 6.031 47.216 47.536 54.203 58.587 65.544 97.688 100.144 142.68 209.70 231.73 253.55 359.55

Annual percentage change -23.1 30.0 -59.4 1203.1 -8.4 10.4 37.4 59.6 -7.5 682.8 0.67 14.0 8.1 11.9 49.0 2.5 42.2 47.0 10.5 9.4 41.8

Remittance income/GDP (%) 0.46 0.28 0.32 0.11 1.33 1.07 1.05 1.36 1.91 1.51 10.69 10.35 11.0 10.9 11.1 14.9 13.8 17.5 21.2 19.4 18.5 23.1

Source: Various issues of economic survey, MOF. Table 8 shows the various aspects of remittance. It depicts year wise inflow of remittances since FY 1990/91 to FY 2011/12, the annual percentage change in inflow of remittance and the ratio of remittance income to GDP of Nepal. In FY 1990/91, the total amount of remittance income received by Nepal was Rs. 550 million (i.e. Rs. 0.550 billion). Which was 0.46 percent of GDP. Up to FY 2000/01, there is volatile in inflow of remittances. We can see many negative as well as positive annual changes in the inflow of remittances. However, after 2000/01, there is only positive annual percentage change in inflow of remittance in Nepal. The remittances inflow has increased by 682.8 percent in 2000/01 as compared with previous fiscal year 1999/00. Likewise, the FY. 2005/06, 2008/09 and 2011/12 are remarkable years in which there are significant inflow of remittances in Nepal. The ratio of remittances to GDP are also increasing. It is also good symbol for Nepalese economy, which is going to be remittance economy.

Conclusion and Recommendations Migration of labour from labour surplus (i.e. underdeveloped) country to labour-deficit country (developed or industrialized country) is becoming one of the major issues in these days. The

70

Mani Ratna Lamsal

migrant worker's earning is sent back to their home country by various channels like: banks, money transfers, hundi system, via friends, etc. Appropriate use of remittance at various micro level help to uplift macro economic activities. Proper use of remittances reduces the poverty, increases the availability of foreign currency, maintains the BOP surplus, helps in business expansion, etc which are key macroeconomic activities. In reality, the contribution of remittances to national economy is more than described by official data. A significant proportion of the remittances enters into nation by unofficial channels. In recent years, the share of remittances in total foreign exchange earning has exceeded income from tourism and export. So, every concerned people says that Nepalese economy has been largely supported by remittances. In the year 1994/95 the number of workers going abroad as job seekers was just 2159 which has reached to 2437111 by the end of 2011/12. The inflow of remittances was Rs. 0.550 billion in 1990/91 which has reached to Rs. 359.55 billion in FY 2011/12. Despite the various importance of remittances, nearly 79 percent (See Table 7) remittance income is used for consumption purpose, purchasing land and houses, etc. But, there is lacking of appropriate use of remittances in productive sectors. Some important recommendation for concerned person/ authorities are: provide easy access to information about foreign employment; job-related training which increases the efficiency, productivity and income; providing all services related to foreign employment from one place, increasing the number of destination, managing the inflow of remittances from formal channels; formulating suitable policies to motivate savings and productive investment of remitted income by discouraging unnecessary consumption.

References Browne, C. and A. Mineshima (2007). Remittances in the pacific region, IMF Working Paper, IMF Washington DC. Dahal, M.K. (2004). Nepalese economy: Towards building a strong economic nation - state in Nepalese economy. Central Department of Economics (CEDECON), Tribhuvan University (TU), Kirtipur Kantipur Nepali National Daily, Tuesday, May 6, 2014. Kayastha, Narendra L. (2002). Nepalese migrant workers and remittance economy of Nepal. A paper submitted to faculty of humanities and social sciences at Tribhuvan University. Ministry of Finance, Economic survey of Nepal (2012/13), Government of Nepal. Nepal Living Standard Survey - III ( 2010/11). Central bureau of statistics, Kathmandu. Neupane, Nirmal Kumar ( 2010). An analysis of impact of remittance on Nepalese economy. A dissartation submitted to Central Department of Economics, T.U. Pant, B. (2006). Remittances inflow to Nepal: Economic impact and policy option. Nepal economic review, Nepal Rastra Bank, Kathmandu. Ratha, D. et al (2007). Remittances trend 2007: Migration and development Brief - 3, Migration and Remittance Team, World Bank. Robert, B. (2004). Remittance in Armenia: Size, impact and their contribution to develop-ment, USAID. Seddon, David; Jagannath Adhikari and Ganesh Gurung ( 1999). The new lahures: Foreign employment and remittance economy of Nepal. Kathmandu: Nepal Institute for Development Studies Shresthe, Bijaya (2004). Foreign employment and the remittance economy of Nepal in Nepalese economy. Kathmandu: Central Department of Economics (CEDECON), Tribhuvan University (TU), Kirtipur Sigdel, Bama Dev ( 2010). Dimentions of Nepalese economy. Human Actions for Rapid Development (HARD), Kathmandu. World Bank ( 1995). World development report. Washington DC.

Non-financial Performance Measurement Practices in Nepalese Commercial Banks

71

NON-FINANCIAL PERFORMANCE MEASUREMENT PRACTICES IN NEPALESE COMMERCIAL BANKS ...?

Naba Raj Adhikari

Abstract Purpose - The purpose of this paper is to examine the non-financial performance measurement practices in Nepalese commercial banks. Design/methodology/approach - Descriptive as well as exploratory research design has been used. Data were obtained through self administered structured questionnaire and interviews with high authority of five commercial banks established before 1990s. It has followed judgmental and convenience sampling technique and a total of 27 usable responses were gathered and used in the data analysis. Findings - Nepalese commercial banks are moderately using a limited number of non-financial measures while measuring their performance. Strategic customer related non-financial measures have not been used yet in both types of banks. Lack of research and management information system are the main problems encountered during the performance measurement practices. Originality/value - The paper shows that one important practical implication to emphasize the use of nonfinancial measures that are fundamental to the long term success of organizations. Key words - Performance Measurement, non-financial measures, out- ward looking, long-term focus, intangible assets, commercial Banks. Paper type - Research paper

Mr. Adhikari is the Asst. Deon and Associate Professor of Management at Tribhuvan University.

72

Naba Raj Adhikari

Measures

1960's

1970's

1980's

1990 onwards

Main Focus

Financial

Financial

Financial / Managerial

Financial / Non Financial

Key Developments

Accounting Earnings

Accounting Earnings

Unit Costs

Balanced Scorecard

Earnings Per share

Residual Income

Joined Budgets

Economic Value Added

Return on Investment

Return on Investment

Operating Profits

Activity-Based Costing

Net Present Value

Cash Flows

(Source: Swamy, 2002) Namazi & Abhari (2010), pointed that prior to 1980's, organizations adopted financial measures (net profit, return on equity, return on investment, etc.) to appraise their performance. According to Johnson and Kaplan (1987), performance measurement based on traditional cost or management accounting system that was introduced in early 1900s is no longer suitable and less useful in today's business environment.


S.N.

Name of bank

73

Type

Establishment year

1.

Nepal Bank Limited

Government owned

1957

2.

Rastriya Banijya Bank

Government owned

1966

3.

NABIL Bank

Joint venture

1984

4.

Nepal Investment Bank Limited

Joint venture

1986

5.

Standard Chartered Bank Nepal Limited

Joint venture

1987

74

Naba Raj Adhikari

Table No.3 Respondents on the basis of banks type Banks type

Number of respondents

Percent

Government owned

15

55.56

Joint venture

12

44.44

Total

27

100

Source: Field Survey 2014

Limitations of the study This study has considered only five commercial banks operating in Nepal. Primary data were collected through self administered structured questionnaire, observation and unstructured interview with the high authority of banks. Therefore the study suffers from the use of small samples.

Discussions and findings Different non-financial measures have been considered to know the use of these measures by Nepalese commercial banks. Table No.4 The existing practices over non-financial performance measures in Nepalese commercial banks (Strongly disagree = 1 Strongly agree = 5)

Cost per customer Revenue per customer Customer retention rate Customer complaints Customer satisfaction index Customer loyalty index Market share growth Percentage of on- time deliveries Process efficiency to provide services Accuracy of handling transactions Employee satisfaction scores Transactions per employee Employees training programmes Employee turnover rates Employee skill levels Qualification growth of employee Implementation of employee suggestions rates Number of employees Corporate social responsibility Number of ATMs Number of branches Field survey 2014

Minimum

Maximum

Mean

2.00 2.00 2.00 2.00 2.00 2.00 3.00 3.00 3.00 3.00 3.00 2.00 3.00 2.00 3.00 3.00 3.00 3.00 2.00 3.00 3.00

3.00 4.00 4.00 5.00 3.00 3.00 5.00 5.00 4.00 5.00 4.00 5.00 5.00 4.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00

2.6667 2.7037 3.3333 3.7407 2.6296 2.7037 3.5556 3.8889 3.6667 4.0741 3.3704 3.3704 4.2593 3.0000 3.8148 4.0741 3.8889 3.9630 3.5556 4.1852 4.2222


75

The above mentioned table indicates that the mean value of customer satisfaction index, customer loyalty index, new customer acquisition rate, cost per customer, revenue per customer and employee turnover rates are less than three. It means that these indicators approximately not in use by Nepalese banks. Furthermore strategic non-financial measures like customer related measures have not used. Employee training programmes, no. of ATMs, no. of branches, qualification growth of employee, number of employees and accuracy of handling transactions are moderately used. The other measures are highly nominal in use. It concludes that Nepalese commercial banks are moderately using a limited number of non-financial measures while measuring their performance. But the respondents have expressed their views towards the significant importance of non-financial performance measures in performance measurement system. Difficult to quantify the qualitative information related with non financial measures, lack of research and study, lack of information and management information system are the main problems encountered during non-financial measurement practices in commercial banks under this study. Financial measures have been significantly used while measuring the performance in Nepalese commercial banks.

Conclusions Maintenance of an effective performance management system is a fundamental issue that every organization must continuously pay attention in order to ensure its survival. The discussion and analysis of this study reveals that Nepalese commercial banking sector has relying on the use of financial measures. Non-financial measures have got negligible importance in evaluating the performance. Strategic customer related non-financial measures have not been used. It is not a good symptom for Nepalese commercial banks to its long term success. Similarly lack of research and lack of management information system are the main problems encountered during the use of non-financial measures.

Implications for Future Research While deciding conclusions of this study some possible areas that can be explored in future research came into existence. A comparative study on performance measurement practices and organizational performance can be conducted between joint ventures banks and private commercial banks in Nepal. Similarly organizational performance can be explored before and after the merger of Nepalese commercial banks.

Reference Bryant, L., Jones, D.A. and Widener, S.K. (2004). Managing value creation within the firm: an examination of multiple performance measures. Journal of management accounting research, Vol. 16, pp. 107-31. Fleming, D.M., Chow, C.W., Chen, G. (2009). Strategy, performance-measurement systems, and performance. A study of Chinese firms, international journal of accounting, Vol. 44, No. 3, pp. 256-278.

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Naba Raj Adhikari

Johnson, H.T. and Kaplan, R.S. (1987). Relevance lost: The rise and fall of management accounting. Harvard business school press, Boston, MA. Joiner, T.A., Spencer, X.S., and Salmon, S. (2009). The effectiveness of flexible manufacturing strategies: The mediating role of performance measurement systems. International journal of productivity and performance measurement, Vol. 58, No. 2, pp. 119-135. Kanji, G. K. (2002). Performance measurement system. Total quality management, Vol. 13, No. 5, pp. 715-728. Kaplan, R.S. and Norton, D.P. (2001). The strategy-focused organization: How balanced scorecard companies thrive in the new business environment. Harvard business school press, Boston, MA Kaplan, R.S. & Norton, D.P. (1996). The balanced scorecard: Translating strategy into action. Boston: Harvard business school press. Lebas, M.J. (1995). Performance measurement and performance management. International journal of production economics, Vol. 41, pp.23-35. Moullin, M. (2007). Linking performance measurement and organizational excellence. International journal of health care quality assurance, Vol. 20, No. 3, pp. 181-183 Mullins, L.J (2010). Management and organizational behavior. England: Pearson Education Limited NABIL Bank limited (2013). Annual report. Kathmandu: NABIL Bank Limited. Namazi, M., & Abhari, H. (2010). An investigation of the balanced- scorecard's applications for performance measurement of the firms accepted in the Tehran securities exchange market. Journal of applied sciences research, Vol. 6 No. 8, pp. 943-955 Neely, A. (1998). Measuring Business Performance. Profile books, London, UK. Neely, A.D., Mills, J.F., Gregory, M.J. and Platts, K.W. (1995). Performance measurement system design-a literature review and research agenda. International journal of operations, and production management, Vol. 15, No. 4, pp.80-116. Nepal Investment Bank limited (2013). Annual report. Kathmandu: Nepal Investment Bank Limited. Nepal Rastra Bank (2013). Banking and financial statistics, Kathmandu. Nepal rastra bank. Nepal Rastra Bank (2013). Bank supervision report. Kathmandu: Nepal Rastra Bank. Standard Chartered Bank Nepal Limited (2013). Annual report. Kathmandu: Standard Chartered Bank Nepal Limited Swamy R. (2002). Strategic performance measurement in the new millennium. CMA management, May, pp.44-47

Dividend Policy, Performance, and the Stock Price in Nepal

77

DIVIDEND POLICY, PERFORMANCE, AND THE STOCK PRICE IN NEPAL ...?

Dr. Nabaraj Adhikari

Abstract Several studies have been documented in the extant literature on the relevance and irrelevance of dividend policy or dividend policy and enterprise performance in developed and emerging capital markets as well as a few studies on dividends and stock prices in pre-emerging capital markets. There is lack of empirical studies on dividend policy, performance, and the stock price in the extant literature. This paper, therefore, aims at investigating the dividend policy, performance, and the stock price in the pre-emerging capital market of Nepal employing descriptive cum analytical research. A priori hypothesis between relationship of the variables indicating dividend policy, performance and stock price are set based on empirical studies, and tested on the data from 22 listed enterprises covering a 5-year period, 2009 to 2013. All regular dividend paying enterprises are selected and data obtained are analysed using portfolio analysis and cross-section regression approach. The findings reveal that higher the dividend payout, better the performance and that a dividend is a major factor affecting the stock price and current year dividend per share affects negatively while dividend paid in the past year and return on equity influence positively the stock price. The implication of the findings is that devoting adequate time in designing and disseminating a dividend policy are desired in improving the performance of listed companies and enhancing the stock price in the preemerging capital markets. As the paper addresses the gap in the extant literature, the findings could be useful for research scholars, financial analysts and investors. Keywords: Capital market; dividend policy; performance; pre-emerging; stock price JEL classifications: C 31; C 87; G32; G 35

1

The earlier version of this paper was presented at 2nd International Conference on Economics and Finance organised by Nepal Rastra Bank during 26-28 February, 2015, Kathmandu, Nepal

*

Dr Adhikari is the Director at Securities Board of Nepal (SEBON), Lalitpur, Email: [email protected]

78

Nabaraj Adhikari

Introduction There is considerable debate on whether dividend payouts affect value of the stock. Some studies state that dividends increase shareholder wealth (Gordon, 1963; Walter, 1963). Some other studies state that dividends are irrelevant (Miller & Modigliani, 1961; Black & Scholes, 1974; Miller & Scholes, 1978); and still other studies argue that dividends decrease shareholders' wealth (Litzenberger & Ramaswamy, 1979; Naranjo et al., 1998). Despite the numerous studies, dividend policy remains an unresolved issue in corporate finance. Amidu (2007) reveals that dividend policy affects enterprise performance as measured by its profitability. The results show a positive and significant relationship between return on assets, return on equity, growth in sales and dividend policy. Banz (1981) reveals that average returns on large stocks are lower while average returns on small stocks are higher. Bolster & Janjigian (1991) indicate that the value of the enterprise is greater for stocks with higher dividend yields as compared to stocks with lower dividend yields. In line of these studies, the present paper aims to find the relationship between dividend policy and performance of the listed company in Nepal. Solomon (1963) contends that dividends may offer tangible evidence of the enterprise's ability to generate cash, and as a result, the dividend policy affects the value of the enterprise. Brennan (1970) proves that if effective capital gains tax rates are lower than effective rates on dividend income, then investors will demand a higher rate of return on securities with higher dividend payout. Pradhan (2003) argues that the share value is affected by dividend payments. It is thus the other issue to be addressed in this paper is: Whether there is any influence of dividend policy on stock price using more recent data? The remainder of the paper is organised as follows. Section 2 provides the review of literature. Research methodology is presented in Section 3. Analysis of data is made in Section 4. Section 5 presents the findings and discussion. Lastly, Section 6 offers the policy implications.

Literature review Miller & Modigliani (1961), designated as MM hereafter present a comprehensive argument for dividend irrelevance by holding the enterprise's investment policy constant in their analysis of dividend policy and showing with perfect capital markets in which there is an absence of taxes, rationality, and perfect information that dividends can be replaced at no cost; thus dividend policy is irrelevant to the valuation of share. MM views dividend policy as the following trade-off: retaining earnings versus paying cash dividends and issuing new shares of stock. According to them an enterprise can offset any dividends it pays by issuing new shares of stock. Since any dividend policy can easily be offset, they argue that dividend policy does not influence the value of share. Friend & Puckett (1964) use cross-section data to test the effect of dividend on stock price. Prior to this work, most studies had related stock prices to current dividends and retained earnings, and reported that higher dividend payout was associated with higher price earnings ratios. The study uses dividends, retained earnings and lagged earnings price ratio as independent variables. Symbolically, Pt = a + bDivt + cREt + d (E/P)t-1

(1)


79

The study suggests that there is little basis for the customary view that in the stock market generally, except for unusual growth stocks, a rupee of dividends has several times the impact on price of a rupee of retained earnings. Khan & Khan (2012) studies the dividend policy and stock prices by taking a sample of 131 companies listed in the Karachi Stock Exchange for a period of 10 years from 2001 to 2010. They use panel data approach to explain the relationship between stock dividend along with cash dividend and stock prices after controlling the profit after tax, earnings per share and return on equity. The findings indicate that dividend policy has significant positive effect on stock prices. Masum (2014) shows the relationship between dividend declaration and its impacts on market price of shares of 30 commercial banks listed in Dhaka Stock Exchange (DSE) for the period of five years from 2007- 2011. The model employed is:

Where, DY is dividend yield, RR is retention ratio, PAT is profit after tax, earnings per share, ROE is return on equity, ?t is the specific characteristics measure of each bank called unobservable heterogeneity, and ?t is a parameter for time dummy variables which is equal for all banks in each year but changes over time and ? is the error term. The empirical estimation of the model reveals that return on equity and earnings per share have statistically significant positive impact on stock prices of the commercial banks of Bangladesh. The assumption of perfect market, no taxation, no transaction cost, possibility of arbitrage, etc., are over simplified and it does not apply in the real world (Dhanani, 2005). For example, in Nepal, the capital market contains all sort of imperfections. Moreover, there is absence of empirical studies on dividend policy, performance, and the stock price in the extant literature. A brief review of capital market trend during mid-July 2008 to mid-July 2011 reveals that on 31 August, 2008 NEPSE index was reached to 1175.38 as the record points and on 15 June 2011, NEPSE index was decreased to 292.31 as the lowest points and within a year also there is a wide deviation between the highest and lowest points of the NEPSE index. NEPSE index rose as high as 1175.38 points as on 31 August, 2008 and as low as 609.46 points as on 22 January, 2009 leading to have 565.92 points deviation between the highest and the lowest index in a single year starting from mid-July 2008 to mid-July 2009. These fluctuations in the index were occurred without having any definite economic and other reasons. Such a fluctuation in market index can be considered quite high and undesirable for the credibility of capital market in the country. In view of the gap in the extant literature as well as in the context of speculative market scenario of the country as aforementioned, it is interesting to investigate dividend policy, performance, and the stock price of the enterprises in Nepal.

Research methodology This section deals with a description of the research methodology employed in addressing the issues of this study.

80

Nabaraj Adhikari

Target population, data source, and sampling procedure The population for this study consists of the enterprises listed on the Nepal Stock Exchange Ltd. (NEPSE). In mid-July 2013, there were 230 enterprises listed on NEPSE. The enterprises are selected based on the availability of information. The criteria by which the enterprises are included in the sample are: (i) The enterprises must have available data for all years, that is 2009-2013. (ii) The enterprises must have been listed on NEPSE before the aforementioned period of time. A review of data sources: individual annual reports of listed enterprises and annual trading reports of NEPSE reveal that till mid-July 2013, there were 22 listed enterprises paying dividends regularly for the study period mid-July 2009 to mid-July 2013 with the required data for the purpose of the study. The reason for selection for 5 years' time span is to have a large number of enterprises having uninterrupted dividend payouts in the sample and that one business cycle is completed in 5-7 years (Rafique, 2012). Thus, cross-sectional data of 22 listed enterprises (first 17 are financial and last five are non-financial) for the period of 2009 to 2013 (inclusive) with a total of 110 observations are used in the study as presented in Appendix 1. Basic regression model and variables with hypothesized signs To examine the relationship between dividend policy and stock price of the enterprise, the following model developed based on empirical findings is employed with the aid of Statistical Package for Social Science (SPSS) 20: Pit = a0 + a1 EPSit + a2 ROEit + a3 BETAit + a4 DPSit + a5 LAGDPSit + a6 REPSit + µit (3) Where, the variables and hypothesised signs are as follows: 'Pit' is per share market price of enterprise 'i' in period't'; it is year-end closing price of the share that indicates the value of the enterprise. It is dependent variable in the model. 'EPSit' is earnings per share of enterprise 'i' in period't', that is, the amount of earnings per each outstanding share of an enterprise's stock. Based on Khan & Khan (2012); & Masum (2014), it is hypothesised that per share market price is positively related to the earnings per share. 'ROEit' is return on equity of enterprise 'i' in period't' which is net income after tax divided by shareholders equity. Shareholders' equity is share capital plus reserves and surpluses. Based on Khan & Khan (2012); & Masum (2014), it is hypothesised that per share market price is positively related to the return on equity. 'BETAit' is systematic risk of the share of enterprise 'i' in period't' and is obtained from the following formula: ? = COV (return on per share and return on market)/ market variance. BETA is considered proxy for enterprise risk in various empirical studies and is referred to as a measure of the sensitivity of the asset's return to variation in the market return, its systemic risk (Rozeff, 1982; Alli et al., 1993; Holder et al., 1998). Based on Friend & Puckett (1964); Ardestani et al. (2013); & Ranti (2013)), it is hypothesised that per share market price is inversely associated with the risk of the enterprise. 'DPSit' is dividend per share of enterprise 'i' in period't', and it is proxy for the dividend policy of the enterprise in this paper as in Gul et al. (2012); S.A. & S.O. (2013); & Yegon et al. (2014). Based on Graham & Dodd (1951); Bolster & Janjigian (1991); Pradhan (2003); Khan


81

& Khan (2012); & Adhikari (2014), it is hypothesised that per share market price will increase with the dividend per share distributed by the enterprise. 'LAGDPSit' is dividend per share of enterprise 'i' in period't-1' that is past year dividend. Based on Baker & Powell (2000); & Adhikari (2014), it is hypothesised that per share market price will increase with the lagged dividend per share of the enterprise. 'REPSit' is retained earnings per share of enterprise 'i' in period't' and it is earnings retained by the enterprise after the payments of preferred dividends and cash dividends to equity shareholders. Based on Pradhan (2003); & Khan & Khan (2012), it is hypothesised that per share market price will fall with the increase in retained earnings per share. 'µit' is random error term.

Analysis of data Examination of the relationship between dividend policy, performance, and stock price is undertaken using the pooled cross-sectional data for various classifications of sample enterprises. As such, the study is attempted at two levels using overall sample, viz., (a) analysis of properties of portfolio formed on dividends and (b) regression analysis. The study is also attempted using group-specific samples by regression analysis. The following sub-sections present the analysis and findings of data. Overall analysis The overall analysis of the dividend policy, performance and valuation of stock price of the enterprise comprises analysis of properties of portfolio formed on dividends and regressions. Properties of portfolios formed on dividends The portfolios are formed on dividends of low and high dividend paying enterprises, and all sampled securities are sorted out into three portfolios based on dividends. The smallest to largest enterprises are contained in portfolios 1, 2, and 3 respectively. The low to high ratios of enterprise performance indicators are provided in portfolios 1 to 3. For each security, various measures of earnings per share, return on equity, risk-beta, dividend per share, lagged dividend per share, and retained earnings per share are computed. They are then classified according to the portfolios formed above, and average values are computed. The results are presented in Table 1. The results, among others, indicated that stocks with higher dividends have higher market price. The market prices per share have increased from Rs.511.06 for the smallest portfolio to Rs.2107.19 for the largest portfolio. Market prices of stocks paying higher dividends are also more variable as compared to stocks paying lower dividends as revealed by standard deviations of market price per share. Similarly, stocks with larger dividends have larger earnings. The earnings per share have increased from Rs.27.24 for the smallest portfolio to Rs.152.17 for the largest portfolio. The mean return on equity has increased from Rs.15.47 for the smallest portfolio to Rs.17.54 for the intermediate portfolio to Rs.34.56 for the largest portfolio of stocks paying larger dividends. The return on equity is also more variable for the stocks paying higher dividends as compared to stocks paying lower dividends as revealed by standard deviation of the return on equity. The stocks with larger dividends have relatively lower risk as shown in Table 1 from the lowest portfolio to the intermediate to the largest portfolio- the extent of increase in risk is quite low as compared to the extent of increase in dividends.

82

Nabaraj Adhikari

Table 1: Summary statistics for portfolios formed on dividends of selected enterprises This table provides descriptive statistics for variables used in the study over the period 2009 to 2013 at the portfolio level. The three portfolios are formed based on dividend per share paid, i.e. < Rs.10 as the smallest portfolio or portfolio 1, dividend per share paid >Rs.10 to Rs.21 portfolio 3 or the largest portfolio. P is the per share closing price of enterprise, EPS is earnings per share, ROE is return on equity, BETA is risk, DPS is dividend per share, LAGDPS is lagged dividend per share, and REPS is retained earnings per share. Portfolios

Number of observations

1 Smallest < Rs.10

2 Intermediat > Rs. 10 to < Rs. 21

3 Largest > Rs.21

36

37

37

Panel A: P

Means (Rs.)

511.06

655.57

2107.19

EPS

(Rs.)

27.24

40.78

152.17

ROE

(%)

15.47

17.54

34.56

BETA

(Coefficient)

0.61

0.67

0.88

DPS

(Rs.)

4.32

13.67

115.12

LAGDPS

(Rs.)

7.81

13.18

96.98

REPS

(Rs.)

19.12

26.33

45.54

Panel B: Standard deviations P (Rs)

443.99

645.15

2066.80

EPS

(Rs.)

16.91

39.46

223.70

ROE

(%)

5.84

7.85

18.97

BETA

(Coefficient)

.39

0.38

0.43

DPS

(Rs.)

2.74

3.08

201.96

LAGDPS

(Rs.)

10.20

7.92

177.12

REPS

(Rs.)

12.70

39.16

50.69

Source: Annual reports of the listed enterprises and annual trading reports of NEPSE for the fiscal year 2009 to 2013. Regression analysis The results of regression analysis of closing price per share on earnings per share, return on equity, beta, dividend per share, lagged dividend per share, and retained earnings per share for total sample are shown in Table 2. The results reveal that coefficients of return on equity and lagged dividend per share have positive signs in all equations, which are as per priori expectation and the coefficients are significant at 1 percent level of significance in all equations, which indicate that return on equity and lagged dividend per share are major determinants of stock price of the enterprise.


83

Current year dividend per share is also appeared to be an important determinant of stock price as its coefficient is significant at 1 percent level of significance in all equations. Irrespective of priori expectation, the coefficient of current year dividend per share has negative sign, therefore, affecting negatively the stock price in Nepal. Table 2: Regression results for total sample enterprises This table shows regression results for the model as defined by equation: Pit = a0 + a1 EPSit + a2 ROEit + a3 BETAit + a4 DPSit + a5 LAGDPSit + a6 REPSit + µit. The regression analysis is based on 22 enterprises over 5 years of data for a total of 110 observations. P is the per share closing price of enterprise, which is dependent variable. The independent variables are defined as: EPS is earnings per share, ROE is return on equity, BETA is risk, DPS is dividend per share, LAGDPS is lagged dividend per share, and REPS is retained earnings per share. Equations

(1)

(2)

Constant

EPS

(6)

REPS

R2

Fstatistics

0.69

38.87*

0.69

46.61*

0.69

57.77*

5.21

22.29

177

-16.39

22.05

-4.86

(3.01)*

(0.88)

(-2.44)**

(3.83)*

(-.73)

((0.01))

((0.52))

((0.91))

((0.01))

((.02))

((.09))

45.90

-

193.76

-

194.34

-

23.84

222.37

-12.59

22.86

0.30

(3.33)*

(1.14)

(-2.49)*

(4.03)*

(0.11)

((0.55))

((0.98))

((0.02))

((0.02))

((0.52))

24.67

-

12.93

23.31

0.03

(3.46)*

(-2.56)*

(4.11)*

(0.01)

((0.56))

(0.02))

((0.2))

((0.53)) -

0.69

77.75*

0.66

33.42*

0.66

39.93*

0.65

65.80*

12.93

23.31

(3.47)*

24.67

-

(-2.58)*

(4.14)*

((0.56))

(0.02))

((0.02))

68.57

6.10

24.05

237.63

-18.08

22.37

-5.92

(0.30)

(0.97)

(3.15)*

(1.14)

(-2.60)*

(3.76)*

(-0.86)

((0.01))

((0.52))

((0.91))

(0.01))

((0.02))

((0.99))

19.27

-

(0.09)

(7)

LAGDPS

(0.86)

(1.21)

(5)

DPS

88.04

(1.12)

(4)

BETA

(0.40)

(0.21)

(3)

ROE

207.60 (1.24)

-

25.86

290.71

-13.63

23.32

0.12

(3.49)*

(1.45)

(-2.61)*

(3.98)*

(0.04)

((0.55))

((0.98))

((0.02))

((0.02))

((0.52))

26.95

-

-

-14.11

23.86

(3.66)*

(-2.71)

(4.09)*

((0.56))

((0.02))

((0.02))

T-statistics are shown in single parentheses under estimated values of the regression coefficients, and tolerances are shown in double parentheses under estimated t-statistics. * & ** denote the significance of coefficients at 1 percent and 5 percent level of significance respectively.

84

Nabaraj Adhikari

To gauge robustness and sensitivity-to-specification error of the regression, each independent variable having insignificant coefficient is removed from the complete model and the regressions are re-estimated. These results are shown in Table 2, Equations 2-4. The coefficients of the variables did not change in sign or size (regression coefficients are not sensitive to these alterations in terms of sign and significance). In the additional three equations, the explanatory power of the regression model as reflected by R2 did not increase at all. The closer tolerance (TOL) is to zero of the variable, the greater the degree of collinearity of that variable with the other regressors (Gujarati & Porter, 2009). The TOL of dividend per share, lagged dividend per share, and earnings per share is close to zero indicating some degree of multicollinearity between these variables. To avoid multicollinearity problem the variable earnings per share is removed from the Equation (2), Equation (3) and Equation (4), the results remain the same in terms of sign and significance of coefficients of the variables, hence, indicating that muticollinearity is not a significant problem. Further, to gauge robustness and sensitivity-tostock price trend and fluctuation error of the regression, the average market price that is average of high, low and closing market price of stock is considered instead of closing price of stock as a dependent variable in the model and the regressions are re-estimated. These results are shown in Table 2, Equations 5-7. The coefficients of the variables did not change in sign or size. In these additional three equations, the explanatory power (R2) of the regression model did not change remarkably. The R2, which has explained about 66 percent of crosssectional variability in stock price with the independent variables used in the models, is considered as good. Similarly, F-value in all equations show that it is significant at 1 percent level of significance reflecting that regression equations provide statistically significant results. Group specific analysis Based on nature of group of the enterprises involved and also number of selected listed enterprises, the overall sample is classified into two groups: (a) financial sector, and (b) nonfinancial sector. The results of regression analysis for financial sector sample are shown in Table 3. Table 3: Regression results for financial sector enterprises This table shows regression results for the model as defined by equation: Pit = a0 + a1 EPSit + a2 ROEit + a3 BETAit + a4 DPSit + a55 LAGDPSit + a6 REPSit + µit. The regression analysis is based on 17 enterprises over 5 years of data for a total of 85 observations. P is the per share closing price of enterprise, which is dependent variable. The independent variables are defined as: EPS is earnings per share, ROE is return on equity, BETA is risk, DPS is dividend per share, LAGDPS is lagged dividend per share, and REPS is retained earnings per share.


85

Equations

Constant

EPS

ROE

BETA

DPS

LAGDPS

REPS

R2

Fstatistics

(1)

11.26

43.58

-2.32

-194.99

-17.73

17.88

-35.70

0.65

23.66*

0.65

28.76*

0.64

35.55*

0.63

45.56*

0.62

20.95*

0.62

25.41*

0.61

41.51*

(0.06)

(2)

(3)

(4)

(5)

(-1.10)

(-1.30)

(2.38)*

(-2.19)**

((0.04)) ((0.59)) ((0.74))

(3.66)* (-0.32)

((0.12))

((0.42))

(0.09))

-17.94

43.52

-180.80

-18.94

18.36

-36.49

(-0.12)

(3.68)*

-

(-1.06)

(-1.46)

(3.01)*

(-2.28)**

((0.04))

((0.79))

((0.13))

((0.45))

(0.09))

-102.24

43.65

-21

18.60

-38.17

(-0.77)

(3.69)*

-

(-1.64)

(3.05)*

(2.40)**

((0.04))

((0.13))

((0.45))

((0.09))

-181.46

26.83

17.77

-16.78

(-1.46)

(4.53)*

(2.89)*

(-1.83)

((0.18))

((0.45))

((0.28))

20.86 (0.10)

42.91

-

-

-2.64

(3.23)* (-0.33)

-

-170.36

-14.72

19.51

-35.82

(-0.86)

(0.97)

(2.76)*

(-1.97)*

((0.12))

((0.42))

((0.09))

-16.10

20.05

-36.72

((0.04)) ((0.59)) ((0.74)) (6)

-12.38 (0.07)

(7)

42.84

-

-

-154.20

(3.24)*

(-0.81)

(-1.11)

(2.94)*

(-2.06)**

((0.04))

((0.79))

((0.13))

((0.45))

((0.09))

-

-

-151.65

28.65

19.55

-19.95

(-1.10)

(4.37)*

-

(2.88)*

(-1.97)*

((0.18))

((0.45))

((0.28))

T-statistics are shown in single parentheses under estimated values of the regression coefficients, and tolerances are shown in double parentheses under estimated t-statistics. * & ** denote the significance of coefficients at 1 percent and 5 percent level of significance respectively. The results reveal that coefficients of earnings per share and lagged dividend per share have positive signs in all equations, which are as per priori expectation and the coefficients are significant at 1 percent level of significance in all equations, which indicate that earnings per share and lagged dividend per share are major determinants of stock price of financial sector enterprises in Nepal. Retained earnings per share is also appeared to be an important determinant of stock price as its coefficient is significant at 5 percent level of significance in majority of equations. Irrespective of priori expectation, the coefficient of retained earnings per share has negative sign, therefore, affecting negatively to the stock price of financial sector enterprises in Nepal. To gauge robustness and sensitivity-to-specification error of the regression, each independent variable having insignificant coefficient is removed from the complete model and the regressions are re-estimated. These results including R2 and F-value are shown in Table 3, Equations 2-4

86

Nabaraj Adhikari

as well as further robustness test results by considering average market price as dependent variable in the model along with R2 and F-value as shown in Table 3, Equations 5-7 have confirmed the results of Equation (1) in Table 3. The results of regression analysis for non-financial sector sample are shown in Table 4. Table 4: Regression results for non-financial sector enterprises This table shows regression results for the model as defined by equation: Pit = a0 + a1 EPSit+ a2 ROEit + a3 BETAit + a4 DPSit + a5 LAGDPSit + a6 REPSit + µit. The regression analysis is based on 5 enterprises over 5 years of data for a total of 25 observations. P is the per share closing price of enterprise, which is dependent variable. The independent variables are defined as: EPS is earnings per share, ROE is return on equity, BETA is risk, DPS is dividend per share, LAGDPS is lagged dividend per share, and REPS is retained earnings per share. Equations

Constant

EPS

ROE

BETA

DPS

LAGDPS

REPS

R2

Fstatistics

(1)

1005.35 (1.47)

-4.67 (-0.56) ((0.01))

16.81 (0.89) ((0.21))

-650.51 (-0.65) (0.51))

-0.98 (-0.08) ((0.01))

16.01 (1.57) ((0.01))

-1.06 (-0.11) ((0.08))

0.87

19.47*

(2)

1141.02 (1.81)

-

14.88 (0.81) ((0.22))

-825.24 (-0.88) (0.56))

-4.69 (-0.49) ((0.01))

15.78 (1.58) ((0.01))

-5.96 (-1.43) (0.44))

0.86

24.28*

(3)

1436.39 (2.82)*

-

-

-881.16 (-0.95) ((0.57))

-0.57 (-0.07) ((0.01))

12.62 (1.38) ((0.01))

-6.88 (-1.74) ((0.47))

0.86

30.58*

(4)

1018.06 (4.04)*

-

-

-

-1.0 (-0.13) ((0.01))

12.14 (1.34) (0.01))

-5.23 (-1.47) ((0.58))

0.85

40.68*

(5)

950.50 (1.63)

-4 (-0.56) ((0.01))

20.68 (1.28) ((0.21))

-668.51 (-0.78) ((0.51))

-2.55 (-0.26) ((0.01))

16.22 (1.87) ((0.01))

-1.58 (-0.19) (0.08))

0.89

24.26*

(6)

1066.74 (1.99)

-

19.03 (1.22) ((0.22))

-818 (-1.02) ((0.56))

-5.73 (0.71) ((0.01))

16.03 (1.89) (0.01))

-5.77 (-1.63) ((0.44))

0.89

30.13*

(7)

1022.14 (4.63)*

-

-

-

-0.90 (-0.13) ((0.01))

-

-5.29 (-1.70) ((0.58))

0.87

47.63*

T-statistics are shown in single parentheses under estimated values of the regression coefficients, and tolerances are shown in double parentheses under estimated t-statistics. * & ** denote the significance of coefficients at 1 percent and 5 percent level of significance respectively.


87

The results reveal that coefficients of all variables are not statistically significant at 1 or 5 percent level of significance in all equations, which indicate that stock price is not influenced by the variables used in the model. The result of Equation (1) in Table 4 is confirmed by the robustness tests in Equations (2) to (4) and further robustness test by considering average market price as dependent variable in Equations (5) to (7). The result is also confirmed by the goodness of fit of the model reflected by the R2 and F-value in all equations in Table 4.

Findings and discussion The overall results for the analysis of dividend policy and performance of the enterprises reveal that stocks with higher dividends have better performance in terms of earnings per share, return on equity, and risk. The current year dividend per share affects negatively and lagged dividend per share affects positively to the stock price in overall sector. Considering the immediate influence of dividends, the present finding is inconsistent with the standard view of the role of dividend policy found in the literature that low-payout enterprises, in general, will sell at a discount (Graham & Dodd, 1951; Harkavy, 1953; Gordon & Shapiro, 1956; Durand, 1959; Clendenin, 1958; Fisher, 1961; Gordon, 1962; Hunt & Donaldson, 1971). Results of the tests of the effect of dividend policy on the value of stock price also contradict with MM hypotheses that given the earnings, dividend is mere detail. When considered the influence of past dividends, the findings corroborate with the empirical evidence of Chawla & Srinivasan, 1987 in India; Khan & Khan, 2012 in Pakistan; and empirical evidence of Pradhan (2003) in Nepal. The overall results imply that stock price in Nepal had no immediate positive response to the dividend payments during the study period and it was more prevalent in non-financial sector enterprises as there was absence of influence of performance factors including dividends on stock price of this sector. The stock price rationality in financial sector as compared to nonfinancial sector is attributed to the regulation by Nepal Rastra Bank as a robust regulator.

Policy implications The current year dividend and lagged dividend are the major determinants of stock price as revealed in the paper. It is thus dividend policy is relevant and that corporate managers should devote adequate time in designing and disseminating a dividend policy. Stock pricing based on rumours in non-financial sector, and current year dividends affecting negatively and delay in responding positively to the dividends by the stock price in overall sector as revealed in the paper is detrimental to the interest of current stockholders as well as credibility of the capital market. Because of this, some concrete actions should be taken for enhancing intensity to protect the investors, perfecting securities laws, improving supervision, and taking tougher enforcement action. Similarly, current and potential investors should be educated on the fundamental performance factors of the enterprises, industry and economy. NEPSE and SEBON as a capital market operator and regulator respectively should be responsible to address these issues. As the paper addresses the gap in the extant literature, it extends new ways to study the stock market regarding the dividend policy, performance, and the valuation of stock thereby helping to enhance the understanding and raise the level of pre-emerging capital market of Nepal. Hopefully, future researchers will add some value to this direction by increasing sample size and study period.

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Nabaraj Adhikari

References Adhikari, N. (2014). Managers' views on dividend policy of Nepalese enterprises. NRB economic review, 26(1), 90-120. Amidu, M. (2007). How does dividend policy affect performance of the firm on Ghana Stock Exchange, Investment management and financial innovations, 4(2), 104-112. Alli, K. L., A. Qayyum K., & Gabriel G. R. (1993). Determinants of corporate dividend policy: a factorial analysis. Financial review, 28, 523-547. Ardestani, H. S., Siti Z. A. R., Rohaida B., & Mohammadghorban M. (2013). Dividend payout policy, investment opportunity set and corporate financing in the industrial products sector of Malaysia. Journal of applied finance and banking, 3(1), 123-136. Baker, H. K., & Gary E. P. (2000). Determinants of corporate dividend policy. A survey of NYSE firms, Financial practice and education, 10(1), 29-40. Banz, Rolf W. (1981). The relationship between return and market value of common stocks. Journal of financial economics, 9(1), 3-18. Black, F., & Myron S. (1974). The effects of dividend yield and dividend policy on common stock prices and returns. Journal of financial economics, 1, 1-20. Bolster, Paul J., & Vahan J. (1991). Dividend policy and valuation effects of the tax reform Act of 1996. National tax journal, 44(4), Part 2, 511-518. Brenann, M. J. (1970). Taxes, market valuation and corporate financial policy. National tax journal, 23(4), 417-427. Chawla, D., & G. S. (1987). Impact of dividend and retention on share price-An econometric study. Decision, 14(3), 137-140. Clendenin, J. (Fall 1958). What do stockholders like? California management review, 1, 47-55. Dhanani, A. (2005). Corporate dividend policy: The views of British financial managers. Journal of business finance & accounting, 37(7 & 8), 1625-1672. Durand, D. (1959). The cost of capital and the theory of investment: Comment. American economic review, 49, 639-654. Fisher, G.R. (1961). Some factors influencing share prices. Economic journal, 71, 121-141. Friend, I., & Marshall P. (1964). Dividends and stock prices. American economic review, 54(5), 656682. Gordon, M. J. (1963). Optimal investment and financing policy. Journal of finance, 18, 264-272. ______ , 1962.The savings investment and valuation of a corporation. Review of economics and statistics, 40(44), 37-51. ______ , & Eli Shapiro (1956). Capital equipment analysis: The required rate of profit. Management science, 3, 102-110. Graham, B. & David L. D. (1951). Security analysis: Principles and techniques (3rd ed.). McGrawHill Book Co, New York.


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Gujarati, Damodar N. & Dawn C. P. (2009). Basic econometrics (5th ed.). McGrew-Hill/Irwin, a business unit of The McGraw-Hill Companies, Inc., 1221 Avenue of the Americas, New York, NY, 10020. Gul, S., Muhammad S., Nasir R., Muhammad Farrukh I., & Muhammad B. K. (2012). The relationship between dividend policy and shareholder's wealth. Economics and finance, 2 (2), 55-59. Harkavy, O. (1953). The relation between retained earnings and common stock prices for large listed corporations. Journal of finance, 8, 283-297. Holder, E. M., Fredrick W. L., & J. Lawrence H. (1998). Dividend policy determinants: An investigation of the influences of stockholder theory. Financial management, 27(3), 73-82. Hunt, W.& Donaldson (1971). Basic business finance: Text & Cases, Richard D. Irwin Inc. Khan, A. A., & Iqbal, K. (2012). Dividend policy and stock prices, SAICON, Lahore: COMSATS Institute of Information Technology. Litzenberger, H. R., & Krishna R. (1979). The effect of personal taxes and dividends on capital asset prices: theory and empirical evidence. Journal of financial economics, 163-196. Masum, A. A. (2014). Dividend policy and its impact on stock price-a study on commercial banks listed in Dhaka Stock Exchange. Global disclosure of economics and business, 3(1), 9-17. Miller, M. H., & Franco M. (1961). Dividend policy, growth and the valuation of shares. Journal of business, 34(4), 411-433. Miller, M. H. & Myron S. S. (1978). Dividends and taxes. Journal of financial economics, 6(4), 333364. Naranjo, A., M N., & Mike R. (1998). Stock returns, dividend yields, and taxes. Journal of finance, 53(6), 2029-2057. Pradhan, R. S. (2003). A survey of dividend policy and practices of Nepalese enterprises. Research in Nepalese finance (1st ed.). Buddha Academic Publishers and Distributors Pvt. Ltd., Kathmandu. Rafique, M. (2012). Factors affecting dividend payout: evidence from listed non-financial firms of Karachi Stock Exchange. Business management dynamics, 1(11), 76-92. Ranti, U. O. (2013). Determinants of dividend policy: a study of selected listed firms in Nigeria. Manager, change and leadership, 17, 107-119. Rozeff, M. S. (Fall 1982). Growth, beta and agency costs as determinants of dividend payout ratios. Journal of financial research, 5(3), 249-259. S.A., Adediran, & Alade S.O. (2013). Dividend policy and corporate performance in Nigeria. American journal of social and management sciences, 4(2), 71-77. Solomon, E. (1963). The theory of financial management, New York: Columbia University Press. Walter, J. E. (1963). Dividend policy: Its influence on the enterprise. Journal of finance, 18, 280-291. Yegon, C., Joseph C., & Jane S. (2014). Effects of dividend policy on firm's financial performance: Econometric analysis of listed manufacturing firms in Kenya. Research journal of finance and accounting, 5(12), 136-144.

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Appendix 1 : List of the selected listed enterprises for the paper including years of dividend payments and number of observations S.N.

Name of the enterprises

Years

Observations

1

Nabil Bank Limited (Nabil)

2009,10,11, 12, 13

5

2

Nepal Investment Bank Limited (NIBL)

2009,10,11,12,13

5

3

Standard Chartered Bank Nepal Limited (SCBNL)

2009,10,11,12, 13

5

4

Himalayan Bank Limited (HBL)

2009,10,11,12, 13

5

5

Nepal SBI Bank Limited (NSBL)

2009, 10,11,12,13

5

6

Bank of Kathmandu Limited (BKL)

2009,10,11,12,13

5

7

Everest Bank Limited (EBL)

2009,10,11,12, 13

5

8

Citizen Bank International Nepal Ltd.(CBINL)

2009, 10, 11, 12,13

5

9

Nirdhan Utthan Bank Ltd. (NUBL)

2009,10,11,12, 13

5

10

Swabalamwan Laghubitta Bikash Bank Ltd.(SLBBL)

2009,10,11,12,13

5

11

Chhimek Laghubitta Bikash Bank Ltd.(CLBBL)

2009,10,11, 12, 13

5

12

Mahalaxmi Finance Limited (MFL)

2009, 10,11,12,13

5

13

Pashchimanchal Finance Co. Limited (PFCL)

2009,10,11,12,13

5

14

Siddhartha Finance Limited (SFL)

2009,10,11,12,13

5

15

International Leasing and Finance Company Limited (ILFCL) 2009, 10,11, 12, 13

5

16

United Finance Company Limited (UFCL)

2009,10,11,12,13

5

17

Shree Investment Finance Company Limited (SIFCL)

2009, 10,11,12,13

5

18

Soaltee Hotel Limited (SHL)

2009, 10, 11, 12, 13

5

19

Bottlers Nepal Terai Limited (BNTL)

2009,10,11, 12, 13

5

20

Salt Trading Company Limited (STCL)

2009, 10,11, 12, 13

5

21

Butwal Power Company Ltd. (BPCL)

2009,10,11,12,13

5

22

Unilever Nepal Limited (UNL)

2009,10,11,12,13

5

Total observations

110

Note : S.N. indicates serial number for the enterprises selected. Source : Annual reports of the listed enterprises for the fiscal year mid-July 2008 to midJuly 2013 and annual trading report of Nepal Stock Exchange Ltd.

The Cross-Section of Expected Stock Returns in Nepal

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THE CROSS-SECTION OF EXPECTED STOCK RETURNS IN NEPAL ...? Dr. Radhe S. Pradhan Abstract The CAPM asserts that market betas are sufficient to explain the cross section of expected stock returns. However, beta showed either no relationship or a weak relationship with the expected stock returns when other company specific variables affecting stock returns are used. This study aims at examining the ability of beta and other company specific factors such as firm size, book to market ratio, sales to price ratio, dividend yield and earning price ratio to explain cross section of stock returns in Nepal. The study reveals that the beta has a very weak relation with stock returns in Nepal. The coefficient of beta is not significant and hence there is no evidence that beta explains variation of stock returns. The study showed that size, dividend yield, and book to market ratio has been found to be significant factors affecting stock returns in Nepal while beta, earning price ratio, and sales to price ratio do not explain the variation in stock returns. Key words: beta, book to market ratio, dividend yield, earning price, firm size, sales to price ratio, and stock returns.

Introduction The pricing implication of common stocks has drawn considerable attention since the publication of seminal work of Markowitz (1952) - the mean-variance portfolio theory. Since then there is an ongoing debate on whether the market risk factors explain better or there are some other anomalies influencing common stock returns. Based on the mean-variance portfolio theory, Sharpe (1964), Linter (1965), and Black (1972) then proposed extensively argued asset pricing theory- the capital asset pricing model (CAPM). The central prediction of the CAPM is that the rate of return associated with common stocks investment is determined by the extent to which the common stock returns are correlated with market portfolio. CAPM asserts that the market risk factors proxied by beta can capture significant variation in common stock returns. Asset pricing theories attempt to understand why some assets have higher returns than other assets. In early stages of the corporate finance, investors and researchers began attributing higher returns for higher risk. It is only with the development of the CAPM that economist were able to quantify risk and the reward for bearing it. The CAPM asserts that expected returns of assets are a positive linear function of their market betas and market betas are sufficient to describe the cross section of expected returns. However, empirical work on asset pricing has identified a number of variables that help explain cross sectional variation in stock returns in addition to the market risk variable. Notably, firm size (Banz, 1981; Keim, 1983), leverage (Bhandari,1988), P/E ratio (Basu, 1983), ratio of cash flow to stock price (Rosenberg et al., 1985), book to market equity (Fama Prof. Pradhan is the Retired Professor of Finance from TU. He is also the Chairman of Professional Educators Limited, the owner company of Global College of Management.

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and French, 1992), and past sales growth (Lakonishok et al., 1994) are among those that are found to have significant explanatory power in asset pricing tests. In their seminal work, (Fama and French, 1992) found that book to market equity stands out as the most significant factor in explaining cross section of returns. Market risk measured by beta, on the other hand, has no explanatory power. The challenge posed by the (Fama and French, 1992) findings to traditional structural models has created a significant hurdle to the understanding of more complex and dynamic properties of the cross section of stock return. The study by (Chan et al., 1991) related the cross sectional differences in stock returns on Japanese stocks to the underlying behavior of four fundamentals variables: earnings yield, size, book to market ratio and cash flow yield. Of the four variables considered, book to market value ratio and cash flow yield have been found to be most significant variables affecting expected returns. The empirical studies pointed out many inconsistencies in the CAPM that prescribes that expected stock return is directly related to systematic risk. The most noteworthy is the size effect on expected stock return. The size, measured as the market value of equity (ME), has significant impact on the stock return, that is, smaller size of the firm, higher would be the returns (Banz and Reinganum, 1981). In Malaysia, size variable alone explains about one third of the expected stock returns (Pandey and Chee, 2001). The finding indicates the significance of B/M ratio disappears in multivariate regressions that also include E/P ratio. It is also indicated that market beta with or without other variables has a positive relation with stock return. The other significant variables include E/P ratio, dividend yield and leverage. The above shows that a number of studies have been conducted on the stock returns in developed and big capital markets but their relevance is yet to be seen in the context of emerging capital markets. Information on stock returns in such emerging capital markets would help development of realistic theoretical models and formulation of relevant hypotheses for empirical testing in finance. In Nepal, the listing of shares in stock exchange and their trading in the stock market is still not very popular. The Nepalese stock market is still characterized by a low trading volume, absence of professional brokers, early stage of growth, limited movement of share prices, and limited information available to investors. Viewed in this way, this study devoted to stock returns in Nepal carries a lot of significance. There is a need to arouse investors' interest in stock markets leading to pursuit of higher returns. Little is known about the nature of stock returns in Nepalese capital market. A study on fundamentals of stock returns in Nepal revealed that dividend yield, capital gain yield and total yield are related to earnings yield, size book to market ratio and cash flow yield (Pradhan and Balampaki, 2006). This study aims at examining the ability of beta and company specific factors like size, book to market ratio, sales to price ratio, dividend yield and earning price ratio to explain stock returns in context of Nepal. The remainder of this paper is organized as follows. Section two describes the sample, data, and methodology. Section three presents the empirical results and the final section draws conclusions and discusses the implications of the study findings.

Methodological aspects The study is based on the secondary data which were gathered for 23 banks in Nepal for the period 2006/07 to 2011/12, leading to the total of 138 observations. The secondary data have


93

been obtained from data base maintained by office of the Security Board of Nepal (SEBON), NEPSE and other concerned banks. The pooled cross-sectional data analysis has been undertaken in the study. The research design adopted in this study is causal comparative type as it deals with relationship of beta, size, book to market ratio, sales to price ratio, dividend yield, and earnings price ratio with stock returns. More specifically, the study examines the effect of beta, size, book to market ratio, sales to price ratio, dividend yield, and earnings price ratio on stock returns. These data were collected for the period 2006/07 to 2011/12. Table 1 shows the number of commercial banks selected for the study along with the study period and number of observations. Table 1: Number of commercial banks selected for the study S.No. Name of the commercial banks 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Ratriya Banijya Bank Limited Nepal SBI Bank Limited Bank of Kathmandu Limited Citizens' Bank International Limited Laxmi Bank Limited DCBL Agricultural Development Bank Limited Bank of Asia Limited Nepal Investment Bank Limited Nepal Standard and Chartered Bank Limited Himalayan Bank Limited NMB Bank Limited Lumbini Bank Limited NABIL Bank Limited NIC Bank Limited Global Bank Limited Kumari Bank Limited Everest Bank Limited Machhapuchhre Bank Prime Bank Limited Sidhartha Bank Limited Sunrise Bank Limited Nepal Bangladesh Bank Limited Total number of observations

Study period

Observations

2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12 2006/07-2011/12

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 138

The cross sectional pooled data analysis has been undertaken for the purpose of the study. The theoretical statement of the models is that the stock return (R) may be regarded as subject to the constraints of beta, size, book to market ratio (BM), sales to price ratio (SP), dividend yield (DY) and earnings price ratio (E/Y). The theoretical statement may be framed as under: R = f (Beta, Size, BM, SP, DY, E/P)

……...……

(i)

94


Variables

N

Minimum

Maximum

Mean

Std. Deviation

Return

138

19.15

56.59

51.65

9.45

Beta

138

0.45

0.95

0.73

0.34

Size

138

1829.32

20114.95

8152.23

7123.12

E/P

138

20.34

52.17

32.12

9.21

DY

138

0.71

5.13

3.15

2.11

SP

138

0.85

2.89

2.12

0.43

BM

138

0.45

2.02

1.05

0.32

The descriptive statistics also shows that the banks differ greatly in terms of their earnings yield and dividend yield. Earnings yield has an average value of 32.12 with a minimum to maximum value ranging from 20.34 to 52.17 respectively, dividend yield has a minimum value of 0.71 and maximum value of 5.13 leading the average of 3.15. Similarly, sales to price ratio has an average value of 2.12 and standard deviation of 0.43. The book to market value of equity ratio of the banks varies significantly. It ranges from minimum of 0.45 times to maximum of 2.02 times with a mean value and standard deviation of 1.05 and 0.32 times respectively.


95

Correlation Analysis Having indicated the descriptive statisitics, the Pearson Correlation Coefficients have been computed and the results are presented in Table 3. All the correlations can be considered as low since the highest correlation has been observed to be 0.567 between ln Size and ln SP. The lowest correlation of -0.132 has been observed between stock return and DY. The stock return is negatively related to DY and BM and positively related to beta, size, E/P and SP. Beta has a positive correlation with Size, E/P, and SP. Table 3: Computation of correlation coefficients for the selected commercial banks of Nepal lnReturn lnReturn

lnBeta

lnSize

lnE/P

lnDY

lnSP

ln BM

1

lnBeta

.295 (.192)

1

lnSize

.253 (.162)

.521* (.012)

1

lnE/P

.231 (.289)

.326 (.115)

.455 (.112)

1

lnDY

-.132 (.389)

-.453* (.069)

-.552 (.023)

-.732 (.012)

1

lnSP

.267 (.189)

.452* (.092)

.567* (.028)

.211* (.298)

-.512* (.039)

1

lnBM

-.457* (.102)

-.221 (0.235)

-.239 (.198)

-.235 (.178)

.236 (.178)

-.283 (.281)

1

Notes: 1. Figures in parentheses are t-values. 2. The sign * denotes that the results are significant at 5 percent level of significance.

Regressions Results In order to analyze the effect of beta, size, E/P, DY, SP and BM on stock returns, the regression equations specified earlier are estimated and the results are presented in Table 4. The regression coefficients for beta are positive in all the regression equations indicating that higher the beta, higher would be the stock returns though the results are not significant at 5 percent level of significance. Stock returns are better explained by size as beta coefficients are all positive and significant at 5 percent level of significance. It indicates that larger the size of the firm, higher would be the stock returns. Among others, this finding supports the findings of Banz (1981), Reinganum (1981), Keim (1983) and Fama and French (1992).


96

Regression Coefficients of

Adj. Rbar2

F

DW

0.34

20.75

1.34

0.43

19.84

1.57

0.31

17.45

1.87

0.45

30.65

1.35

0.31

32.72

1.74

0.48

29.21

1.60

0.78

35.67

2.09

0.82

39.28

1.94

-0.45 (-3.24)*

0.75

43.31

1.96

0.45 2.21 -0.16 -0.67 (1.45) (4.14)* (-.63) (-4.65)*

0.82

47.95

2.04

Models Intercept lnBeta (1)

2.11 (8.21)

(2)

9.12 (4.23)

(3)

7.21 (2.23)

(4)

4.78 (2.38)

(5)

10.32 (2.87)

lnSize

lnE/P

lnDY

lnSP

lnBM

0.41 (0.92) 1.32 (2.32)* -0.65 (1.32) 1.98 (2.87)* -0.92 (0.78)

(6)

-0.92 (2.82)*

(7)

2.36 (2.23)

0.28 (1.43)

1.42 -1.85 (2.91)* (1.13)

(8)

3.21 (3.23)

0.33 (0.62)

0.28 -1.73 (2.84)* (3.27)*

(9)

6.21 (2.73)

0.46 (0.83)

0.86 (2.66)*

(10)

3.59 (3.86)

0.392 (1.34)

1.43 (3.13)*

0.54 (2.87)*

However, the earnings yield (E/P) could explain the variation on stock returns as beta coefficients for this variable are sometimes positive and sometimes negative and the results are also not significant at 5 percent level of significance. But the dividend yield (DY) has been found to be an important factor affecting stock returns as not only beta coefficients are positive but they are also significant at 5 percent level of significance. It indicates that higher dividend yield leads to higher stock returns. This finding on dividend yield, among others, support the findings of Lamont (1980) and Boudoukh et al. (2007). Like earnings yield, sales to price ratio could not explain the variation in stock returns as the signs of beta coefficient are not consistent and the results are also not significant at 5 percent level of significance. However, book to market (BM) has been found to be an important factor affecting stock returns as beta coefficients are consistently negative and significant at 5 percent level of


97

significance in all the equations. It indicates that higher the book to market, lower would be the stock returns. Among others, this finding is in consistency with the findings of Stattman (1980) and Chan et al. (1991).

Summary and conclusion Attempts were made by asset pricing theories to understand why some assets have higher returns than other assets. According to CAPM, the expected stock returns are a positive linear function of their market betas. The model asserts that market betas are sufficient to explain the cross section of expected stock returns. As a result, the CAPM has been widely used by portfolio mangers, institutional investors, financial mangers and individual investors to predict asset returns. Beta is a measure of systematic risk in CAPM and is assumed to be positively related to stock returns. However, several studies revealed that other variables could significantly explain the variation in stock returns and the beta showed either no relationship or a weak relationship with the expected stock returns. The studies on cross-sectional variation in common stock returns provide an important insight into the understanding of pricing implication of common stock. This study aims at examining the ability of beta and company specific factors such as firm size, book to market ratio, sales to price ratio, dividend yield and earning price ratio to explain cross section of stock returns of Nepalese stock market. This study reveals that the beta has a very weak relation with stock returns. The result of regressions show that the coefficient of beta is insignificant and it does not explain variation of stock returns. Firm size displays a positive and statistically significant coefficient in explaining stock returns. The study, therefore, reveals that size has a significant impact on stock returns and suggests larger stocks have higher returns. The relationship of E/P with stock return is uncertain and hence does not explain the variation in stock returns. The coefficients for sales to price ratio (SP) are negative in all the equations but they are not significant. The dividend yield (DY) coefficient is positive and significant indicating that higher dividend yield leads to higher stock returns. The book to market (BM) coefficients are all negative and significant also indicating that higher book to market leads to lower stock returns or vice versa. To conclude, size, dividend yield, and book to market ratio has been found to be significant factors affecting stock returns in Nepal. Overall, beta, earning price ratio, and sales to price ratio have been observed to be poor predictors of stock returns.

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100 Mr. Santosh Poudel

AN EMPIRICAL STUDY ON STOCK MARKET, BANK AND ECONOMIC GROWTH ...?

Mr. Santosh Poudel

Abstract Many researchers have addressed that financial market also determines the sustainable growth of the economy. This study tries to find the relation between economic growth with financial growth. Financial growth indicators are stock market capitalization and liquidity. Banking growth indicators are private credit by commercial banks. These indicators help in GDP growth through capital formation in the economy which is hereby termed as channels for growth. OLS regression model suggests that stock market and banking growth is positively linked with growth in GDP and capital formation. Test of significance suggests that only banking growth helps in economic growth. Test of autocorrelation, heterescedasticity and multi-collinearity suggests the robustness of the study. Key words: GDP, Capital Formation, Stock Market Capitalization, Liquidity, Bank Credits etc.

Introduction Over the years, there has been a long discussion on what factors and forces cause economic growth. Different pillars of economy are key factors for health of an economy. Many researchers have addressed that financial market also determines the sustainable growth of the economy. Financial market, more specifically stock market, is a market where securities of different firms are traded. Savings are converted into investment through the security market as investors like to buy security market instruments like shares, bonds, futures and options for liquidity, income and tax aversion. We can sense the contribution of security market in the economic growth, capital formation and productivity improvements (King and Levine, 1993a). Stock Markets are basically similar to other kinds of market. People buy and sell, win and lose in this market. In stock market people buy and sell securities, stocks and bonds which are less tangible than gold but not less valuable (Ritter and Silber (2008)). To establish huge infrastructures and industries require long run commitment of capital and these projects are necessary for the economic development of nation. But investors are reluctant to give up of their savings to long-run. A cautious investor is always concerned with return and risk. In a risky market like in Nepal risk is a major factor in investment decision. This would require creating conducive investment atmosphere and developing efficient stock market, which help to the investors to sell their share to other investors easily. As a result the capital is not prematurely removed (Levine and Zerovs (1996)). Mr. Poudel is the Program Coordinator at Global College of Management. He is the MPhil Scholar at Kathmandu University School of Management (KUSOM).

An Empirical Study on Stock Market, Bank and Economic Growth 101 Stock market liquidity, the ability to trade equity easily, is crucial for economic growth. Without a liquid stock market, many profitable long-term investments, which require a longrun commitment of capital, would not be undertaken because savers would be unwilling to renounce control of their savings for long periods. A liquid equity market allows savers to sell their shares easily, quickly and inexpensively, thereby permitting firms to have permanent access to capital on favorable terms. By facilitating longer-term and more profitable investments, a liquid market improves the allocation of capital and enhances prospects for long-term economic growth. Liquidity lowers the cost of the foreign capital essential for development, increases investor incentive to acquire information on firms and improve corporate governance, thereby facilitating growth (Kyle, 1984; Holmstrom and Tirole, 1993; Neusser and Kugler, 1998; Bencivenga et. al., 1996;).A third link between of stock market development on the economy is that the presence of stock markets would mitigate the principal agent problem, thus promoting efficient resource allocation and growth (Adjasi and Biekpe,2006). As the stock price is the mirror of a firm's performance, weakening corporate governance would be reflected as a fall in share price. In such a situation, management would have a disincentive to work in their personal interests if their compensation is tied to stock performance (Jensen and Murphy, 1990). By exerting a continuous and strict control over the management of firms, stock markets provide proper incentives for managers to make investment decisions and positively affect the average return on investments (Diamond and Verrecchia, 1982; Laffont and Tirole, 1988; Scharfstein, 1988). A strong stock market can generate, promote and acquire more information about firms, the innovative activity of entrepreneurs, the aggregate state of technology or their consequences also plays important role in the investment decisions, thereby promoting efficient resource allocation, improving the productivity of capital and achieving better growth (Caporale et al, 2004; Atje and Jovanovic, 1993; Grossman and Stiglitz, 1980; Allen, 1993:81-108). A new stock exchange can increase economic growth by aggregating information about firms' prospects, thereby directing capital to investment with returns (Greenwood and Jovanovic, 1990; King and Levine, 1993). Based on such accurate and improved information, the organization makes investment decisions through intelligent profit projections which improve resource allocation and promote economic growth. Moreover, stock markets play a key role in allocating capital to the corporate sector, which will have a real effect on the economy on aggregate. A well-functioning financial sector channels limited resources from surplus units to deficit units and in so doing providing an efficient allocation of resources, thereby resulting in economic growth (Majid, 2007:140-141). Another channel through which stock markets may positively affect capital accumulation and economic growth is the improvement of risk diversification through international financially integrated markets. The role of equity markets in providing portfolio diversification, enabling individual firms to engage in specialized production is bound to result in efficiency gains (Acemoglu and Zilibotti, 1997; Capasso, 2006). An increase in the degree of international integration of stock markets reduces the level of average investment risk through diversification and leads to a shift in the global portfolio from safe low-yield projects to riskier high-yields projects. By facilitating risk diversification through internationally integrated stock markets and increasing the array of possible investments, stock markets can augment the rate of investment in diversified portfolios (Saint-Paul, 1992; Obstfeld, 1994). This shift boosts economic growth by inducing capital mobility, productivity and saving rates. Nepal is encircled by and confronting with the problems of state of underdevelopment, turbulent socio-political situation preventing economic growth, and economic policy of globalization and liberalization, demanding global standards of economic behavior. Inadequate

102 Santosh Poudel capital availability and its ineffective use is the crux of the problems of economic development. Stock market plays important role both by making provision of capital and encouraging its effective use for economic growth. Historically, the development of capital market dates back to 1936 with the flotation of share by Biratnager Jute Mills Ltd (NEPSE (2002)). The then government of Nepal announced industrial policy in 1974 and under this policy an institution named Securities Marketing Centre (SMC) was established to deal in government securities- development bond, national saving bonds and corporate securities of few companies. In 1976 the Securities Marketing Centre (SMC) was renamed by Securities Exchange Centre (SEC). At that time SEC itself was under taking job of brokering, underwriting, and managing public issue as only capital market institution in Nepal. Under the financial sector liberalization policy, Government of Nepal converted SEC into Nepal Stock Exchange Ltd. (NEPSE) in 1993 and assigned the responsibility of secondary market operation. And Government of Nepal established Securities Board of Nepal (SEBON) in 1993 as securities market regulatory authority. At the above backdrop, this paper aims to examine the relationship between stock market development and economic growth in Nepal. Banking activities is also a key variable for economic growth as they help to channelize funds of savings into investment. It is associated with creating a sound financial system with stock market to boost economic development. Mostly it helps to promote different sectors of economy by lending loans. Historically many researches have indicated that bank's contribution in the economic growth is vital (Schumpter 1912) as it spurs funds into innovative and productive activities. Almost one hundred years ago, Schumpeter (1912) already addressed the relation between financial development and economic growth. He asserted that a wellfunctioning financial system should promote economic growth through the selection of the productive investments which are the most likely to be successful and the efficient allocation of resources (via bank credits) to these innovative technologies. Since then, the financial system has significantly evolved. Access of private companies to funding through financial markets has been improved and stock markets have been established in almost any part of the world. New financial products have also been created which allow better risk diversification and allocation. Although all these improvements may have had a positive impact on economic development in many countries through better resource allocation and risk diversification, recent events have also shown that misused financial innovations can have adverse effects on short run economic stability. Moreover, measures taken to reestablish systemic stability in the wake of the recent subprime crisis have important implications for economic development policies. If financial development facilitates long run economic development, expanding the banking system and stock markets in developing countries might help promote their long run economic growth (Laurent, et. al 2011). One central question is then to investigate whether financial development has had a positive impact on economic growth in the long run. In addition, it is also of prime importance to determine whether the structure of the financial system is relevant. In other words, we want to know whether banks and stock markets can both promote long run economic development. This paper consists of three sections containing literature review in the first section, data and modeling in second section followed by data analysis and finally third section concludes the paper.

An Empirical Study on Stock Market, Bank and Economic Growth 103

Literature Review From Schumpter in 1912 till today's research has concluded many things on multi-field perspective on relationship between financial system and economic growth with many models. Work of Levine and King in 1993 is a remarkable work in identifying relationship of bank and stock market with economic growth. Though Schumpter's work was a path-breaking for many studies in 1980s and Levine and King (1993) article on Stock market and Bank was criticized for lack of economic modeling, many researches have taken their footsteps in their studies. Here we present some of the prominent literature on the work of bank, stock market and economic growth. Before presenting the evidence on the bank, stock market and economic growth relationship, we need to briefly describe the theory dedicated to this particular aspect of the literature. In this regard, theory provides conflicting predictions about whether banks and stock markets are substitutes, complements, or whether one is more conducive to growth than the other. Boyd and Prescott (1986) stress the fundamental role of banks in producing information and reducing misallocation of resources while Stiglitz (1985) and Bhide (1993) show that stock markets will not enhance resource allocations and corporate government as banks. Some models stress that stock markets reduce the inefficiencies monopoly power of banks and therefore encourage growth-enhancing activities (Allen and Gale (2000)). Finally, some models emphasize that it is bank and markets altogether that reduce information asymmetries and transaction costs. Levine and Zervos (1998) have focused on the relationship between economic growth and financial development using both bank and stock market indicators. They tested this relationship for a sample of 42 countries over the period [1976-1993]. They used banking development, GDP, market size capitalization as proxy, productivity growth and capital accumulation as variables for study. They found that the initial level of stock market development liquidity and the initial level of banking development are positively and significantly associated with long term economic growth, productivity growth and capital accumulation. They also find that stock market size, as measured by market capitalization divided by GDP, is not correlated with growth indicators. The variables used are similar to King and Levine (1993a) and statistical method to test the relation is also same. However, many critics commented on limited statistical testing and robustness testing on those results. So, this study uses OLS modeling to identify the regression relationship between variables and dependent variable economic growth. But few variables will be omitted in this article as data about is unavailable in Nepal. Rousseau and Wachtel (2000), and Beck and Levine (2003) extend the Levine and Zervos approach of stock markets, banks and growth by using panel techniques (GMM estimator). Rousseau and Wachtel (2000) use annual data and the difference estimator. Beck and Levine (2003) use data averaged over five-year periods, use the system estimator to reduce potential biases related to the difference estimator, and extend the sample through 1998. This study is basically based panel data published by central bank and central bureau of statistics. Both studies used econometric modeling to show that banking and stock market development explain altogether subsequent growth. These studies stressed the benefits of panel data techniques.

104 Santosh Poudel

Data and variable definition: To see the relationship between economic growth and both stock market and banking development we need empirical indicators of stock market liquidity, size given by capitalization of market and a measure of banking development. This article also sees the measures growth of economic growth through growth in gross domestic product and capital formation by the stock market and other financial activities. This section defines the stock market indicators, banking development indicator and economic growth indicators. Information related to the stock market development has collected from annual report published by Nepal Stock Exchange from 1993-2014. Banking development indicators were collected from the annual report of Nepal Rastra Bank of the same time period.

Stock Market Development Indicators: Size: Capitalization measures the size of the stock market and equals the value of listed domestic shares on domestic exchange divided by GDP. The size variable definition is similar to Levine and Zervos (1998). Higher the value of capitalization higher will be contribution to the economy as it shows growth in value of stock market. Liquidity: Liquidity market is a key variable in explaining the trend in transaction cost as high liquidity reflects the low transaction costs for the investors (Levine 1998). It is the value of the trades of domestic shares on exchange market divided by the value of listed shares.

Banking Development Indicators: Banking sector helps economy by channelizing the deposits into profitable investments. Banks and financial institutions are major source of funding different private and public projects. So to see their contribution to the economy we must see credits given by the banking sector to the private sector. Thus value of loans made by commercial banks and other deposit taking banks to the private sector divided by GDP will be the indicator of banking development. The ratio is here referred as Banking Credit. Credit improves upon traditional financial depth, measures of banking development by isolating credit issued by banks, as opposed to credit issued by the central bank or other intermediaries, and by identifying credit to the private sector, as opposed to credit issued to governments (Levine et al 1991). Model: This study stands on two grounds of testing the relationship of stock market and banking activities. First it examines the relationship between these financial development indicators and per capital GDP growth and also studies two channels through which banks and stock markets may be linked to the growth of the economy. It sees how indicator of banks and stock market contributes in GDP growth and assesses how it affects capital formation. Two regression models are used in the study to test the relationship with GDP growth and capital formation. Model 1:

Where, Y1 refers to the growth in real per capital GDP growth used as dependent variable. X1 refers to the Market Capitalization of Nepal Stock Exchange (NEPSE) X2 refers to the

An Empirical Study on Stock Market, Bank and Economic Growth 105 Market Liquidity of NEPSE and X3 refers to private credits issued by the banks in Nepal used as independent variable. Natural log of these variables has been used to regress the OLS regression relation. Model 2:

Where, Y2 refers to Capital Formation in the economy used as dependent variable. X4 refers to the Market Capitalization of Nepal Stock Exchange (NEPSE) X5 refers to the Market Liquidity of NEPSE and X6 refers to private credits issued by the banks in Nepal used as independent variable. Natural log of these variables has been used to regress the OLS regression relation.

Summary Statistics and Correlations Table 1 presents summary statistics on the economic growth indicators using GDP and stock market growth indicators with banking development indicators whereas table 2 presents statistics using capital formation as growth indicators of economy. Total 21 yearly data related to the indicators during 1993-2013 has been included in the study. Table 3 presents the correlations among the study variables. Table 1: Summary Statistics of Annual Averages during 1993-2013 Variable

Obs

Mean

Std. Dev.

Min

Max

GDP Capitaliza~n Liquidity Credit

21 21 21 21

3.659249 4.269085 2.45167 4.35953

.1462643 .4335327 .4407008 .5676206

3.353381 3.547041 1.343409 3.227828

3.865826 5.087409 3.176085 5.286007

Notes: GDP is the growth in the real per capital GDP in the economy; Capitalization is the stock market overall capitalization of NEPSE; Liquidity refers to value of shares traded in NEPSE ; Credit refers to the private sector lending by the banks. All the variables are the natural log of actual values. Table 2: Summary Statistics of Annual Averages during 1993-2013 Variable

Obs

Mean

Std. Dev.

Min

Max

Cap_form Capitaliza~n Liquidity Credit

21 21 21 21

3.046254 4.269085 2.45167 4.35953

.235471 .4335327 .4407008 .5676206

2.636338 3.547041 1.343409 3.227828

3.423388 5.087409 3.176085 5.286007

Notes: Cap_form is the Capital Formation in the economy; Capitalization is the stock market overall capitalization of NEPSE; Liquidity refers to value of shares traded in NEPSE; Credit refers to the private sector lending by the banks. All the variables are the natural log of actual values.

106 Santosh Poudel GDP

Capital Formation

Capitalization

Liquidity

GDP Capital Formation

1.00 0.6596* (0.0011)

1.00

Capitalization

0.6154* (0.0030)

0.2913 (0.2002)

1.00

Liquidity

-0.2282 (0.3199)

-0.3836 (0.0860)

0.0229 (0.9215)

1.00

Credit

0.6347* (0.0020)

0.9545* (0.000)

0.2479 (0.2787)

-0.5040* (0.0198)

Credit

1.00

Note: The figures represent the correlation coefficients among the variables of the study. The value in the parentheses refers to the p-value testing the significance level of 95%. The sign * shows the significance. As expected GDP growth has positive relationship with capitalization of stock market and credit lent by the private banks in Nepal. However opposite of expectation, liquidity has negative relation with GDP growth. The relationship between GDP growth and market capitalization is positive significant and it is same with credit. Though relation of GDP growth is negative its coefficient is insignificant. We can conclude there is positive and significant relationship of capitalization and credit with GDP growth. These findings are similar to Bencivenga (1995) who found significant relation between stock market capitalization and GDP growth but contradict with Baro (1995). These findings about market liquidity and opposite the findings of Shliefer and Vishny (1986) who found positive implications stock market liquidity. Though relation of capitalization with capital formation is positive in absence of significance we cannot say that boom in market capitalization supports capital formation. Private lending by banks is positively and significantly related with capital formation suggesting banks are contributing in forming capital in the economy.

Regression Analysis GDP growth and stock market indicators with bank development indicator: Linear regression analysis using capitalization, liquidity and bank credit as independent variables and growth in GDP as dependent variable has been done. Following table suggests positive relation dependent variable and independent variable. With high percentage of value of R2 we can say that GDP is affected positively by the capitalization in stock market, liquidity in stock market and bank credit. However P-value suggests only bank credit is significant in affecting the growth in GDP. Source

SS

df

MS

Model Residual

.395856236 .0320085

3 17

.131952079 .001882853

Total

.427864736

20

.021393237

Number of obs F(3, 17) Prob > F R-squared Adj R-squared Root MSE

= = = = = =

21 70.08 0.0000 0.39252 0.9120 .04339

An Empirical Study on Stock Market, Bank and Economic Growth 107 GDP

Coef.

Std. Err.

t

p> |t|

[95% Conf. Interval]

Capitalization Liquidity Credit _cons

.0131174 .0408175 .2594453 2.372119

.0234707 .0258986 .02075 .1438584

0.56 1.58 12.50 16.49

0.584 0.133 0.000 0.000

-.0364017 -.0138239 .2156667 2.068604

.0626363 .0954588 .3032239 2.675633

Notes: GDP is the growth in the real per capita GDP in the economy; Capitalization is the stock market overall capitalization of NEPSE; Liquidity refers to value of shares traded in NEPSE; Credit refers to the private sector lending by the banks. Coef refers to the regression coefficients for the model prescribed in Model 1. To see impact of various variables on dependent variable multiple regression models using different combination of independent variables has been used. Altogether six models has been created and their respective regression coefficient with test for goodness-of-fit has been presented in Table 4. The results are similar with the multiple variable regression model stated in above summary. In each model bank credit has been positive and significant. We can easily conclude that banking activities are deterministic in deciding growth of GDP in Nepal. Table 3: Regression Coefficients and Different Models Model

Capitalization

1

0.098 (0.2)

2

Liquidity

-0.127 (0.086)

5 6

0.15 0.245* (0.000)

0.1 (0.162)

0.13 (0.58)

R2 0.085

3 4

Credit

-0.13 (0.074)

0.91 0.24

0.043 (0.100)

0.263* (0.000)

0.92

0.041 (0.133)

0.26* (0.000)

0.91

Notes: Above values are the coefficients of OLS regression of different models keeping GDP growth as dependent variable and other variables as independent variables in 6 different models. Values in parentheses refer to their respective p-value to test the significance. GDP is the growth in the real per capita GDP in the economy; Capitalization refers to the stock market overall capitalization of NEPSE; Liquidity refers to value of shares traded in NEPSE and Credit refers to the private sector lending by the banks. The sign * shows significant relation at 95% level of significance. R2 is the test of goodness-of-fit. Capital Formation growth and stock market indicators with bank development indicator: Now, to see the channel for growth in GDP relation of capital formation with stock market indicators and bank development indicator has been used. If banks are helping to grow the

108 Santosh Poudel domestic products in Nepal that growth must be channelized through formation capital stock in the economy. OLS model has been used to see the relation and summary of the multiple variable regression model has been presented below: Source

SS

df

MS

Model Residual

.695233396 .413698692

3 17

.231744465 .024335217

Total

1.10893209

20

.055446604

Number of obs F(3, 17) Prob > F R-squared Adj R-squared Root MSE

= = = = = =

21 9.52 0.0006 0.6269 0.5611 .156

Capital_Form!n

Coef.

Std. Err.

t

p> |t|

[95% Conf. Interval]

Capitalization Liquidity Credit _cons

.262796 .0144728 .2191951 .9332854

.0843792 .091078 .074598 .5171835

3.11 0.16 2.94 1.80

0.006 0.878 0.009 0.089

.0847715 -.1819676 .0618071 -.1578763

.4408206 .2109131 .376583 2.024447

Notes: Capital Formation is value of capital created in the economy; Capitalization is the stock market overall capitalization of NEPSE; Liquidity refers to value of shares traded in NEPSE; Credit refers to the private sector lending by the banks. Coef. refers to the regression coefficients for the model prescribed in Model 2. Summary suggests the independent variables have positive relation with dependent variable. We can see that capitalization, liquidity and bank credit is helping to form capital in the economy but only stock market capitalization and bank credit is having significant relation with the capital formation. Multiple models for different set of control variables also suggest similar result. In each case capitalization and bank credit is showing positive and significant relation with capital formation. It concludes that value of stock trades and bank credit to private sector is serving significantly to form capital in the economy. Model

Capitalization

1

0.33* (0.03)

2

Liquidity

-0.122 (0.32)

5 6

0.053 0.26* (0.020)

0.34* (0.02)

0.26* (0.006)

R2 0.38

3 4

Credit

-0.13 (0.187)

0.4 0.44

0.065 (0.56)

0.29* (0.004)

0.41

0.14 (0.878)

0.22* (0.009)

0.63

An Empirical Study on Stock Market, Bank and Economic Growth 109 Notes: Above values are the coefficients of OLS regression of different models keeping Capital Formation as dependent variable and other variables as independent variables in 6 different models. Values in parentheses refer to their respective p-value to test the significance. GDP is the growth in the real per capita GDP in the economy; Capitalization refers to the stock market overall capitalization of NEPSE; Liquidity refers to value of shares traded in NEPSE and Credit refers to the private sector lending by the banks. The sign * shows significant relation at 95% level of significance. R2 is the test of goodness-of-fit.

Test for Robustness To see the robustness of the results from the correlation and regression analysis autocorrelation test is done. Durbin-Watson d-statistics of 1.88 suggests that autocorrelation is not clearly seen in the model 1 whereas in model 2 it was clearly not seen as d-statistics is 2.00. (dstatistics above 2.00 suggests no autocorrelation). The calculation of the d-statistics using STATA has been included in the annex. To see the probability of multi-collinearity condition index has been calculated. The value of condition index (CI) is obtained as (Maximum eigenvalue /minimum eigenvalue) 0.5. The basis of decision for chance of multi-collinearity is that the value of condition index must be less than 10. In each model the value of condition index is below 10 suggesting no multicollinearity among the independent variables. The test of heteroscedasticity using Bruesch-Pagan Test suggests low correlation between fitted values of dependent variables and error in the regression model. The p-value in each model is more than 0.05 suggesting no heterescedasticity. The calculation process of each test of robustness has been included in the annex.

Summary and Conclusion Almost one hundred years ago, Schumpeter (1912) already addressed the relation between financial development and economic growth. He asserted that a well -functioning financial system should promote economic growth through the selection of the productive investments which are the most likely to be successful and the efficient allocation of resources (via bank credits) to these innovative technologies. In Nepal substantial growth in banking activities and share market capital gain is often linked with economic growth of the country. This study tries to see how financial development has helped in growth of GDP and tries to see the channel of such growth through capital formation. Correlation and regression analysis suggests that only banking activities are significant in promoting economic growth as growth in GDP is significantly related with the bank credits. The relation of bank credit with capital formation is also positive and significant indicating that banks are helping in growth of GDP through capital formation. Though stock market growth is positively related with GDP and capital formation but due lack to statistical verification we cannot conclude that stock market growth is significant in helping growth in the economy.

110 Santosh Poudel

Annex: Test of Autocorrelation Model 1 . gen asu = abs ( uh ) . estat dwatson Durbin-Watson d-statistic (4, 21) = 1.884353 Model 2 . tset year time variable : delta :

year, 1 to 21 1 unit

. estat dwatson Durbin-Watson d-statistic (4, 21) = 2.00638

Test of multi-collinearity Model 1 . pca GDP Capitalization Liquidity Credit Principal components / correlation Rotation: (unrotated = principal)

Number of obs Number of comp. Trace Rho

= 21 = 4 = 4 = 1.0000

Component

Eigenvalue

Difference

Proportion

Comulative

Comp 1 Comp 2 Comp 3 Comp 4

2.34882 1.02572 .58975 .0357125

1.3231 .43597 .554038 .

0.5872 0.2564 0.1474 0.0089

0.5872 0.8436 0.9911 1.0000

The value of condition index (CI) is obtained as (Maximum eigenvalue /minimum eigenvalue)0.5 = (2.34882/0.0357125)0.5 = 2.55

An Empirical Study on Stock Market, Bank and Economic Growth 111

Model 2 . pca GDP_form Capitalization Liquidity Credit Principal components / correlation Rotation: (unrotated

=

principal)

Number of obs Number of comp. Trace Rho

= 21 = 4 = 4 = 1.0000

Component

Eigenvalue

Difference

Proportion

Comulative

Comp 1 Comp 2 Comp 3 Comp 4

2.17227 1.1511 .453479 .223154

1.02117 .697619 .697619 .

0.5431 0.2878 0.1134 0.0558

0.5431 0.8308 0.9442 1.0000

The value of condition index (CI) is obtained as (Maximum eigenvalue /minimum eigenvalue)0.5 = (2.17227/0.223154)0.5 = 3.12 Test of heteroscedasticity: Breusch-Pagan Test for heteroscedasticity: Model 1 Breusch - Pagan / Cook-Weisberg test for heteroskedasticity Ho : Constant variance Variables : fitted values of uh chi2 (1) Prob > chi 2

= =

0.55 0.4586

Model 2 Breusch - Pagan / Cook-Weisberg test for heteroskedasticity Ho : Constant variance Variables : fitted values of Cap_form chi2 (1) Prob > chi 2

= =

3.54 0.0600

112 Santosh Poudel

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