Caspian Journal of Applied Sciences Research, 2(3), pp. 117-127, 2013 Available online at http://www.cjasr.com ISSN: 2251-9114, ©2012 CJASR
Full Length Research Paper Foreign Direct Investment (FDI) in Pakistan: Measuring Impact of Cost of War Against Terrorism, Political Instability and Electricity Generation Afza Talat 1, Anwar Zeshan 2 1
COMSATS Institute of Information Technology, Lahore COMSATS Institute of Information Technology, Sahiwal (PAKISTAN) *Corresponding Author: Anwar Zeshan,
[email protected] 2
Received 21 December 2012; Accepted 24 February 2013 Foreign Direct Investment (FDI) was proven to be a significant source of investment for developing countries which helps to bridge saving-investment gap, creation of employment opportunities, transfer of technology, and ultimately increasing economic growth of the host countries. This study empirically investigated the determinants of FDI for Pakistan for the period 1980 to 2010 by using annual secondary time series data. The study for the first time tested the impact of cost of war against terrorism, political instability, electricity generation, (along with the control variables of market size, inflation rate, exchange rate stability, trade openness and incentives provided to investors) on FDI inflows in Pakistan by using both ARMA model and ordinary least square regression technique. As expected, the estimated results confirmed that the war against terrorism and political instability had negative impact whereas electricity generation had a positive impact on FDI flows in Pakistan. Among the control variables market size, exchange rate stability, trade openness and incentives provided to investors had positively influenced the FDI whereas the inflation rate shown a negative relationship with foreign direct investment flows. Key words: Foreign direct investment, Pakistan, cost of war against terrorism, political instability, electricity generation.
by different countries to attract and benefit from this phenomenon. Developing countries face the dilemma of saving-investment gap and thus foreign direct investment may be helpful in fostering economic growth by bridging this gap, transferring innovative and advanced technology and escalating productivity, creation of employment and also increasing competition. FDI has proven to be a breath providing factor to third world countries to strengthen their national markets. Therefore, most of the developing countries are very keen to attract more inflows of FDI. FDI is very crucial for the economic growth of Pakistan as well since its economy faces the dilemma of saving-investment gap. Pakistan does not have sufficient internally generated sources to maintain the tempo of economic activities, therefore, FDI is very important to complement the domestic investment in order to achieve economic objectives. FDI is crucial for Pakistan in order to finance development projects, strengthening industrial sectors, increasing employment opportunities, attaining improved technology, enhancing domestic managerial skills, enhancing
1. INTRODUCTION During the last couple of decades, much has been written and discussed about the role and decisiveness of foreign direct investment in the context of its contribution to the growth of developing economies. FDI not only provides developing countries with the much needed capital for investment, it also enhances job creation, managerial skills as well as transfer of technology. All of these ultimately contribute to the economic growth and development (Wafure and Nurudeen, 2010). Developing countries are motivated enough to contest in attracting the foreign investment in order to foster and regulate the industrial sector in their respective countries. Policies are being framed, amended, and regulated in order to make it convenient for foreign investors to make investment in these countries. Fortunately or unfortunately, few nations benefited in attracting foreign investment and few started suffering. This situation leads to pondering on the issue of investigating the reasons behind, while evaluating the nature of the strategies and policies formulated
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productivity and output, improving balance of payments, improving foreign exchange reserves, improving physical infrastructure and human resources and ultimately achieving higher rate of economic growth. Economy of Pakistan has been under severe economic pressure because of War against Terrorism, which is expanding for the last four years in Afghanistan. Since 2006, that War has spread like contamination in Pakistani areas and it has cost us more than 35,000 people, 3,500 security staff, infrastructural destruction, millions of citizens’ internal migration, deterioration of investment environment, huge decline of productivity, rising unemployment and especially decline of economic activity (Economic Survey, 2010-2011). Pakistan’s economy has not experienced such a destructive economic and social turmoil ever before. Pakistan is continuously paying serious price both in security and economic terms and a larger proportion of its resources is being utilized for this war since the year 2000. Pakistan’s economy is bearing massive direct and indirect costs, which have risen from $ 2.669 billion during 2001-2002 to $ 13.6 billion during 2009-2010, and are expected to reach at $ 17.8 billion during 2010-2011 (Economic Survey, 20102011). During the last 10 years, direct and indirect costs of war against terrorism for Pakistan are $ 67.926 billion (Economic Survey, 2010-2011). Investments to GDP ratio of Pakistan has dropped from 22.5 % during 2006-2007 to 13.4 % during 2010-2011 and it also has severe affects on economy’s job creating capacity (Economic Survey, 2010-2011). Current security conditions are the crucial determinant of present and future FDI flows. Based on facts and figures, it is expected that cost of war against terrorism is significantly influencing FDI inflows in Pakistan. Poon (2000) argued that MNCs select a location that is politically stable for investment. Thus, stability of political environment in a country is a major factor for MNCs while selecting their investment destination. Since its independence in 1947, Pakistan is facing the problem of political instability which hinders inflows of FDI in Pakistan. Akhtar (2000) has mentioned that political instability has been a common phenomenon in Pakistan and affecting almost all sectors of the economy and also deteriorating investors’ confidence on Pakistan’s investment environment. Domestic as well as foreign investors are hesitant to make investments in Pakistan due to its unstable political environment. Investors are uncertain about their future return on investment
due to the volatile political conditions and therefore, are unwilling to undertake investment projects in Pakistan. Hence, it can be hypothesized that political instability in Pakistan is also adversely affecting FDI inflows. Another major current challenge being faced by Pakistan is the electricity shortfall resulting in load shedding. Load shedding of electricity in Pakistan has risen manifold and is severely affecting all sectors of the economy including FDI inflows. Although the Government assured that the load shedding will end by the end of 2009, whereas it has been doubled in comparison to 2009. Government has been unsuccessful in fulfilling their promises and therefore, investors are hesitant to make investment within Pakistan. It is one of the major issues in Pakistan and also expected to affect FDI inflows significantly as the domestic and foreign investors are shutting down their industrial units since it is impossible to sustain without the provision of electricity. A remarkable growth for world FDI has been witnessed during the last 20 to 25 years. Aggregate FDI stock amounted to merely 6.6 % of world GDP in 1980, whereas, it has risen to nearly 23 % in 2003 (UNCTAD, 2004). World FDI inflows during 2010 accomplished a projected amount of $1,244 billion (UNCTAD, 2010) – representing a smaller rise from 2009 position of $1,185 billion. The FDI growth within developing economies grew from $ 2.4 billion annually in year 1962 to about $ 17 billion in year 1980. Flows of developing nations grew by 40% ($ 233 billion) during 2004. Consequently, their portion of aggregate FDI stock was recorded at 36% – which is the highest percentage since year of 1997. Contrary to the developed region and transition economies where FDI flows declined during the year of 2010, FDI flows mounted by 12 % (i.e. $ 574 billion) in developing countries during 2010. Pakistan has received relatively greater FDI flows during the last two decades, because of its market oriented investment strategies and investment enabling environment. Because of the restrained investment strategies, FDI flows were meager upto 1991; though, it gradually went up during post liberalization era (Khan, 2000). FDI improved from $ 23 million during 1970 to $64 million during 1980 (UNCTAD, 2010). The second spur took place during late 1980s, when government eliminated restrictions for flows of capital, ownerships and transfer of remittances. The time period after 1988 is associated with privatization and liberalization processes which helped in accelerating FDI inflows from $ 110
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million during 1987 to $ 711 million during 1997 (Husain, 1999). These flows declined by $ 183 million during 2000. There is a major rise in capital inflows since 2004 where FDI amounts reached to $ 5.4 billion during 2008, representing 443 % increase in comparison to 2004; but, just 0.26 % greater than 2007. FDI flows had a decreasing trend tendency after 2007. Consequently, during 2009 FDI amounted to $ 3.21 billion, presenting a 51.1% decrease as compared to 35.3% decrease in previous year. Overall, Pakistan has a lot of potential for attracting FDI. Even though growth in FDI trend for several sectors reveals policies success; however, FDI flows significantly slowed down because of the worsening security conditions, institution’s weaknesses, corruption, political instability, weaker regulatory structures, and unstable global political relationships. The present study therefore, aims at exploring the relationship of cost of war against terrorism, political instability, electricity generation, market size, inflation rate, exchange rate stability, trade openness and incentives provided to investors with inflows of FDI in Pakistan for the period of 1980 to 2010 through Ordinary Least Squares (OLS) regression technique. The rest of the study has been organized as follows: section two presents literature review, section three explains materials and methods whereas results have been explained in section four and section five presents the discussions.
balance and dummy variable for the Canadian investment were significantly negative. Yang et al. (2000) analyzed the quarterly FDI inflows to ascertain the important determinants of Australian FDI. The change in the host country’s interest rate, changes in wage rates and industrial disputes enhanced FDI flows, whereas lagged inflation and openness decreased these flows. Fuat and Ekrem (2002) investigated the determinants of FDI inflows in Turkey for the period of 1980-1998 by using Johansen cointegration technique. The study found that the host country’s market size, infrastructure, attractiveness of domestic economy and openness of economy were positively related to inflows of FDI. The results had further shown that instability of exchange rate negatively affect FDI, whereas the variable representing instability of economy had negative but insignificant relationship with FDI inflows. Fedderke and Romm (2004) probed FDI determinants within South Africa by utilizing cointegration along with error correction techniques. Their findings demonstrated that political risk, property rights, market size, labor cost, openness and corporate tax rates were important variables in attracting FDI. Elijah (2006) examined the locational factors of FDI inflows in Kenya by applying Johansen co-integration, OLS and ECM techniques. The study found that openness of economy and human capital had positive effect on inflows of FDI in the shorter time period. But real exchange rate and inflation had negative relationship with FDI inflows in the long-run and short-run respectively. Moolman et. al (2006) focused on the supply side determinants of FDI in South Africa for the period 1970-2003. The findings pointed that openness, size of market, nominal exchange rates and infrastructure were the variables which policy makers in South Africa should concentrate on while striving to attract FDI. Sinha (2007) in his thesis focused on what the emerging economies (India) could learn from leader economies (China) for inviting FDI flows. He compared FDI inflows in India and China and found that India had developed because of its human capital, market size, political stability and market growth rate. Whereas, in case of China, congenial business climate variables consisting of creating strategic infrastructure, making structural changes, undertaking strategic policy initiatives for providing economic freedom, creating flexible labor laws and opening up of its economy were recognized as significant factors for attracting FDI. Mottaleb (2007) identified influential variables of FDI in 60 developing nations through OLS
2. LITERATURE REVIEW A number of perspectives and theories have been established to explain the pattern and level of FDI since the late 1950s. Both empirical and theoretical research on the motivation for FDI and the formation of multinational enterprises (MNEs) has emphasized and pointed out different variable effecting FDI flows. Given that there are numbers of theoretical models which explain FDI flows, a number of variables have been tested in empirical studies to ascertain their impact on FDI. For instance, Tcha (1999) explored the determining factors of Australian FDI flows utilizing a combination of country-specific and aggregate quarterly pooled data (six developed economies including the US, the UK, Japan, New Zealand, Germany and Canada). In quarterly FDI model, labor disputes and real exchange rate were the only two determining variables. Whereas, in country-specific model of FDI, volatility of exchange rate, home country’s current account
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resources, economy’s openness and governance system quality had significant positive association whereas individualism, hierarchal distance and corruption control had negative association with FDI inflows. Researchers had also investigated various factors which determine the level of FDI inflows in Pakistan. For example, Akhtar (2000) analyzed locational determinants of FDI. The author argued that market size, exchange rate and relative interest rate had positive and significant relationship with FDI stock. Shah and Ahmad (2003) examined the determinants of FDI for the period of 1961-2000 by applying Johansen co-integration which was followed by Error Correction Model (ECM). The author found that cost of capital had negative relationship, while infrastructure, tariffs, market size and political stability had positive relationship with FDI inflows. Aqeel and Nishat (2004) empirically identified the variables of FDI growth in Pakistan for the period of 1961 to 2003. They used co-integration along with error correction techniques for identifying factors which influence level of FDI. The results had shown that corporate tax rate, import tariffs, exchange rate, devaluation of rupee and liberalization measures had positive and significant relationship with FDI inflows. Dar et al. (2004) analyzed the explanatory variables which determine the patterns of FDI flows in Pakistan for the period of 1970-2002 through applying ARDL econometric technique. The variables which were considered in the analysis consist of economic growth rate, economy’s openness, stability of exchange rate, interest rate, unemployment and political risk index. The authors found that all the variables were significant with expected signs to explain FDI inflows in Pakistan. Azam and Luqman (2006) investigated effects of a variety of economic factors on FDI inflows into Pakistan, Indonesia and India for the period of 1971 to 2005. The authors found that that market size, infrastructure, trade openness, domestic investment, return on investment had significant and positive relationship while external debt, indirect taxes had significant and negative relationship with FDI inflows. Azam and Kahttak (2009) evaluated the influence of political instability and human capital on FDI stock in Pakistan for the period ranging from 1971 to 2005 by utilizing least square method. This paper found a positive and significant relationship between human capital and FDI stock, while the relationship between political instability and FDI was positive but statistically insignificant.
methodology for period of 2003-2005. He confirmed that more GDP, larger growth rate of GDP, friendly business environment and infrastructure effectively attracted FDI. Demirhan and Mascan (2008) explored determining variables of FDI inflows within 38 developing nations through regression analysis covering period of 2000-2004. Results revealed that per capita GDP growth rate, telephone lines per 1,000 persons and openness had significant and positive relationship, while taxation rates and inflation had significant but negative association with FDI inflows. Masuku and Dlamini (2009) investigated locational variables of FDI in Switzerland by utilizing Cointegration along with ECM techniques over period of 1980-2001. The authors concluded that internal and external economic stability, infrastructure and economy’s openness had positive correlation whereas home market size and domestic market attractiveness had negative correlation with FDI stock. Yol and Teng (2009) explored short run and long run domestic variables affecting FDI in Malaysia through cointegration econometric analysis covering period of 19752006. The results depicted that GDP, exchange rate and infrastructure positively whereas exports negatively affected FDI in long run. In short run, GDP, infrastructure and exports negatively whereas exchange rate and openness positively influenced FDI. Sen and Mohsin (2010) examined the determinants and problems which decelerated FDI stock in Bangladesh for period from 1986 to 2008. They discovered that inferior infrastructure, urban violent activities, political disturbances, inconsistency of economic policies and bureaucracy were the crucial deterrents of FDI. Shahrudin et al (2010) analyzed FDI determinants in Malaysia for period of 1970-2008 by using ARDL framework. The study established that GDP growth rate and money supply had positive and significant correlation with FDI inflows. Wafure (2010) observed the determining factors of Nigerian FDI for period of 1977-2006 through employing Error Correction Model (ECM) technique. The results of the study stated that the host country’s market size, deregulation of economy and political instability had a positive and significant effect on FDI, whereas the exchange rate had negative and significant relationship with FDI. Rihab and Lotfi (2011) investigated important variables to determine the level of FDI for 71 developing countries by utilizing dynamic panel data technique for period of 2001-2006. They found that GDP, human
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Awan et al. (2010) evaluated the FDI determinants for period of 1971-2008 by applying co-integration and ECM econometric techniques. The authors concluded that Gross Fixed Capital Formation, inflation and level of trade openness had statistically significant and positive impact on FDI, whereas, current account balance had statistically significant and negative impact on FDI inflows in Pakistan. Awan et al. (2011) studied the most important economic determining factors of FDI flows within Pakistan’s commodity producing sector for the period of 1996-2008. This paper applied Error Correction Model (ECM) and Cointegration techniques to estimate the explanatory factors of FDI inflows. The study found that GDP, GDP real growth rate in commodity producing sector, foreign exchange reserves, gross fixed capital formation, per capita income and trade openness had positive signs with FDI inflows within Pakistan’s commodity producing sector. Hakro and Gumro (2011) observed the determinants of FDI in Pakistan for the period of 1970-2007. Four broad groups of variables had been tested to determine their relationship with FDI which consisted of cost related variables (wage rate, foreign exchange rate and interest rate); factors improving investment environment (liberalization and economy’s openness); macroeconomic variables (output growth, human capital, market size, and infrastructure quality); development strategy, political stability, and cumulative risk rating together with structural shocks related to 1988, Nuclear tests in 1999 and event of Sept. 11, 2001. The results suggested that the macro-economic factors, cost related factors and cumulative risk index factors as the key determinants in short-term analysis. The finding also suggested that there was a long run relationship among FDI, macro economic variables and openness. Currently, Pakistan is facing severe problems of cost of war against terrorism, political instability and electricity generation and these factors are expected to affect level of foreign direct investment as foreign investors are losing confidence on Pakistan’s economic and political environment. After reviewing existing literature on determinants of FDI, it can be observed that there is a dearth of literature which investigated these variables as determinants of foreign direct investment in general and for Pakistan in particular. Therefore, this study for the first time, intends to determine the relationship of cost of war against terrorism, political instability, electricity generation, market size, inflation rate, exchange
rate stability, trade openness and incentives provided to investors with inflows of FDI in Pakistan for the period of 1980 to 2010 through Ordinary Least Squares (OLS) regression technique. 3. MATERIALS AND METHODS The data for the period 1980 to 2010 has been collected from reports of State Bank of Pakistan (SBP), Board of Investment (BOI) Pakistan, Economic Surveys of Pakistan, Federal Board of Revenue (FBR) Pakistan and Federal Bureau of Statistics (FBS) Pakistan, World Bank Development Indicators, IMF, USDA/ERS International Macroeconomic Database and United Nations Statistical Division Database. First of all, descriptive statistics have been calculated for dependent and Independent variables. Correlation matrix has been calculated to analyze the prevalence of correlation among the variables. The time series nature of the data has made it essential to check the stationarity of the data, therefore, stationarity of the data has been measured through Augmented Dickey-Fuller (ADF) Unit Root Test. The Least Squares regression model has been used for measuring the relationship of FDI inflows with cost of war against terrorism, political instability, electricity generation, market size, inflation rate, exchange rate stability, trade openness and incentives provided to investors. The following regression model has been stimated: LnFDI = β0 + β1LnTerror + β2Pol + β3LnElec+ β4RGDP + β5Trade + β6Exch + β7Inf + β8Incen + Ut Where: LnFDI = Inflows of foreign direct investment in million rupees LnTerror = Cost of war against terrorism in million rupees Pol = Value of 0 for civilian rule and value of 1 for military rule LnElec = Electricity production in KWH RGDP = Real growth rate of gross domestic product in percentage Trade = Trade openness calculated as ratio of exports to Imports Exch = Annual growth rate in exchange rate of Rupee / $ Inf = Annual rate of inflation in percentage Incen = 1 for the period of 1989 to 2010, 0 otherwise 4. RESULTS
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First of all, the time series nature of the data had made it essential to analyze the stationarity of the variables. Therefore, before estimating the regression model, the Augmented Dickey Fuller (ADF) unit root test had been performed to check the stationarity of the dependent and independent variables. The results of the ADF unit root test had been presented in table 3: The results of table 3 shown that variables of Foreign Direct Investment (FDI), electricity generation, real growth rate of GDP, exchange rate and inflation rate were stationary at level, whereas variables for cost of war against terrorism and trade openness were stationary at first difference. After testing stationarity of the variables, the ARMA model had been employed to determine the relationship of cost of war against terrorism, political instability, electricity generation, real growth rate of GDP, trade openness, exchange rate stability, inflation rate and incentives provided to investors with FDI inflows in Pakistan. Least Squares method had been used for estimation of ARMA parameters. The results of ARMA model had shown that the moving average term for dependent variable i.e. LnFDI(-1) had insignificant coefficient, indicating that FDI lag value was not affecting FDI inflows in case of Pakistan.
Therefore, ARMA method was not appropriate in this case, and consequently, Ordinary Least Squares (OLS) regression model had been employed to estimate the relationship of FDI inflows with independent variables. The values of adjusted R-square, log likelihood, F-statistic and Durbin-Watson statistics had also shown that the results of OLS regression model were better than results of ARMA model. Therefore, OLS estimation results had been presented in the table 4. Estimated results of regression equation demonstrated that the value of Adjusted R-square was 0.95 which indicated that the independent variables in the regression equation had explained about 95 percent variations occurring in inflows of foreign direct investment for Pakistan. The value of Durbin Watson statistic for this regression model was 2.37 which indicated that the mathematical form of the regression equation was accurate and also absence of autocorrelation among the variables used in the regression equation. The value of AIC for this regression model was 0.78, which indicated that the model had substantial support for relative goodness of fit and highly capable of being utilized for making inferences.
Table 3: ADF Stationarity Unit Root Test for Variables Variables
T-ADF Statistics
LnFDI
-4.843915 (0.0033)
LnTerror
-5.444722 (0.0001)
LnElec
-4.488018 (0.0013)
RGDP
-4.032378 (0.0041)
Trade
-5.423869 (0.0001)
Exch
-4.113373 (0.0033)
Inf
-3.753901 (0.0091)
Critical Values
Decision
1% level = -4.356068 5% level = -3.595026 10% level = -3.233456
Stationary at level
1% level = -3.679322 5% level = -2.967767 10% level = -2.622989 1% level = -3.670170 5% level =-2.963972 10% level = -2.621007 1% level = -3.670170 5% level =-2.963972 10% level = -2.621007 1% level = -3.679322 5% level = -2.967767 10% level = -2.622989 1% level = -3.670170 5% level = -2.963972 10% level = -2.621007 1% level = -3.711457 5% level = -2.981038 10% level = -2.629906
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Stationary at 1st difference Stationary at level
Stationary at level Stationary at 1st difference Stationary at level
Stationary at level
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Table 4: OLS Regression Estimates Dependent Variable: LNFDI Method: Least Squares Included observations: 31 after adjustments Variable
Coefficient
Std. Error
t-Statistic
LNTERROR POL LNELEC RGDP TRADE EXCH INF INCEN C
-0.009942 -0.586467 2.524508 0.097663 0.126975 0.023206 0.016170 1.037961 -25.24071
0.020866 0.301843 0.315306 0.035629 0.026525 0.011460 0.026123 0.384701 3.419254
-0.476471 -1.942954 8.006535 2.741119 4.786925 2.024926 0.619001 2.698095 -7.381934
R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic)
0.966203 0.953913 0.317437 2.216859 -3.099705 78.61873 0.000000
Mean dependent var S.D. dependent var Akaike info criterion Durbin-Watson stat
Prob. 0.6384 0.0649 *** 0.0000 * 0.0119 ** 0.0001 * 0.0552 *** 0.5423 0.0131** 0.0000* 5.965065 1.478668 0.780626 2.366091
* Significant at 1 Percent. ** Significant at 5 Percent. *** Significant at 10 Percent.
The estimated results had shown that the cost of war against terrorism had a negative sign as expected which was consistent with results of Agrawal (2011) who investigated the impact of terrorism on FDI inflows and reported that transnational terrorism events negatively affect total FDI inflows in developed countries. In case of Pakistan, this variable had insignificant relationship with inflows of FDI which might be due to the fewer observation for cost of war against terrorism for 10 year i.e. from year 2001 to year 2010. However, it confirmed the expectation that it is one of the major hindrances in attracting overseas investors and foreign direct investment in Pakistan as the foreign investors were facing security threats and they are also uncertain about return on their investment. The results also revealed that political instability had a negative and significant affect on inflows of FDI as anticipated. This result was similar to the results of Azam and Khattak (2009). The investors made investment in only those countries where they believed that their capital investment and return on that investment would be safe and sound. But unfortunately, Pakistan constantly faced the dilemma of instable political
environment, therefore, foreign investors were hesitating to make investment in Pakistan because of political instability. The electricity generation was positively and significantly affecting the inflows of FDI in Pakistan as expected. The high coefficient for electricity generation indicated the magnitude and effect of electricity generation for attracting FDI inflows. Pakistan was continuously unable to generate sufficient quantity of electricity to fulfill the existing demand for electricity. The shortfall in the supply of electricity resulted in electricity load shedding and causing all sorts of troubles for businesses as well as residents of Pakistan. The business and industrial units were not able to survive and a large number of businesses were shutting down their production units resulting in outflows of capital investment from Pakistan. The market size had significant and positive role in attracting inflows of FDI into Pakistan. This result is consistent with findings of Azam and Lukman (2006), Awan et.al. (2010) and Azam et. al., (2011). The estimated results further revealed that trade openness of the Pakistan’s economy also had a positive and significant relationship with inflows of FDI in Pakistan. This finding
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corresponds with findings of Dar et.al. (2004), Azam and Lukman (2006) and Awan et.al. (2010). Moreover, the estimated results also disclosed that exchange rate stability had a positive and significant effect on FDI. This result is in align with the findings of Aqeel and Nishat (2004) and Dar et.al. (2004) that appreciation of exchange rate encourages FDI within host economy. Another finding of regression results was that the fiscal incentives provided by the Pakistani government were positively associated with inflows of FDI, was significantly attracting FDI. This finding corresponds with results of Aqeel and Nishat (2004) and Wafure and Nurudeen (2010). Finally, the variable of inflation rate had positive association with inflows of FDI which was contrary to its expected sign but this relationship was statistically insignificant. This finding is consistent with the findings of Azam and Lukman (2006).
The regression diagnostics have been estimated to verify and support the regression results. First of all, normality of the data has been tested through One-Sample Kolmogorov-Smirnov Test. The results have been shown in table 5: The results of One Sample KolmogorovSmirnov Test indicates that the data has normal distribution because the P-Value is 0.949 which is greater than 0.05, therefore, the hypothesis regarding normality of data has been accepted. As mentioned above, the value of Durbin-Watson Statistics is 2.366092 which depicts that that the observations are independent of each other as the values is within acceptable range of 1.5-2.5. Secondly, to check collinearity of predictors, Variance Inflation Factor (VIF) Values have been estimated and the results have been shown in table 6:
Table 5: One-Sample Kolmogorov-Smirnov Test Unstandardized Residual N
31
Normal Parametersa
Mean
.0000000
Std. Deviation Most Extreme Differences
.27183687
Absolute
.094
Positive
.092
Negative
-.094
Kolmogorov-Smirnov Z
.521
Asymp. Sig. (2-tailed)
.949
a. Test distribution is Normal.
Table 6: Coefficients Table Variable
Collinearity Statistics Tolerance VIF
LnTerror
.208
4.811
Pol
.147
6.825
LnElec
.097
9.305
RGDP
.706
1.417
Trade
.221
4.518
Exch
.669
1.495
Inf
.320
3.127
.107
9.381
Incen a. Dependent Variable: LnFDI
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The results of Variance Inflation Factor (VIF) have shown that the predictors don’t have problem of collinearty because the VIF Values for all the predictors are less than 10, so it indicates that all the predictors are acceptable. Thirdly, the results of Studentized (Residuals) test have shown that there is no outliar value in the data because all the values are within acceptable range of -3 to +3. Finaly, results of Cook-D Test have shown that there is no influential value in the data as all values are less then acceptable value of 1.
Thirdly, Pakistan should take some effective measures to increase electricity generation on urgent basis for improving economic conditions of the country. The government should immediately formulate policies aimed at increasing electricity generation and implement these policies effectively to restore investors’ confidence. It will assist in improving economic and financial conditions and also attract domestic and foreign investors to make investment in Pakistan. Fourthly, the market size is also a very important variable for increasing inflows of FDI in Pakistan. Larger market size and increasing GDP growth rate indicates better market opportunities for foreign investors to earn greater investment returns. Therefore, efforts should be made to increase market size and GDP growth rate for attracting overseas investors. Finally, the exchange rate of Pakistani rupee should be strengthened in order to lure the foreign investors and to attract more inflows of foreign direct investment. Finally, more fiscal incentives should be offered to the foreign investors along with further deregulation of the economy for attracting inflows of FDI in Pakistan. Although this empirical investigation has produced very interesting results however, there are few limitations of the study. The data for cost of war against terrorism in Pakistan has been available only for the period of 2001-2010. Some other appropriate proxy for cost of war against terrorism in Pakistan can be used in the analysis for a longer time period. The dummy variable has been used in the regression model for measuring the political stability in Pakistan. Some other quantifiable proxy may be used for measuring political stability.
5. DISCUSSION This study has investigated the determinants of FDI in Pakistan including cost of war against terrorism, political instability, electricity generation, real growth rate of GDP, tradeopeness, exchange rate stability, inflation rate and incentives provided to investors for the period 1980 to 2010 based on time series data. The results indicate that the electricity generation, political instability, market size, trade openness, exchange rate stability and fiscal incentives provided to investors have significant and positive relationship with inflows of foreign direct investment whereas variables for cost of war against terrorism and inflation rate have insignificant relationship with foreign direct investment. The main contribution of this study is to investigate, for the first time, the relationship of cost of war against terrorism, political instability and electricity generation with FDI inflows in Pakistan since these variables have not yet been focused in the existing literature. The estimated results have shown that these variables are affecting, as expected, FDI inflows in Pakistan. Therefore, these variables need to be focused in order to attract more FDI inflows. Based on empirical findings, the following recommendations have been put forward in order to attract more inflows of FDI in Pakistan: First of all, the regulatory authorities and policy makers should take some concrete measure in order to reduce the cost of war against terrorism and improve the security conditions in the country. In this context, some sincere governmental policies and efforts are required to bring the country out of this problem and increase the foreign direct investment in Pakistan. Secondly, the government should strengthen political institutions and adopt democratic principles for ensuring stability of political environment which may lead to increased FDI inflows.
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