Evidence from Malaysia and Thailand - Core

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ScienceDirect Procedia - Social and Behavioral Sciences 145 (2014) 51 – 60

ICGSM 2014

Monitoring financial risk ratios and earnings management: evidence from Malaysia and Thailand Nor Farhana Selahudina*, Nor Balkish Zakariaa, Zuraidah Mohd Sanusia and Pornanong Budsaratragoonb* a

Accounting Research Institute, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia b University of Chulalongkorn, 245 Phayathai Road, Pathumwan, Bangkok 10330, Thailand

Abstract The main focus of this study is to examine the mean difference of earnings management, leverage, financial distress and free cash flow between the neighbours —Malaysia and Thailand. Based on 335 Malaysian listed firms and 224 Thailand listed firms from 2010 to 2012, this study finds that there is a significant mean difference for earnings management, leverage, and financial distress between Malaysia and Thailand. These results should be of interest to public listed firms, regulators and various stakeholders to assist proper guidelines and understanding on earnings management. © 2014 2014 Published by Elsevier Ltd. is anLtd. open access article under the CC BY-NC-ND license © The Authors. Published byThis Elsevier (http://creativecommons.org/licenses/by-nc-nd/3.0/). Peer-review under responsibility of the Accounting Research Institute, Universiti Teknologi MARA. Peer-review under responsibility of the Accounting Research Institute, Universiti Teknologi MARA. Keywords: leverage, financial distress, free cash flow, earnings management;

1. Introduction Within the opportunities and loopholes offered by the accounting system, managers are able to manage earnings by choosing accounting methods that are acceptable by the General Accepted Accounting Principles (GAAP) or by making changes in ways which given methods are applicable (Pornsit, Miller, Yoon, and Kim, 2008). Other than that, managerial intervention may occur in the reporting process through operational decisions like alterations in shipment schedules, acceleration of sales and delaying of maintenance and research and development (R&D) expenditures (Roychowdhury, 2006) . According to Dechow and Skinner (2000), accrual accounting is part of

* Corresponding author. E-mail address: [email protected]

1877-0428 © 2014 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Peer-review under responsibility of the Accounting Research Institute, Universiti Teknologi MARA. doi:10.1016/j.sbspro.2014.06.010

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Nor Farhana Selahudin et al. / Procedia - Social and Behavioral Sciences 145 (2014) 51 – 60

earnings management and it is the most common tool in earnings management practice that uses discretionary accruals. Prior studies had reviewed several issues regarding leverage, financial distress and free cash flow towards earnings management (Andrade and Kaplan, 1998; Jones and Sharma, 2001; Bukit and Iskandar, 2009; Habib, Bhuiyan and Islam, 2012; Tan, 2012). However, the empirical evidence regarding this is not conclusive. There are several reasons why it is desirable to conduct a study on Malaysia and Thailand. First, there are limited studies on the comparison between Asian countries on earnings management. Second, Malaysia and Thailand share the same experience of financial crisis turmoil in 1997. Third, Thailand has recorded the highest score in ASEAN corporate governance scorecard and Malaysia is one of the largest market capitalizations of listed firms for 2009 to 2012 among the Asian countries. Thus, this study is conducted on two Asian countries which are Malaysia and Thailand. This study aims to compare whether there is a significant difference in earnings management, leverage, financial distress and free cash flow between Malaysia and Thailand. This study was driven by several motivations. First, financial distress has long been an issue of concern to governments and other stakeholders because the decline in financial performance may eventually result in bankruptcy and increased costs (Habib et al., 2012). If the firm falls under financially distress condition, the firm might be unable to fund its business operation and the managers’ remunerations and positions are expected to be unsecured. This may lead the financially distress firm to suffer loss of reputation and be subjected to acquisition by other firms in an extreme case (Liberty and Zimmerman, 1986; Gilson, 1989). Next, free cash flow may create agency problems (Jones and Sharma, 2001). According to Jensen (1986) agency problems may worsen particularly when investment opportunities are low with high free cash flow. This happens because managers may have the choice of any unprofitable investments that benefits their self-interest such as shirking (Ross, 1973) and perquisites (Jensen and Meckling, 1976). As a result, the firm may experience low growth (Gul, 2001). In order to conceal these activities, managers are forced to manage earnings via accounting discretions (Jones and Sharma, 2001; Bukit and Iskandar, 2009; Chung, Firth and Kim, 2005). Lastly, a firm with high leverage may face the risk of bankruptcy if it is unable to make payments on its external debt financing (Zagers-mamedova, 2009). If a high leverage firm wishes to take out a new loan, lenders will scrutinize several measures and demand that it keeps its debt within reasonable boundaries. This will put tremendous pressure on the managers to manage earnings. Managers in high leverage firms are expected to manage earnings in order to inflate income by using accounting procedures and avoid debt covenant violations (Sweeney, 1994; Dichev and Skinner, 2002; Beatty and Weber, 2003). However, the evidences are not conclusive when compared to different countries (Aman, Iskandar, Pourjalali and Teruya, 2006).

2. Literature review There are no specific or clear definitions of earnings management. Schipper (1989) defined earnings management as management intervention in the external financial reporting process based on the manager’s self interest purposes. Roychowdhury (2006) argued that managerial intervention may occur through operational decisions like alterations in shipment schedules, acceleration of sales and delaying of maintenance and research and development (R&D) expenditures. Although earnings management has been defined in many ways, the basic concept of earnings management underlies the manipulation of financial reporting information by management of a firm for their selfinterests in the expense of others. On the other hand, Healy and Wahlen (1999) proposed that financial reports can be manipulated by complementing with the manager’s judgmental opinion. These can be done by selecting accounting methods which are accepted by the General Accepted Accounting Principles (GAAP) or by making changes in the ways given methods are applied as offered by accounting system (Pornsit et al., 2008). Hence, the loopholes in accounting rules provide opportunities to managers to engage in earnings management (Simon, 2001; Jiang, Lee and Anandarajan, 2008). Consequently, the role of accrual accounting is believed to have caused some forms of earnings management and it is difficult to distinguish between the manipulated accruals item from the appropriate accrual accounting choice (Dechow and Skinner, 2000; Aman et al., 2006). Earnings management is therefore a device used by the management to deliberately manipulate the firm's earnings so that the figures perfectly match an expected value of the firms.


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Jones and Sharma (2001) conducted a study to examine the impact of free cash flow and leverage on earnings management for the period of before and after the establishment of Australian cash flow regulations. The study found that leverage had given different impact on earnings management while free cash flow gave the same impact before or after the establishment of the regulations. In another study, Habib et al. (2012) found that managers of distressed firms engage in more income-decreasing earnings management practices as compared to healthy firms and these findings are consistent even after the global financial crisis period. They stated that earnings management occurred in firms which faced financial distress condition and this could provide incentives for managers to manipulate earnings (Habib et al., 2012). Sometimes manager tend to get involved in earnings management in order to hide unlawful transactions and hence, face high litigation risk (Jiang et al., 2008; Rahman and Ali, 2006). However, the study claimed that management is more likely to manage earnings in order to avoid reporting the volatility of the earnings and losses. Indirectly, management intentionally tries to maintain the reputation of the firm by showing that their firms are performing well in the market. As a result, management will gain better compensation such as bonus, prestige, job security, pension contributions, stock awards and future promotions (Bukit and Iskandar, 2006; Demirkan and Platt, 2009). A study done by Chung et al. (2005) argued that manager in low growth firms with surplus free cash flow intentionally manage earnings because they want to avoid reporting loss and negative earnings. This low growth is accompanied with investments in negative values of net present values (NPVs). A study by Eldenburg, Gunny, Hee and Soderstrom (2007) reported that managements who manage accruals are motivated by intention to meets the external benchmark such as to maintain or increase the organization’s donation base, to allay creditors’ concerns and to reduce the cost of debt capital since they have no publicly share fund. Thus, earnings management might differ according to the technique applied, motivation, type of organization and country. There is a dearth of study that focusing on earnings management in Thailand and most of the studies are based on the international comparison between several countries (Simon, 2001; Charoenwong and Jiraporn, 2009; Kanagaretnam, Lim and Lobo, 2010; Sukeecheep, Yarram and Farooque, 2013). Sukeecheep et al. (2013) had conducted a study to investigate the association between board characteristics and earnings management behaviour by using 550 public listed firms in Thailand as the sample for their study. By using four proxies for board characteristics, they found that boards of directors are likely to restrain earnings management because they have acquired enough knowledge and expertise in business affairs. Hence, they applied their knowledge and expertise in monitoring the performance of their firms rather than using earnings management. According to Charoenwong and Jiraporn (2009), they found that management of the firms in Thailand and Singapore used earnings management in order to avoid reporting losses and negative earnings growth. However, the results are inconsistent when financial crisis and across different types of industry are being considered. On the other hand, study in Thailand offers unique culture of the country which would contribute a significant impact to the attitude of managers on earnings management. As reported by Simon (2001), Thailand managers tended to be less willing to highlight earnings management activities as compared to the western managers because of difference in culture. Hence, there are many factors that may influence earnings management especially for two or more different countries (Guan, Pourjalali, Sengupta and Teruya, 2005).Thus, this study proposes the following hypothesis; H 1: There is mean significant difference for earnings management between Malaysia and Thailand H 2: There is mean significant difference for leverage between Malaysia and Thailand H 3: There is mean significant difference for financial distress between Malaysia and Thailand H 4: There is mean significant difference for free cash flow between Malaysia and Thailand 3. Methodology The sample for this study consists of seven industrial sectors listed in Bursa Malaysia and in the stock exchange of Thailand. The seven sectors from Malaysia consists of industrial products, consumer products, trading and services, construction, properties, plantations and technology while the seven sectors from Thailand consists of industrials, consumer products, services, property and construction, agro and food, resources and technology. These sectors are chosen because of homogeneous characteristic between these sectors will contribute more accurate result.

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This study excludes the finance, investment, trust and funds firms due to different regulatory requirement on these industries which are in compliance with Bank and Financial Institution Act 1989 (BAFIA); and different accruals behaviour (Srinidhi and Gul, 2007). In addition, industries with less than ten firms are also excluded from the study because it could affect the measurement of earnings management and they are inappropriate to be generalized as an industry (Peasnell, Pope and Young, 2000). The pool data for this study was from 2010, 2011 and 2012. However the data was collected from 2009 to 2012. The sample selection process is summarized in Table 1 as shown below. Table 1: Sample selection for evidence from Malaysia and Thailand Malaysia st

Thailand

928

615

Banking, finance and insurance sector.

(59)

(60)

Industry with less than 10 firms

(11)

(19)

(523)

(312)

335

224

Total number of firms listed in Bursa Malaysia as at 31 July 2013. Less:

Firms with missing data (Unavailable data for year end 2009, 2010, 2011 and 2012). Final sample

3.1 Dependent variable

This study used discretionary accruals as a proxy for earnings management. The model employed to measure earnings management in this study is Modified Jones Model as proposed by Dechow, Sloan and Sweeney (1995) because the model is the most relevant for economic environment in Malaysia and Thailand. This model provides a cross sectional version in measuring the earnings management (Habib et al., 2012; Kim and Yoon, 2008; Siregar and Utama, 2008). This study used transformed method in order to get absolute value of earnings management because it could provide the mixed effect of earnings management irrespective of whether managers are increasing or decreasing of income and it is consistent with the studies of Rahman and Ali (2006), Choi, Kim, Kim and Zhang (2010) and Jouber and Fakhfakh (2012). Formula of estimated Total Accruals as proposed by Dechow et al. (1995) as below: TACCit = EBEIt it - CFO it (1) Where: EBEItit CFO it TACC it

Income before extraordinary items of firm i in year t Cash flow from operation of firm i in year t Total accruals

Thus, the total accruals are included in the regression model to generate the normal accruals and the residual value is represented as discretionary accruals (proxy of earnings management) with the following equation: TACCit/ TA it – 1 = ɑ 0 (1 / TAit – 1 ) + ɑ1 [(∆ REV it - ∆ ARit) / TAit -1] + ɑ2 (PPE it / TAit – 1)+ Ɛ it Where: TAit – 1 ∆ REVit ∆ ARit PPE it TACCit

Total assets of firm i at the end of year t -1 Change in revenue from year t – 1to year t Change in account receivables from year t – 1to year t Property, plant, and equipment of firm i in year t Total accruals of firm i in year t

J

(2)

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3.2 Independent Variables This study utilized three independent variables which consists of leverage, financial distress and free cash flow. There are mixed sentiments on whether leverage may influence the potential for the manager to exercise earnings management. Based on studies in Malaysia, leverage did not affect earnings management (Aman et al., 2006). There was also a study that provides evidence that high levered firms managed earnings in order to avoid debt covenants violations (Chen and Liu, 2010). Some literatures suggested that debt may discourage free cash flows from business operations. Hence, debt or leverage will reduce the tendency of managers to exercise earnings management (Stulz, 1990; Hart and Moore, 1995). This current study will use debt ratio (total debt/total assets) as a measurement for leverage of the public listed firms similar to the measurements used in previous studies (Rahman and Ali, 2006; Choi et al., 2010). For financial distress, Altman Z-Score will be employed in order to measure the financial condition of the firm as a signal for financial distress developed by Altman (1968). Firm that has Z-scores smaller than 1.81 will be classified as financially distressed firms while firms with Z-scores over 2.67 will be classified as financially healthy. Firms will be classified as being in the gray area if their Z-scores are between the range of financially healthy and financially distressed firms as suggested by Demirkan and Platt (2009). The linear equation of Altman Z-Score model is as follows: Z = 0.012X1 + 0.014X2 + 0.033X3 + 0.006X4 + 0.999X5 Where: X1 working capital/total assets X2 retained earnings/total assets X3 earnings before interest and taxes/total assets X4 market value of equity/total liabilities X5 sales/total assets Z overall index, the lower a firm’s Z-score the higher its probability to bankrupt.

(3)

Free cash flow will be measured by deducting tax expense, interest expense, and dividend from operating income before depreciation as introduced by Lehn and Poulsen (1989) and scaled by total assets as employed by Jones and Sharma (2001). Firms are categorized as having potential free cash flow agency problems when free cash flow is above-median and price to book ratio is below-median. Moreover, the manager may expect extra rewards such as bonus and other incentives if the firms have surplus cash (Chung et al., 2005) 3.3 Control variables The cultural values of a country would affect various accounting decisions and choices including managers’ tendencies to manage earnings (Guan et al., 2005). Thus, the sample selection firms were categorized based on their country in this study. The country is coded as 1 if the firm categorized as public listed firms in Malaysia and 0 if the firm categorized as public listed firms in Thailand. There is evidence that accruals may vary by industry (Gu, Lee and Rosett, 2005). According to Charoenwong and Jiraporn (2009), earnings management practices is inconsistent when considering different types of industry. Thus, the sample selection firms were categorized according to industries provided in Bursa Malaysia and SET listed firms (Bursa Malaysia Listed Companies, 2013; The Stock Exchange of Thailand Listing Companies, 2013). The industry is coded as 1 if the firm categorized as either one of the industry and 0 of otherwise.

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4. Findings Table 2. Descriptive statistic for Malaysia and Thailand Malaysia Minimum Maximum Dependent variable DACC Independent variables LEV DISTRESS FCF Control variables

Mean

Std. Dev

Thailand Minimum

Maximum

Mean

Std. Dev

0.0001

0.6258

0.0596

0.06810

0.0000

0.7508

0.0726

0.08778

0.0000 0.0070 -0.4520

0.7410 4.4480 1.8480

0.1888 0.7958 0.0346

0.16379 0.62336 0.10365

0.0000 0.0114 -0.5910

3.5592 6.1545 0.4204

0.2319 0.9993 0.0300

0.24686 0.6778 0.09206

Frequency

Percentage

Frequency

Percentage

234 66 288 90 60 54 213

23.3 6.6 28.7 9.0 6.0 5.4 21.2

84 72 123 105 63 159 66

12.5 10.7 18.3 15.6 9.4 23.7 9.8

CONSPROD CONSTR INDSPROD PLANT PROPERTY TECH TRDGSER

AGRFOOD CONSPRO D INDSPROD PROPCONS RESOURCE S SERVICES TECH

Table 3. Descriptive statistic for full sample

Dependent variable DACC Independent variables LEV DISTRESS FCF Control variables

Minimum

Maximum

Mean

Std. Dev

0.0000

0.7508

0.0648

0.07684

0.0000 0.0065 -0.5910

3.5592 6.1545 1.8475

0.2061 0.8773 0.0328

0.20228 0.65320 0.09917

Frequency COUNTRY

AGRFOOD CONSPROD CONSTR INDSPROD PLANT PROPCONS PROPERTY RESOURCES SERVICES TECH TRDGSER

Thailand 672

Percentage Malaysia 1005

Thailand 40.1

Frequency

Percentage

84 306 66 411 90 105 60 63 159 120 213

5.0 18.2 3.9 24.5 5.4 6.3 3.6 3.8 9.5 7.2 12.7

Malaysia 59.9

Table 2 and 3 show the result of descriptive analysis for Malaysia, Thailand and full sample. For leverage (LEV) of the firm, the maximum value of leverage is 0.7410 for Malaysia, and 3.5592 for Thailand. This indicates that Thailand has higher debt as compared to Malaysia. As a result, the maximum value of value of full sample is


reporting the same value as Thailand. The mean value of leverage for Malaysia and Thailand is 0.1888 and 0.2319. However, the mean value for full sample is 0.2061. For financial distress (DISTRESS), the maximum value of Zscore is 0.7410 for Malaysia and 6.1545 for Thailand. The higher of Z-score value will indicate that the firm is healthier as compared to the lower value of Z-score. The mean value of Z-score for Thailand is slightly higher than Malaysia represented by 0.9993 and 0.7958 respectively. However, in average, the Z-score value is 0.8773. According to Demirkan and [26], the firm is classified as financially distressed if the Z-score value is smaller than 1.8. Hence, most of the firms listed in Malaysia and Thailand are considered as financially distressed firms since the mean value is smaller than 1.8. For Malaysia, the result shows that free cash flow are reported in range of -0.4520 to 1.8480. But, free cash flow for public listed firms in Thailand is reported in range of -0.5910 to 0.4204. The negative value of free cash flow indicates that the firm are suffering deficit free cash flow while positive free cash flow indicates that the firm are having surplus free cash flow to fund positive net present value of project and improve the firm growth. As shown in Table 2 and Table 3 the mean value of free cash flow for Malaysia and Thailand is 0.0346 and 0.0299. However, the mean value for full sample is 0.0328. In this study, 24.5% is dominant by industrial product industry followed by consumer product at 18.2% from the full sample. On the other hand, 59.9% of sample is public listed firms from Malaysia while 40.1% is public listed firms in Thailand. Next, the Table 2 and Table 3 present the standard deviation for all continuous variables used in the study. Standard deviation is defined as square root of variance. Standard deviation is used to report how much the data is spread out in the same units of measurement as the original data (Field, 2009). In this study, the result shows that DISTRESS have the highest standard deviation as compared to the other variables for Malaysia, Thailand and full sample. Hence, this indicates that this variable has the largest dispersion among the other variables. Table 4. Summary results of Independent T – test

Country

DACC

LEV

DISTRESS

FCF

N

Mean

Std. Deviation

Malaysia

1005

0.05957

0.0681

Thailand

672

0.07255

0.08778

Malaysia

1005

0.18876

0.16379

Thailand

672

0.23193

0.24686

Malaysia

1005

0.79575

0.62336

Thailand

672

0.9993

0.67781

Malaysia

1005

0.03462

0.10365

Thailand

672

0.02997

0.09206

t-test for Equality of Means Sig.

Mean Difference

0.001

-0.01298

0.000

-0.04317

0.000

-0.20355

0.347

0.00465

The mean for earnings management, leverage, financial distress and free cash flow between Malaysia and Thailand has been tabulated in the Fig. 1.

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58


Fig. 1. Mean according to country

Table 4 shows that the number of samples firm (N) is 1005 firm-year observations for Malaysia and 672 firmyear observations for Thailand. Table 4 also summarized the result of independent t-test analysis between Malaysia and Thailand on DACC, LEV, DISTRESS and FCF. The independent t – test results indicated that the mean value for DACC for Malaysia is (Mean=0.05957, SD=0.06810) and Thailand is (Mean=0.07255, SD=0.08778). Thus, the mean difference for DACC is -0.01298 at p = 0.001 (p < 0.05). Therefore, the result indicates that there is statistically significant difference in mean for DACC between Malaysia and Thailand. Hypothesis H1 (a) is accepted. For LEV, the results showed that the mean value for Malaysia is (Mean= 0.18876, SD=0.16379) and Thailand is (Mean=0.23193, SD=0.24686). Mean difference for LEV is -0.04317 at p = 0.000 (p < 0.05). Therefore, the results indicate that there is a statistically significant difference in mean for LEV for Malaysia and Thailand. Hypothesis H 1 (b) is accepted. This study also reported significant difference in mean for financial distress (DISTRESS) for Malaysia and Thailand. The mean value of DISTRESS for Malaysia is (Mean=0.79575, SD=0.62336) and for Thailand, the result reported as (Mean=0.99930, SD=0.67781). The mean difference for DISTRESS is -0.20355 at p = 0.00 (p < 0.05). Therefore, the result indicates that there is a statistically significant difference in mean for DISTRESS between Malaysia and Thailand. Hypothesis H 1 (c) is accepted. However, there is no statistically difference in mean for free cash flow (FCF) between Malaysia and Thailand because the mean difference is 0.00465 at p = 0.347 (p>0.05). The result reported that mean value for Malaysia is (Mean=0.03462, SD=0.10365) and Thailand is (Mean=0.02997, SD=0.09206).Thus, H 1 (d) is rejected. 5. Conclusions This study investigates seven industries of public listed firms in Malaysia and Thailand from 2010 to 2012 as pool data to identify the mean significant different of earnings management, leverage, financial distress and free cash flow between Malaysia and Thailand. With regard to the objective of the study, independent t – test analysis found that there is statistically a significant different in mean for discretionary accruals as a proxy for earnings management, leverage and financial distress for both Malaysia and Thailand. However, there is no statistically significant different in mean for free cash flow between Malaysia and Thailand. Thus, H1 (a), (b), and (c) are accepted and H 1 (d) is rejected. From the result of independent t – test analysis, eta square value provide that the country has a large effect on financial distress and has a small effect on discretionary accruals, leverage and free cash flow. In other words, the variance of financial distress for full sample set is affected by the number of firms for two different countries which are Malaysia and Thailand. This is supported by the number of firms in Malaysia is higher than Thailand. As provided in the descriptive statistics analysis, 59.9% of the full sample of the study is dominant by firms from Malaysia. This is supported by the study of Simon (2001) which proposed that the culture of the country will contribute to a significant impact to the attitude of managers on earnings management. Earnings management overthrows the value of information in financial report that helps the communication among investors, shareholders and the public. The user of financial report should be convinced on the reliability and high quality information provided in order to make financial decision. Nonetheless, earnings management may harm


the value of information and lead the financial report users to inaccurate economic decision. This study provides the understanding on the difference in mean of earnings management, leverage, financial distress and free cash flow between Malaysia and Thailand. This study also provides the evidence that validates the difference in mean of earnings management, leverage and financial distress between two countries is significant because the culture of different countries may influence the way managers choose the accounting method and give judgmental opinion. Furthermore, standard setters and regulators should be aware on the earnings management practices, which have a greater impact on the reliability and credibility of the accounting information. They should enhance the control mechanism to govern the management action. In particular, the enforcement of legislation is important because it may discourage the manager of the firms to involve in any earnings management activities. Thus, by strengthening existing rules and regulation, it can mitigate the issues arisen in the earnings management particularly.

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