Debt Equity Choice of Life and Non-Life Insurers: Evidence from Pakistan

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1 Debt Equity Choice of Life and Non-Life Insurers: Evidence from Pakistan Talat Afza* and. Naveed Ahmed** Abstract Capital structure has attracted scholarly attention in corporate finance literature over the past decades. However, in the context of financial sector especially in insurance sector, it has received a little attention. Current study provides the empirical evidence on firm level determinants of capital structure of insurance sector of Pakistan over nine years from 2001 to Present study split the data set according to the type of insurance companies such as; life, non-life and overall insurance sector and accordingly three Ordinary Least Square (OLS) regression models are applied to estimate the relationship between the dependant (Debt Ratio) and independent variables i.e. size, profitability, tangibility, liquidity and risk. The results revealed that both life and non-life insurance companies in Pakistan followed Pecking Order patterns in case of profitability and liquidity as both variables negatively and significantly related with leverage in life and non-life insurance companies of Pakistan. Moreover, positive and significant relationship between debt ratio and size in all of the three models, support the Static Trade-Off hypothesis. Furthermore, the results also indicate that profitable, more liquid, more tangible and risky insurance companies focus on retained earnings or equity than debt financing. Keywords: Capital structure, Firm level determinants, Insurance sector of Pakistan. 1. Introduction Over the past several decades, theories on a firm s capital structure choice have focused on many directions. Different models have been presented in the literature to explain a firm s financing behavior (Harris and Raviv, 1991). In 1952, Durand proposed the concept of capital structure and he is considered to be the one of the pioneers who analyzed it theoretically. According to his approach (Net income Approach), any firm can increase its value and decrease the cost of capital by using debt financing. Later on, Durand (1952) proposed another approach (Net Operating Income Approach) related to capital structure and provided evidence that market value of the firm is irrelevant of the debt-equity choice. These two approaches were purely definitional and no economic and behavioral meanings could be derived from outcome of his work. In order to fill these gaps, Nobel Prize winning finance theorist, Modigliani and Miller (1958), presented behavioral approach and the modern concept of capital structure in which they theoretically and algebraically analyzed the affect of capital structure on firm s value and concluded under certain assumptions that the firm s value does not depend upon the financing choices. Corresponding author: * Professor and Director Academics, COMSATS Institute of Information Technology, Lahore, Pakistan. ** PhD Student, COMSATS Institute of Information Technology, Lahore, Pakistan 1

2 MM provided path and guidelines for researchers to analyze the affects of capital structure and later several hypothesis have been put forward by researchers related to the debt-equity choices, but none of them exactly explains as to how much debt and equity should be used by any firm to get the desired results (Zhou, 2008). The rationale of target debt-equity depends on many micro and macro factors which are different across industries and regions. Therefore, keeping in view all micro and macro factors the firm formulates its capital structure prior to starting its operations and modifying it according to the requirements of business. For this purpose, firm requires the services of financial experts or managers and board of directors for making right decision about financing choices (debt and equity), because wrong decision may lead not only to increase cost of capital but also to insolvency or bankruptcy of the firms. Hence, when management plays its role in the selection of financing options, the core objective is to reduce the cost of debt and equity along with increasing the benefits or value of the firm (Baral, 1996). The measurement of Cost of debt and equity is also essential in determining the capital structure because it provides link for increasing the value of shareholders along with attaining the financial goals of the firm (Agymin, 1998) If a business raises its capital through large portion of equity then it is attractive for the operational activities for two major reasons; first, It plays significant role for corporate growth of every organization because it does not carry any fixed charges and maturity period. Second, it enhances the credit worthiness due to reduction in gearing. But, on the other hand, firms with poor prospects merely prefer to issue equity capital in order to bring new investors to share losses. In addition, when an announcement for issuing new stock is made, it gives negative signal to investors and as a result the market value of the stocks will decline. Moreover, when equity is issued for financing the operational activities, different costs are attached with it including the agency cost of equity. This cost arises in the firm due the conflict of interests between shareholder and managers related to firm s decision. Therefore, equity should be the last option for raising funds (Aoun, 2006). Consequently, the management finds right kind of solution or source of finance which minimizes the costs and increases the value of firm. One possible solution is to use debt capital for financing its assets which can be employed as a tool which not only reduces the cost of equity but also enhances the market value of the firm. When the firm shifts its capital structure towards more debt, then this forces managers to be more disciplined in the operational activities. For the last sixty years, different approaches have emerged regarding the use of debt. Debt acts as an engine for the growth of the firm and it encourages the managers to get maximum returns that enable them to pay interest. Furthermore, it minimizes free cash flows which make the manager to work less for their own interest and as a result reduces the wasteful expenditures of business. Debt financing also provides tax shelter which makes one to pay less taxes because the interest paid on debt is tax deductibles. Under certain assumptions MM also proposed that a firm can increase its market value of stocks if it is use 100% debt as a source of capital. But in the real world, the firm rarely uses 100% debt in order to reduce or minimize agency and bankruptcy related costs. When a large potion of debt is used by firms in the capital structure, different types of costs (agency and bankruptcy) are also attached with it. The bankruptcy cost exists, when the firm feels that it would not be able to pay interest on debt. As a result, the threat of bankruptcy also forces a firm to sell or liquidate its assets less than their actual market value. In addition, lenders may demand more interest rates, 2

3 suppliers may refuse to grant credit and employees may also jump towards alternative jobs due to this threat. Furthermore, the agency cost of debt arises; when there is some controversy between the shareholders and debt holder in the firm. Thus, when the management is improperly (against target ratio) used debt or equity in the formation of capital structure, it would be harmful for the existence of the firm. Therefore, researchers have proposed the idea of optimal capital structure. According to Myers (1984) the firm should have optimal capital structure and this can be achieved through keeping a balance between the benefits and costs of equity and debt. It is the mix of debt and equity in target proportion which not only maximizes the firm s value but also reduces the costs of financing choices. Corporate finance literature reveals that some researchers describe capital structure in narrow sense so as to include only long term financial instruments in its composition (Passilaki, 2008). According to Devic and krstic (2001) Capital structure is expressed as ratio of long term liabilities to the sum of long term liabilities and firms equity. Capital structure is described as long term debt divided by total assets (Pandy, 2001; Omet, 2006; Delcour, 2007). But in the words of Nemmers and Grunewald (2000) capital structure refers to all financial resources marshaled by the firm, it includes short as well as long-term, and all forms of debt as well as equity. It includes all liabilities (Mashharawe,2003; Gaud,2005; Joeveer,2006; Mitton,2007). Nikolaos (2007) refers that capital structure of firm is actually the relationship between the total debt and assets of the firm. Insurance Sector of Pakistan This paper attempts to investigate the determinants of capital structure of insurance companies of Pakistan. In 1947, after the creation of Pakistan, the first step taken by government to promote the insurance activities in Pakistan was the establishment of Insurance Association of Pakistan (IAP) on 9 February The core objective of Insurance Association of Pakistan is to protect the interests of its member insurance companies and to support their businesses. Another step to further strengthen the insurance industry was taken in 1953 by establishing Pakistan Insurance Corporation (now Pakistan Reinsurance Company Ltd) to boost the re-insurance activities. In 1955, when foreign insurers appeared as competitors, National Co-Insurance Scheme (NCIS) was introduced to enhance the capacity of small insurance companies of local market. When East Pakistan broke its links with west Pakistan in 1971, Insurance industry as well as the whole economy faced financial crises and as a result Pakistan lost Rs.180 million in terms of premium revenue of non-life insurance sector. In 1972 all life insurance companies were taken over by the government through the policy of nationalization but this process did not track out the growth of insurance sector of Pakistan. For instance, insurance companies received premiums of Rs.290 million in 1973, Rs.335 million in 1976, Rs.820 million in 1980, Rs billion, Rs billion in 2005 and Rs billion in 2006 (Insurance Year Book, 2007). The year 2000 brought many changes in the insurance sector of Pakistan since Insurance Act 1938 was replaced by Insurance Ordinance This ordinance enhanced the financial health of 3

4 insurance companies by increasing the paid up capital requirements of both non-life and life insurance companies. Therefore, the minimum requirement of paid-up capital of general insurance companies was enhanced to Rs.80 million from Rs.50 million whereas capital requirement of life insurers was increased from Rs.100 million to Rs.150 million. Furthermore, In 2002, Security and Exchange Commission of Pakistan and Ministry of Commerce notified and implemented the Insurance Rules 2002 in insurance sector of Pakistan to support the financial growth of insurance industry of Pakistan. As a result of these financial reforms total assets and net premiums of life insurance companies have reached Rs billion and Rs billion respectively in 2006 while assets and net premiums of non-life insurers have reached Rs billion and Rs respectively in 2006 (Insurance Year Book, 2007). In addition, the share of Pakistani insurance sector in the world also has reached 0.02% in 2009 while insurance density has touched the level of 6.9% in 2009 (World Insurance Report, 2010). Moreover, total market capitalization of insurance sector of Pakistan has reached Rs.224 billion in Therefore, statistical figures show that financial regulations have really contributed in the development of the insurance industry in Pakistan. Objective and Significance of the Study The Current study Identifies the firm level characteristics which have significant impact on capital structure of insurance companies of Pakistan. Specifies the firm level factors that can affect the financing decisions of life insurance and non-life insurance companies. Also helps to indicate the factors which have less significant or no impact on leverage of insurance sector of Pakistan. Assists the regulators and management of insurance companies that how much debt and equity should be used to formulate their capital structure for getting the desired results. 2. Determinants of Capital Structure In this section, we provide a review of the factors which are considered as important determinants of capital structure of insurance companies of Pakistan. 2.1 Size (SZ) Size is considered a key factor that can influence the financial structure of the firm. It has been extensively used by the corporate finance researchers as control variable in the empirical analysis of determining the capital structure of the firm and found that proportion of debt and equity formulates according to the size of the firm (Scott and Martin, 1976; Booth et al., 2001). Various studies report a positive relationship between size and leverage (Hamaifer et al,1994;al- Sakran,2001;Antoniou et al,2002;gaud, 2005) while several studies intended negative relationship between debt ratio and firms size (Rajan and Zingales, 1995; Bevan and Danbolt,2002). According to the Rajan and Zingales (1995), the relationship between size and 4

5 leverage could be negative because larger firms have less asymmetric information that reduces the chances of undervaluation of issuing new stock and thus they prefer to issue more equity than debt. On the other hand, Static Trade-off hypothesis explores a positive relationship between size and firm because larger firms are normally diversified and considered less risky, hence, prefer to utilize more debt. In addition, larger firms prefer to issue more debt because it reduces direct bankruptcy costs due to market confidence (Warner, 1977). Moreover, smaller firms prefer to acquire lower debt because, these firms might face the risk of liquidation at the time of financial distress. (Ozkan, 1996). Consistent with the results of Static Trade-Off theory, current study expects a positive relationship between size and debt ratio. The natural log of sales or the natural log of assets is generally used as a proxy to determine the size of the firm. Current study uses natural log of sale (premiums) to measure the size of insurance industry of Pakistan. Therefore, first hypothesis is that there is a positive relationship between leverage and size of the firm. 2.2 Profitability (PF) Theoretical literature has no consistent relationship between debt ratio and profitability. Jensen (1986) argued that profitable firms use debt as a tool which enforces managers to invest in more disciplined way and as a result reduces free cash flows, which implies a positive relationship between leverage and profitability. Static Trade-off model also predicts a positive relationship between profitability and debt ratio due to the tax shield benefits. But according to the Pecking Order Theory (Myers and Majluf, 1984), firms prefer to use internal source of financing (retained earnings), then debt and finally issue external equity if more funds are required. Therefore, the more profitable the firms are the more retained earnings they will have, which exhibit a lower debt may utilized in the capital structure. This shows a negative relationship between profitability and leverage of the firm. In addition, profitable firms avoid to get loan in inefficient markets due to disciplinary role of debt ( Agency Theory).Various studies (Gonedes et al, 1988; Friend and Hasbrouck,1989; Shah and Khan, 2007) also reported a negative relationship between profitability and debt ratio. Present study also expects a negative relationship between profitability and leverage. Thus, second hypothesis is that there is a negative relationship between leverage and profitability of the firm. 2.3 Tangibility of assets (TG) Tangible assets are considered to have an impact on borrowing decisions because they have greater value in case of bankruptcy.a firm with large portion of fixed assets can easily raise debt 5

6 at relatively lower rates by providing the collateral of these assets to the creditors. Having the incentive of getting the loan at nominal rates, these types of firms are expected to borrow more as compared to those firms where cost of borrowing is higher due to less proportion of fixed assets (Suto, 1990). Hence, firms with large proportion of fixed assets prefer to employ more debt for getting the advantage of this opportunity. On the contrary, negative relationship have been reported between leverage and fixed assets in small and medium firms (Daskalakis and Psillaki,2007) and in less developed economies ( Joever,2006 ). Therefore, according to the nature of insurance industry, current study is expected to have negative relationship between leverage and tangibility of assets and use ratio of net fixed assets to total assets for measuring the tangibility of assets of insurance industry. The amount of net fixed assets indicates the cost of fixed assets less depreciation. Therefore, fourth hypothesis is that there is a negative relationship between leverage and tangibility of assets of the firm. 2.4 Liquidity (LQ) Liquidity ratio not only specifies the ability of the firm to cover its short term liabilities but also shows the liquidity position of the firm. Liquidity ratio has a mixed impact on the leverage decision. Firms with higher liquidity ratio prefer to acquire more debt because of their ability to meet short term obligations (Ozkan, 2001). This shows a positive relationship between the debt ratio and firms liquidity position. On the other hand, when firms have high liquidity ratios or have more liquid assets then then may prefer to use these assets to finance their investments and discourage to raise external funds (Pecking Order Theory). Therefore, the firm s liquidity position shows a negative relationship with capital structure of the firm. Current study is expects to have a negative relationship between liquidly and leverage because insurance companies in Pakistan seem to utilize only premium funds for paying claims. Current ratio (which is calculated as current assets over current liabilities) is used as a proxy to measure the liquidity. It is given by, Therefore, fifth hypothesis is that there is a negative relationship between leverage and liquidity of the firm. 2.5 Risk (RK) Risk is another key explanatory variable that may affect the capital structure of the firm. It is considered to be either the inherent business risk or it may arise in the firm as a result of inefficient management practices. Firms with high volatility in earnings might face higher risk that forces the management to reduce the debt level because higher risk increases the chances of bankruptcy (Pandy, 2001). This predicts a negative relationship between leverage and risk and this result is also consistent with trade-off and pecking order hypothesis. Consistent with the results of Pecking Order Theory and Static Trade-off Theory, present study is expected to have a negative relationship between risk and leverage. Several proxies have used in empirical studies to measure the risk of the firm such as standard deviation of the difference in operating cash flows to total assets, standard deviation of returns on net income, and standard deviation of percentage change in net income (Xiaoyan, 2008). According to the nature of business of 6

7 insurance companies, current study use standard deviation of ratio of total insurance claims to total premiums as a proxy to measure the risk. Therefore, seventh hypothesis is that there is negative relationship between leverage and risk of the firm. 3. Methodology Regression Model Leverage = β0 + β1 (Size) + β2 (Profitability) + β3 (Tangibility) + β4 (Liquidity) + β5 (Risk) + ε Where Size = Natural Log of Premiums Profitability = Net Income before Interest and Tax divided by Total Assets Tangibility = Fixed Assets Divided by Total Assets Liquidity = Current Assets Divided by Current Liabilities Risk = Standard Deviation of Total Claims Divided by Total Premiums 3.1 Sample and Sources of Data The study uses various sources have been used for data collection. The book value based yearly financial data from 2001 to 2009 has been collected from the financial statements (Balance Sheet & Profit and Loss A/c) of insurance companies and various Insurance Year Books published by Insurance Association of Pakistan. Currently only 5 companies are providing the services of life insurance in Pakistan, including; two domestic owned, two foreign and one government owned. The life insurance companies comprising 59% of entire insurance sector in terms of total assets in 2009 whereas total premium revenue of life insurance companies has also reached Rs billion in 2009(IAP, 2007). Non-life insurance industry in Pakistan comprises 45 private companies, out of which only 32 are currently operating while the remaining 13 non-life insurance companies have closed their operations due to the limit of paid-up capital requirements. 4. Empirical Results 4.1 Descriptive Statistics Table 4.1 reports the descriptive statistics of leverage, size, profitability, tangibility, liquidity and risk of Life insurance sector of Pakistan from 2001 to On average all life insurers are highly leveraged over nine years with ratios of not less than In 2006 leverage reaches at maximum level i.e which shows the aggressive behavior of life insurers about utilization of large portion of debt. On the other hand, variation in selection of debt capital also seems to be at 7

8 maximum level in 2007 i.e Size is explanatory variable which is proxied by log of total premiums. Statistics shows that on average size of life insurance companies are continuously increasing from 2001 to 2009 which predicts that in Pakistan, people prefer to transfer their risk by getting insurance policy. Terrorism aftermaths might be one of the key reasons of increasing the life insurance policy premium revenues. Statistics also predict that with the enhancement of size debt ratio of life insurers is also increases throughout nine years. On the other hand, variation in size approximately same in all seven years i.e. around Profitability of life insurers is reported in third column of Table 4.1. Life insurers exhibit uniformity with respect to the profitability from 2001 to 2006.i.e.approximately But in 2007, average ratio jump into 0.07 which shows a healthy change in the profitability of life insurance sector. In the same manner variation in profitability is considerably lesser and shows a consistency from 2001 to 2006 except The average values of tangibility in Table 4.1 also shows minor or small portion of tangibility of assets of life insurers and depicts consistency in mean values from 2001 to 2009 approximately The standard deviation of ratio of fixed assets to total assets is slightly lesser i.e. around 0.02 and is not varied over nine years. Table 4.1 also indicated all life insurance companies, on average, continuously improving their liquidity position through out nine years. This trend shows that life insurers keep large portion of funds in liquid form for settlement of claims. The highest mean value of liquidity is observed in 2007 which is But in the same year the value of standard deviation is at maximum level i.e among all the years which also predicts inconsistency in liquidity position. Table 4.1 also describes that insurers seem to be risky from 2004 to 2009 with respect to the settlement of claims. In 2003, the mean value of risk seems at minimum level with the ratio of 0.58 which reached at 7.23 in This continuously increasing trend over nine years predicts that life insurance companies become more risky.table 4.2 provides descriptive statistics of variables leverage, size, profitability, tangibility, liquidity and risk for the same study period of 2001 to 2009 for non life insurance industry. The average value of leverage is approximately 0.50 over nine years which is quite lower than the mean values of life insurance industry. The highest mean value of leverage is 0.54 in 2003 and lowest mean value is 0.45 in 2007.The inter industry variation in selection of leverage is minimum in 2005 at 0.17 and maximum in at The variation of non-life insurers is around 0.20 over nine years which is almost the same as the life insurance industry. Although the size of non life insurance industries is slightly lower than life insurance industry but variable size is having the same growing trend throughout the study period. The maximum mean value of size for non life insurers is 5.24 in 2007 which is almost 26% above than the size in The variation in size of non-life insurers is slightly lower than the life insurance companies over seven years i.e An increasing trend can be seen in the mean values of profitability from the minimum of 0.05 in 2001 to a maximum of 0.22 in These values show continuously improvement in profitability of non-life insurance companies. Table 2 also indicates that the average values of profitability of non life insurance sector are much higher than life insurance sector along with inter industry variability which is at its minimum level in 2004 at 0.06 and maximum in 2007 at

9 Consistent with the descriptive statistics of life insurers, table 4.2 shows that non-life insurance companies also have less portions of fixed assets i.e. around 0.12 during nine years. On the other hand, inter industry variability is on average 0.20 from 2001 to 2009 which is also consistent with the standard deviations of life insurance industry. The maximum average value of liquidity of non-life insurers is 6.10 found in year 2007 while on average, other eight years show relatively lower level of liquidity i.e. around In addition, average liquidity values of both life and non-life insurers are approximately the same in all the years. Table 4.2 also depicts that non-life insurance companies face higher risk (8.21) in 2004 as compare to other eight years. Descriptive statistics also predicts that on average risk of non-life insurers is relatively higher than the life insurers. Table 4.3 provides the descriptive statistics of leverage, size, risk, tangibility, liquidity and profitability of entire insurance sector (life plus non-life) of Pakistan. The average value of leverage is approximately 0.55 over nine years of all insurance companies in Pakistan. In 2005 leverage reaches at maximum level i.e which shows the aggressive behavior of insurers about utilization of large portion of debt. On the other hand variation in selection of debt capital also seems to be at minimum level in 2005 i.e as compare to other years. The mean value of size is at maximum level in 2009 i.e which shows around 73 % increase in premium revenues from On the other hand, variation in size approximately same in all nine years i.e. around An increasing trend can be seen in mean values of profitability from the minimum value 0.04 in 2001 to a maximum value 0.23 in In the same manner variation in profitability is having increasing trend from 2001 to As insurance companies face uncertainty for settlements of claims, therefore companies prefer to keep large portion of current assets than fixed assets. The average values of Table 4.3 also shows minor portion of fixed assets of insurers and depicts consistency in mean values from 2001 to 2009 approximately The standard deviation of tangibility is around 0.19 over nine years. Table 4.3 also shows insurance companies, on average, continuously improving their liquidity position through out nine years. This trend shows that life and non-life insurers keep large portion of funds in liquid form for settlement of claims. The highest mean value of liquidity is observed in 2007 which is But in the same year the value of standard deviation is at maximum level i.e among all the years which also predicts inconsistency in liquidity position. Statistics of Table 4.3 describes that in 2003, the mean value of risk seems at minimum level with the ratio of 4.24 which reaches at 7.06 in On the other hand, in 2004, the value of standard deviation is which is the highest value over nine years. 4.3 Regression Analysis Finally the impact of five explanatory variables size, profitability, liquidity, risk and tangibility on capital structure of insurance companies of Pakistan has been examined by using three ordinary least square regression models. These three regression models employ different data sets according to the type of insurers. Model A uses the financial data of life insurance sector while Model B and Model C are regress the data of five explanatory variables on capital 9

10 structure of non-life insurance companies and entire insurance sector respectively over nine years from 2001 to Table 4.4 of Model A reports the value of adjusted R square (0.768) indicates that debt ratio is nearly 77% dependant on variables i.e. size, profitability, tangibility, risk and liquidity. Therefore, leverage is mainly defined by these five variables of life insurers in Pakistan over nine years. Table 4.4 of Model A shows that coefficient of variable size is positive and statistically significant at 1% level. This predicts that large size life insurance companies in Pakistan prefer to utilize more debt in their capital structure. These results also confirm the notion that large firms employ more debt because these are less risky and diversified in nature (Static trade- off Theory). In addition, larger firms are prefer to issue more debt because it reduces direct bankruptcy costs due to market confidence (Warner, 1977). Moreover, smaller firms prefer to acquire lower debt because, these firms might face the risk of liquidation at the time of financial distress (Ozkan, 1996). The coefficient of profitability is found to be negative and statistically significant at 5% level. This negative sign indicates the negative relationship between leverage and profitability and predicts that, in Pakistan, profitable life insurance companies prefer to utilize small portion of debt. This result confirms the notion that Pakistani life insurance companies follow the Pecking Order pattern i.e. prefer to employ internal financing than debt. In addition, negative relationship also confirms the implication of Agency Theory which predicts that profitable firms avoid to get loan from inefficient markets due to the disciplinary role of debt. Table 4.4 depicts that the beta value of explanatory variable tangibility of assets is with the positive coefficient sign. However, tangibility is not statistically significant with the large p-value. Although positive relationship shows that a firm with the large portion of fixed assets can easily raise debt or obtains more debt at relatively lower rates by providing collaterals of these assets to creditor but due to the insignificant relationship of tangibility and leverage is not considered a powerful explanatory variable to define the debt ratio of life insurance companies in Pakistan over nine years. Results of regression model A indicate that the control variable liquidity with the negative coefficient is statistically significant at 5% level. Therefore, Pakistani life insurance companies with high liquidity ratios or more liquid assets are preferred to utilize these assets to finance their investments and discourage to raise external funds. Table 4.4 also shows that the coefficient of variable risk is positive and statistically significant at 5% level. This indicates that in order to fulfill the claims of the life insurance policyholder at the time of death or expiry of the policy, companies acquire external funds. Table 4.5 of Model B depicts the results of regression analysis of Pakistani non-life insurance companies from 2001 to The value of adjusted R square (0.713) indicates that debt ratio is nearly 72% dependant on explanatory variables i.e. size, profitability, tangibility, risk and liquidity. Consistent with the results of Model A, Table 4.5 of Model B shows that coefficient of variable size is positive and statistically significant at 1% level. This predicts that large size non-life insurance companies in Pakistan prefer to employ more debt in their capital structure. These results consistent with the hypothesis that large firms employ more debt because these firms are less risky and diversified in nature (Static Trade-off Theory). 10

11 The coefficient of profitability is found to be negative and statistically significant at 1% level. This negative sign indicates the negative relationship between leverage and profitability and predicts that, in Pakistan, profitable non-life insurance companies prefer to utilize small portion of debt. This result confirms the notion that Pakistani non-life insurance companies follow Pecking Order pattern i.e. preferred to employ internal financing than debt. The results of regression model B indicate that the coefficient of variable liquidity with the negative coefficient is statistically significant at 1% level. This negative sign shows the inverse relationship between the liquidity and capital structure of non-life insurance sector. Therefore, results predict that Pakistani non-life insurance companies with high liquidity ratios or more liquid assets prefer to utilize internal source of financing than debt. Negative coefficient of variable tangibility specifies the negative relationship between tangibility of assets and debt ratio of non-life insurance sector of Pakistan. This inverse relationship indicates that in Pakistan non-life insurance companies with large portion of fixed assets are preferred to utilize small portion of debt in their capital structure. Negative relationship has also been reported between leverage and tangibility in small and medium firms (Daskalakis and Psillaki,2007) and in less developed economies ( Joever,2006 ). The variable risk is negative and statistically significant at 5% level. Negative sign indicates that at the time of the destruction or loss of the subject matter, non-life insurance companies prefer to employ their internal source of financing for settlement of claims than external financing. This negative relationship between leverage and risk is also consistent with the results of trade-off and pecking order hypothesis. Table 4.6 of Model C reports the results of regression analysis of entire insurance sector (life plus non-life) of Pakistan from 2001 to The value of adjusted R square (0.823) indicates that capital structure of Pakistani insurance sector is nearly 82% dependant on control variables (size, profitability, tangibility, risk and liquidity). Therefore, leverage is mainly defined by these five control variables of insurance sector of Pakistan over nine years. Table 4.6 of Model C shows that coefficient of variable size is positive and statistically significant at 1% level. This predicts that large size insurance companies (life plus non-life) in Pakistan prefer to utilize more debt in formation of capital structure. The coefficient sign of explanatory variable profitability is found to be negative and statistically significant at 5% level. This negative sign shows the negative relationship between leverage and profitability and predicts that, in Pakistan, profitable insurance companies (both life and non-life) discourage to employ debt capital over seven years. This result confirms the notion that Pakistani insurance companies follow the Pecking Order pattern i.e. preferred to employ internal source of financing than debt. The negative relationship between the tangibility and debt ratio shows that Pakistani insurance companies (both life and non-life) with large portion of fixed assets discourage to employ debt capital. Al-Bahsh and Sentis (2008) also found the negative relationship between tangibility and leverage by taking the sample of less developed economies. Various studies like Joeveer (2006) and Daskalakis and Psillaki (2007) also predict the same negative relationship between debt ratio and tangibility. The negative and statistically significant relationship between liquidity and leverage ) indicates that Pakistani insurance companies (both life and non-life with high liquidity ratios or more liquid assets prefer to utilize these assets to finance their investments and discourage to raise external funds over nine years. Ozkan (2001) and Mashharawe (2003) also show the inverse relationship between liquidity and debt ratio. In 11

12 addition, the relationship between risk and debt ratio illustrates statistically insignificant results of insurance sector of Pakistan. Conclusion This study investigates the determinants of capital structure of insurance companies of Pakistan over the period of nine years from 2001 to Empirical results indicate that size, profitability, liquidity tangibility and risk are important determinants of capital structure of insurance companies of Pakistan. In addition, Pakistani insurers follow Pecking Order pattern in terms of profitability, risk, tangibility and liquidity as leverage has a negative relationship with profitability, risk, tangibility and liquidity while positive relationship between leverage and size shows consistency with the Trade-off theory. Moreover, the results also indicate that the management of profitable, more liquid, more tangible and risky non-life insurance companies emphasize on retained earnings or equity rather than debt financing. Limitations and Future Implications This study considers only one financial sector i.e. insurance sector of Pakistan. Other financial institutions of Pakistan like banks, mutual funds, modaraba companies etc. could be selected for future research. In addition, present study selected only five explanatory variables (size, profitability, risk, tangibility and liquidity), therefore, academicians may choose other determinants of capital structure for future research. References Afza, T. and Ahmed, N. (2010), Determinants of Capital Structure: A Case of Non-Life Insurance Sector of Pakistan, Interdisciplinary Journal of Contemporary Research in Business, Vol. 02, No.08.pp Al-Bashs, R. and P. Sentic, (2008) Determinants of Capital Structure in Gulf region States and Egypt. Working paper, University of Montpellier. Baral (1996), Capital Structure and Cost of Capital in Public Sector Enterprisesin Nepal. Ph.D thesis. Delhi University. Delcoure N. (2007), The determinants of capital structure in transitional economies International Review of Economics and Finance, 16, Devic, B. and Krstic, B. (2001), Comparatible Analysis of the Capital Structure in Polish and Hungarian Enterprises- empirical Study, journal of economics and Organization Vol. 1, Girard E., M. Omran (2007), What are the Risks When Investing in Thin Emerging Equity Markets: Evidence from the Arab World. Int. Fin. Markets, Inst. and Money Vol. 17: Glen J., Atkin M. (1992), Comparing Corporate Capital Structures Around the Globe. The International Executive, ( ); Sep/Oct; 34, 5; ABI/INFORM Global,P:

13 Grinblatt M., Titman S. (1998), Financial Markets and Corporate Strategy, International edition (Boston: McGrawHill). Harris, M and A Raviv (1991), Capital Structure and the Informational Role of Debt, Journal of Finance, 45, Insurance Year Book (2004), Insurance Association of Pakistan. Insurance Year Book (2005), Insurance Association of Pakistan. Insurance Year Book (2007), Insurance Association of Pakistan. Jensen M. C., Meckling W.H., (1976), Theory of the Firm: Managerial Behavior, Agency Costs, and Ownership Structure, Journal of Financial Economics V. 3, No. 4, Jensen, M.C., (1986), Agency Costs of Free Cash Flow, Corporate Finance and Takeovers, American Economic Review, Vol. 76, Mitton T. (2007), Why Have Debt Ratios Increased for Firms in Emerging Markets?, European Financial Management, Vol. 14, n 1, Modigliani, F, and Miller, M.H. (1958), "The Cost of Capital, Corporation Finance and the Theory of Investment,, The American Economic Review 48 (3), Modigliani, F. and Miller, M.H. (1963), "Corporate Income Taxes and the Cost of Capital; A Correction, The American Economic Review 53 (3), Mitton, U.R. and Zhang, Z. (2008), Capital Structure of Multinational Corporations: Canadian versus U.S. Evidence, Journal of Corporate Finance 14, Morocco. Miller H. M. (1977), Debt and Taxes, Journal of Finance, Vol. 32, n 2, Myers, S.C. (1977), "Determinants of Corporate Borrowing, Journal of Financial Economics 5, Myers S. C. (1984), The Capital Structure Puzzle, Journal of Finance, Vol. 34, Myers, S., and N. Majluf (1984), Corporate Financing and Investment Decisions When Information Investors Do not Have, Journal of Financial Economics 13, Firms Have Nivorozhkin, E. (2005) Capital Structure in Emerging Stock Market: The Case of Hungry, The Developing Economies, XL-2, Ozkan, A., (2001), Determinants of Capital Structure and Adjustment to Long Run Target: Evidence from UK Company Panel Data, Journal of Business Finance & Accounting, 28(1) & (2). Pandey I. (2001), Capital Structure and the Firm Characteristics: Evidence From an Emerging Market Indian Institute of Management Ahmedabad. Working Paper No. (2001) Psillaki, M. and Daskalakis, D. (2008), Are the Determinants of Capital Structure Country or Firm Specific? Evidence from SMEs, Working Paper, University of Nice-Sophia Antipolis. 13

14 Rafiq, M., Iqbal, A., Atiq, M. (2008), The Determinants of Capital Structure of the Chemical Industry in Pakistan, The Lahore Journal of Economics, 13: 1, Rajan, R. and Zingales, L (1995), "What Do We Know about Capital Structure? Some Evidence from International Data, Journal of Finance, 50: Ross, S.A. (1977), The Determination of Financial Structure: The Incentive Signaling Approach, Bell Journal of Economics, 8(1): Shah, Atta, and Hijazi S. (2004), "The Determinants of Capital Structure in Pakistani Listed Non- Financial Firms, The Pakistan Development Review, 43. Shah, A. and Khan, S. (2007), Determinants of Capital Structure: Evidence from Pakistani Panel Data, International Review of Business Research Papers Vol. 3 No.4, Smith, C. W., and Warner, J. B. (1979), On Financial Contracting: An Analysis of Bond Covenants, Journal of Financial Economics, Vol. 7, (1979) State Bank of Pakistan (2001), Balance Sheet Analysis of Joint Stock Companies Listed on the Karachi Stock Exchange, Karachi, Pakistan. State Bank of Pakistan (2007), Balance Sheet Analysis of Joint Stock Companies Listed on the Karachi Stock Exchange, Karachi, Pakistan. Tariq, B. Yasir, and Hijazi S. (2006), Determinants of Capital Structure: A Case for Pakistani Cement Industry, The Lahore Journal of Economics, 11(1): Wald, J.K. (1999), How Firms Characteristics Affect Capital Structure: An International Comparison, Journal of Financial Research, 22: Wiwattanakantang, Y. (1999), An Empirical Study on the Determinants of the Capital Structure of Thai Firms, Pacific-Basin Finance Journal 7, Yu, H. (2000), Banks Capital Structure and Liquid Asset- Policy Implication of Taiwan, Journal of Pacific Economic Review, 5:1,

15 TABLE 4.1: Descriptive Statistics for Study Variables (Life Insurance) Years Leverage Size Profitability Mean SD Min Max Mean SD Min Max Mean SD Min Max

16 TABLE 4.1 (Continued): Descriptive Statistics for Study Variables (Life Insurance) Years Tangibility Liquidity Risk Mean SD Min Max Mean SD Min Max Mean SD Min Max

17 TABLE 4.2: Descriptive Statistics for Study Variables (Non-Life Insurance) Years Leverage Size Profitability Mean SD Min Max Mean SD Min Max Mean SD Min Max

18 TABLE 4.2 (Continued): Descriptive Statistics for Study Variables (Non-Life Insurance) Years Tangibility Liquidity Risk Mean SD Min Max Mean SD Min Max Mean SD Min Max

19 TABLE 4.3: Descriptive Statistics for Study Variables (Entire Insurance Sector) Years Leverage Size Profitability Mean SD Min Max Mean SD Min Max Mean SD Min Max

20 TABLE 4.3 (Continued): Descriptive Statistics for Study Variables (Entire Insurance Sector) Years Tangibility Liquidity Risk Mean SD Min Max Mean SD Min Max Mean SD Min Max

21 Table: 4.4 Regression Coefficients & Significance level of Model A (Life Insurance) Variables Unstandardized Standardized t-value Sig. Coefficients Coefficients B Std. Error Beta (Constant) Size * Profitability ** Tangibility Liquidity ** Risk ** R Square Adjusted R Square F statistics *Significant at 1% level ** Significant at 5% level 21

22 Table: 4.5 Regression Coefficients & Significance level of Model B (Non-Life Insurance) Variables Unstandardized Standardized t Sig. Coefficients Coefficients B Std. Error Beta (Constant) Size * Profitability * Tangibility ** Liquidity * Risk ** R Square Adjusted R Square F statistics * Significant at 1% level ** Significant at 5% level 22

23 Table: 4.5 Regression Coefficients & Significance level of Model B (Entire Insurance Sector) Model Unstandardized Standardized t Sig. Coefficients Coefficients B Std. Error Beta (Constant) Size * Profitability ** Tangibility *** Liquidity *** Risk R Square Adjusted R Square F statistics *Significant at 1% level ** Significant at 5% level *** Significant at 10% level 23

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