Impact of Firm Level Characteristics

Impact of Firm Level CharacteristicsAbstractOrganizational cognitive process has attracted scholarly attention in corporate finance publications oer the several decades. However, in the context of amends policy sector, it has received a elflike attention. Current excogitate examines the regard of soaked take characteristics ( size of it, leverage, tangibility, pretend, harvest-feast, liquidness and age) on surgery of listed liveliness-time indemnification companies of Pakistan all all everywhere vii classs from 2001 to 2007. The results of usual Least Squ ar (OLS) regression summary indicate that size, risk and leverage are important determining factors of motion of emotional state insurance companies of Pakistan while ROA has statistically in solid family relationship with growth, favorableness, age and liquidity.Keywords execution, firm take characteristics, feel insurance companies.IntroductionThe deed of any firm non only plays the billet to incr ease the market look upon of that specific firm that as well leads towards the growth of the whole industry which ultimately leads towards the overall prosperity of the economy. mensu dimensionn the exploit of insurers has gained the importance in the corporate finance literature because as intermediaries , these companies are not only providing the mechanism of risk transfer but also helps to channelizing the funds in an appropriate way to fight back the rail line activities in the economy . Insurance companies have importance both for championshipes and individuals as they indemnify the losses and put them in the same positions as they were onward the occurrence of the loss. In addition, insurers provide economic and social benefits in the ordination i.e. prevention of losses, reduction in anxiousness, fear and increasing employment. Therefore, the current line of reasoning world without insurance companies is unsustainable because risky businesses have not a qualifica tion to retain all types of risk in current extremely diffident environment.For the past six decades, Pakistani life insurance companies have shown the fulgurant progress which not only creates the employment opportunities but also enhances the business activities in the economy. Financial statistics reported the phenomenal growth of Pakistani life insurance companies as these companies comprise 52% and 69% share of whole (life plus non-life) insurance market in terms of simoleons premiums and assets (Insurance division declare, 2007). In addition, the premium of these life insurers increased by 36% in 2007 (Insurance Year Book, 2007) shows the remarkable progress of life insurance sector of Pakistan. Therefore, what determines the performance of the life insurance industry is an important discussion for the regulators and policy makers to support the sector in achieving the excellence so that desirable economic fruits could be reaped from the help of the life insurance sector of Pakistan.Literature ReviewThe Determinants of performance have been extensively studied in corporate finance literature from the last several decades. For illustrate by selecting the model of US banks, Berger (1995) investigated the impact of capital asset balance on return on equity. He concluded that capital asset ratio has a positive relationship with profitableness. Anghazo (1997) examined the impact of firm level characteristics on US bank net interest margin. The results documented that bank interest margin positively cogitate with leverage, opportunity cost, and default risk and management efficiency. Neeley and Wheelock (1997) explored the determinants of favourableness of commercial banks and recall that favorableness positively link with changes in per capita income.To investigate the performance of banks (Naceur Goaied, 2001)used the sample of Tunisian banks over the completion of 1980 to 1995. They advocated that the banks who tried to maintain their super ior deposits and better their capital and labor productivity are performed well. Guru et al. (2002) examined the determinants of performance of Malaysian banks over the 10 years period from 1986 to 1995. For this purpose, they selected both micro and macro level characteristics. The results revealed that inflation positively while efficient expense management and eminent interest rate controvertly related with profitability. The results of Goddard et al. (2004) showed that Profit is an important requisite for future growth of banks and the banks that maintain a high capital assets ratio tend to grow slowly.A study conducted by the (Sufian Parman, 2009)to investigate the determinants of profitability by selecting the non-commercial banks fiscal institutions. The findings indicated that credit risk and loan intensity forbidly related with profitability while banging size and financial institutions with high operational expenses tended to high profitability ratio. (Hakim Neaime, 2005) Observed that liquidity, current capital and enthronisation are the important determinants of banks profitability. (Aburime, 2006) Identified the firm level determinants of profitability of Nigerian banks over the five years period from 2000 to 2004. He concluded that credit portfolio, size, capital size and ownership concentration are important determinants of Nigerian banks. (Kosmidou, 2008) showed that money supply growth has in noteworthy impact on profitability while GDP and stock market capitalization to assets are significant and have negative relation with the ROA. (Asimakopoulos, Samitas, Papadogonas, 2009) illustrated that Firms profitability is positively affected by size, sales growth and investment. On the other hand, leverage and current assets negatively related with profitability.Severeral studies also have been conducted to dance step the performance of the insurance compnies. For instance Sloan, A and Conover, J.(1998) deduced that functional status of in surers do not affect the profitability of being insured but public coverage have significant impact on profitability of insurance companies. Chen and Wong ( 2004) examined that size, investment, liquidity are the important determinants of financial health of insurance companies. Chen et al.( 2009) examined the determinants of profitability and the results showed that profitability of insurance companies decreased with the increase in equity ratio. In addition, insurance companies must have to diversify their investment and use effective hedge techniques which help them to create better financial revenues.Research Methodology attempt and DataCurrently, there are five life insurance companies operating(a) in Pakistan and all these five companies are selected to measuring their performance over the period of seven years from 2001 to 2007. For this purpose, financial data has been collected from financial statements (Balance Sheets and Profit and Loss a/c) of insurance companies and In surance Year Book? which is published by Insurance Association of Pakistan.ModelPR = 0 + 1 (LG) + 2 (TA) + 3 (SZ) + 4 (LQ) + 5 (AG) + 6 (RK) + 7 (GR) + WherePR = Performance (Net income before interest and tax divided by total assets)LG = supplement (Total debts divided by total assets)TA = palpability (Fixed assets divided by total assets)SZ = Size (Log of premiums)LQ = Liquidity (Current assets divided by current liabilities)AG = Age (Difference b/w observation year and establishment year)RK = lay on the line ( touchstone deviation of ratio of total claims to total premiums)GR = process (Percentage change in premiums) = the error termDescriptive Statistics control board 4.1 presents descriptive analysis of the firm level characteristic associated with life insurance sector. This study considers performance as dependent variable whereas leverage, size, growth, tangibility, liquidity, age and risk as independent variables. The industry average is provided by correspond along wi th are the minima and maxima for respective year while standard deviation indicates the inter-industry variation of the variables time evaluate within the respective year. bow 4.1 indicates that the borderline value of industry fee-tail of leverage is 0.79 in 2004 and 2007 while the mean value is at its uttermost level in 2006 at 0.84.The uttermost variation in leverage is observed in 2007 valuing at 0.30 and minimum is found in 2003 at 0.19.The variable size constantly shows the increasing disposition from year 2001 to 2007. The mean value of size is at maximal level in 2007 i.e. 7.51 whereas minimum mean value for size is observed at 6.02 in 2001. In addition, the inter industry variation is minimum in 2001 at 2.12. Table 4.1 also shows that growth of Pakistani life insurance companies is not self-consistent in all seven years and mean value of growth is reached 34.84 in 2007 from 11.53 which is observed in 2001. The mean value of performance (dependent variable) is maxi mum in 2007 valuing at 0.07 and the minimum value is observed in 2001, 2002, 2003 and 2005 at 0.02. The standard deviation is also not very high i.e. near 0.02 as compare to other variables except in the year 2007 in which it touches it maximum of 0.07.Table 4.2 also provides descriptive results of tangibility, liquidity, age and risk for the period of seven years from 2001 to 2007 for the life insurance sector of Pakistan. The mean determine and standard deviations of tangibility is around 0.03 and 0.02 respectively in all seven years from 2001 to 2007.The mean values of liquidity are indicating an increasing trend from the minimum of 1.70 in 2001 to the maximum value at 6.36 in 2007. The standard deviation is also establishing an increasing trend from a minimum value of 0.76 in 2001 to a maximum value of8.63 in 2007.The mean value of risk is at its lowest level in 2003 at 0.58 with a minimum standard deviation of 0.45 while these values have reached their maximum level in 2007 i .e. 6.35 and 6.51 respectively.AnalysisTable 4.2 reports the results of regression analysis in which seven independent variables are regressed by using the data of life insurance sector of Pakistan from 2001 to 2007. The value of R square (0.816) indicates that performance of life insurance companies is nearly 82% dependent on independent variables i.e. size, leverage, growth, tangibility, age, risk and liquidity. Therefore, performance is mainly defined by these seven variables of life insurers in Pakistan over seven years.Table 4.2 indicates that leverage is negatively and significantly related with the performance of the life insurance companies. This predicts that the performance of highly levered Pakistani life insurance companies is not up to the mark. Table 4.2 also shows that coefficient of variable size is positive and statistically significant at 1% level. This predicts that performance of large size life insurance companies is better than small size companies. The negativ e coefficient of growth indicates a negative relationship between growth and performance. However, this negative relationship is found to be statistically insignificant with the p-value of 0.809. Therefore, growth is not considered as a proper explanatory variable of performance in life insurance sector.The beta values of explanatory variables tangibility and liquidity are 0.507 and 0.001 respectively with the positive coefficient sign. However, tangibility and liquidity are not statistically significant with the large p-values. Therefore, tangibility and liquidity are notModelUnstandardized CoefficientsStandardized CoefficientstSig.BStd. Error of import(Constant).010.051.204.841Leverage-.265.090-1.579-2.940.008*Size.038.0091.7224.120.001* process-4.69.000-.032-.245.809Tangibility.507.367.1831.382.183Liquidity.001.003.058.205.840Age-.003.003-.235-1.169.257Risk.004.002.3741.903.072**considered a powerful explanatory variable to define the performance of life insurance companies in Pa kistan over seven years. Negative coefficient of variable age specifies theTable 4.2 Regression Coefficients Their meaning levelR Square 0.816Adjusted R Square 0.749F statistics 12.062* solid at 1% level** meaning(a) at 10% level______________________________________negative relationship between performance and age of the Pakistani life insurance companies. However, the relationship between performance and age is statistically insignificant. Table 4.2 indicates that the coefficient of variable risk is positive and statistically significant at 10% level. According to the nature of insurance industry, ratio of total claims to total premiums (loss ratio) is used as a proxy to measure the risk of the life insurance companies in Pakistan. Positive sign shows a positive relationship between performance and risk of the insurance companies i.e. performance increases with the increase of loss ratio.ConclusionThe current study investigates the impact of firm level characteristics on perform ance of the life insurance sector of Pakistan over the period of seven years from 2001 to 2007. For this purpose, size, profitability, age, risk, growth and tangibility are selected as explanatory variables while ROA is taken as dependent variable. The results of OLS regression analysis reveal that leverage, size and risk are most important determinant of performance of life insurance sector whereas ROA has statistically insignificant relationship with profitability, growth, tangibility and liquidity. plug-in 4.1 Descriptive StatisticsYearsLeverageSizeGrowthPerformance thinkSD hour pocketMeanSDMinMaxMeanSDMinMaxMeanSDMinMax20010.800.210.450.996.022.123.068.9311.5311.903.2232.390.020.010.000.0320020.810.200.470.996.212.113.299.0722.2123.523.6860.990.020.010.000.0320030.820.190.510.996.502.083.579.2037.1832.628.3090.710.020.010.000.0320040.790.240.380.996.682.093.569.3122.2027.93-1.7861.160.030.020.000.0520050.830.210.470.996.952.033.969.5331.1810.3024.9748.980.020.020.000.0520060.840 .200.490.997.212.024.249.6831.7926.143.7472.780.030.020.000.0620070.790.300.261.007.512.064.5010.0334.829.2522.4445.660.070.070.000.17TABLE 4.1 (Continued) Descriptive StatisticsYearsTangibilityLiquidityAgeRiskMeanSDMinMaxMeanSDMinMaxMeanSDMinMaxMeanSDMinMax20010.030.020.000.061.700.761.072.6516.6020.406.0053.001.921.330.703.9420020.030.020.000.061.730.861.143.0117.6020.407.0054.000.830.470.401.3420030.030.020.000.052.181.111.223.7218.6020.408.0055.000.580.450.181.3420040.020.020.000.042.241.771.094.8519.6020.409.0056.003.343.080.007.2320050.020.020.000.043.022.261.155.9420.6020.4010.0057.004.702.151.236.3620060.020.010.000.033.982.721.367.3721.6020.4011.0058.003.603.860.519.7220070.020.020.000.056.368.631.3316.3322.6020.4012.0059.006.356.511.7816.00Table 4.2 Regression Coefficients Their Significance levelModelUnstandardized CoefficientsStandardized CoefficientstSig.BStd. ErrorBeta(Constant).010.051.204.841Leverage-.265.090-1.579-2.940.008*Size.038.0091.7224.120.001*Growth-4.69.00 0-.032-.245.809Tangibility.507.367.1831.382.183Liquidity.001.003.058.205.840Age-.003.003-.235-1.169.257Risk.004.002.3741.903.072**R Square 0.816Adjusted R Square 0.749F statistics 12.062* Significant at 1% level**Significant at 10% level