Determinants of Performance: A Case of Life Insurance Sector of Pakistan NAVEED AHMED Hailey College of Commerce, University of the Punjab, Lahore.

Determinants of Performance: A Case of Life Insurance Sector of Pakistan

NAVEED AHMEDHailey College of Commerce,

University of the Punjab, Lahore

INTRODUCTION

The performance of any firm not only plays the role to increase the market value of that specific firm but also leads toward the growth of the whole industry which ultimately leads towards the overall prosperity of the economy.

Measuring the performance 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 support the business activities in the economy.

•Insurance companies have importance both for businesses and individuals as they indemnify the losses and put them in the same positions as they were before the occurrence of the loss. In addition, insurers provide economic and social benefits in the society i.e. prevention of losses, reduction in fear and increasing employment.

Therefore, the current business world without insurance companies is unsustainable because risky businesses have not a capacity to retain all types of risk in current extremely uncertain environment.

Financial statistics reported the phenomenal growth of Pakistani life insurance companies as these companies comprise 52% and 69% share of entire (life plus non-life) insurance market in terms of net premiums and assets (Insurance Year Book, 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 REVIEW

•Wessels (1988)•Chiarella et al. (1991) •Kjellman and Hansen (1995)•Rajan (1995) •Wiwattanakantang (1999) •Chen and Jiang (2001) •Miguel and Pindado (2001) •Nivorozhkin (2002) •Frank and Goyal (2003)

•Cassar and Holmes (2003) •Low and Chen (2004) •Buferna et al. (2005) •Huang and Song (2006) •Daskalakis and Psillaki (2007) •Cheng and Weiss (2008) •Bhaird and Lucey (2008) •Li et al. (2009) •Chang et al. (2009)

RESEARCH METHODOLOGY

Sample and Data

Currently, there are five life insurance companies operating 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 “Insurance Year Book” which is published by Insurance Association of Pakistan.

The following statistical analysis have been used to deduce the results of present study:

Descriptive Analysis Correlation Analysis Regression Analysis

Regression Model

PR = β0 + β1 (LG) + β2 (TA) + β3 (SZ) + β4 (LQ) + β5 (AG) + β6 (RK) + β7 (GR) + ε

Where:• PR = Performance (Net income before interest and tax divided by total

assets)• LG = Leverage (Total debts divided by total assets)• SZ = Size (Log of premiums)• GR =Growth (Percentage change in premiums)• TA = Tangibility of assets (Fixed assets divided by total assets)• LQ = Liquidity (Current assets divided by current liabilities)• AG = Age (Difference b/w observation year and establishment year)• RK = Risk (standard deviation of ratio of total claims to total

premiums)• ε = the error term

EMPIRICAL FINDINGSDescriptive Statistics

Years Leverage Size

Mean SD Min Max Mean SD Min Max

20010.80 0.21 0.45 0.99 6.02 2.12 3.06 8.93

20020.81 0.20 0.47 0.99 6.21 2.11 3.29 9.07

20030.82 0.19 0.51 0.99 6.50 2.08 3.57 9.20

2004

0.79 0.24 0.38 0.99 6.68 2.09 3.56 9.312005

0.83 0.21 0.47 0.99 6.95 2.03 3.96 9.532006

0.84 0.20 0.49 0.99 7.21 2.02 4.24 9.682007

0.79 0.30 0.26 1.00 7.51 2.06 4.50 10.03

Years Growth Performance

Mean SD Min Max Mean SD Min Max

200111.53 11.90 3.22 32.39 0.02 0.01 0.00 0.03

200222.21 23.52 3.68 60.99 0.02 0.01 0.00 0.03

200337.18 32.62 8.30 90.71 0.02 0.01 0.00 0.03

2004

22.20 27.93 -1.78 61.16 0.03 0.02 0.00 0.052005

31.18 10.30 24.97 48.98 0.02 0.02 0.00 0.052006

31.79 26.14 3.74 72.78 0.03 0.02 0.00 0.062007

34.82 9.25 22.44 45.66 0.07 0.07 0.00 0.17

Years Tangibility Liquidity

Mean SD Min Max Mean SD Min Max

20010.03 0.02 0.00 0.06 1.70 0.76 1.07 2.65

20020.03 0.02 0.00 0.06 1.73 0.86 1.14 3.01

20030.03 0.02 0.00 0.05 2.18 1.11 1.22 3.72

2004

0.02 0.02 0.00 0.04 2.24 1.77 1.09 4.852005

0.02 0.02 0.00 0.04 3.02 2.26 1.15 5.942006

0.02 0.01 0.00 0.03 3.98 2.72 1.36 7.372007

0.02 0.02 0.00 0.05 6.36 8.63 1.33 16.33

Years Age Risk

Mean SD Min Max Mean SD Min Max

200116.60 20.40 6.00 53.00 1.92 1.33 0.70 3.94

200217.60 20.40 7.00 54.00 0.83 0.47 0.40 1.34

200318.60 20.40 8.00 55.00 0.58 0.45 0.18 1.34

2004

19.60 20.40 9.00 56.00 3.34 3.08 0.00 7.232005

20.60 20.40 10.00 57.00 4.70 2.15 1.23 6.362006

21.60 20.40 11.00 58.00 3.60 3.86 0.51 9.722007

22.60 20.40 12.00 59.00 6.35 6.51 1.78 16.00

CORRELATION ANALYSIS

Leverage Size Growth Tangibility Liquidity AgeLeverage Pearson

Correlation

Sig. (2-tailed)

Size Pearson Correlation .374**

Sig. (2-tailed) .000Growth Pearson

Correlation .077 .072

Sig. (2-tailed) .661 .680Tangibility Pearson

Correlation -.476** -.142** .051

Sig. (2-tailed) .000 .000 .771Liquidity Pearson

Correlation -.225** -.429* .052 .229

Sig. (2-tailed) .000 .025 .796 .250Age Pearson

Correlation .415* .401** -.153 -.356** .491**

Sig. (2-tailed) .013 .000 .379 .000 .009Risk Pearson

Correlation -.427* -.200 -.060 .084 .364** -.071

Sig. (2-tailed) .012 .256 .334 .538 .000 .771

REGRESSION ANALYSIS

Model

Unstandardized Coefficients

Standardized

Coefficie

nts

t Sig.B Std. Error Beta(Constant) .010 .051 .204 .841Leverage -.265 .090 -1.579 -2.940 .008*

Size .038 .009 1.722 4.120 .001*Growth -4.69 .000 -.032 -.245 .809

Tangibility .507 .367 .183 1.382 .183Liquidity .001 .003 .058 .205 .840

Age -.003 .003 -.235 -1.169 .257Risk -.004 .002 -.374 1.903 .072**

CONCLUSION

The results reveal that leverage, size and risk are most important determinant of performance of life insurance sector whereas ROA has statistically insignificant relationship with age, growth, tangibility and liquidity.

FUTURE RESEARCH

Thanks