EFFICIENCY ANALYSIS OF INSURANCE COMPANIES IN PAKISTAN

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Determinants of
Performance: A Case of Life
Insurance Sector of Pakistan
NAVEED AHMED
Hailey 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 FINDINGS
Descriptive Statistics
Years
2001
2002
2003
Leverage
Size
Mean
SD
Min
Max
Mean
SD
Min
Max
0.80
0.21
0.45
0.99
6.02
2.12
3.06
8.93
0.81
0.20
0.47
0.99
6.21
2.11
3.29
9.07
0.82
0.19
0.51
0.99
6.50
2.08
3.57
9.20
0.79
0.24
0.38
0.99
6.68
2.09
3.56
9.31
0.83
0.21
0.47
0.99
6.95
2.03
3.96
9.53
0.84
0.20
0.49
0.99
7.21
2.02
4.24
9.68
0.79
0.30
0.26
1.00
7.51
2.06
4.50
10.03
2004
2005
2006
2007
Years
Growth
Mean
2001
2002
2003
SD
Min
Performance
Max
Mean
SD
Min
Max
11.53 11.90
3.22 32.39
0.02
0.01
0.00
0.03
22.21 23.52
3.68 60.99
0.02
0.01
0.00
0.03
37.18 32.62
8.30 90.71
0.02
0.01
0.00
0.03
2004
22.20 27.93 -1.78 61.16
2005
2006
2007
0.03
0.02
0.00
0.05
31.18 10.30 24.97 48.98
0.02
0.02
0.00
0.05
31.79 26.14
3.74 72.78
0.03
0.02
0.00
0.06
9.25 22.44 45.66
0.07
0.07
0.00
0.17
34.82
Years
Tangibility
Mean
2001
2002
2003
SD
Min
Liquidity
Max
Mean
SD
Min
Max
0.03
0.02
0.00
0.06
1.70
0.76
1.07
2.65
0.03
0.02
0.00
0.06
1.73
0.86
1.14
3.01
0.03
0.02
0.00
0.05
2.18
1.11
1.22
3.72
0.02
0.02
0.00
0.04
2.24
1.77
1.09
4.85
0.02
0.02
0.00
0.04
3.02
2.26
1.15
5.94
0.02
0.01
0.00
0.03
3.98
2.72
1.36
7.37
0.02
0.02
0.00
0.05
6.36
8.63
1.33 16.33
2004
2005
2006
2007
Years
Age
Mean
2001
2002
2003
SD
Risk
Min
Max
Mean
SD
Min
Max
16.60 20.40
6.00 53.00
1.92
1.33
0.70
3.94
17.60 20.40
7.00 54.00
0.83
0.47
0.40
1.34
18.60 20.40
8.00 55.00
0.58
0.45
0.18
1.34
19.60 20.40
9.00 56.00
3.34
3.08
0.00
7.23
20.60 20.40 10.00 57.00
4.70
2.15
1.23
6.36
21.60 20.40 11.00 58.00
3.60
3.86
0.51
9.72
22.60 20.40 12.00 59.00
6.35
6.51
1.78 16.00
2004
2005
2006
2007
CORRELATION ANALYSIS
Leverage
Leverage
Size
Growth
Tangibility
Liquidity
Age
Pearson
Correlation
Sig. (2-tailed)
Size
Growth
Tangibility
Pearson
Correlation
Sig. (2-tailed)
.000
Pearson
Correlation
.077
.072
Sig. (2-tailed)
.661
.680
-.476**
-.142**
.051
.000
.000
.771
-.225**
-.429*
.052
.229
Sig. (2-tailed)
.000
.025
.796
.250
Pearson
Correlation
.415*
.401**
-.153
-.356**
.491**
Sig. (2-tailed)
.013
.000
.379
.000
.009
-.427*
-.200
-.060
.084
.364**
-.071
.012
.256
.334
.538
.000
.771
Pearson
Correlation
Sig. (2-tailed)
Liquidity
Age
Risk
.374**
Pearson
Correlation
Pearson
Correlation
Sig. (2-tailed)
REGRESSION ANALYSIS
Unstandardized
Coefficients
Standard
ized
Coefficie
nts
Model
(Constant)
B
.010
Std. Error
.051
Beta
t
.204
Sig.
.841
Leverage
-.265
.090
-1.579 -2.940 .008*
Size
.038
.009
1.722
4.120 .001*
Growth
-4.69
.000
-.032
-.245
Tangibility
.507
.367
.183
1.382 .183
Liquidity
.001
.003
.058
.205
Age
-.003
.003
-.235
-1.169 .257
Risk
-.004
.002
-.374
1.903 .072**
.809
.840
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
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