Growth of life insurance in India
| ✅ Paper Type: Free Essay | ✅ Subject: India |
| ✅ Wordcount: 5089 words | ✅ Published: 1st Jan 2015 |
Abstract
The paper examines the relationship between economic growth and life insurance. In this context, we study contributions made by some authors across international and Indian domains.
The literature review begins with examining the work done in the international context by Arena (2008) and Zheng (2008). Arena (2008) examines the causal effect of insurance on economic growth in a cross-country study. Zheng (2008) attempt to develop comprehensive paradigms for an international insurance comparison.
In the Indian context, we examine the work done by Sadhak (2008) and Sinha (2005). Sadhak (2008) analyses the relationship between insurance and the macroeconomy. Sinha (2005) gives a crisp account of insurance in India since pre-independence times.
The paper wraps up with an examination of the Malhotra Committee report.
The effect of liberalization on the growth of life insurance in India
It is a commonly held belief that there is a strong interrelationship between insurance and the macroeconomy. Thus the objective of this review paper is to understand the factors that contribute to growth of life insurance.
Skipper (1997) highlights how insurance aids economic development in seven ways:
First, it promotes financial stability.
Second, it substitutes for government security programs.
Third, it facilitates trade and commerce.
Fourth, it mobilizes national savings.
Fifth, it enables risk to be managed more efficiently.
Sixth, insurers and reinsurers have economic incentives to help insureds reduce losses.
Seventh, it fosters a more efficient allocation of a country’s capital.
Literature Review
This literature review consists of four sections:
I. Cross country study and a new paradigm.
II. Insurance and the Macroeconomy in India.
III. Progress of Insurance in India.
IV. The Malhotra Committee report.
I. Cross country study and a new paradigm
Economic theory suggests that there is an interaction between insurance and the macroeconomy: growth in insurance promotes economic growth by giving support to savings that can be funnelled into the capital market. On the other hand, high economic growth will lead to demand for insurance.
• Arena (2008)
Objective
The objective of Arena’s paper is to study the effect of insurance on economic growth.
Hypothesis
Considering the increased activity in insurance markets, in the recent decades, Arena hypothesizes that there is going to be an effect of insurance markets on economic growth. He expects to find a causal relationship between insurance market activity and economic growth; further there should be evidence of complementarity between insurance and banking as well as insurance and the stock market activity.
Methodology
Arena uses the generalized method of moments (GMM) for dynamic models of panel data that were developed by Arellano and Bond (1991) and Arellano and Bover (1995).
The general regression equation to be estimated is:
Yi,t = β’Xi,t + μ t + ηi + ξi,t
where subscripts i and t are country and time period; Y is the dependent variable representing economic growth; X is a set of time – and country-varying explanatory variables, proxies of banking, stock market and insurance market development and interaction terms; β is the vector of coefficients to be estimated; μt is an unobserved time-specific effect; ηi is an unobserved country specific effect, and ξ is the error term.
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Control variables include average rate of secondary school enrolment for human capital investment; average inflation rate to account for monetary discipline; average growth of the terms of trade ratio and the average ratio of government consumption to GDP as a measure of government burden.
papers.ssrn.com/sol3/Delivery.cfm/4098.pdf?
Banking sector development is observed by using the ratio of bank claims on the private sector divided by the GDP.
Stock market development is observed by taking the turnover ratio.
For explanatory variables of insurance market development, life and non-life insurance premiums are used as proxies. This was done given the absence of consistent time series data for the ratio of financial investments to GDP, that captures their role as institutional investors.
Data
He takes a pooled data set consisting of 56 countries grouped under the World Bank classification of High income, Middle income and Low income categories. There are 6 non – overlapping five year periods over 1976-2004. The data was taken from the Swiss Re database.
Results
a) The Linear effects
For exposition, we take one of the equations for a linear effect. The equation is framed below:
Y = 0.162*** – 0.015X1*** -0.003X2 + 0.025X3*** + 0.138X4 ***+ 0.501X5 * – 2.206X6*** – 0.003X7*** + 0.043X8 ***+ 0.055X9***
*** significance at 1%
** significance at 5%
* significance at 10%
Here, Y is the dependent variable representing average rate of real per capita GDP growth. The equation is dynamic as it includes the initial level of per capita GDP as an explanatory variable. The equation has various explanatory variables and various control variables. X1 represents the log of initial GDP per capita; X2 represents private credit to GDP; X3 represents stock market turnover; X 4 represents life and non life insurance to GDP; X 5 represents the degree of openness; X 6 represents government consumption; X 7 represents inflation; X 8 represents the terms of trade; X 9 represents school enrolment.
|
EXPLANATORY VARIABLE |
PROXY |
|
Insurance market development |
Life insurance premium to GDP and the ratio of non-life premium to GDP |
|
CONTROL VARIABLES |
PROXY |
|
Human capital investment |
Average secondary school enrolment |
|
Inflation |
Average inflation rate |
|
Terms of trade |
Relative price of exports to Imports |
|
Government |
Government consumption |
|
Banking sector development |
Private credit to GDP |
|
Stock market development |
Turnover ratio |
Source?
Coefficient for initial level of per capita GDP is negative as expected – growth rates are inversely related to initial levels of GDP per capita.
Coefficient of private credit to GDP is negative. However, the result is not significant.
The coefficient of stock market activity is positive. This is because liquid equity markets make investment less risky and more attractive, by allowing savers to acquire an asset (equity) and to sell it quickly and cheaply if they need access to their savings.
The coefficient of government spending is negative. This gives support to studies that show that beyond a certain level, government spending does not have a positive effect on the economy.
The coefficient of inflation is negative. This is expected, since inflation leads to uncertainty about future profitability of investment projects, reduces international competitiveness and distorts borrowing and lending.
The coefficient of degree of openness is positive. This is because trade promotes a competitive environment which leads to efficient resource allocation; this promotes growth.
The coefficient of degree of terms of trade is positive. This is because a high terms of trade increases returns to producers. This in turn raises investment, promoting economic growth.
The coefficient for human capital is positive. This is because economic development depends on advances in technological and scientific knowledge.
Further, the author analyses in terms of income group of the countries. He finds that in case of life insurance, the conclusions for the linear effect of insurance on economic growth would hold good only for high income countries. This is because he finds the coefficient on life insurance for developing countries as not significant.
In case of non life insurance, the author finds that his conclusion for linear effect of insurance on economic growth hold good for both high income and developing countries.
b) Non – Linear effects.
For life insurance, the coefficients of the linear and quadratic term are positive but not significant; for non-life, the coefficient for the linear term is negative but not significant while the coefficient for the quadratic term is positive but not significant.
c) Complementarities
In case of interaction between insurance variables and private credit the coefficient of interaction term is negative and significant. This suggests that banking sector and insurance (life and non-life premiums to GDP) are substitutes than complements.
In case of interaction between stock market turnover and insurance variables, the coefficient of interaction term is negative. This suggests that stock market and insurance ( life and non-life premiums to GDP) are substitutes than complements.
However, the author notes that the results are contradictory and exist due to collinearity issues.
Findings
The important finding of the paper is that both life and non-life insurance have a positive and significant causal effect on economic growth. Further, high – income countries drive the results in case of life insurance. On the other hand, both high income and developing countries drive the results in case of non-life insurance.
• Zheng (2008)
The objective of this paper is to build a new paradigm for international insurance comparison.
The paper has two parts :
a) Constructing the Benchmark Ratio of insurance penetration.
b) Decomposing growth rates by a ‘Trichotomy’.
a) The Benchmark Ratio of Insurance Penetration (B.R.I.P)
Zheng (2008) consider the insurance industry as one of economic segments whose growth is related to the level of economic development.
Just as insurance ‘density’ is an adjustment to premium income by considering the population factor, and just as insurance ‘penetration’ is adjustment of insurance density by the GDP per capita, the BRIP is an adjustment of penetration by a ‘benchmark’ level of world average penetration at that country’s economic development stage. Thus, the Benchmark Ratio of Insurance Penetration (B.R.I.P) gives the penetration level of the country, in relation to the world average insurance penetration at a country’s economic level :
The numerator is the penetration level of the country. The denominator comprises of the logistic function. The logistic model for insurance penetration was given by Enz (2000), who described that insurance penetration and GDP per capita are related by an S – shaped curve. Zheng (2008) term it as the ‘ordinary growth model’.
Note that the S – curve is a logistic function represented by Y= 1/(C1+C2.C3x) , where, C1 C2 and C3 are the three parameters and X is growth rate.
Zheng (2008) describes the benchmark penetration as premiums divided by GDP:
Y = premium / G.D.P.= 1 / (C1+C2.C3x),
where, Y is insurance penetration, X is the independent variable real GDP per capita. C1 ,C2 and C3 are the three parameters of the logistic function. The normal case of penetration increasing as real GDP per capita increases, is when C3<1. The steepness of the S-curve increases upto the level of income given by the inflection point - and decreases thereafter.
A pooled dataset comprising of 95 countries and regions over the last 27 years (1980-2008) was taken from the Sigma database of Swiss Re.
On this basis, the estimates of the BRIP for world life insurance, non-life insurance and the insurance industry aggregate are got by plotting the regression curves for life, non-life and insurance industry aggregate.
As seen in the diagram above, the regression curves resemble the shape of the letter ‘S’, S-curve model. The insurance penetration rises with the GDP per capita.
Further, various levels of GDP per capita have different growth rates of insurance penetration: at low levels of GDP per capita, the growth rate of insurance penetration is relatively slow. However, as the GDP per capita rises, the growth rate of insurance penetration also increases. However, after a certain level, the insurance penetration tends to plateau.
Thus, if BRIP =1, it means that country’s actual penetration is equal to the world average penetration at that economic development stage. If BRIP <1, the actual penetration is less than world average; if BRIP>1, the actual penetration is greater than world average level. The world average level of penetration is given by the relevant S – curve.
Zheng (2008) find that rankings of the insurance industries of developed countries under B.R.I.P descend compared to the ranks got by using traditional indicators; similarly, the rankings of emerging countries under B.R.I.P rise compared to the ranks got by using traditional indicators.
b). Decomposing growth rates by ‘Trichotomy’
The authors now modify the ‘ordinary growth model’ by a ‘Trichotomy’ of decomposing growth.
For attempting the Trichotomy, the ordinary growth model has to be modified to bring out the effects of the economic and institutional factors. This is done by modifying the ordinary model by including country specific dummies which include like the legal system, culture, religion, social security on the insurance growth.
Growth is decomposed into ‘Regular growth’, ‘Deepening growth’ and ‘Institutional growth’.
‘Regular growth’ measures the insurance growth that happens while keeping the insurance penetration unchanged, i.e., premiums/GDP are increasing at the same pace. This arises out of economic factors.
‘Deepening growth’ caused by the increase of insurance penetration induced by economic growth. This also arises out of economic factors.
‘Institutional Growth’ is the residual that remains after the economic factors of growth, (represented by the Regular and Deepening growth) are deducted from deducted from the overall aggregate growth. It is caused by institutional factors that are country specific such as legal system, culture, religion etc.
After performing the decomposition by using the ‘adjusted growth model’, the authors show that insurance growth in developed countries is mainly driven by economic factors (i.e., regular and deepening), while institutional factors act as the major driving power for the insurance growth in emerging countries.
The authors remark that institutional aspects facilitate growth of the private insurance industry especially in case of developing countries.
However, as the economy develops, the contribution of the institutional factors to the insurance growth gradually decreases; the economic factors begin to play a more active role in driving the insurance growth.
Finally, in case of developed countries, the social security system is well developed. This acts as a substitute for insurance. As such, insurance growth is hindered.
The authors conclude the following:
Firstly, there should be recognition of insurance growth level of each country or region, relative to their own stage of development, as given by BRIP;
Secondly, insurance growth in developed countries is driven by economic factors while in emerging countries is driven by institutional factors.
Thirdly, as an economy develops, the contribution of institutional factors would gradually decrease and economic factors play a greater role. Consequently the emerging countries should upgrade its growth strategy to attain sustainable development.
II. Insurance and the Macroeconomy in India
• Sadhak (2006)
Sadhak’s paper is on the relationship between demand for life insurance and macroeconomic variables of growth. These are GDP, domestic savings, household financial savings and disposable income.
Sadhak expects to find a continued preference for insurance, given the strong economic performance of the Indian economy in the post liberalization period.
He remarks that although the savings are increasing (Table I) there is a decline in life insurance savings in India as a proportion of savings (Table II).
(Table I):
|
1998-99 to 2000-01 |
2001-02 to 2004-05 |
||
|
GDS as % of GDP |
23% |
25.8% |
The improved performance is attributed to growth of the economy, expansion of service sector and increase in household savings |
|
1993-94 |
1999-2000 |
2002-03 |
2003-04 |
2004-05 |
||
|
Life insurance savings in India as proportion of household savings |
8.7% |
12.1% |
15% |
13.5% |
13% |
There is a fall in the insurance component of savings from 2003-04 |
(Table II)
The author finds a decline in the overall savings as a percentage of personal disposable income – from a high of 14.5% in 1950-51 to a low of 3.6% in 2002-03. However, it must be mentioned here that the author does not cite the source of data which he used to arrive at this conclusion; he merely says that personal disposable income can be arrived at after deduction of payment of direct taxes and other miscellaneous receipts of the government. A detailed examination of how Sadhak (2006) got this result is required.
This increased diversion of funds leaves a small amount to be saved and consequently affects the growth of life insurance funds. Hence, life insurance funds have failed to keep pace with PDY. Sadhak (2006) opines that the opening of the market has not provided much momentum to growth of the industry. He sums up the article by remarking that a spread of financial literacy, awareness of financial risk management, and customer focused service management could help create the required demand for the Indian life insurance industry.
III. The progress of insurance in India
The objective of Sinha (2005) is to examine the Indian insurance industry. He structures his article into evolution of insurance in the pre – nationalization era and the nationalized era.
• Evolution under the pre – nationalization era
Sinha (2005) feels that the pre – independence time is of importance, as developments of the period culminated in the landmark Insurance Act of 1938.
During the pre-independence period, the pioneering European companies did not initially ensure the lives of Indians; when they did, it was done at rates that were nearly 20% more, compared to the European rates! He notes that such discrimination was practiced by European companies even in other markets like Latin America.
The initial period was marked by an absence of regulation on the insurance companies, except for compliance to Companies Act (1866). The Swadeshi Movement from 1905 lead to emergence of many indigenous companies. This necessitated a need for legislations specific to the Indian companies. Legislative controls were extended on foreign companies much later.
The Insurance Act of 1938 was a comprehensive legislation the covered life and non – life business. It covered deposits, supervision of insurance companies, investments, commissions of agents. Unfortunately, the act lost its importance in the post independence nationalization wave of the country. The act was reinstated only after the opening up of the markets in 1999. However, necessary modifications were done.
Non – revision of Mortality tables was a hallmark of this era. Sinha (2005) notes that tables based on the British experience during 1863-1893 were used. To further worsen the situation, the ratings were increased by seven years for Indians! Indian tables emerged much later, based on the experience of 1905-25. The Life Insurance Corporation revised these in the 70s!
• Evolution during nationalized era
Sinha (2005) asks two very important questions to bring out rationale for nationalization: First, why did the Government nationalize life insurance in 1956? Further, why was general insurance not nationalized at the same time?
Regarding the first question, he gives interesting insight that comes out of a document given by H.D. Malaviya of the Congress that justifies nationalization on the following grounds: First, that it is by nature, a ‘cooperative enterprise’; thus the government should run it on behalf of the people. Secondly, the Indian companies were claimed to be excessively expensive. Third, private competition could not improve the sales to the public. Fourth, the lapse rates were said to be high, leading to national waste. He then analyses the speech made by finance minister C.D. Deshmukh. Its examination leads the Sinha (2005) to conclude that the main rationale for nationalization of insurance was to bring out a social orientation of resources and also to increase market penetration.
For the second question, concerning delay in nationalization of non life insurance, Sinha (2005) examines the speech made by finance minister C. D. Deshmukh. He saw ‘general insurance as a part and parcel of the private sector… not affecting the individual citizen…’ It seems to as if the government emphasized the elimination of uncertainty through insurance as a relatively minor benefit!
Moving forward, Sinha (2005) touches on rural insurance. The Government had specific hopes from rural insurance. Specifically, it was reaching into hitherto neglected rural areas. Sinha (2005) mentions that to promote rural insurance, the Life Insurance Corporation followed a segmented approach for marketing. It involved targeting the rural wealthy with regular policies and offering group policies to people who could not afford individual policies.
Sinha (2005) takes the rural insurance drive to be a success for three reasons. Firstly, from 1980 onwards the proportion of policies sold in rural areas stated to increase, i.e., headcount for rural areas has gone up; Secondly, in terms of value of policies sold, the total value of all policies sold in rural areas has not gone up beyond 40%. This fact along with declining headcount implies that more policies were sold in the rural areas with a smaller average value.
The author gives reasons for nationalization of general insurance business. First, the subsidiary companies were expected to “set up standards of conduct and sound practices” Second, the General Insurance Corporation was to help with ‘controlling their expenses’. Third, it was to help with the investment of funds. Fourth, it was to bring in general insurance in the rural areas of the country. Fifth, the General Insurance Corporation was also designated the National Reinsurer. By law, all domestic insurers were to cede 20% of the gross direct premium in India to the General Insurance Corporation. The idea was to retain as much risk as possible domestically to minimize the expenditure on foreign exchange. Sixth, all the four subsidiaries were supposed to compete with one another. Sinha (2005) observes that the above goals were scarcely met. For instance, though various schemes were introduced in rural areas, like crop insurance and cattle insurance, they could not expand their business.
Coming to the analysis of General insurance business, Sinha (2005) finds that general insurance business in India is a much smaller. Even in this, fire insurance (in terms of premium earned) accounted for about a quarter of all business. Marine insurance has shrunk to under 10% by 2001. Interestingly, the ‘miscellaneous’ component is 68% of the general insurance market. This is the unfortunate outcome of the Insurance Act of 1938 – which stipulated whatever cannot be classed as life insurance or fire insurance or marine insurance is put as ‘miscellaneous’. Thus, the biggest component of general insurance – motor insurance – is lumped with a range of other general insurance such as aviation, engineering and crop insurance!
Even the profitability of General insurance business is lesser – in terms of premium, motor insurance accounts for around 54% of premium income. The Tariff Advisory Committee has been unwilling to revise motor premium upward for political reasons. This leads to mounting loss in motor insurance for general insurance companies.
The article concludes with a detailed discussion of the current state of the market. Sinha (2005) feels that India is a very important emerging insurance market. He identifies the major drivers to be a sound economic base, a rising middle-income class, an improving regulatory framework and rising risk awareness. The changes in regulation shall be crucial to ensure future growth.
IV. The Malhotra Committee Report
In 1993, the first step towards insurance sector reforms was initiated with the formation of the Malhotra Committee, headed by former RBI Governor R.N. Malhotra. The committee was formed to evaluate the Indian insurance industry and recommend its future direction with the objective of complementing the reforms initiated in the financial sector.
The resolution highlights how the committee was formed for “creating an efficient and competitive financial system” and how the government saw “insurance as an important part of the overall financial system and felt the needs for similar reforms in this sector…”
The other members of the committee were R Narayanan, former chairman, LIC; R.K. Daruwala, the former chairman of GIC; S.K. Dave, the chairman of UTI R. Ramakrishna, President, Actuarial Society of India; Deepak Parekh and M.P. Modi, Special Secretary, Insurance. Indeed, the committee was well represented by eminent personalities from the financial sector.
The principal terms of reference for the committee were quite comprehensive: to examine the institutional structure for creating an efficient and viable insurance industry; suggesting changes in the structure of the industry; review of the regulatory framework and to give specific suggestions for the LIC and GIC.
The methodology for working of the committee was through constitution of working groups from senior executives of the LIC and GIC to analyze the practice of insurance in India. The committee met various interest groups and opinion leaders, which was preceded by circulation of questionnaire. Lastly, there was engagement of Market research agency to elicit popular perceptions about insurance. The committee made all effort to understand what an average Indian wanted from this process of liberalization. For instance, the objective of the Market Action Research Group survey was to get the perceptions of the population. It did so by means of a questionnaire which consisted of two parts – life and General Insurance. In life insurance, there were 14 questions relating to the operations and future growth areas. It was circulated to 412 renowned persons and organizations that comprised of chairmen of industrial and cooperative organizations, academicians, businessmen, union leaders from all parts of India for eliciting their views. Questions ranging from ‘What have been the achievements of LIC?’ to ‘Should there be private insurance companies?’ were asked.
We analyse the report in three parts –
a) Life insurance
b) Non-life insurance
c) Regulatory issues
a) Life Insurance:
The findings that emerged from consultations of the working groups and survey committees revealed that Life Insurance coverage was expensive. The returns were significantly lower due to excessive dictated investments. The committee prescribed that the LIC should move on from conservative portfolio management and take advantage of market returns. The committee remarked that emphasis should be shifted from `security of capital’ to maximising the yield on the total investment. The investment regulations suggested by the committee are given below:
Life insurance
|
Type of Investment |
Percentage |
|
|
I. |
Government Securities |
25% |
|
II. |
Government Securities or other approved securities (including I) above |
Not less than 50% |
|
III. |
Approved Investments as specified in Schedule I |
|
|
Infrastructure and Social Sector |
Not less than 15% |
|
|
Others to be governed by Exposure / Prudential Norms |
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