Literature Review

The purpose of this study is to get an in depth understanding of the insurance industry to understand what could be the impact of FDI on Indian insurance industry. To strengthen this study and get in-depth understanding of the variables that could impacted due to FDI a review of the past research has been done in this section.
An empirical study by (Li, Donghui; Moshirian, Fariborz; Sim, Ah-Boon, 2003) done on the U.S. insurance sector concludes that FDI contributes significantly to the volume of trade. This prompted studies to identify what are the important and significant variables that attract FDI in insurance. There have been many papers published that study the factors that lead to participation of in international insurers in a country’s insurance sector.
A study by (Li & Moshirian, 2004) of the US insurance services for the period 1984-1998 tries to identify factors that increases the desirability for FDI in insurance. The major factors that this study identifies are national income, relative cost of capital, relative wage rate, total trade in insurance services, exchange rate volatility, FDI in banking, source country’s insurance market size and the financial development of the host country.
Other studies that intend to find determinants that attract foreign participation in insurance market include study by (Ma & Pope, 2003) .The study reveals that major foreign market characteristics that determine international insurers participation are market structure , the trade barriers in the country and the GDP. The study further states that in countries that don’t have competitive markets can improve their desirability by lowering trade barriers.
Further study by the same authors (Ma & Pope, 2008) reiterates that market structure is an important determinant of foreign insurer participation. It states that foreign insurers disdain markets that are highly concentrated and have low levels of liberalization. By reducing any one variable the foreign market can significantly improve its desirability. The study in addition to the above factors finds other variables which are level of social security benefits, working population, profitability that determine the level of participation.
While the above studies show various factors that determine international insurer’s participation in foreign markets it is important to review research that led to identification of these characteristics. There are a number of paper published on factors that drive insurance growth and factors that share a strong correlation with insurance growth.
A study by (Outrville, 1990) examines the relationship between financial development and insurance premium written by studying data from 55 developing countries. The study conforms a positive and statistically significant relationship between demand for insurance and the level of financial development.
A study by (Browne & Kim, n.d.) identifies variables that have a bearing on demand for life insurance across countries spread across the world (the sample includes under developed, developing, and developed countries). The empirical results of the study reveal that income level is statistically significant and positively correlated while inflation is statistically significant and negatively correlated to life insurance growth. The other statistically significant variables that have an impact on life insurance are the dependency ratio, government spending on social security, price of insurance and the dominant religion of the country.

Another paper by (Beenstock, et al., n.d.) studies the relationship between income and spending on property-liability insurance by pooling the data of 12 countries for the period 1970-1981. The inference from the study concludes that as the country gets richer the relationship between insurance premium and income deteriorates and therefore the marginal propensity to insure comes down as income increases. The study by (Lee, et al., n.d.) gives a further evidence of the above findings. In order to partially remove the assumption of homogeneity in economic growth the 41 countries taken as sample are divided into high income, middle income and low income countries. The study is for the period 1979-2007 and the analysis shows that there is a small period of rapid growth in insurance in the three different types of economies. It starts in the high income countries, then spreads to low income countries and finally reaches the low income countries.

(Arena, 2008) Studies the causal relationship between Insurance market activity and economic growth across 55 countries, for the time period 1976-2004, and finds significant evidence of it using the generalized method of moments (GMM). The study further reveals that while it is life insurance that has significant impact on economic growth in high income countries, it is non-life insurance growth that has significant impact on economic growth in middle income countries.

Other studies that are important from this project point of view are studies related to efficiency of the insurance firms as the FDI players naturally look at this aspect while investing.
Cummins and Xie (2008a) examine efficiency, productivity and scale economies in the US PC insurance industry over the period 1993-2006. They find that the majority of firms below median size in the industry are operating with increasing returns to scale, and the majority of firms above median size are operating with decreasing returns to scale. However, a significant number of firms in each size decile have achieved constant returns to scale. Over the sample period, the industry experienced significant gains in total factor productivity, and there is an upward trend in scale and allocative efficiency. However, cost efficiency and revenue efficiency did not improve significantly over the sample period. Regression analysis shows that efficiency and productivity gains have been distributed unevenly across the industry. More diversified firms, stock insurers, and insurance groups were more likely to achieve efficiency and productivity gains than less diversified firms, mutuals, and unaffiliated single insurers. Higher technology expenditures increase the probability of achieving optimal scale for direct writing insurers but not for independent agency firms.

Another study which is particularly relevant for this project is a study by (Huang & Eling, 2013) studies the efficiency of Non-life insurance companies of the BRIC nations using multistage data envelopment analysis. The study incorporates uncontrollable variables (which capture the effect of environment) to analyze the efficiency of non-life insurance operations of BRIC countries and the environment it operates in as the country specific environmental conditions influence a country’s insurance industry. It concludes that Indian insurers are the least efficient in the BRIC countries. It also reveals four important variables that positively correlate to an insurer’s efficiency which are size, profitability, solvency and ownership form.