# **Annex I:  Factors influencing insurance sector development**

Outreville (2013) identifies more than 70 papers that examine the factors that influence insurance sector growth. The World Bank has produced the most recent paper in this sequence (Feyen, Lester and Rocha, 2013), using fully disaggregated AXCO data (life v. P&C) and a number of structural variables for the first time. This section draws on the Outreville literature review with an initial overview from the Feyen et al paper. The findings of a Swiss Re. (2011) anecdotal paper on the development of insurance in emerging markets are then described.

The empirical research on the determinants of the insurance sector has focused on the life sector. Early contributions to the empirical literature were also mostly focused on the US, and explored the role of education, income, religion, and cultural factors, as well as prices. By way of illustration, Hammond, Houston and Melander (1967) stress the importance of the occupation of the main wage earner. Headen and Lee (1974) show that the demand for life insurance depends on savings and interest rates. Burnett and Palmer (1984) show that education, income and religion are key determinants of the demand for life insurance. Babbel (1985) shows that price has a negative effect on the demand for life insurance. Beenstock, Dickinson, and Khajuria (1986) provided one of the first empirical studies exploring cross-country data. Using a dataset of 10 developed countries, the authors conclude that income, life expectancy, and the dependency ratio have a positive impact on life insurance demand, while social security expenditures have a negative impact.

More recent empirical studies include Browne and Kim (1993), Outreville (1996), Beck and Webb (2003), and Li et al (2007). These studies rely on larger cross-country datasets, especially the latter two. Browne and Kim (1993) use data from 1987 for a cross-section of 45 developed and developing countries, while Outreville (1996) bases his analysis on a cross-section of 48 developing countries for the year 1986. Beck and Webb (2003) use a large dataset of 68 developed and developing countries over the 1961-2000 period, while Li et al (2007) rely on a panel of 30 OECD countries over the 1993-2000 period. These studies use life premiums as the dependent variable (usually expressed as ratios to GDP or the population). Browne and Kim (2003) and Li et al (2007) define the estimated equation as the demand for life insurance. Outreville (1996) specifies briefly the demand and supply for life insurance and defines the estimated equation as a reduced form. Beck and Webb (2003) also indicate that the life premium reflects both demand and supply factors, while stressing the difficulties of distinguishing between the demand and supply sides.

Table 5 shows the strongest predictors of insurance sector growth (mainly at the 1% confidence level) by Feyen et al category, and the papers supporting these findings. While some predictive economic, structural and cultural variables (e.g. population, religion) cannot be easily changed, or can only be changed over the long term, other policy variables are amenable to reform. However even some invariant variables can be addressed (e.g. the introduction of Takaful in Islamic countries).

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