This dissertation comprises two topics. In Chapter 1, I explore the short- and long-run relation between insurance development and economic growth for 40 countries between 1981 and 2010. Applying a pooled mean group estimation, I find that life and nonlife insurance have different short- and long-run effects on the growth. On a full sample analysis, life insurance exerts a significantly positive long-run effect on the growth, while its short-run effect is not significant. Nonlife insurance, in contrast, has a significantly positive short-run growth effect but no long-run effect. On a reduced sample analysis, the observation on life insurance is qualitatively similar, but the growth effect of nonlife insurance is no longer significant both in short and long run, suggesting that specific countries drive the overall effect in the full sample. The results pass a battery of robustness tests. The analysis on individual countries reveals that the short-run effect and adjustment speed toward the long-run equilibrium varies across countries. I also analyze if the level of income and insurance development makes any difference on the growth effect of insurance. The results show that the growth effect of life insurance is significant in non-high income countries and countries with low level of life insurance development, while the effect is not significant both for life and nonlife insurance in high income countries. In Chapter 2, I employ the dynamic panel threshold model to investigate how institutional environments shape the impact of insurance development on economic growth. I conduct four hypotheses for possible intermediate effects of institutional environments on insurance-growth nexus: quasi-institution positivity, quasi-institution negativity, quasi-institution duality, and quasi-institution neutrality. I use multiple measures related to political, economic, and legal environments to evaluate the soundness of institutional environments. Empirical results show that the quasi-institution negativity hypothesis is supported for life insurance because the observation is consistent across all institution-related measures. The results in nonlife insurance are not as uniform as those in life insurance. The quasi-institution positivity, negativity, and neutrality are respectively supported in different institutional measures, and the coefficients in most cases are significant only at a marginal significance level. The overall findings suggest that a sound institutional environment does not necessarily benefit the growth effect of life insurance, but an unhealthy one does deter it and that the effect depends on specific measure in the case of nonlife insurance. In Chapter 3 I briefly introduce some directions for further research.