The CCE model applied to the nexus of real GDP and the insurance market

Abstract: Existing studies on the relationship between the insurance market and economic development tend to use empirical methods that rely on the unrealistic assumption of cross-sectional independence. This thesis aims to highlight the drawbacks of this assumption. The results are achieved by comparing the results of the Common Correlated Effects (CCE) model to the two-way fixed effects model as well as the fixed effects model. All three models confirm most previous research, stating that there is a positive cointegrated relationship between the insurance market and real GDP. However, the results show that the CCE model accounts for more unobserved heterogeneity than the competition. This is indicated by a higher degree of normally distributed residuals which are assigned a significantly lower degree of absolute average pairwise correlation. Therefore, the estimates produced by the CCE model are more reliable, making it more appropriate to use when investigating cross-sectionally dependent panel data.