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In chapter 2, we study the effects of world and trading-block insurance market liberalization. For this purpose, we use a computable general equilibrium (CGE) model that includes 8 regions and 5 sectors. Except for the insurance and financial sectors, all other sectors are considered as perfectly competitive. To capture an imperfectly competitive structure, we assume that insurance firms with a noncompetitive structure charge customers a price higher than their marginal cost. Then we estimate the GlobalTrade Analysis Project (GTAP) model both under a perfectly competitive structure and an imperfectly competitive one. Comparing the results of moving toward liberalization (Le. moving from an imperfectly competitive structure to a perfectly competitive one), we conclude that the action that ensures a benefit for all parties consists in taking progressive steps toward liberalization based on GATS commitments. In chapter 3, we investigate the relationship between insurance market development and economic growth within the UK. Some previous studies have ·shown that there is no long-run relationship between insurance development and economic growth for some GECO countries, including the UK. Those studies considered insurance markets as a whole. As it is possible to observe no cointegration at the aggregate level and cointegration at the disaggregated one and vice versa, we reassessed the conclusions using disaggregate data for insurance markets. We find a long-run relationship between insurance market development and economic growth. On the basis of a causality test, .we conclude that the structure of the UK's insurance industry tends to display a demand-following pattern rather than a supply-leading. one (Le. growth promotes insurance market development, but not vice versa¥. In chapter 4, we use disaggregate data for both the insurance industry and GOP, to be able to uncover any long-run relationship between insurance market development and sectoral growth in the UK. We find results consistent with those of chapter 3. Since it is generally accepted that unit root and cointegration tests suffer from a lack of power in distinguishing the unit root null from stationary alternatives, we use panel unit root and cointegration tests, which have higher power when compared both to univariate and multivariate counterparts. The panel unit root test results show that the variables are best characterized as being integrated of order one while the panel cointegration test results puts forward a long-run relationship between sectoral GOP and insurance market development, regardless of the importance of the sector in the UK economy1. 1 Still, given the limitations of the estimation techniques adopted, as recently highlighted by

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