The authors analyze the demand for life and non-life insurance across 103 Italian provinces in 1994-2004, assessing the determinants of insurance consumption in the light of the empirical literature and the distinctive features of the Italian market, which we thoroughly describe. The authors discuss common issues in the empirical literature on insurance development, presenting the sub-regional perspective as a partial solution; at the same time, they elaborate on the peculiar issues arising from the use of sub-regional data: spatial heterogeneity and spatial correlation. They describe the evolution of provincial heterogeneity and of the spatial features of the data over the observation period. In order to control for both unobserved heterogeneity and spatial correlation, they specify a spatial panel model with random provincial effects and macroregional fixed effects, which is estimated by maximum likelihood. The chapter carefully assesses the properties of model residuals, concluding that the specification allows for reliable inference on the drivers of insurance consumption. It concludes describing the empirical findings and giving some suggestions for future research.
Insurance in Italy: a spatial perspective
MILLO, GIOVANNI;CARMECI, GAETANO
2012-01-01
Abstract
The authors analyze the demand for life and non-life insurance across 103 Italian provinces in 1994-2004, assessing the determinants of insurance consumption in the light of the empirical literature and the distinctive features of the Italian market, which we thoroughly describe. The authors discuss common issues in the empirical literature on insurance development, presenting the sub-regional perspective as a partial solution; at the same time, they elaborate on the peculiar issues arising from the use of sub-regional data: spatial heterogeneity and spatial correlation. They describe the evolution of provincial heterogeneity and of the spatial features of the data over the observation period. In order to control for both unobserved heterogeneity and spatial correlation, they specify a spatial panel model with random provincial effects and macroregional fixed effects, which is estimated by maximum likelihood. The chapter carefully assesses the properties of model residuals, concluding that the specification allows for reliable inference on the drivers of insurance consumption. It concludes describing the empirical findings and giving some suggestions for future research.Pubblicazioni consigliate
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