We analyze the demand for life and non-life insurance across 103 Italian provinces in 1996-2002. We assess the determinants of insurance consumption, in the light of the empirical literature and the distinctive features of our country, trying to explain the underdevelopment of the South in the insurance sector. Among the benefits of using sub-regional data on insurance expenditure, one seems to us particularly relevant. Since loadings on life insurance contracts tend to be uniform across regions of the same country, an important limitation of cross-country analyses, i.e. the difficulty of observing prices in this market, may be alleviated. On the other hand, a regional analysis raises issues of cross-sectional dependence, either due to common nationwide and/or regional factors or to spatial proximity. We analyze the form of cross-sectional dependence in different ways: we employ the CD test for global cross-sectional dependence by Pesaran (2004) both as a test and informally as a descriptive statistic; we apply an adaptation to irregular lattices of the CD(p) test for local cross-sectional dependence and we test for different orders of contiguity. We also employ panel versions of the standard diagnostics for spatial dependence (Anselin 1988) and recent joint and marginal tests for random effects and serial-spatial correlation (Baltagi, Song, Jung and Koh 2004). We explore the possibility of a characterization of sectional dependence based on geographic proximity through random effects panel models including combinations of spatial lags, spatial errors and serial dependence (Case 1991, Elhorst 2003, Baltagi et al., cit.), which we estimate by maximum likelihood through new procedures written in the R language.

Insurance consumption in Italy: a sub-regional panel data analysis.

MILLO, GIOVANNI;CARMECI, GAETANO
2008-01-01

Abstract

We analyze the demand for life and non-life insurance across 103 Italian provinces in 1996-2002. We assess the determinants of insurance consumption, in the light of the empirical literature and the distinctive features of our country, trying to explain the underdevelopment of the South in the insurance sector. Among the benefits of using sub-regional data on insurance expenditure, one seems to us particularly relevant. Since loadings on life insurance contracts tend to be uniform across regions of the same country, an important limitation of cross-country analyses, i.e. the difficulty of observing prices in this market, may be alleviated. On the other hand, a regional analysis raises issues of cross-sectional dependence, either due to common nationwide and/or regional factors or to spatial proximity. We analyze the form of cross-sectional dependence in different ways: we employ the CD test for global cross-sectional dependence by Pesaran (2004) both as a test and informally as a descriptive statistic; we apply an adaptation to irregular lattices of the CD(p) test for local cross-sectional dependence and we test for different orders of contiguity. We also employ panel versions of the standard diagnostics for spatial dependence (Anselin 1988) and recent joint and marginal tests for random effects and serial-spatial correlation (Baltagi, Song, Jung and Koh 2004). We explore the possibility of a characterization of sectional dependence based on geographic proximity through random effects panel models including combinations of spatial lags, spatial errors and serial dependence (Case 1991, Elhorst 2003, Baltagi et al., cit.), which we estimate by maximum likelihood through new procedures written in the R language.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2335039
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