... for the demeaned model, a common pitfall), so we felt there was need for an all in one econ... more ... for the demeaned model, a common pitfall), so we felt there was need for an all in one econometrics-oriented package allowing to make specification searches, estimation ... Although the first strategy is the most efficient one, diagnostic testing on panel models mostly employs ...
We analyze the consumption of life and non-life insurance across 103 Italian provinces in 1996-20... more We analyze the consumption of 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 fea- tures of our country, trying to explain the underdevelopment of the South as regards this sector. Among the benefits of using sub-regional data on insurance expenditure, one
Maintainer Achim Zeileis <Achim.Zeileis@R-project.org> Description A collection of tests, d... more Maintainer Achim Zeileis <Achim.Zeileis@R-project.org> Description A collection of tests, data sets, and examples for diagnostic checking in linear regres-sion models. Furthermore,some generic tools for inference in parametric models are provided.
splm is an R package for the estimation and testing of various spatial panel data specifications.... more splm is an R package for the estimation and testing of various spatial panel data specifications. We consider the implementation of both maximum likelihood and generalized moments estimators in the context of fixed as well as random effects spatial panel data models. This paper is a general description of splm and all functionalities are illustrated using a well-known example taken from Munnell (1990) with productivity data on 48 US states observed over 17 years. We perform comparisons with other available software; and, when this is not possible, Monte Carlo results support our original implementation. PLEASE NOTICE JSS IS OPEN ACCESS: download from jstatsoft.org, this is vol. 47/1
Italian insurance shows a high degree of regional differentiation in per capita expenditure. Of c... more Italian insurance shows a high degree of regional differentiation in per capita expenditure. Of course this is, at least partially, due to heterogeneity in the economic development of Italian territory. This research aims at assessing the drivers of insurance consumption from this new perspective and testing whether these observable economic, social and demographic factors are able to fully account for regional variability in insurance density or, on the converse, diffusion effects of some kind, such as cross-border or global spillovers, are present. We find evidence of spatial effects and try to assess their nature. We highlight the importance of taking the spatial perspective into account when doing inference on regional data.
We analyze the consumption of life and non-life insurance across 103 Italian provinces in 1996-20... more We analyze the consumption of 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 fea- tures of our country, trying to explain the underdevelopment of the South as regards this sector. Among the benefits of using sub-regional data on insurance expenditure, one seems to us particularly relevant. Since load- ings on life insurance contracts tend to be uniform across regions of the same country, an important limitation of cross-country analyses, i.e. the diculty of observing prices in this market, may be alleviated. On the other hand, a sub-regional analysis raises issues of cross-sectional depen- dence, either due to common nationwide and/or regional factors or to spatial proximity. We assess cross-sectional dependence in dierent ways: we employ a recent joint test for random eects, serial and spatial correla- tion (Baltagi, Song, Jung and Koh 2007) and ...
We analyze the consumption of non-life insurance across 103 Italian provinces in 1998-2002 in ord... more We analyze the consumption of non-life insurance across 103 Italian provinces in 1998-2002 in order to assess its determinants, in the light of the empirical literature. Using sub-regional data we overcome an important limitation of cross-country analyses, i.e. the systemic heterogeneity due to country-specific characteristics. Individual heterogeneity is accounted for through panel data techniques. However, considering spatial units within a single market raises issues of cross-sectional or spatial dependence, either due to common nationwide and/or regional factors or to spatial proximity. We carefully assess spatial dependence, employing recent diagnostic tests, finding out that the regressors included in our specification successfully account for spatial dependence. Insurance turns out to depend on income, wealth and some demographics, as already established, but also on trust, judicial efficiency and borrowing conditions. These findings help in explaining the gap between Central-Northern Italy and the South of the country.
... Author: Roger Bivand, with contributions by Luc Anselin, Olaf Berke, Andrew Bernat, Marilia C... more ... Author: Roger Bivand, with contributions by Luc Anselin, Olaf Berke, Andrew Bernat, Marilia Carvalho, Yongwan Chun, Carsten Dormann, Stéphane Dray, Rein Halbersma, Nicholas Lewin-Koh, Jielai Ma, Giovanni Millo, Werner Mueller, Hisaji Ono, Pedro Peres-Neto, Markus ...
ABSTRACT with either a spatial lag or spatial correlation in the error term, based on both the co... more ABSTRACT with either a spatial lag or spatial correlation in the error term, based on both the concurrent approaches prevailing in the literature, i.e. the Maximum Likelihood framework pioneered by Anselin (1988) and the Generalized Moments framework of Kapoor, Kelejian and Prucha (2007). Some of the model estimation procedures are generalized to the case of spatially and serially correlated error terms. GM estimators for systems of equations are also available. We also provide the Lagrange Multiplier joint, marginal and conditional specication tests from the work of Baltagi et al. (2003, 2007). The user interface aims at consistency w.r.t. the spatial (non-panel) estimators in package spdep and the panel (non-spatial) estimators in package plm. We briey discuss code optimization aspects of the computationally heavy Maximum Likelihood routines that have up to now hindered the practical implementation of these estimators. The GM approach, on its part, yields very fast estimators that can be applied to comparatively big datasets. We conclude with an empirical illustration on a well-known data set from the panel data literature.
ABSTRACT splm is an R package for the estimation and testing of various spatial panel data specif... more ABSTRACT splm is an R package for the estimation and testing of various spatial panel data specifications. We consider the implementation of both maximum likelihood and generalized moments estimators in the context of fixed as well as random effects spatial panel data models. This paper is a general description of splm and all functionalities are illustrated using a well-known example taken from Munnell (1990) with productivity data on 48 US states observed over 17 years. We perform comparisons with other available software; and, when this is not possible, Monte Carlo results support our original implementation. PLEASE NOTICE JSS IS OPEN ACCESS: download from jstatsoft.org, this is vol. 47/1
Specification search strategies in econometric regression modelling are based on zero-restriction... more Specification search strategies in econometric regression modelling are based on zero-restrictions testing on a maintained model (or, in the case of non-nested models' comparison, on an encompassing one). Also in the model validation stage many diagnostic tests may be seen as restriction testing on an auxiliary model derived from the maintained one. Thus, software implementation of both restriction tests and of restrictions-based diagnostic tests may rely on the same computing engine. We focus first on robustness of the latter under deviations from the classical normal linear regression model, then on a flexible implementation framework giving rise to a number of functions for mainstream tests.
... for the demeaned model, a common pitfall), so we felt there was need for an all in one econ... more ... for the demeaned model, a common pitfall), so we felt there was need for an all in one econometrics-oriented package allowing to make specification searches, estimation ... Although the first strategy is the most efficient one, diagnostic testing on panel models mostly employs ...
We analyze the consumption of life and non-life insurance across 103 Italian provinces in 1996-20... more We analyze the consumption of 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 fea- tures of our country, trying to explain the underdevelopment of the South as regards this sector. Among the benefits of using sub-regional data on insurance expenditure, one
Maintainer Achim Zeileis <Achim.Zeileis@R-project.org> Description A collection of tests, d... more Maintainer Achim Zeileis <Achim.Zeileis@R-project.org> Description A collection of tests, data sets, and examples for diagnostic checking in linear regres-sion models. Furthermore,some generic tools for inference in parametric models are provided.
splm is an R package for the estimation and testing of various spatial panel data specifications.... more splm is an R package for the estimation and testing of various spatial panel data specifications. We consider the implementation of both maximum likelihood and generalized moments estimators in the context of fixed as well as random effects spatial panel data models. This paper is a general description of splm and all functionalities are illustrated using a well-known example taken from Munnell (1990) with productivity data on 48 US states observed over 17 years. We perform comparisons with other available software; and, when this is not possible, Monte Carlo results support our original implementation. PLEASE NOTICE JSS IS OPEN ACCESS: download from jstatsoft.org, this is vol. 47/1
Italian insurance shows a high degree of regional differentiation in per capita expenditure. Of c... more Italian insurance shows a high degree of regional differentiation in per capita expenditure. Of course this is, at least partially, due to heterogeneity in the economic development of Italian territory. This research aims at assessing the drivers of insurance consumption from this new perspective and testing whether these observable economic, social and demographic factors are able to fully account for regional variability in insurance density or, on the converse, diffusion effects of some kind, such as cross-border or global spillovers, are present. We find evidence of spatial effects and try to assess their nature. We highlight the importance of taking the spatial perspective into account when doing inference on regional data.
We analyze the consumption of life and non-life insurance across 103 Italian provinces in 1996-20... more We analyze the consumption of 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 fea- tures of our country, trying to explain the underdevelopment of the South as regards this sector. Among the benefits of using sub-regional data on insurance expenditure, one seems to us particularly relevant. Since load- ings on life insurance contracts tend to be uniform across regions of the same country, an important limitation of cross-country analyses, i.e. the diculty of observing prices in this market, may be alleviated. On the other hand, a sub-regional analysis raises issues of cross-sectional depen- dence, either due to common nationwide and/or regional factors or to spatial proximity. We assess cross-sectional dependence in dierent ways: we employ a recent joint test for random eects, serial and spatial correla- tion (Baltagi, Song, Jung and Koh 2007) and ...
We analyze the consumption of non-life insurance across 103 Italian provinces in 1998-2002 in ord... more We analyze the consumption of non-life insurance across 103 Italian provinces in 1998-2002 in order to assess its determinants, in the light of the empirical literature. Using sub-regional data we overcome an important limitation of cross-country analyses, i.e. the systemic heterogeneity due to country-specific characteristics. Individual heterogeneity is accounted for through panel data techniques. However, considering spatial units within a single market raises issues of cross-sectional or spatial dependence, either due to common nationwide and/or regional factors or to spatial proximity. We carefully assess spatial dependence, employing recent diagnostic tests, finding out that the regressors included in our specification successfully account for spatial dependence. Insurance turns out to depend on income, wealth and some demographics, as already established, but also on trust, judicial efficiency and borrowing conditions. These findings help in explaining the gap between Central-Northern Italy and the South of the country.
... Author: Roger Bivand, with contributions by Luc Anselin, Olaf Berke, Andrew Bernat, Marilia C... more ... Author: Roger Bivand, with contributions by Luc Anselin, Olaf Berke, Andrew Bernat, Marilia Carvalho, Yongwan Chun, Carsten Dormann, Stéphane Dray, Rein Halbersma, Nicholas Lewin-Koh, Jielai Ma, Giovanni Millo, Werner Mueller, Hisaji Ono, Pedro Peres-Neto, Markus ...
ABSTRACT with either a spatial lag or spatial correlation in the error term, based on both the co... more ABSTRACT with either a spatial lag or spatial correlation in the error term, based on both the concurrent approaches prevailing in the literature, i.e. the Maximum Likelihood framework pioneered by Anselin (1988) and the Generalized Moments framework of Kapoor, Kelejian and Prucha (2007). Some of the model estimation procedures are generalized to the case of spatially and serially correlated error terms. GM estimators for systems of equations are also available. We also provide the Lagrange Multiplier joint, marginal and conditional specication tests from the work of Baltagi et al. (2003, 2007). The user interface aims at consistency w.r.t. the spatial (non-panel) estimators in package spdep and the panel (non-spatial) estimators in package plm. We briey discuss code optimization aspects of the computationally heavy Maximum Likelihood routines that have up to now hindered the practical implementation of these estimators. The GM approach, on its part, yields very fast estimators that can be applied to comparatively big datasets. We conclude with an empirical illustration on a well-known data set from the panel data literature.
ABSTRACT splm is an R package for the estimation and testing of various spatial panel data specif... more ABSTRACT splm is an R package for the estimation and testing of various spatial panel data specifications. We consider the implementation of both maximum likelihood and generalized moments estimators in the context of fixed as well as random effects spatial panel data models. This paper is a general description of splm and all functionalities are illustrated using a well-known example taken from Munnell (1990) with productivity data on 48 US states observed over 17 years. We perform comparisons with other available software; and, when this is not possible, Monte Carlo results support our original implementation. PLEASE NOTICE JSS IS OPEN ACCESS: download from jstatsoft.org, this is vol. 47/1
Specification search strategies in econometric regression modelling are based on zero-restriction... more Specification search strategies in econometric regression modelling are based on zero-restrictions testing on a maintained model (or, in the case of non-nested models' comparison, on an encompassing one). Also in the model validation stage many diagnostic tests may be seen as restriction testing on an auxiliary model derived from the maintained one. Thus, software implementation of both restriction tests and of restrictions-based diagnostic tests may rely on the same computing engine. We focus first on robustness of the latter under deviations from the classical normal linear regression model, then on a flexible implementation framework giving rise to a number of functions for mainstream tests.
Uploads
Papers by Giovanni Millo