... 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
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 ...
... 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
... 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
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 ...
... 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
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Papers by Giovanni Millo