Measuring spatial effects in the presence of institutional constraints: The case of Italian Local Health Authority expenditure

被引:32
作者
Atella, Vincenzo [1 ,2 ,3 ]
Belotti, Federico [2 ]
Depalo, Domenico [4 ]
Mortari, Andrea Piano [2 ]
机构
[1] Dept Econ & Finance, I-00133 Rome, Italy
[2] CEIS Tor Vergata, I-00133 Rome, Italy
[3] Stanford Univ, CHP PCOR Stanford Univ, Stanford, CA 94305 USA
[4] Bank Italy, I-00184 Rome, Italy
关键词
Spatial; Health expenditures; Institutional setting; Panel data; MODEL; IDENTIFICATION; INFERENCE; GROWTH;
D O I
10.1016/j.regsciurbeco.2014.07.007
中图分类号
F [经济];
学科分类号
02 ;
摘要
Over the last deeades spatial econometric models have represented a common tool for measuring spillover effects across different geographical entities (counties, provinces, regions or nations). The aim of this paper is to investigate the issue of measuring spatial spillovers in the presence of institutional constraints that can be geographically defined. In these cases, assuming that spatial effects are not affected by the institutional setting may produce biased estimates due to the composition of twodistinct sources of spatial dependence. Our approach is based on redefining the contiguity structure so as to account for the institutional constraints using two different contiguity matrices: the within matrix, which defines contiguity among units obeying the same institutional setting, and the between matrix, which traces spatial linkages among contiguous units across different jurisdictions. This approach allows to disentangle the two sources of spatial correlation and to easily test for the existence of binding institutional constraints. From the econometric perspective, we extend Lacombe (2004) approach to incorporate the aforementioned institutional constraints in a spatial Durbin model with individual specific slopes, while inference is conducted using a two-way cluster robust variance-covariance matrix controlling for both spatial and time correlations. We apply this methodology to analyze spatial dependence of per-capita public health expenditures in Italyat Local Health Authority level using a balanced panel dataset from 2001 to 2005. Our results show robust evidence of a significant and positive spatial coefficient for the within effect, while the between effect, although significant, is very close to zero, thus confirming the importance and validity of the proposed approach. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:232 / 241
页数:10
相关论文
共 42 条
[1]   Spatial externalities, spatial multipliers, and spatial econometrics [J].
Anselin, L .
INTERNATIONAL REGIONAL SCIENCE REVIEW, 2003, 26 (02) :153-166
[2]   Institutions and geography: Empirical test of spatial growth models for European regions [J].
Arbia, Giuseppe ;
Battisti, Michele ;
Di Vaio, Gianfranco .
ECONOMIC MODELLING, 2010, 27 (01) :12-21
[3]  
Atella V., 2014, POLITICHE SANITARIE, V15, P11
[4]  
Barreira A., 2011, SPATIAL ORG DYNAMICS, V2011-2
[5]  
Bartolucci F., 2013, WORKING PAPERS SERIE, P1312
[6]   How much should we trust differences-in-differences estimates? [J].
Bertrand, M ;
Duflo, E ;
Mullainathan, S .
QUARTERLY JOURNAL OF ECONOMICS, 2004, 119 (01) :249-275
[7]   Bailing out expectations and public health expenditure [J].
Bordignon, Massimo ;
Turati, Gilberto .
JOURNAL OF HEALTH ECONOMICS, 2009, 28 (02) :305-321
[8]   Identification of peer effects through social networks [J].
Bramoulle, Yann ;
Djebbari, Habiba ;
Fortin, Bernard .
JOURNAL OF ECONOMETRICS, 2009, 150 (01) :41-55
[9]   Multimodel inference - understanding AIC and BIC in model selection [J].
Burnham, KP ;
Anderson, DR .
SOCIOLOGICAL METHODS & RESEARCH, 2004, 33 (02) :261-304
[10]   Robust Inference With Multiway Clustering [J].
Cameron, A. Colin ;
Gelbach, Jonah B. ;
Miller, Douglas L. .
JOURNAL OF BUSINESS & ECONOMIC STATISTICS, 2011, 29 (02) :238-249