Beyond Univariate Measurement of Spatial Autocorrelation : Disaggregated Spillover Effects for Indonesia

Most studies that incorporate spatial effects use a very limited number of spatial variables in the growth model, e.g. growth spillovers or infrastructure impacts of neighbouring regions. This article innovates on previous work in spatial econometrics by differentiating among spatial contributions t...

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Main Authors:	Day, Jennifer, Lewis, Blane
Format:	Journal Article
Language:	en_US
Published:	Taylor and Francis 2013
Subjects:	spatial statistics spillovers economic growth Durbin representation
Online Access:	http://hdl.handle.net/10986/16186

id	okr-10986-16186
recordtype	oai_dc
spelling	okr-10986-161862021-04-23T14:03:27Z Beyond Univariate Measurement of Spatial Autocorrelation : Disaggregated Spillover Effects for Indonesia Day, Jennifer Lewis, Blane spatial statistics spillovers economic growth Durbin representation Most studies that incorporate spatial effects use a very limited number of spatial variables in the growth model, e.g. growth spillovers or infrastructure impacts of neighbouring regions. This article innovates on previous work in spatial econometrics by differentiating among spatial contributions to economic development; e.g. infrastructure, capital, human capital, land and labour. We explore whether including more spatial effects can improve the viability of a growth model, and also test the hypothesis that the differential spatial effects of various important predictor variables are discernible for Indonesia. We develop two econometric estimations based on the Durbin representation of the Spatial Error Model. We take advantage of a panel data set spanning Indonesia's post-decentralization years, 2003–2008. The first model uses a modified fixed effects formulation, and the second uses a maximum likelihood estimator. The two sets of models are reported together to serve as a check to the robustness of the results. Multiple estimation methods were attempted, including (to control for potential endogeneity) two-stage least squares (2SLS) and generalized method of moments (GMM). The findings suggest that various types of spillover effects affect a place by different processes, and accounting for this variety of processes in growth models improves the efficacy of those models. Our findings suggest that, for Indonesian districts, the influence of neighbours extends beyond GRDP per capita levels and growth, and also includes demographics, human capital and infrastructure components. We also demonstrate empirically that accounting for spatial effects in analysis of GRDP per capita can improve growth-model estimations. 2013-10-17T18:26:29Z 2013-10-17T18:26:29Z 2013-08-02 Journal Article Annals of GIS 1947-5683 http://hdl.handle.net/10986/16186 en_US CC BY-NC-ND 3.0 IGO http://creativecommons.org/licenses/by-nc-nd/3.0/igo/ World Bank Taylor and Francis Publications & Research :: Journal Article Publications & Research East Asia and Pacific Indonesia
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
language	en_US
topic	spatial statistics spillovers economic growth Durbin representation
spellingShingle	spatial statistics spillovers economic growth Durbin representation Day, Jennifer Lewis, Blane Beyond Univariate Measurement of Spatial Autocorrelation : Disaggregated Spillover Effects for Indonesia
geographic_facet	East Asia and Pacific Indonesia
description	Most studies that incorporate spatial effects use a very limited number of spatial variables in the growth model, e.g. growth spillovers or infrastructure impacts of neighbouring regions. This article innovates on previous work in spatial econometrics by differentiating among spatial contributions to economic development; e.g. infrastructure, capital, human capital, land and labour. We explore whether including more spatial effects can improve the viability of a growth model, and also test the hypothesis that the differential spatial effects of various important predictor variables are discernible for Indonesia. We develop two econometric estimations based on the Durbin representation of the Spatial Error Model. We take advantage of a panel data set spanning Indonesia's post-decentralization years, 2003–2008. The first model uses a modified fixed effects formulation, and the second uses a maximum likelihood estimator. The two sets of models are reported together to serve as a check to the robustness of the results. Multiple estimation methods were attempted, including (to control for potential endogeneity) two-stage least squares (2SLS) and generalized method of moments (GMM). The findings suggest that various types of spillover effects affect a place by different processes, and accounting for this variety of processes in growth models improves the efficacy of those models. Our findings suggest that, for Indonesian districts, the influence of neighbours extends beyond GRDP per capita levels and growth, and also includes demographics, human capital and infrastructure components. We also demonstrate empirically that accounting for spatial effects in analysis of GRDP per capita can improve growth-model estimations.
format	Journal Article
author	Day, Jennifer Lewis, Blane
author_facet	Day, Jennifer Lewis, Blane
author_sort	Day, Jennifer
title	Beyond Univariate Measurement of Spatial Autocorrelation : Disaggregated Spillover Effects for Indonesia
title_short	Beyond Univariate Measurement of Spatial Autocorrelation : Disaggregated Spillover Effects for Indonesia
title_full	Beyond Univariate Measurement of Spatial Autocorrelation : Disaggregated Spillover Effects for Indonesia
title_fullStr	Beyond Univariate Measurement of Spatial Autocorrelation : Disaggregated Spillover Effects for Indonesia
title_full_unstemmed	Beyond Univariate Measurement of Spatial Autocorrelation : Disaggregated Spillover Effects for Indonesia
title_sort	beyond univariate measurement of spatial autocorrelation : disaggregated spillover effects for indonesia
publisher	Taylor and Francis
publishDate	2013
url	http://hdl.handle.net/10986/16186
_version_	1764432433085677568

Beyond Univariate Measurement of Spatial Autocorrelation : Disaggregated Spillover Effects for Indonesia

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