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Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models

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  • Guilherme Resende

    ()

  • Alexandre Carvalho
  • Patrícia Sakowski
  • Túlio Cravo

    ()

Abstract

The goal of this paper is to evaluate the results of regional economic growth model estimations at multiple spatial scales using spatial panel data models. The spatial scales examined are minimum comparable areas, microregions, mesoregions and states between 1970 and 2000. Alternative spatial panel data models with fixed effects were systematically estimated across those spatial scales to demonstrate that the estimated coefficients change with the scale level. The results show that the conclusions obtained from growth regressions depend on the choice of spatial scale. First, the values of spatial spillover coefficients vary according to the spatial scale under analysis. In general, such coefficients are statistically significant at the MCA, microregional and mesoregional levels, however, at state level those coefficients are no longer statistically significant, suggesting that spatial spillovers are bounded in space. Moreover, the positive average-years-of-schooling direct effect coefficient increases as more aggregate spatial scales are used. Population density coefficients show that higher populated areas are harmful to economic growth, indicating that congestion effects are operating in all spatial scales, but their magnitudes vary across geographic scales. Finally, the club convergence hypothesis cannot be rejected suggesting that there are differences in the convergence processes between the north and south in Brazil. Furthermore, the paper discusses the potential theoretical reasons for different results found across estimations at different spatial scales. Copyright The Author(s) 2016

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  • Guilherme Resende & Alexandre Carvalho & Patrícia Sakowski & Túlio Cravo, 2016. "Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 1-31, January.
  • Handle: RePEc:spr:anresc:v:56:y:2016:i:1:p:1-31
    DOI: 10.1007/s00168-015-0706-9
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    Cited by:

    1. Bulent Esiyok & Mehmet Ugur, 2018. "Spatial dependence in the growth process and implications for convergence rate: evidence on Vietnamese provinces," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 23(1), pages 51-65, January.
    2. Alberto Díaz Dapena & Fernando Rubiera Morollón & Dusan Paredes Araya, 2017. "Are there different local patterns of convergence concealed beneath the regional level? An analysis for US states and counties using a multilevel approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(3), pages 623-640, May.

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    Keywords

    C23; O18; R11;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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