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

Ann Reg Sci (2016) 56:1–31 DOI 10.1007/s00168-015-0706-9 ORIGINAL PAPER Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models Guilherme Mendes Resende1 · Alexandre Xavier Ywata de Carvalho1 · Patrícia Alessandra Morita Sakowski1 · Túlio Antonio Cravo2 Received: 8 March 2013 / Accepted: 31 August 2015 / Published online: 9 December 2015 © The Author(s) 2015. This article is published with open access at Springerlink.com 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. B Guilherme Mendes Resende Túlio Antonio Cravo 1 Institute for Applied Economic Research (IPEA)/Government of Brazil, Brasília 70076-900, Brazil 2 United Nations University, World Institute for Development Economics Research (UNU-WIDER), Helsinki, Finland 123 2 JEL Classification G. M. Resende et al. C23 · O18 · R11 1 Motivation The goal of this paper was to evaluate the results of regional economic growth estimates at multiple spatial scales using alternative spatio-temporal models recently proposed in the spatial econometrics literature. During the last two decades, an increasing dissemination of spatial econometrics techniques has been observed among regional scientists, economists, and researchers in several fields (Anselin 1988; Lesage 1999; Conley 1999). The vast research of applied spatial econometrics on the interdependencies among spatial units and their effects on, among others, regional economic growth, trade flows, knowledge spillovers, migration, housing prices, tax interactions, and city’s growth controls1 is well known. However, this literature still lacks a better understanding of the potential reasons why models estimated at different geographic scales yield different results in the context of regional economic growth empirics.2 Resende (2011) engages in an initial discussion on the determinants of Brazil’s regional economic growth at a variety of geographic scales using a cross-sectional data set over the 1990s period. Resende (2013) improves this analysis by using standard panel data models across several spatial scales, but the process of economic growth in Brazil is only examined using non-spatial panel data models. This investigation refers back to the modifiable areal unit problem (MAUP),3 but it sheds new light on a core problem in the literature related to regional economic growth by estimating models that are able to provide more insights about different spatial spillover effects due to changes in the spatial scale. The choice of the spatial scale of analysis is a problematic issue in applied research (Behrens and Thisse 2007). This paper seeks to investigate the extent to which ambiguities about spatial scale undermine, or inform, our understanding of regional growth determinants and convergence. With the exception of Resende (2011, 2013) and Resende and Cravo (2014)4 studies thus far have only investigated the determinants of economic growth at a single spatial scale to infer the consistency of spatial growth models with reality (e.g., Rey and Montouri 1999; Fingleton 1999; López-Bazo et al. 2004; Ertur and Koch 2007; Elhorst 2010; Fischer 2011). For instance, Elhorst (2010) employ spatial econometric techniques to focus on time–space models, but they only examine the process of economic growth at a single spatial scale. To our knowledge, this is the first study of regional economic growth exploring both time and different spatial scale dimensions in the context of spatial panel data models. 1 See, for instance, Azzoni (2001), López-Bazo et al. (2004), Gamboa (2010), Fischer et al. (2009), Lesage and Fischer (2008), Jeanty et al. (2010) Gérard et al. (2010) and Brueckner (1998). 2 It is worth noting that there is growing empirical literature analyzing MAUP in several areas of urban and regional economics such as Yamamoto (2008), Briant et al. (2010), Fingleton (2011) and Menon (2012). 3 MAUP is associated with the uncertainties between choice of an alternative number of zones (or zoning systems) and the implications that this holds for spatial analysis (Openshaw and Taylor 1981). 4 Of note, Ávila and Monastério (2008) analyze MAUP on per capita income convergence process in the Rio Grande do Sul state in Brazil using two geographic scales (municipalities and “Conselhos Regionais de Desenvolvimento”/COREDEs). 123 Evaluating multiple spatial dimensions of economic growth. . . 3 The idea of this paper is to systematically repeat a spatial panel data model originally developed to examine this phenomenon at a single geographic scale across multiple scales. The spatial scales examined are minimum comparable areas (referred to as municipalities), microregions, mesoregions and states, which are often employed in the empirical literature about Brazil and cover the period between 1970 and 2000.5 Initially, this approach led us to the investigation of the measurement issue that might cause variability in regional economic growth estimates due to the use of different spatial scales, likely due to the MAUP. However, it is important to bear in mind that structural (theory based) issues may be underlying economic growth at different scales; thus, we provide theoretical arguments for such variability in empirical results found across different geographic scales.6 The paper is organized as follows. Section 2 discusses the potential theoretical reasons for different results found across economic growth mod (...truncated)