Convergence clubs among Brazilian municipalities

Andrade, Eduardo de Carvalho; Laurini, Márcio Poletti; Madalozzo, Regina; Pereira, Pedro L. Valls

doi:10.1016/j.econlet.2003.11.005

Cited by 36 publications

(20 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…As in the basic Solow-Swan model, the assumption of diminishing returns to the accumulable factors of production k and h yields convergence to a steady-state and the addition of the assumption of a common level of technology A implies that the steady state is common across countries. 14 The assumption of diminishing returns to human capital is justified by the observation that higher education is bounded from above and as well as by studies in labor economics finding that human capital's contribution to income is diminishing (see, e.g., Becker 1994). 15 Nonetheless, as a voluminous literature has shown, this is not clear at all with respect to productivity improvements stemming from technological innovation and adoption (see e.g., Schumpeter, 1950;Aghion and Howitt, 1992;Zeira, 1998).…”

Section: Theoretical Considerationsmentioning

confidence: 99%

What Remains of Cross-Country Convergence?

Johnson

Papageorgiou

2020

Journal of Economic Literature

195

116

View full text Add to dashboard Cite

We examine the record of cross-country growth over the past 50 years and ask if developing countries have made progress on closing income gap between their per capita incomes and those in the advanced economies. We conclude that, as a group, they have not and then survey the literature on absolute convergence with particular emphasis on that from the last decade or so. That literature supports our conclusion of a lack of progress in closing the income gap between countries. We close with a brief examination of the recent literature on cross-individual distribution of income which finds that, despite the lack of progress on cross country convergence, global inequality has tended to fall since 2000. (JEL E01, E13, O11, O47, F41, F62)

show abstract

Section: Theoretical Considerationsmentioning

confidence: 99%

What Remains of Cross-Country Convergence?

Johnson

Papageorgiou

2020

Journal of Economic Literature

195

116

View full text Add to dashboard Cite

show abstract

“…Indeed, there is growing evidence that the club convergence hypothesis is the correct one for the Brazilian case. Classifying regions into similar groups (or clubs) has been the approach adopted in recent studies (Andrade et al 2004;Laurini et al 2005;Coelho and Figueiredo 2007;Cravo 2010; Resende 2011;Cravo and Resende 2013;Cravo et al 2015). Moreover, the variability of conditional β-convergence coefficients due to the geographic scale of analysis seems to be small using fixed effects models.…”

mentioning

confidence: 99%

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

et al. 2015

View full text Add to dashboard Cite

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. JEL Classification C23 · O18 · R11 MotivationThe 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 controls 1 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 s...

show abstract

“…Furthermore, it is worth noting that the club convergence hypothesis cannot be ruled out given the growing evidence that this hypothesis is the correct one for the Brazilian case [3,42,44,88]. Interestingly, as noted by Islam [1] "instead of adopting the panel data approach, the other way to control for differences in technology and institutions is to classify the countries into similar groups. "…”

Section: Resultsmentioning

confidence: 99%

Spatial Dimensions of Economic Growth in Brazil

Resende

2013

ISRN Economics

View full text Add to dashboard Cite

The contribution of this paper is to explore time and spatial scale dimensions of economic growth in Brazil using alternative panel data techniques to provide a measure of the extent of spatial autocorrelation (in kilometres) over three decades as well as discussing the determinants of economic growth at a variety of geographic scales (minimum comparable areas, microregions, meso-regions, and states). The magnitude and statistical significance of growth determinants such as schooling, population density, population growth, and transportation costs are dependent on the scale of analysis. Moreover, the extent of residual spatial autocorrelation showed that it seems to vary across spatial scales. Indeed, spatial autocorrelation seems to be bounded at the state level and it shows positive and statistically significant values across distances of more than 1,500 kilometres at the other three spatial scales. Among other results, the study suggests that the nonspatial panel data techniques are not able to deal with spatially correlated omitted variables across different spatial scales, except for the state level where nonspatial panel data models seem to be appropriate to investigate growth determinants and convergence process in the Brazilian states case.

show abstract

Convergence clubs among Brazilian municipalities

Cited by 36 publications

References 6 publications

What Remains of Cross-Country Convergence?

What Remains of Cross-Country Convergence?

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

Spatial Dimensions of Economic Growth in Brazil

Contact Info

Product

Resources

About