Agglomeration Externalities and 1981-2006 Regional Growth in Brazil

Matlaba, Valente José; Holmes, Mark J.; McCann, Philip; Poot, Jacques

doi:10.2457/srs.42.145

Cited by 5 publications

(6 citation statements)

References 20 publications

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“…Both laws, however, are expected to hold at high levels of development. Our conclusions are consistent with theories that argue that increasing returns to scale arise as a result of agglomeration of economic activities (see, e.g., Matlaba et al, for a Brazil‐focused discussion).…”

Section: Resultssupporting

confidence: 92%

A Century of the Evolution of the Urban System in Brazil

Matlaba

Holmes

McCann

et al. 2013

Rev Urban & Reg Develop

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In this paper, we study the hitherto unexplored evolution of the size distribution of 185 urban areas in Brazil between 1907 and 2008. We find that the power law parameter of the size distribution of the 100 largest urban areas increases from 0.63 in 1907 to 0.89 in 2008, which confirms an agglomeration process in which the size distribution has become more unequal. A panel fixed effects model pooling the same range of urban size distributions provides a power law parameter equal to 0.53, smaller than those from cross-sectional estimation. Clearly, Zipf's Law is rejected. The lognormal distribution fits the city size distribution quite well until the 1940s, but since then applies to small and medium size cities only. These results are consistent with our understanding of historical-political and socio-economic processes that have shaped the development of Brazilian cities.

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Section: Resultssupporting

confidence: 92%

A Century of the Evolution of the Urban System in Brazil

Matlaba

Holmes

McCann

et al. 2013

Rev Urban & Reg Develop

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“…The choice of geographical and industrial unit of analysis is another important issue when anlaysing dynamic agglomeration externalities (Beaudry & Schiffauerova, 2009;Matlaba, Holmes & McCann, 2012). This paper uses 'state' as a geographical unit of analysis.…”

Section: Related Literaturementioning

confidence: 99%

“…The externalities could be properly measured at more disaggregated levels but due to data constraints, the present study restricts the analysis to 'state' level. There are many empirical studies that have studied dynamic externalities at the state/provincial level (e.g., Batisse, 2002;Gao, 2004;Matlaba et al, 2012). This paper takes a 'two-digit industry' of the manufacturing sector as an industrial unit of analysis.…”

Section: Related Literaturementioning

confidence: 99%

Dynamic Externalities and Regional Manufacturing Growth: Evidence from India

Sharma¹

2017

Studies in Business and Economics

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Using Annual Survey of Industries (ASI) dataset for 11 two-digit manufacturing industries and 20 states, this paper tests the relationship between dynamic agglomeration externalities and regional manufacturing growth for India. Three types of dynamic externalities have been proposed in the literature for explaining this relationship – Marshall-Arrow-Romer (MAR) specialization externalities, Jacobs’s diversity externalities, and Porter’s competition externalities. This paper examines the effect of these dynamic externalities on regional manufacturing employment and total factor productivity (TFP) growth for selected Indian industries between 2001-02 and 2011-12. The panel data model results show that dynamic externalities are important in influencing employment growth but they do not seem to have an impact on the growth of manufacturing productivity. Further, the results show that specialization externalities positively affect the employment growth of capital-intensive industries whereas diversity externalities favourably affect the employment growth in labour-intensive industries. Our results suggest that the importance of dynamic externalities should not be examined by pooling all industries. The results also highlight the importance of infrastructural investments for boosting the growth of manufacturing employment and productivity.

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“…The results show that the externalities caused by industrial specialization among industries make up one of the explicative factors of manufacturing employment growth during 1988-1993. Matlaba et al (2012) employed the Glaeser et al (1992) approach to identify the role played by knowledge externalities in manufacturing employment growth and convergence across 26 states of Brazil. They found diverse results depending on the model specification.…”

Section: Agglomeration Economies Externalities and Regional Growth: mentioning

confidence: 99%

Industrial structure and total factor productivity: the Tunisian manufacturing sector between 1998 and 2004

Thabet¹

2015

Ann Reg Sci

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Using a panel of manufacturing firms operating in 138 delegations across the Tunisian coast and observed over the 1998-2004 period, we study the impact of industrial structure on regional economic growth measured by total factor productivity. The results of an unbalanced panel data-based model indicate that the diversity of the industrial scene seems to be a local growth-promoting factor for high-tech sectors. Specialization often articulates the impact of diversity, while competition positively affects productivity. JEL Classification

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Agglomeration Externalities and 1981-2006 Regional Growth in Brazil

Cited by 5 publications

References 20 publications

A Century of the Evolution of the Urban System in Brazil

A Century of the Evolution of the Urban System in Brazil

Dynamic Externalities and Regional Manufacturing Growth: Evidence from India

Industrial structure and total factor productivity: the Tunisian manufacturing sector between 1998 and 2004

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