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Path-Dependent Dynamics and Technological Spillovers in the Brazilian Regions

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Abstract

This article investigates the influence of path dependence, of spatial spillovers and of production specialization on regional technological specialization. We use patent data and characteristics of industrial activity by Brazilian regions in the period of 2000–2011 to estimate a spatial dynamic panel using the Generalised Method of Moment (GMM) estimator, which deals with unobserved fixed effects and with the endogeneity problem. The results show that the regional production specialization influences technological specialization in Brazilian regions. Furthermore, this article finds that regional technological development is highly path-dependent and characterized by spatial spillovers. The former result means that regional technological development is influenced by its own technological specialization trajectory. The latter shows that the technological specialization of the neighborhood has proved to be a determining factor in local technological specialization. These results may help in the understanding of the development of technological clusters, suggesting that the strategies to reinforce the regional innovation processes should consider the specificities of the regional production pattern.

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Notes

  1. Non-patent sectors such as computer programming, consultancy and related activities and information service accounted for 4.9% out of the total of employment in the manufacturing industries and KIBS sector in Brazil in 2010, while low and high intensity technological sectors, respectively, were responsible for 78.7 and 16.1% of this total.

  2. The Queen contiguity matrix assumes the value 1 if the regions are contiguous and 0 otherwise. The elements of the diagonal are equal to zero and the matrix is row-normalized, so that the sum of each row is equal to unity (Anselin 1988). Other matrices of spatial weights were tested, however, the results remained stable, corroborating the evidence found by LeSage and Pace (2014).

  3. The following alternative estimates have been made and are available upon request to the authors: (i) all variables as endogenous: the Hansen test and the C Test indicate that the instruments are no longer orthogonal, rendering the results unreliable; (ii) only employment density as exogenous: results were close to those presented here.

  4. The C Test (difference-in-Hansen) indicates that the set of instruments formed by lags > 2 of the spatial lag is not orthogonal to the error; so the instruments were used from the third lag of this variable. Specifications were estimated considering different groups of instruments for all variables, but the tests did not guarantee their reliability.

  5. There was a 1.1% reduction in the initial total number of patents, totaling 72,989 patents used because there were patents whose sum of the weights assigned by the MERIT table was less than 1 or did not contain information on the IPC code, making it impossible to assign it to the corresponding production sector.

  6. The characteristics of the patenting process in Brazil compared to the standard in developed countries can be found in Albuquerque (2000).

  7. The coefficient of the time lag of TS is greater than that estimated by fixed effect and smaller than that estimated by OLS (results not presented here), considering the informal test of suitability of the estimator proposed by Bond (2002) and Roodman (2006).

  8. Roodman (2009, p.142) recommends a p-value of at least 0.25 instead of the conventional 0.05 or 0.10 for non-rejection of the null hypothesis of exogeneity of the instruments in the Hansen test.

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Acknowledgments

The authors gratefully acknowledge the support of research funding agencies such as the National Council for Scientific and Technological Development (CNPq), the Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES) and the Minas Gerais State Research Foundation (FAPEMIG). We are also grateful to INPI team by the patent database.

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  1. Department of Economics / Territorial and Sectorial Analysis Laboratory (LATES), Federal University of Juiz de Fora, Rua José Lourenço Kelmer s/n, Universidade Federal de Juiz de Fora, Faculdade de Economia, Campus Universitário, Juiz de Fora, MG, Brazil

    Eduardo Gonçalves, Cirlene Maria de Matos & Inácio Fernandes de Araújo

  2. Instituto de Ciências Sociais Aplicadas (ICSA) da Universidade Federal de Alfenas (UNIFAL-MG), Avenida Celina Ferreira Ottoni, 4000, Padre Vitor, Varginha, MG, CEP: 37048-395, Brazil

    Cirlene Maria de Matos

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  1. Eduardo Gonçalves
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Correspondence to Eduardo Gonçalves.

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Cirlene Maria de Matos declares that she has no conflict of interest. Prof. Eduardo Gonçalves has received research grants from FAPEMIG and CNPq. Inácio Fernandes de Araújo Junior declares that he has no conflict of interest.

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Gonçalves, E., de Matos, C.M. & de Araújo, I.F. Path-Dependent Dynamics and Technological Spillovers in the Brazilian Regions. Appl. Spatial Analysis 12, 605–629 (2019). https://doi.org/10.1007/s12061-018-9259-5

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