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Research infrastructures in less developed countries: the Brazilian case

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Abstract

High quality research infrastructure is required to conduct S&T activities which may help to address national challenges and contribute to innovation processes. Given this, an exhaustive survey conducted by the Brazilian Institute of Applied Economic Research (Instituto de Pesquisa Econômica Aplicada) was undertaken to diagnose the current research infrastructure situation in Brazil. Using this data, the present paper provides information that allows us to yield new insights based on the peculiarities of the research infrastructure in Brazil, complementing the studies already present in the literature. Two econometric models—logit and probit—were used to “measure” the relative modernity of the research infrastructure in the country. We test the impact of variables frequently present in innovation studies—lab size, S&T production scale and scope, lab longevity and interactions with other labs and profit-seeking firms. We found that scaling up, modernizing and interacting with other agents of the innovation system increase the chances of a research infrastructure to be considered “advanced”.

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Notes

  1. “National System of Political Economy”.

  2. “Theory of Economic Development” and “Capitalism, Socialism, and Democracy”.

  3. https://www.economist.com/the-americas/2011/01/06/go-south-young-scientist.

  4. Centro Brasileiro de Pesquisas Físicas—CBPF.

  5. Comissão Nacional de Energia Nuclear—CNEN.

  6. Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPq.

  7. Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Capes.

  8. Financiadora de Estudos e Projetos—FINEP.

  9. Fundações de Amparo à Pesquisa —FAPEs.

  10. Ministério da Ciência e Tecnologia—MCT and today Ministério da Ciência, Tecnologia, Inovações e Comunicações—MCTIC.

  11. For simplicity, “research infrastructure” is exchangebely called “lab” throughout this paper and both have the same meaning for us.

  12. Those methodological procedures were described by De Negri and De Squeff (2016).

  13. As argued by De Negri and De Squeff (2016), it not seems a limitation since Crow and Bozeman (1998) were able to identify approximately 15,000 infrastructures in United States.

  14. Empresa Brasileira de Pesquisa Agropecuária—Embrapa.

  15. Aeronautics Institute of Technology (Instituto Tecnológico de Aeronáutica—ITA), Aeronautics and Space Institute (Instituto de Aeronáutica e Espaço—IAE) and Advanced Studies Institute (Instituto de Estudos Avançados—IEAv).

  16. An ordered Probit/Logit model would be preferred by some researchers to perform the empirical analysis. However, our methodological choice lies upon the flexibility of comparison. When applying two distinct models (either Probit or Logit), one can observe different values of coefficients when comparing the three groups of dependent variables (insufficient, sufficient and advanced research infrastructures). If ordered model (either Logit or Probit) were chosen, the resulting coefficient would be just one, the result of comparison of two groups against one group (for example, insufficient and sufficient against advanced or advanced and sufficient against insufficient). Notwithstanding that, the results for ordered Probit and ordered Logit models are presented in the Table 10 (in the “Appendix”) for robustness check.

  17. Centro de Tecnologias Estratégicas do Nordeste—CETENE.

  18. Instituto Nacional do Semiárido—INSA.

  19. Universidade Federal do Recôncavo da Bahia—UFRB.

  20. Universidade Federal da Grande Dourados—UFGD.

  21. Results for multicollinearity test are presented in Table 10 (“Appendix”).

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Acknowledgments

The opinions expressed herein are those of the authors alone. They do not necessarily reflect the views of, or involve any responsibility on the part of, the institutions to which the authors are affiliated. Very early versions of this article were presented at the XVIII Congreso Latino-Iberoamericano de Gestión Tecnológica (ALTEC), Medellin (Colombia) and at the IV Encontro Nacional de Economia Industrial e Inovação (ENEI), Campinas (Brazil). Authors would like to thank Instituto de Pesquisa Econômica Aplicada (IPEA) for making available the data from the survey regarding the research infrastructure in Brazil.

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Authors and Affiliations

  1. Instituto Tecnológico de Aeronáutica (ITA), São José dos Campos, Brazil

    Thiago Caliari

  2. Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil

    Márcia Siqueira Rapini

  3. Instituto Nacional de Tecnologia (INT), Rio de Janeiro, Brazil

    Tulio Chiarini

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  1. Thiago Caliari
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  2. Márcia Siqueira Rapini
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  3. Tulio Chiarini
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Correspondence to Tulio Chiarini.

Appendix

Appendix

See Tables 10, 11, 12.

Table 10 Logit ordered model and probit ordered models.
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Table 11 Multicollinearity test for dependent variables.
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Table 12 Alternative econometric models.
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Caliari, T., Rapini, M.S. & Chiarini, T. Research infrastructures in less developed countries: the Brazilian case. Scientometrics 122, 451–475 (2020). https://doi.org/10.1007/s11192-019-03245-2

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