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Measuring the aggregate effects of the Brazilian Development Bank on investment

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  • de Menezes Barboza, Ricardo
  • Vasconcelos, Gabriel F.R.

Abstract

In this paper, we show that the Brazilian Development Bank (BNDES), one of the largest development banks in the world, had a positive and statistically significant impact on Brazilian aggregate investment during the 2002–2016 period. Each $1 BRL of BNDES loans increased the investment on average by $0.46 BRL. Our results lie between what is alleged by BNDES critics (zero impact) and what is claimed by unconditional advocates of state-owned banks (impact near one). In addition, our results are compatible with micro evidence on the effects of BNDES. We obtained these results using the impulse responses from a large Bayesian VAR and we used double selection inference for robustness.

Suggested Citation

  • de Menezes Barboza, Ricardo & Vasconcelos, Gabriel F.R., 2019. "Measuring the aggregate effects of the Brazilian Development Bank on investment," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 223-236.
  • Handle: RePEc:eee:ecofin:v:47:y:2019:i:c:p:223-236
    DOI: 10.1016/j.najef.2018.12.013
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    1. Gutierrez, Eva & Rudolph, Heinz P. & Homa, Theodore & Beneit, Enrique Blanco, 2011. "Development banks : role and mechanisms to increase their efficiency," Policy Research Working Paper Series 5729, The World Bank.
    2. Levy Yeyati, Eduardo & Micco, Alejandro & Panizza, Ugo, 2004. "Should the Government Be in the Banking Business?: The Role of State-Owned and Development Banks," IDB Publications (Working Papers) 1543, Inter-American Development Bank.
    3. Bonomo, Marco & Brito, Ricardo D. & Martins, Bruno, 2015. "The after crisis government-driven credit expansion in Brazil: A firm level analysis," Journal of International Money and Finance, Elsevier, vol. 55(C), pages 111-134.
    4. de Aghion, Beatriz Armendariz, 1999. "Development banking," Journal of Development Economics, Elsevier, vol. 58(1), pages 83-100, February.
    5. Danilo Santa Cruz Coelho & João Alberto De Negri, 2011. "Impacto Do Financiamento Do Bndes Sobrea Produtividade Das Empresas: Uma Aplicação Do Efeito Quantílico Detratamento," Anais do XXXVIII Encontro Nacional de Economia [Proceedings of the 38th Brazilian Economics Meeting] 119, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    6. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
    7. Oliveira, Fernando Nascimento, 2019. "Investment of Firms in Brazil: Do Financial Restrictions, Unexpected Monetary Shocks and BNDES Play Important Roles?," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 73(2), June.
    8. António Antunes & Tiago Cavalcanti & Anne Villamil, 2015. "The effects of credit subsidies on development," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 58(1), pages 1-30, January.
    9. Gianmarco I. P. Ottaviano & Filipe Lage de Sousa, 2014. "Relaxing Credit Constraints in Emerging Economies: The Impact of Public Loans on the Performance of Brazilian Manufacturers," Development Working Papers 369, Centro Studi Luca d'Agliano, University of Milano, revised 26 Jun 2014.
    10. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    11. Claudio Frischtak & Ceyla Pazarbasioglu & Steen Byskov & Adriana Hernandez Perez & Igor Andre Carneiro, 2017. "Towards a More Effective BNDES," World Bank Publications - Reports 28398, The World Bank Group.
    12. Han, Xu, 2015. "Tests for overidentifying restrictions in Factor-Augmented VAR models," Journal of Econometrics, Elsevier, vol. 184(2), pages 394-419.
    13. Fernando N. de Oliveira, 2014. "Investment of Firms in Brazil: do financial restrictions, unexpected monetary shocks and BNDES play important roles?," Working Papers Series 366, Central Bank of Brazil, Research Department.
    14. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    15. Lazzarini, Sergio G. & Musacchio, Aldo & Bandeira-de-Mello, Rodrigo & Marcon, Rosilene, 2015. "What Do State-Owned Development Banks Do? Evidence from BNDES, 2002–09," World Development, Elsevier, vol. 66(C), pages 237-253.
    16. J. Bradford De Long & Lawrence H. Summers, 1991. "Equipment Investment and Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(2), pages 445-502.
    17. J. Bradford DeLong & Lawrence H. Summers, 1992. "Equipment Investment and Economic Growth: How Strong Is the Nexus?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 23(2), pages 157-212.
    18. Kornai, J, 1979. "Resource-Constrained versus Demand-Constrained Systems," Econometrica, Econometric Society, vol. 47(4), pages 801-819, July.
    19. Rafael La Porta & Florencio Lopez‐De‐Silanes & Andrei Shleifer, 2002. "Government Ownership of Banks," Journal of Finance, American Finance Association, vol. 57(1), pages 265-301, February.
    20. Reichlin, Lucrezia & Giannone, Domenico & De Mol, Christine, 2006. "Forecasting Using a Large Number of Predictors: Is Bayesian Regression a Valid Alternative to Principal Components?," CEPR Discussion Papers 5829, C.E.P.R. Discussion Papers.
    21. Rodrik, Dani, 2004. "Industrial Policy for the Twenty-First Century," CEPR Discussion Papers 4767, C.E.P.R. Discussion Papers.
    22. Filipe Lage De Sousa & Gianmarco Ottaviano, 2014. "Relaxing Credit Constraints In Emergingeconomies: The Impact Of Public Loans On The Performance Of Brazilianfirms," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 128, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    23. Ades, Alberto & Di Tella, Rafael, 1997. "National Champions and Corruption: Some Unpleasant Interventionist Arithmetic," Economic Journal, Royal Economic Society, vol. 107(443), pages 1023-1042, July.
    24. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "Inference on Treatment Effects after Selection among High-Dimensional Controlsâ€," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(2), pages 608-650.
    25. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    26. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
    27. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    28. Francisco Buera & Benjamin Moll & Yongseok Shin, 2013. "Well-Intended Policies," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 16(1), pages 216-230, January.
    29. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    30. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?," Journal of Econometrics, Elsevier, vol. 146(2), pages 318-328, October.
    31. Cavalcanti, Tiago & Vaz, Paulo Henrique, 2017. "Access to long-term credit and productivity of small and medium firms: A causal evidence," Economics Letters, Elsevier, vol. 150(C), pages 21-25.
    32. Mara Faccio, 2006. "Politically Connected Firms," American Economic Review, American Economic Association, vol. 96(1), pages 369-386, March.
    33. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
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