Corrupção e Crescimento: os impactos da corrupção ponderados pelos diferentes graus de eficiência entre as firmas

Autores

  • Leonardo Andrade Rocha Universidade Federal Rural do Semi-Árido
  • Ahmad Saeed Khan Universidade Federal do Ceará
  • Patrícia Verônica Pinheiro Sales Lima Universidade Federal do Ceará
  • Maria Ester Soares Dal Poz Universidade Estadual de Campinas. Faculdade de Ciências Aplicadas

DOI:

https://doi.org/10.1590/0101-4161464782lapm

Palavras-chave:

eficiência, corrupção, desempenho, crescimento

Resumo

O presente estudo analisou os impactos da corrupção no crescimento das firmas conforme diferentes ‘graus’ de eficiência. Usando uma técnica não-paramétrica de escores de eficiência, foi estimado um modelo de regressão linear interagindo os diferentes escores com um índice de corrupção. Os resultados apontam que a corrupção apresenta impactos negativos nas firmas com baixa performance, ao contrário das firmas com alta performance. Nas firmas eficientes e com menor dominância o custo da corrupção na redução do crescimento das vendas é estatisticamente menor em comparação com as firmas com maior dominância. Tais resultados corroboram com importantes estudos destacando Batra, Kaufmann e Stone (2003), Wang e You (2012) e Jiang e Nie (2014).

Downloads

Não há dados estatísticos.

Biografia do Autor

Leonardo Andrade Rocha, Universidade Federal Rural do Semi-Árido

Doutor em Economia

Professor da Universidade Federal Rural do Semi-Árido

 

Ahmad Saeed Khan, Universidade Federal do Ceará

PhD em Economia

Bolsista pesquisadora do CNPq

Professor do Departamento de Economia Agrícola da Universidade Federal do Ceárá.

Patrícia Verônica Pinheiro Sales Lima, Universidade Federal do Ceará

Doutora em Economia Aplicada

Bolsista pesquisadora do CNPq

Professora do Departamento de Economia Agrícola da Universidade Federal do Ceárá.

 

 

Maria Ester Soares Dal Poz, Universidade Estadual de Campinas. Faculdade de Ciências Aplicadas

Docente da Faculdade de Ciências Aplicadas FCA, área de Administração e do Instituto de Economia - IE, UNICAMP. Pesquisadora e docente de pós-graduação na área de Economia Industrial e de Empresas, com foco em Gestão da Inovação.Tem doutorado em Política Científica e Tecnológica pela Universidade Estadual de Campinas (2006). Pós-doutorado no Centro de Desenvolvimento Tecnológico em Saúde, CDTS - FIOCRUZ (2007 e 2009), no desenvolvimento de ferramentas de gestão da inovação e Pós-doutorado (2009) no Instituto de Economia da UNICAMP.

Referências

ACEMOGLU, D., & VERDIER, T. The Choice between Market Failures and Corruption. American

Economic Review, 90(1), 194-211, 2000.

ACEMOGLU, D., AGHION, P., & ZILIBOTTI, F. Distance to Frontier, Selection and Economic Growth.

Journal of the European Economic Association, 4(1), 37–74, 2006.

ALEXEEV, M., & SONG, Y. Corruption and product market competition: An empirical investigation.

Journal of Development Economics, 103, 154–166, 2013.

ANDREWS, D., & BUCHINSKY, M. Evaluation of a Three-Step Method for Choosing the Number of Bootstrap Repetitions. Journal of Econometrics, 103(1-2), 345–386, 2001.

ANOKHIN, S., & SCHULZE, W. Entrepreneurship, innovation, and corruption. Journal of Business Venturing, 24, 465–476, 2009.

ARAGON, Y., DAOUIA, A., & THOMAS-AGNAN, C. Nonparametric Frontier Estimation : A Conditional Quantile-based Approach. Econometric Theory, 21(2), 358-389, 2005.

ASIEDU, E., & FREEMAN, J. The Effect of Corruption on Investment Growth: Evidence from Firms in Latin America, Sub-Saharan Africa, and Transition Countries. Review of Development Economics, 13(2), 200–214, 2009.

BADIN, L., & DARAIO, C. Explaining Efficiency in Nonparametric Frontier Models: Recent Developments

in Statistical Inference. In I. KEILEGOM, & P. WILSON (Eds.), Exploring Research

Frontiers in Contemporary Statistics and Econometrics (pp. 151-175 ). Heidelberg: Springer, 2012.

BADIN, L., DARAIO, C., & SIMAR, L. How to measure the impact of environmental factors in a

nonparametric production model. European Journal of Operational Research, 223, 818–833, 2014.

BAILEY, D. The effects of corruption in a developing nation. Western Political Quarterly, 19(4),

–732, 1966.

BANERJEE, A., MULLAINATHAN, S., & HANNA, R. Corruption. Cambridge, MA: National Bureau

of Economic Research, NBER Working Papers 17968, 2012.

BATRA, G., KAUFMANN, D., & STONE, A. Investment Climate Around the World: Voices of the

Firms from the World Business Environment Survey. Washington, DC: The World Bank, 2003.

BOGLIACINO, F. Innovation and employment: A firm level analysis with European R&D Scoreboard

data. EconomiA, v. 15, n. 2, p. 141-154, 2014.

BOGLIACINO, F.; CORDONA, S. G. The determinants of R&D Investment: the role of Cash flow and

Capabilities. European Commission’s Joint Research Centre (JRC). [S.l.], 2010.

CAMERON, A., & TRIVEDI, P. Microeconometrics: Methods and Applications. New York: Cambridge

University Press, 2005.

CAZALS, C., FLORENS, J., & SIMAR, L. Nonparametric frontier estimation: a robust approach.

Journal of Econometrics, 106, 1-25, 2002.

CHARNES, A., COOPER, W., & RHODES, E. Measuring the efficiency of decision making units.

European Journal of Operational Research, 2, 429–444, 1978.

COMMISSION, E. The 2013 EU Industrial R&D Investment Scoreboard.Acesso em 15 de jul de 2014,

disponível em Publications Office of the European Union: http://ipts.jrc.ec.europa.eu/, 2013.

DAOUIA, A., & SIMAR, L. Robust Nonparametric Estimators of Monotone Boundaries. Journal of

Multivariate Analysis, 96, 311–331, 2005.

DARAIO, C., & SIMAR, L. Introducing Environmental Variables in Nonparametric Frontier Models:

a Probabilistic Approach. Journal of Productivity Analysis, 24(1), 93-121, 2005.

DARAIO, C., & SIMAR, L. Advanced Robust and Nonparametric Methods in Efficiency Analysis.

Springer: New York, NY, 2007.

DEBREU, G. The coefficient of resource utilization. Econometrica, 19, 273–292, 1951.

DEPRINS, D., SIMAR, L., & TULKENS, H. Conditional nonparametric frontier models for convex and

nonconvex technologies: A unifying approach. Journal of Productivity Analysis, 28, 13–32, 1984.

DREHER, A., & GASSEBNER, M. Greasing the wheels of entrepreneurship? The impact of regulations

and corruption on firm entry. Zurich, Switzerland: Swiss Economic Institute - KOF, Working

paper nº 166, 2007.

EFRON, B. Bootstrapping Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1–26, 1979.

EFRON, B., & TIBSHIRANI, R.. An Introduction to the Bootstrap. New York: Chapman & Hall, 1993.

FARREL, J. The measurement of productive efficiency. Journal of the Royal Statistical Society, A 120,

–281, 1957.

FLORENS, J.-P., SIMAR, L., & KEILEGOM, I. Frontier estimation in nonparametric location-scale

models. Journal of Econometrics, 178, 456–470, 2014.

GARCΝA-MANJΣN, J. V.; ROMERO-MERINO, M. E. Research, development, and firm growth.

Empirical evidence from European top R&D spending firms. Research Policy, v. 41, n. 6, p.

- 1092, 2012.

GAVIRIA, A. Assessing the Effects of Corruption and Crime on Firm Performance: Evidence from

Latin America. Emerging Markets Review, 3, 245–68, 2002.

GREENE, W. Econometric Analysis (7ª ed.). Boston, MA: Prentice Hall, 2012.

HALLWARD-DRIEMEIER, M., WALLSTERN, S., & XU, L. The investment climate and the firm:

Firm-level evidence from China. Policy Research Working Paper 3003. The World Bank, 2004.

HUNTINGTON, S. Political order in changing societies. New Haven: Yale University Press, 1968.

JIANG, T., & NIE, H. The stained China miracle: Corruption, regulation, and firm performance. Economics

Letters, 123, 366–369, 2014.

KAUFMANN, D., & WEI, S.-J. Does ‘grease money’ speed up the wheels of commerce? Cambridge,

MA: National Bureau of Economic Research, NBER Working Paper No. 7093, 1999.

KAUFMANN, D., KRAAY, A., & MASTRUZZI, M. The Worldwide Governance Indicators: Methodology

and Analytical Issues. Policy Research Working Paper Series 5430. The World Bank, 2013.

KNEIP, A., SIMAR, L., & WILSON, P. Asymptotics for DEA Estimators in Nonparametric Frontier

Models. Institut de Statistique, UCL. Discussion Paper no. 0317, 2003.

KOENKER, R. Quantile Regression. New York: Cambridge University Press, 2005.

KOENKER, R., & HALLOCK, K. Quantile Regression. Journal of Economic Perspectives, 15(4),

-156, 2001.

KOOPMANS, C. An analysis of production as an efficient combination of activities. In T. KOOPMANS

(Ed.), Activity Analysis of Production and Allocation (pp. 33–97). New York: John-Wiley and

Sons, Inc, 1951.

KUMBHAKAR, S., PARK, B., SIMAR, L., & TSIONAS, E. Nonparametric stochastic frontiers: A local

maximum likelihood approach. Journal of Econometrics, 137(1), 1–27, 2007.

LAMBSDORFF, J. How Corruption Affects Productivity. International Review for Social Sciences,

(4), 459–476, 2003.

LAMBSDORFF, J. The Institutional Economics of Corruption and Reform: Theory, Evidence, and

Policy. New York: Cambridge University Press, 2007.

LEFF, N. Economic development through bureaucratic corruption. In A. HEIDENHEIMER, M.

JOHNSTON, & V. LEVINE, Political corruption: A handbook (pp. 389–403). Oxford, UK:

Transaction Books, 1964.

LIVANIS, G.; LAMIN, A. Knowledge, Proximity and R&D Exodus. Research Policy, v. 45, n. 1, p.

-26, 2016.

LUI, F. An equilibrium queuing model of bribery. Journal of Political Economy, 93(4), 760–781, 1985.

MÉNDEZ, F., & SEPÚLVEDA, F. Corruption, growth and political regimes: Cross country evidence.

European Journal of Political Economy, 22, 82–98, 2006.

MÉON, P., & SEKKAT, K. Does corruption grease or sand the wheels of growth? Public Choice, 122,

–97, 2005.

MÉON, P., & WEIL, L. Is corruption an efficient grease? World Development, 38(3), 244–259, 2010.

MOCAN, N. What Determines Corruption? International Evidence from Micro Data. Cambridge, MA:

National Bureau of Economic Research, NBER Working Paper No. 10460, 2004.

MONTRESOR, S.; VEZZANI, A. The production function of top R&D investors: Accounting for size

andsector heterogeneity with quantile estimations. Research Policy, v. 44, n. 2, p. 381-393, 2015.

ROSE-ACKERMAN, S. Corruption and Government: Causes, Consequences and Reform. Cambridge,

UK: Cambridge University Press, 1999.

SCHUMACHER, I. Political stability, corruption and trust in politicians. Economic Modelling, 31,

–369, 2013.

SCHWARZ, M., VAN BELLEGEM, S., & FLORENS, J.-P. Nonparametric Frontier Estimation from

Noisy Data. In I. KEILEGOM, & P. WILSON (Eds.), Exploring Research Frontiers in Contemporary

Statistics and Econometrics (pp. 45-64). Heidelberg: Springer, 2012.

SHLEIFER, A., & VISHNY, R. Corruption. The Quarterly Journal of Economics, 108(3), 599–617, 1993.

SIMAR, L., & WILSON, P. Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric

frontier models. Management Science, 44(1), 49-61, 1998.

SIMAR, L., & WILSON, P. Statistical Inference in Nonparametric Frontier Models: The State of the

Art. The Journal of Productivity Analysis, 13, 49-78, 2000a.

SIMAR, L., & WILSON, P. A general methodology for bootstrapping in non-parametric frontier models.

Journal of Applied Statistics, 27(6), 779-802, 2000b.

SIMAR, L., & WILSON, P. Estimation and Inference in Nonparametric Frontier Models: Recent Developments

and Perspectives. Foundations and Trends in Econometrics, 5(3–4), 183–337, 2013.

SMARZYNSKA, B., & WEI, S.-J. Corruption and Cross-Border Investment: Firm-Level Evidence.

NBER working paper W7969. Cambridge, MA: National Bureau of Economic Research, 2002.

SVENSSON, J. Who must pay bribes and how much? Evidence from a cross section of firms. Quarterly

Journal of Economics, 118(1), 207–230, 2003.

TANZI, V. Corruption around the world: causes, scope and cures. IMF Staff Papers, 45, 559–594, 1998.

TREISMAN, D. The causes of corruption: a cross-national study. Journal of Public Economics, 76(3),

–458, 2000.

WANG, Y., & YOU, J. Corruption and firm growth: Evidence from China. China Economic Review,

, 415–433, 2012.

WILSON, P. Asymptotic Properties of Some Non-Parametric Hyperbolic Efficiency Estimators. In I.

KEILEGOM, & P. WILSON (Eds.), Exploring Research Frontiers in Contemporary Statistics

and Econometrics (pp. 115-150). Heidelberg: Springer, 2012.

Downloads

Publicado

2020-10-19

Edição

Seção

Artigo