Doutora em Economia pela EESP-FGV, com estágio na Boalt Hall (Law School) da University of California, Berkeley (EUA); Mestre em Economia Aplicada e em Relações Industriais pela University of Wisconsin–Madison (EUA); Bacharel em Economia pela FEA-USP. Como pesquisadora, dedica-se à área da Análise Econômica do Direito (ou Law and Economics) e Estudos Empíricos em Direito. Tem artigos e capítulos em publicações nacionais e internacionais, entre eles: Journal of Institutional Economics, European Journal of Law and Economics, IMA Journal of Management Mathematics, Encyclopedia of Law and Economics (Ed. Springer), Estudos Econômicos, Economia Aplicada, Economic Analysis of Law Review, Revista de Estudos Empíricos em Direito, Revista de Estudos Institucionais, entre outros.
In this paper, we aim at empirically and quantitatively measuring the evolution of the efficiency of Brazilian State Courts. We use Data Envelopment Analysis (DEA) and the Malmquist Productivity Index to set up a data panel (2006 to 2018). The State Court of the State of São Paulo appeared to be the most efficient unit over the 3 years, even considering its size (numbers of new cases and pending cases). In this period, State Courts throughout the country had, on average, an annual evolution of 7.7% in Total Factor Productivity (TFP) and 24% in the evolution of Technical Efficiency. However, Technological Change had a negative result, and was responsible for “pulling down” the entire result of the (TFP). Despite the long path already taken by scientific research, and the long path already taken by courts themselves in managing their efficiency, much remains to be done.
References
Charnes, A., Cooper, W. W. & Rhodes, E. (1978) Measuring the efficiency of decision-making units. European Journal of Operational Research, v. 2, p. 429-444.
Conselho Nacional da Justiça (2019). Justiça em Números 2019. Brasília: CNJ. Disponível em https://www.cnj.jus.br/pesquisas-judiciarias/justica-em-numeros/
Cooper, W. W., Seiford, L. M., & Tone, K. (2007) Data Envelopment Analysis: a Comprehensive Text with Models, Applications, References and DEA-Solver Software. Second Edition. New York: Springer Science Business Media, LLC.
Dakolias, M. (1999) Court Performance around the World – A Comparative Perspective. World Bank Technical Paper No. 430. Washington DC: The World Bank.
Dalton, T. & Singer, J. (n.d.) Bigger isn’t always better: an analysis of court efficiency using hierarchical linear modeling. Disponível em: <www.ssrn.com/abstract=1133242>. Acessado em 07 março de 2021.
Daraio, C. & Simar, L. (2005) Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach. Journal of Productivity Analysis, v. 24, p. 93-121.
Freitas, V. P. (2003) Justiça Federal: Histórico e Evolução no Brasil. Curitiba: Juruá Editora.
Gomes, A. O. & Guimarães, T. A. (2013) Desempenho no Judiciário: conceituação, estado da arte e agenda de pesquisa. Revista de Administração Pública, v. 47, p. 379-401.
Grosskopf, S. (1996) Statistical Inference and Nonparametric Efficiency: A Selective Survey. Journal of Productivity Analysis, v. 7, p. 161–176.
Ostrom, B. J. & Hanson, R. A. (2000) Efficiency, timeliness, and quality: A new perspective from nine state criminal trial courts. US Department of Justice: Office of Justice Programs, National Institute of Justice.
Shephard, R. W. (1970) Theory of Cost and Production Functions. Princeton: Princeton University Press.
Simar, L. & Wilson, P. W. (1998) Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models. Management Science, v. 44, p. 49-61.
Simar, L. & Wilson, P. W. (2000) Statistical inference in nonparametric frontier models: the state of the art. Journal of Productivity Analysis, v. 13, p. 49-78.
Simar, L. & Wilson, P. W. (2001) Aplicación Del bootstrap con estimadores DEA. In Alvarez Pinilla, A. (Coord.). La medición de la eficiencia y productividad. Madrid: Ediciones Pirámide.
Simar, L. & Wilson, P. W. (2007) Estimation and Inference in two-stage semi-parametric models of production processes. Journal of Econometrics, v. 136, p. 31-64.
Souza, G. S. (2001) Statistical Properties of Data Envelopment Analysis Estimators of Production Functions. Brazilian Review of Econometrics, v. 21, p. 291-322.
Sousa, M. M. & Guimarães, T. A. (2017) The adoption of innovations in Brazilian labour courts from the perspective of judges and court managers. Revista de Administração, v. 52, p. 103-113.
Tavares, A. R. (2005) Reforma do Judiciário no Brasil Pós-88: (Des)estruturando a Justiça – Comentários completos à Emenda Constitucional n. 45/04. São Paulo: Editora Saraiva.
Voigt, S. (2016) Determinants of judicial efficiency: a survey. European Journal of Law and Economics, v. 42, p. 183-208.
Yeung, L. L. & Azevedo, P. F. (2011) Measuring efficiency of Brazilian courts with data envelopment analysis (DEA). IMA Journal of Management Mathematics, v. 22, p. 343-356.
Yeung, L. L. (2020) Measuring Efficiency of Brazilian Courts: one decade later, Revista de Direito Administrativo, v. 279, p.111-134.