Resumo
Este artigo tem o objetivo de analisar a diferença no desempenho dos alunos de escolas brasileiras públicas e privadas, a partir da análise de Identificação Parcial ou Limites introduzida por Manski (1989). No contexto do forte viés de seleção decorrente de fatores socioeconômicos, a comparação com as estimativas da metodologia de Pareamento no Escore de Propensão e a tradicional análise de regressão busca verificar se os limites estimados sob suposições menos restritivas permanecem informativos. Utilizando as informações mais recente de microdados do Sistema de Avaliação da Educação Básica (SAEB) de 2005 para os estudantes do 5º ano do Ensino Fundamental, os resultados apontam a sobreestimação do efeito das escolas privadas com as metodologias que se baseiam nas suposições de ignorabilidade e imputação, mas o efeito ainda permanece significativamente positivo. A possível explicação desse viés pode ser atribuido ao forte viés de seleção relacionado ao baixo nível de renda dos pais dos alunos de escolas públicas, que limita a escolha da escola do filho e impossibilita a determinação de um aceitável contrafactual.
Referências
AAKVIK, A. Bounding a matching estimator: the case of a Norwegian training program. Oxford Bulletin of Economics and Statistics, v. 63, n. 1, p. 115–143, 2001.
ALTONJI, J. G.; ELDER T. E.; TABER C. R. Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools. Journal of Political Economy, v. 113, n. 1, p. 151-184, 2005.
BARBOSA FILHO, F. H.; PESSÔA, S.. Retorno da Educação no Brasil. Pesquisa e Planejamento Econômico, v. 38, n.1, 2008.
BECKER, S.O.; CALIENDO, M. Sensitivity analysis for average treatment effect. Stata Journal, v. 7, n. 1, p. 71–83, 2007.
BLUNDELL, R.; DEARDEN, L.; SIANESI, B. Evaluating the impact of education on earnings in the UK: models, methods and results from the NCDS. Journal of the Royal Statistical Society, Series A, v. 168, n. 3, p. 473–512, 2005.
BLUNDELL, R.; COSTA-DIAS, M. Alternative Approaches to Evaluation in Empirical Microeconomics. Journal of Human Resources, v. 44, n. 3, 2009.
CALIENDO, M.; HUJER, R.; THOMSEN, S. The employment effects of job creation schemes in Germany – a microeconometric evaluation. IZA Discussion Paper, Nº. 1512, 2007.
CALIENDO, M.; KOPEINIG, S.. Some Practical Guidance for The Implementation of Propensity Score Matching. Journal of Economic Surveys, v. 22, p. 31–72, 2008.
Coleman, J.S.; Hoffer, T.; Kilgore, S.. High School Achievement: Public, Catholic and Private Schools Compared. Basic Books. 1982. Disponível em: http://www.questia.com/PM.qst?a=o&d=100282593. Acesso em: 21 out. 2010.
CRUMP, R.; HOTZ V. J.; IMBENS G.; MITNIK, O. Dealing with Limited Overlap in Estimation of Average Treatment Effects. forthcoming Biometrika, 2008.
CURI, A. Z.; MENEZES-FILHO, N. A.. Determinantes dos Gastos com Educação no Brasil. Pesquisa e Planejamento Econômico, v. 40, n. 1, 2010.
DEHEJIA, R.; WABBA, S. Causal Effects in Nonexperimental Studies: Reevaluating the Evaluation of Training Programs. Journal of the American Statistical Association, v. 94, p. 1053-1062, 1999.
EVANS, W.; SCHWAB R. M. Finishing High School and Starting College: Do Catholic Schools Make a Difference? The Quarterly Journal of Economics, v. 110, n. 4, p. 941-974, 1995.
FRANÇA, M. T. A.; GONÇALVES, F. O.. Provisão pública e privada de educação fundamental: diferenças de qualidade medidas através de propensity score matching. In: XXXVII Encontro Nacional de Economia – ANPEC, 2009.
HANUSHEK, E; WOESSMANN, L.. The role of cognitive skills in economic development. Journal of Economic Literature, v 46, n.3, p. 607-668, 2008.
HECKMAN, J.; ICHIMURA, H.; TODD, P. Matching as an econometric evaluation estimator. Review of Economic Studies, v. 65, n. 2, p. 261–294, 1998.
HOXBY, C. M. Do Private Schools Provide Competition for Public Schools? NBER working paper, no. 4978, 1994.
HOXBY, C. M. The effects of class size on student achievement: new evidence from population variation. Quarterly Journal of Economics, v.116, p. 1239–1286, 2000a.
HOXBY, C. M. Does competition among public schools benefit students and taxpayers. The American Economic Review, v.90, n. 5, p. 1209-1238, 2000b.
ICHINO, A.; MEALLI, F.; NANNICINI, T. From temporary help jobs to permanentemployment: what can we learn from matching estimators and their sensitivity. IZA Discussion Paper, Bonn, No. 2149, 2006.
IMBENS, G. The role of the propensity score in estimating dose–response functions. Biometrika, v. 87, n. 3, p. 706–710, 2000.
________. Sensitivity to exogeneity assumptions in program evaluation. American Economic Review, v. 93, n. 2, p. 126–132, 2003.
________. Nonparametric estimation of average treatment effects under exogeneity: a review. Review of Economics and Statistics, v. 86, n. 1, p 4–29, 2004.
IMBENS, J.; WOODRIDGE, J.. Recent Developments in the Econometrics of Program Evaluation. Journal of Economic Literature, v. 47, n. 1, p. 5–86, 2009. Disponível em: http:www.aeaweb.org/articles.php?doi=10.1257/jel.47.1.5 . Acesso em: 21 out. 2010.
INEP. Primeiros Resultados: Médias de desempenho do SAEB/2005 em perspectiva Comparada. Publicações do INEP, 2007. Disponível em: http://www.inep.gov.br/download/saeb/2005/SAEB1995_2005.pdf. Acesso em: 21 out. 2010.
KHANDKER, S.; KOOLWAL, G.; SAMAD, H. Handbook on Impact Evaluation. World Bank, Washington DC, 2010.
LECHENER, M. Earnings and employment effects of continuous off-the-job training in East Germany after unification. Journal of Business Economic Statistics, v. 17, n. 1, p. 74–90, 1999.
_________. Identification and estimation of causal effects of multiple treatments under the conditional independence assumption. Econometric Evaluation of Labour Market Policies, Heidelberg, p. 1–18, 2001.
NANNICINI, T. A Simulation-Based Sensitivity Analysis for Matching Estimators. The Stata Journal, v. 7, n.3, p. 334-350, 2007.
MANSKI, C. Anatomy of the Selection Problem. The Journal of Human Resource, v. 24, p. 343-360, 1989.
__________. Nonparametric Bounds on Treatment Effects. American Economic Review Papers and Proceedings, v. 80, p. 319-323, 1990.
__________. Identification of Endogenous Social Effects: The Reflection problem. Review of Economic Studies, v. 60, p 531-542, 1990.
__________. Monotone Treatment Rsponse. Econometrica, v. 65, p. 1311-1334, 1997.
__________. Identification for Prediction and Decision. Princeton University Press, Princeton, 2008.
MANSKI, C.; PEPPER, J. V. Monotone Instrumental Variable: With an Aplication to the Returns to Schooling. Econometrica, v. 68, p. 997-1010, 2000.
NERI, M. Motivos da Evasão Escolar no Brasil. Disponível em: http://www.ufgd.edu.br/faed/nefope/publicacoes/pesquisa-motivos-da-evasao-escolar. Acesso em: 21 out. 2010.
ROSENBAUM, P.R. Observational Studies. Springer, New York, 2002.
ROSENBAUM, P.R.; and RUBIN, D. The central role of the propensity score in observational studies for causal effects. Biometrika, v. 70, n. 1, p. 41–50, 1983a.
__________. Assessing sensitivity to an unobserved binary covariate in an observational study with binary outcome. Journal of the Royal Statistical Society, Series B, v. 45, p. 212–218, 1983b.
SMITH, J.; TODD, P. Does matching overcome Lalonde’s critique of nonexperimental estimators? Journal of Econometrics, v. 125, n. 1-2, p. 305-353, 2005.
TABER, C.; FRENCH, E.. Identification of Models of the Labor Market. Federal Reserve Bank of Chicago, 2010. Disponível no site: bhttp://www.chicagofed.org/digital_assets/publications/working_papers/2010/
TODD, P. Evaluating Social Programs with Endogenous Program Placement and Selection of the Treated. In: Handbook of Development Economics, v. 60, n. 4, p. 3847-389, 2008.
WEBBINK, D. Causal Effects in Education. Journal of Economic Surveys, v. 19, p. 535–560, 2005.
ZOGHBI, A. C.; MENEZES, R. T; FELÍCIO, F.. Produtividade Relativa dos Setores Público e Privado em Educação: Impacto sobre a Escolha da Escola pela Família. In: XXXVIII Encontro Nacional de Economia – ANPEC, 2010.