Portal InstitucionalUFPEL

Objetivo Geral:

Bibliografia Básica:

• Heckman, J. 2001. Micro Data, Heterogeneity, and the Evaluation of Public Policy. Journal of Political Economy, v. 109, n. 4.
• Ravallion, M.. 2001. “The Mystery of Vanishing Benefits: An Introduction to Impact Evaluation,” World Bank Economic Review, 15(1), 115-140.
• Angrist, Joshua D. and Jörn-Steffen Pischke. 2009. Mostly Harmless Econometrics. Princeton University Press.
• Bourguignon, François e Luiz A. Pereira da Silva (eds.). 2003. The Impact of Economic Policies on Poverty and Income Distribution. Evaluation Techniques and Tools. Nova York: Oxford University Press for the World Bank.
• Bourguignon, F., F. H. G. Ferreira, P. G. Leite 2002. „Ex-ante Evaluation of Conditional Cash Transfer Programs: The Case of Bolsa Escola,‟ William Davidson Working Paper 516, University of Michigan Business School.
• ADB 2007. Poverty Impact Analysis: Selected Tools and Applications, Parts 1 and 2.
• Duflo, Esther; Glennerster, Rachel e Kremer Michael 2006. Using Randomization in Development Economics Research: A Toolkit, NBER Technical Working Paper No. 333.
• Heckman, J. e B. Honoré. 1990. The Empirical Content of the Roy Model. Econometrica. 58(5): 1121-1149.
• Heckman, J. (2008), "Econometric Causality." IZA Discussion Paper Series n. 3425.
• Imbens, G. and Wooldridge, J. (2008), "Recent Developments in the Econometrics of Program Evaluation," NBER WP 14251.
• Rubin, D. 1974. Estimating Causal Effects of Treatments in Randomized and Non-randomized Studies. Journal of Educational Psychology, 66, 688-701
• Lalonde, R. (1986), "Evaluating the Econometric Evaluations of Training Programs," American Economic Review, 76, 604-620.
• Duflo, Esther. (2005). Field Experiments in Development Economics. MIT: Dezembro. Mimeo.
• Imbens, G. , (2004), "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," Review of Economics and Statistics, 86, 4-29.
• Brand, J. E. and Y. Xie (2007). „Identification and Estimation of Causal Effects with Time- Varying Treatments and Time-Varying Outcomes,‟ Published in Sociological Methodology 37 (1): 393-434, 2007.
• Imbens, G. (2000), "The Role of the Propensity Score in Estimating Dose-Response Functions," Biometrika, Vol. 87, No. 3, 706-710.
• Angrist J. D. and A. Krueger (1991), "Does Compulsory School Attendance Affect Schooling and Earnings?," Quarterly Journal of Economics, vol. 106, 979-1014.
• Becker, S. and M. Caliendo, (2007), Sensitivity analysis for average treatment effects, Stata Journal, Volume 7 Number 1, 71-83.
• Rosenbaum, P. (2002) Observational Studies, 2nd ed., New York: Springer.
• Abadie, A. (2005), "Semiparametric Difference-in-Differences Estimators," Review of Economic Studies
• Abadie, A. Gardeazabal, JThe Economic Costs of Conflict: A Case Study of the Basque Country, American Economic Review 2003
• Duflo E. (2001), "Schooling and Labor Market Consequences of School Construction in Indonesia: Evidence from an Unusual Policy Experiment," American Economic Review, vol. 91, 795-813.
• Heckman, J. J. (1997). „Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations,‟ Journal of Human Resources 32 (3): 441-462.
• Altonji, J. G., T. E. Elder, C. R. Taber (2002). „An Evaluation of Instrumental Variable Strategies for Estimating the Effects of Catholic Schooling,‟ Working Paper 9358, NBER, Cambridge MA. Published in Journal of Human Resources 40 (4): 791-821, 2005.
• Imbens,G. W. e T. Lemieux. 2008. Regression Descontinuity Designs: A Guide to Practice. Journal of Econometrics, vol. 142, issue 2: 615-635.
• Heckman, J. J., N. Hohmann, J. Smith, M. Khoo (2000). „Substitution and Dropout Bias is Social Experiments: A Study of an Influential Social Experiment,‟ Quarterly Journal of Economics 115 (2): 651-694.
• Miguel, E. and M. Kremer (2004). „Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities,‟ Econometrica 72 (1): 159-217.
• Barrera-Osorio, F., M. Bertrand, L. L. Linden, F. Perez-Calle (2008). „Conditional Cash Transfers in Education: Design Features, Peer and Sibling Effects: Evidence from Randomized Experiment in Colombia,‟ Working Paper 13890, NBER, Cambridge MA.
• Duflo, E. (2003). „Scaling Up and Evaluation,‟ ABCDE Annual World Bank Conference on Development Economics, Bangalore.
• Duflo, Esther; Glennerster, Rachel e Kremer Michael 2006. Using Randomization in Development Economics Research: A Toolkit, NBER Technical Working Paper No. 333.
• Heckman, J. J., L. Lochner, C. Taber (1998). „General-Equilibrium Treatment Effects: A Study of Tuition Policy,‟ American Economic Review 88 (2): 381-386.
• Abadie, A., Diamond, A., and Hainmueller, J (2010. “Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of Californias‟s Tobacco Control Program”, Journal of the American Statistical Association, 105 (490), 493-505.