Fundamentals and Methods for Impact. Evaluation of Public Policies



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Istituto per la Ricerca Valutativa sulle Politiche Pubbliche Fondazione Bruno Kessler - Via S. Croce, 77 38100 Trento - Italy Fundamentals and Methods for Impact Evaluation of Public Policies 20-24 April 2009 12-13 May 2009 IRVAPP, Trento DOSSIER NO. 0 Indicazioni bibliografiche selezionate

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Letture introduttive e brevi rassegne Blundell, R. and M. Costa Dias (2008), Alternative approaches to evaluation in empirical microeconomics, IZA Discussion Paper No. 3800, Bonn, IZA [forthcoming in Journal of Human Resources]. Heckman, J.J. (2001), Microdata, heterogeneity and the evaluation of public policy: Nobel Lecture, Journal of Political Economy, 109 (4), pp. 673-748. Imbens, G. and J.M. Wooldridge (2008), Recent developments in the econometrics of program evaluation, IZA Discussion Paper No. 3640, Bonn, IZA. Martini, A., E. Rettore e U. Trivellato (2009), Valutare gli effetti delle politiche attive del lavoro: la logica controfattuale, in M. Cantalupi e M. Demurtas (a cura di), Politiche di attivazione e performance dei servizi per l impiego. Esperienze e percorsi di implementazione in Italia e in Europa, Bologna, Il Mulino [in corso di pubblicazione]. Rettore, E., U. Trivellato e A. Martini (2003), La valutazione delle politiche del lavoro in presenza di selezione: migliorare la teoria, i metodi o i dati?, Politica Economica, 19 (3), pp. 301-341. Wooldridge, J. (2002), Econometric analysis of cross-section and panel data, Cambridge, MA, The MIT Press, pp. 603-644. Volumi Heckman, J.J., R. LaLonde and J. Smith (1999), The economics and econometrics of active labor market programs, in O. Ashenfelter e D. Card (eds.), Handbook of Labor Economics Vol. 3A, Amsterdam., Elsevier. Imbens, G. and D. Rubin (2009), Causal inference in statistics, and in the social and biomedical sciences, New York (NY), Cambridge University Press [forthcoming]. Lee, M.-J. (2005), Micro-econometrics for policy, programme, and treatment effects, Oxford, Oxford University Press. Pearl, J. (2000), Causality. models, reasoning, and inference, Cambridge, UK, Cambridge University Press. Rosenbaum, P.R. (2002) Observational Studies, 2nd Edition, New York (NY), Springer Verlag. Winship, C. and S. Morgan (2007), Counterfactuals and causal inference, Cambridge, UK, Cambridge University Press. 3

Temi specifici: (i) l approccio potential outcomes Holland, P. (1986), Statistics and causal inference, Journal of the American Statistical Association, 81 (396), pp. 945-960. Rubin, D.B (1974), Estimating causal effects of treatments in randomized and nonrandomized studies, Journal of Educational Psychology, 66 (5), pp. 688-701. Temi specifici: (ii) esperimenti sociali Berk, R. (2005), Randomized experiments as the Bronze Standard, Paper 2005080201, Los Angeles, Department of Statistics Papers, UCLA. Bloom H.S. (2008), The core analytics of randomized experiments for social research, in P. Alasuutari, L. Bickman and J. Brannen (eds), The SAGE Handbook of Social Research Methods, Thousand Oaks, CA, Sage Publications [also MDRC Working Papers on Research Methodology, 2006]. Temi specifici: (iii) selezione nelle osservabili e matching Dehejia, R.H. and S. Wahba (1999), Causal effects in nonexperimental studies: Reevaluating the evaluation of training programs, Journal of the American Statistical Association,. 94, pp. 1053-62. Heckman, J.J. H., Ichimura, J. Smith, J. and P. Todd. (1998) Characterizing selection bias using experimental data, Econometrica, 66, pp. 1017-1098 Imbens, G.W. (2000) The Role of the propensity score in estimating dose-response functions, Biometrika, 87 (3), pp. 706-710. Imbens G. (2004), Nonparametric estimation of average treatment effects under exogeneity: A review, The Review of Economics and Statistics, 86 (1), pp. 4-29. Lechner M. (2002), The evaluation of heterogeneous labour market programmes by matching methods, Journal of the Royal Statistical Society, Series A, 165 (1), pp. 59-82. Rosenbaum P.R. and D.B. Rubin (1983), The central role of the propensity score in observational studies for causal effects, Biometrika, 70 (1), pp. 41-55. Sianesi, B. (2004), An evaluation of the Swedish system of active labour market programmes in the 1990s, Review of Economics and Statistics, 86 (1), pp. 133-155. 4

Temi specifici: (iv) RDD e Instrumental Variables Angrist J.(1990), Lifetime earnings and the Vietnam era draft lottery: evidence from social security administrative records, American Economic Review, 80 (3), pp. 313-336. Angrist J. (2004), Treatment effect heterogeneity in theory and practice, The Economic Journal, 114, pp. C52-C83. Angrist J., G. Imbens and D. Rubin (1996), Identification of causal effects using Instrumental Variables (with discussion), Journal of the American Statistical Association, 91 (434, pp. 444-472. Fort M. (2008), Just a matter of time: Empirical evidence on the causal effect of education on fertility in Italy, Dipartimento di Scienze Economiche, Università di Bologna, mimeo. Garibaldi P., F. Giavazzi, A. Ichino, E. Rettore (2007), College cost and time to complete a degree: evidence from tuition discontinuities, Cambridge (MA), NBER Working Paper No 12863. Hahn J., P. Todd, W. Van der Klaauw (2001), Identification and estimation of treatment effects with a Regression-Discontinuity Design, Econometrica, Vol. 69, No. 1, 201-209. Imbens, G. and T. Lemieux (eds.) (2008), The regression discontinuity design: Theory and applications, special issue of Journal of Econometrics, 144 (2). Lee D. (2008), Randomized experiments from non-random selection in U.S. House elections, Journal of Econometrics, 142 (2), pp. 675-697. Temi specifici: (v) selezione nelle non-osservabili Heckman, J.J., H. Ichimura, and P. Todd (1997), Matching as an econometric evaluation estimator: Evidence from evaluating a job training programme, Review of Economic Studies, 64, pp. 605-654. Temi specifici: (vi) distribuzione dell effetto Battistin E. and M. Fort (2008), What s missing from policy evaluation: Identification and estimation of the distribution of treatment effects, in Società Italiana di Statistica, Atti della XLIV Riunione Scientifica, Padova, Cleup, pp. 127-134. 5

Blundell R., A. Gosling, H. Ichimura and C. Meghir (2007), Changes in the distribution of male and female wages accounting for employment composition using bounds, Econometrica, 75 (2), pp. 323-363. Abadie A., J. Angrist, J. and G. Imbens (2002), Instrumental variables estimates of the effect of subsidized training on the quantiles of trainee earnings, Econometrica, 70 (1), pp. 91-117. Carneiro P.M., K.T. Hansen and J.J. Heckman (2003), 2001 Lawrence Klein Lecture. Estimating distributions of treatment effects with an application to the returns to schooling and measurement of the effects of uncertainty on college, International Economic Review, 44 (2), pp. 361-422. Chernozhucov V. and C. Hansen (2005), An IV model of quantile treatment effects, Econometrica, 73 (1), pp. 245-261. Chernozhucov V. and C. Hansen (2006), Instrumental quantile regression inference for structural and treatment effect models, Journal of Econometrics, 73 (1), pp. 245-261. Chesher A. (2001), Exogenous impact and conditional quantile functions, London, Centre for Microdata Methods and Practice Working Paper CWP01/01. Chesher A. (2003), Identification in nonseparable models, Econometrica, 71, pp. 1405-1441. Firpo S. (2007), Efficient semiparametric estimation of quantile treatment effect, Econometrica,75, pp. 259-276. Heckman J.J., J. Smith and N. Clements (1997), Making the most out of programme evaluations and social experiments: Accounting for heterogeneity in programme impacts, Review of Economic Studies, 64 (4), pp. 487-535. Heckman J.J., J. Tobias and E. Vytlacil (2003) Simple estimators for treatment parameters in a latent variable framework, Review of Economics and Statistics, 85 (3). pp. 748-755 Imbens G.W. and D. Rubin (1997), Estimating outcome distributions for compliers in Instrumental Variable models, Review of Economic Studies, 64, pp. 555-574. Manski C.F. (2003), partial identification of probability distributions, New York (NY), Springer-Verlag. 6

Temi specifici: (vii) test di sovra-identificazione Battistin E. and E. Rettore (2008), Ineligibles and eligible non-participants as a double comparison group in Regression Discontinuity Designs, Journal of Econometrics, 142 (2), pp. 715-730. Blundell R., M. Costa Dias, C. Meghir and J. Van Reenen (2004), Evaluating the employment impact of a mandatory job search assistance program, Journal of European Economic Association, 2 (4), pp. 569-606. Lee D. (2008), Randomized experiments from non-random selection in U.S. House elections, Journal of Econometrics, 142 (2), pp. 675-697. Rosenbaum, P (1987), The role of a second control group in an observational study (with discussion), Statistical Science, 2, pp. 292-316. Temi specifici (viii): meta-analisi di studi di valutazione di effetti Cottingham, P., R.A. Maynard and M. Stagner (2004), Synthesizing evidence on the impacts of programmes and policies in education, crime and justice, and social welfare: Practical recommendations based on 14 Test-Bed reviews, Evaluation and Research in Education, 18 (1 & 2), pp. 28-53. Cottingham, P., R.A. Maynard and M. Stagner (2005), Generating and using evidence to guide public policy and practice: Lessons from the Campbell test-bed project, Journal of Experimental Criminology, 1 (3), pp. 279-294. 7