Josh Angrist and Jorn-Steffen Pischke, Mostly Harmless Econometrics, Princeton University Press

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1 Syllabus Advanced Microeconometrics Instructor: Andrea Weber office N Office hours: will be announced at the beginning of the term. Credits: 4 (8 ECTS) Term: Winter 2019 Course level: PhD Prerequisites: Advanced Econometrics 1 and 2 (or equivalent) Course description This course examines econometric identification issues in empirical microeconomics and public policy analysis. It supplements topics covered Advanced Econometrics with a focus on the sensible application of econometric methods to empirical problems. The course provides background on issues that arise when analyzing nonexperimental social science data and a guide for tools that are useful for applied research and policy analysis. The course also emphasizes how a basic understanding of economic theory and institutions can help inform the analysis. Learning outcomes By the end of this course, students will: - have a firm grasp of the types of research design that can lead to convincing analysis, - understand threats to uncovering causal effects from economic data - be able to apply a range of micro-econometric tools and interpret results - be comfortable working with large scale data sets - be encouraged to develop independent research interests and applied research projects. Reading list Textbooks: Josh Angrist and Jorn-Steffen Pischke, Mostly Harmless Econometrics, Princeton University Press Jeffrey Wooldridge, Econometric Analysis of Cross Section and Panel Data (MIT Press). Additional Readings: topic specific reading list with mandatory and optional papers; see below. Assessment 1

2 Readings for each week will be assigned one week in advance. Students are expected to read the material in advance and be prepared for class discussions. 4 5 problem sets will be posted on the course website over the term. Students will give short presentations in class. Topics will be discussed and assigned in class. At the end of the term there will be a 90 minute final exam. Final grades are based on Problem sets: in total 25% Participation in class discussions: 10% Class presentation: 20% Final exam: 45% Course schedule and reading materials for each session (the reading list is still preliminary and may change) 1. Introduction: Research questions, the concept of causality Mostly Harmless Econometrics, Chapter 1 and 2 Freedman, David A. (1991) Statistical Models and Shoe Leather, Sociological Methodology, 21, A.B. Krueger (1999) Experimental Estimates of the Education Production Function, The Quarterly Journal of Economics, 114, issue 2, Abadie, M. Cattaneo, Econometric Methods for Program Evaluation, Working Paper, S. Athey, G. Imbens The State of Applied Econometrics: Causality and Policy Evaluation Journal of Economic Perspectives. May 2017, Vol. 31, Issue 2, Pages Conditional Expectation Functions, Regression Functions, Omitted Variables Formula Mostly Harmless Econometrics, Chapter 3 3. Decomposition Methods DiNardo, Fortin and Lemieux (1996) Labor Market Institutions and the Distribution of Wages, : A Semiparametric Approach, Econometrica, Vol 64, Fortin, Nicole, Thomas Lemieux, and Sergio Firpo (2011) Decomposition Methods in Economics, Handbook of Labor Economics (Volume 4A) Bell, Brian, Michael Böhm, Nicole Fortin (2017) Top Earnings Inequality and the Gender Pay Gap: Canada, Sweden, and the United Kingdom working paper. 2

3 Kline, Patrick, (2011) Oaxaca-Blinder as a Reweighting Estimator, American Economic Review: Papers and Proceedings, 101, pp Linear Regression, Propensity Scores, Matching Mostly Harmless Econometrics, Chapter 3 Alan B. Krueger (1993) "How Computers Have Changed the Wage Structure: Evidence from Microdata ", The Quarterly Journal of Economics John E. DiNardo and Jorn-Steffen Pischke (2004) "The Returns to Computer Use Revisited: Have Pencils Changed the Wage Structure Too?", The Quarterly Journal of Economics Imbens, Guido W. (2004) Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review Review of Economics and Statistics, 86, Rosenbaum, Paul R. and Donald B. Rubin (1984) Reducing Bias in Observational Studies Using Subclassification on the Propensity Score Journal of the American Statistical Association, 79, LaLonde, Robert J. (1986), "Evaluating the Econometric Evaluations of Training Programs with Experimental Data", American Economic Review, 76, Ashenfelter, Orley (1987), "The Case for Evaluating Training Programs with Randomized Trials", Economics of Education Review, 6, LaLonde, Robert J. (1986), "Evaluating the Econometric Evaluations of Training Programs with Experimental Data", American Economic Review 76, Rosenbaum, Paul R. and Donald B. Rubin (1984) Reducing Bias in Observational Studies Using Subclassification on the Propensity Score Journal of the American Statistical Association, 79, Dehejia, Rajeev H. and Sadek Wahba (1999) "Causal Effects in Nonexperimental Studies: Reevaluating the Evaluation of Training Programs" Journal of the American Statistical Association, 94, Heckman, Ichimura, Smith, Todd (1998) Smith and Todd (2004) 5. Fixed Effects and Panel Data Methods, Differences-in-Differences, Event Study Designs Wooldridge, Chapter 10 Mostly Harmless Econometrics, Chapter 5 Card and Krueger (1994) Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania, American Economic Review, 84(4), Bertrand, Marianne, Esther Duflo, Sendhil Mullainathan, " How Much Should We Trust Differences-in- Differences Estimates?," The Quarterly Journal of Economics, Entorf, Horst, Michel Gollac and Francis Kramarz (1999), New Technologies, Wages, and Worker Selection, Journal of Labor Economics, 17, pp

4 Davis, Lucas W. (2004) The Effect of Health Risk on Housing Values: Evidence from a Cancer Cluster, American Economic Review, 94(5), John Gruber (1994) The Incidence of Mandated Maternity Benefits, American Economic Review, Vol 84, Jacobson, LaLonde, Sullivan (1993) "Earnings Losses of Displaced Workers", American Economic Review Fadlon, Nielsen (2015) "Household Responses to Severe Health Shocks", NBER Working Paper Halla, M., J. Schmieder, A. Weber (2017) "Job Displacement, Family Dynamics, and Spousal Labor Supply" Abadie, A., M. M. Chingos, and M. R. West Endogenous stratification in randomized experiments. Working Paper A. Abadie, A. Diamond, J. Hainmueller Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California s Tobacco Control Program, Journal of the American Statistical Association, Vol. 105, No. 490, June A. Abadie, A. Diamond, J. Hainmueller Comparative Politics and the Synthetic Control Method, American Journal of Political Science, Vol. 59, No. 2, April 2015, Pp G. Peri, V. Yasenov, The Labor Market Effects of a Refugee Wave: Synthetic Control Method Meets the Mariel Boatlift, IZA Discussion Paper 10605, Edson Severnini, The Power of Hydroelectric Dams: Agglomeration Spillovers IZA Discussion Paper 8082, Marianne Bertrand, Esther Duflo, and Sendhil Mullainathan. How much should we trust differences-in-differences estimates? The Quarterly Journal of Economics, 119(1): , Abadie, Athey, Imbens, Wooldridge When Should We Adjust Standard Errors for Clustering?, Working paper, Measurement Error Ashenfelter, Orley and Alan Krueger (1994) Estimates of the Economic Return to Schooling from a New Sample of Twins. American Economic Review, 84, Z. Pei, S Pischke, H. Schwandt (2017) Poorly Measured Confounders are More Useful on the Left than on the Right. Oster, Emily (forthcoming). Unobservable Selection and Coefficient Stability: Theory and Evidence." Journal of Business & Economic Statistics. Altonji, Joseph G., Timothy Conley, Todd E. Elder, and Christopher R. Taber Methods for Using Selection on Observed Variables to Address Selection on Unobserved Variables." mimeographed. Altonji, Joseph G, Todd E Elder, and Christopher R Taber Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools." Journal of Political Economy, 113(1): Instrumental Variables Estimation, Control Functions, Local Average Treatment Effects, Marginal Treatment Effects 4

5 Mostly Harmless Econometrics, Chapter 4 Bound, Jaeger, and Baker (1995) Weak Instruments Angrist, Joshua D. and Alan B. Krueger (1991) Does Compulsory School Attendance Affect Schooling and Earnings? The Quarterly Journal of Economics, 106, Angrist, Joshua D., Guido W. Imbens and Donald B. Rubin (1996) Identification of Causal Effects Using Instrumental Variables, Journal of The American Statistical Association, 91, Garen, John (1984) The Returns to Schooling: A Selectivity Bias Approach with a Continuous Choice Variable, Econometrica, 52, Card, David and Laura Giuliano (2014) Do Gifted Education Programs Work? For Which Students?, NBER Working Paper No. w Card, David and Laura Giuliano (2016) Universal Screening Increases the Representation of Low Income and Minority Students in Gifted Education Proceedings of the National Academy of Sciences, 113(48): , with David Card. Bhuller, Manudeep, Gordon Dahl, Katrine Loken, Magne Mogstad (2016) Incarceration, Recidivism and Employment, working paper, University of Bergen Dobbie, Grönqvist, Palme et al. Intergenerational Effects of Parental Incarcaration Cornelissen, Thomas, Christian Dustmann, Anna Raute and Uta Schönberg (2016) From LATE to MTE: Alternative Methods for the Evaluation of Policy Interventions, Labour Economics,41, Cornelissen, Thomas, Christian Dustmann, Anna Raute and Uta Schönberg (forthcoming) Who benefits from universal childcare? Estimating marginal returns to early childcare attendance, Journal of Political Economy. P. Goldsmit-Pinkham, I. Sorkin, H. Swift Bartik Instruments: What, When, Why, and How?, Regression Discontinuity Designs Imbens, Guido W. and Thomas Lemieux (2008) "Regression Discontinuity Designs: A Guide to Practice" Journal of Econometrics, 142, David S. Lee and Thomas Lemieux (2010) "Regression Discontinuity Designs in Economics" Journal of Economic Literature, 48, David Card, Raj Chetty, Andrea Weber, (2007), "Cash-on-Hand and Competing Models of Intertemporal Behavior: New Evidence from the Labor Market", Quarterly Journal of Economics, 122(4), Thistlethwaite and Campbell (1960) Regression-Discontinuity Analysis: An Alternative to the Ex-Post Facto Experiment Van der Klaaw (2002) Estimating the Effect of Financial Aid Offers on College Enrollment: A Regression- Discontinuity Approach International Economic Review,Vol 43(4). Angrist, Joshua D. and Victor Lavy (1999) Using Maimonides Rule to Estimate the Effect of Class Size on Scholastic Achievement The Quarterly Journal of Economics, 114, Miguel Urquiola and Eric Verhoogen (2009), Class-Size Caps, Sorting, and the Regression-Discontinuity Design, American Economic Review, 99:1,

6 McCrary, Justin (2008) Manipulation of the running variable in the regression discontinuity design: A density test, Journal of Econometrics, 142, Card, David and David S. Lee (2005) Regression Discontinuity Inference with Specification Error, Journal of Econometrics, 142(2) Calonico, S., Cattaneo, M. D., and Titiunik, R. (2014), Robust Nonparametric Confidence Intervals for Regression- Discontinuity Designs, Econometrica, 82, Calonico, S., Cattaneo, M. D., and Titiunik, R. (2014), Robust Data-Driven Inference in the Regression- Discontinuity Design? Stata Journal, 14, Calonico, S., Cattaneo, M. D., and Titiunik, R. (2015), Optimal Data-Driven Regression Discontinuity Plots, JASA, 110, Regression Kink Designs Card, David, David Lee, Zhuan Pei and Andrea Weber (2015) Inference on Causal Effects in a Generalized Regression Kink Design, Econometrica, 83(6), Card, David, David Lee, Zhuan Pei and Andrea Weber (2017) Regression Kink Design: Theory and Practice, Advances in Econometrics, volume 38. Card, David, Andrew Johnston, Pauline Leung, Alexandre Mas, and Zhuan Pei, (2015) The Effect of Unemployment Benefits on the Duration of Unemployment Insurance Receipt: New Evidence from a Regression Kink Design in Missouri, , American Economic Review: Papers and Proceedings, 105 (5), Manoli Turner (2016) Cash-on-Hand & College Enrollment: Evidence from Population Tax Data and Policy Nonliearities. 10. Bunching Methods Kleven, Henrik (2016) Bunching Annual Review of Economics 8, Manoli, D. and A. Weber (2016) Nonparametric Evidence on the Effects of Financial Incentives on Retirement Decisions, AEJ: Economic Policy, 8(4), Meta Analyis Card, David, Jochen Kluve and Andrea Weber (forthcoming) What Works? A Meta Analysis of Recent Active Labor Market Program Evaluations. Journal of the European Economic Association. Havranek,Tomaš (2015) Measuring Intertemporal Substitution: The Importance of Method Choices and Selective Reporting, Journal of the European Economic Association, 13(6). 6