Documents Workshop Elias Dinas

 

 

Key readings "Causal Inference":
  •  Angrist, Joshua and Jörn-Steffen Pischke. 2009. Mostly Harmless Econometrics: An Empiricist’s Companion, Princeton: Princeton University Press. 
  •  Morgan Stephen L. and Christopher Winship. 2007. Counterfactuals and Causal Inference: Methods and Principles for Social Research, Cambridge: Cambridge University Press.
  •  Diamond and Sekhon 2013, “Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies.” Review of Economics & Statistics.
  •  Angrist, Joshua, Guido Imbens, and Donal Rubin. “Identification of Causal Effects Using Instrumental Variables.” Journal of the American Statistical Association, 91(434):444-55.
  •  Lee, David. “Randomized Experiments from Non-Random Selection in U.S. House Elections.” Journal of Econometrics, 142: 675-97.
  •  Montalvo, José. 2011. “Voting after the Bombings: A Natural Experiment on the Effect of Terrorist Attacks on Democratic Elections.” Review of Economics and Statistics, 93(4):1146-1154.

 

Key readings "Advances in Causal Inference":
  • Gerber & Green, 2012, Field Experiments, Norton. 
  •  Morgan Stephen L. and Christopher Winship. 2007. Counterfactuals and Causal Inference: Methods and Principles for Social Research, Cambridge: Cambridge University Press.
  •  Lee, D. S. (2009). Training, wages, and sample selection: Estimating sharp bounds on treatment effects. The Review of Economic Studies, 76(3), 1071-1102.
  •  Ho, D. E., & Imai, K. (2006). Randomization inference with natural experiments: An analysis of ballot effects in the 2003 California recall election. Journal of the American Statistical Association, 101(475), 888-900.
  •  Glynn, A. N., & Ichino, N. (2015). Using qualitative information to improve causal inference. American Journal of Political Science, 59(4), 1055-1071.
  •  Abadie, A., & Gardeazabal, J. (2003). The economic costs of conflict: A case study of the Basque Country. American economic review, 113-132.
  •  Abadie, A., Diamond, A., & Hainmueller, J. (2012). Synthetic control methods for comparative case studies: Estimating the effect of California?s tobacco control program. Journal of the American Statistical Association.
  •  Abadie, A., Diamond, A., & Hainmueller, J. (2015). Comparative politics and the synthetic control method. American Journal of Political Science, 59(2), 495-510.
  •  Glynn, A. N. (2012). The product and difference fallacies for indirect effects. American Journal of Political Science, 56(1), 257-269.
  •  Glynn, A., & Kashin, K. (2014). Front-door Difference-in-Differences Estimators. Manuscript. Harvard University, Cambridge, MA.
  •  Glynn, A. N., & Quinn, K. M. (2011). Why process matters for causal inference. Political Analysis, 19(3), 273-286.
  •  Imai, K., Keele, L., & Yamamoto, T. (2010). Identification, inference and sensitivity analysis for causal mediation effects. Statistical Science, 51-71.
  •  Bullock, J. G., Green, D. P., & Ha, S. E. (2010). Yes, but what?s the mechanism?(don?t expect an easy answer). Journal of personality and social psychology, 98(4), 550.
  •  Tingley, D., Yamamoto, T., Hirose, K., Keele, L., & Imai, K. (2014). Mediation: R package for causal mediation analysis.
  •  Imai, K., Keele, L., Tingley, D., & Yamamoto, T. (2011). Unpacking the black box of causality: Learning about causal mechanisms from experimental and observational studies. American Political Science Review, 105(04), 765-789.

 

Additional readings on Difference-in-Difference:
Nach oben scrollen