Resources
Martin Huber (2021). Causal analysis: Impact evaluation and causal machine learning with applications in R.
Matheus Facure Alves(2021). Causal Inference for The Brave and True
Gábor Békés and Gábor Kézdi(2021). Data Analysis for Business, Economics, and Policy
Masa Asami, Causal Inference Using Synthetic Difference in Differences with Python
Victoria L. Prince (2019). Synthetic Controls: brief overview with practical recommendations
DAVID MCKENZIE (2013). Evaluating Regulatory Reforms Using the Synthetic Control Method
DAVID MCKENZIE(2015). Evaluating an Argentine regional tourism policy using synthetic controls: tan linda que enamora?
R pkg: synthdid
(Slide) David Hirshberg “Synthetic difference in differences” (2020), Emory QTM, Stanford Univ.
(Slide) Susan Athey “Synthetic Differences in Differences”(2020), Stanford Univ.
(Slide)“Difference-in-Differences Alberto Abadie Guest Talk — Synthetic Control”(2020), Introduction to Causal Inference by Brady Neal
Botosaru, I., & Ferman, B. (2019). On the role of covariates in the synthetic control method. The Econometrics Journal, 22(2), 117-130.
Abadie, A. (2021). Using synthetic controls: Feasibility, data requirements, and methodological aspects. Journal of Economic Literature, 59(2), 391-425.
Athey, S., Bayati, M., Doudchenko, N., Imbens, G., & Khosravi, K. (2021). Matrix completion methods for causal panel data models. Journal of the American Statistical Association, 116(536), 1716-1730.
Ferman, B., Pinto, C., & Possebom, V. (2020). Cherry picking with synthetic controls. Journal of Policy Analysis and Management, 39(2), 510-532.
Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2021. Synthetic Difference-in-Differences, American Economic Review, vol 111(12), pages 4088-4118.
Eli Ben‐Michael & Avi Feller & Jesse Rothstein, 2022. Synthetic controls with staggered adoption, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol 84(2), pages 351-381.
Ben-Michael, E., Feller, A., & Rothstein, J. (2021). The augmented synthetic control method. Journal of the American Statistical Association, 116(536), 1789-1803.
Ferman, B., & Pinto, C. (2021). Synthetic controls with imperfect pretreatment fit. Quantitative Economics, 12(4), 1197-1221.
Wiltshire, J. C. (2022). allsynth: Synthetic Control Bias-Correction Utilities for Stata.
Andersson, Julius J. 2019. Carbon Taxes and CO2 Emissions: Sweden as a Case Study. American Economic Journal: Economic Policy, 11 (4): 1-30.
Leroutier, M. (2022). Carbon pricing and power sector decarbonization: Evidence from the UK. Journal of Environmental Economics and Management, 111, 102580.
Isaksen, E. T. (2020). Have international pollution protocols made a difference?. Journal of Environmental Economics and Management, 103, 102358.
Wiltshire, J. C. (2021). Walmart Supercenters and Monopsony Power: How a Large, Low-Wage Employer Impacts Local Labor Markets. Job market paper.
Dube, A., & Zipperer, B. (2015). Pooling multiple case studies using synthetic controls: An application to minimum wage policies. Available at SSRN 2589786.
Powell, D. (2021). Synthetic Control Estimation Beyond Comparative Case Studies: Does the Minimum Wage Reduce Employment?. Journal of Business & Economic Statistics, 1-13.
Ferman, B. (2021). On the properties of the synthetic control estimator with many periods and many controls. Journal of the American Statistical Association, 116(536), 1764-1772.
Abadie, Alberto, and Javier Gardeazabal. 2003. The Economic Costs of Conflict: A Case Study of the Basque Country. American Economic Review, 93 (1): 113-132.
Abadie, A., Diamond, A. and Hainmueller, J., 2010. Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program. Journal of the American statistical Association, 105(490), pp.4
Abadie, A., Diamond, A. and Hainmueller, J., 2015. Comparative politics and the synthetic control method. American Journal of Political Science, 59(2), pp.495-510.
Liu, L., Wang, Y., & Xu, Y. (2022). A practical guide to counterfactual estimators for causal inference with time-series cross-sectional data. American Journal of Political Science.
Firpo, Sergio, and Vitor Possebom. "Synthetic Control Method: Inference, Sensitivity Analysis and Confidence Sets". Journal of Causal Inference 6.2 (2018)
Abadie, A., & L’Hour, J. (2021). A penalized synthetic control estimator for disaggregated data. Journal of the American Statistical Association, 116(536), 1817-1834.
Alberto Abadie, Matias D. Cattaneo. (2021) Introduction to the Special Section on Synthetic Control Methods. Journal of the American Statistical Association 116:536, pages 1713-1715.