Matching Methods for Causal Inference with Time‐Series Cross‐Sectional Data
Abstract
Matching methods improve the validity of causal inference by reducing model dependence and offering intuitive diagnostics. Although they have become a part of the standard tool kit across disciplines, matching methods are rarely used when analysing time‐series cross‐sectional data. We fill this methodological gap. In the proposed approach, we first match each treated observation with control observations from other units in the same time period that have an identical treatment history up to the prespecified number of lags. We use standard matching and weighting methods to further refine this matched set so that the treated and matched control observations have similar covariate values. Assessing the quality of matches is done by examining covariate balance. Finally, we estimate both short‐term and long‐term average treatment effects using the difference‐in‐differences estimator, accounting for a time trend. We illustrate the proposed methodology through simulation and empirical studies. An open‐source software package is available for implementing the proposed methods.
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Cites
Arellano, M., & Bond, S. (1991) · The Review of Economic Studies · doi:10.2307/2297968 · Cited by 33,272 · see citing works
How Much Should We Trust Differences-in-Differences Estimates?
Bertrand, M., Duflo, E., & Mullainathan, S. (2004) · The Quarterly Journal of Economics · doi:10.1162/003355304772839588 · Cited by 10,641 · see citing works
Mostly Harmless Econometrics: An Empiricist's Companion
Angrist, J. D., & Pischke, J.-S. (2009) · doi:10.1515/9781400829828 · Cited by 9,467 · see citing works
Biases in dynamic models with fixed effects
Nickell, S. (1981) · Econometrica · doi:10.2307/1911408 · Cited by 8,735 · see citing works
What To Do (and Not to Do) with Time-Series Cross-Section Data
Beck, N., & Katz, J. N. (1995) · American Political Science Review · doi:10.2307/2082979 · Cited by 6,840 · see citing works
Marginal Structural Models and Causal Inference in Epidemiology
Robins, J. M., Hernán, M. Á., & Brumback, B. (2000) · Epidemiology · doi:10.1097/00001648-200009000-00011 · Cited by 5,581 · see citing works
Abadie, A., Diamond, A., & Hainmueller, J. (2010) · Journal of the American Statistical Association · doi:10.1198/jasa.2009.ap08746 · Cited by 5,513 · see citing works
Matching Methods for Causal Inference: A Review and a Look Forward
Stuart, E. A. (2010) · Statistical Science · doi:10.1214/09-sts313 · Cited by 5,478 · see citing works
Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference
Ho, D. E., Imai, K., King, G., & Stuart, E. (2007) · Political Analysis · doi:10.1093/pan/mpl013 · Cited by 4,411 · see citing works
Self-citationCausal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
Imbens, G. W., & Rubin, D. B. (2015) · doi:10.1017/cbo9781139025751 · Cited by 4,210 · see citing works
Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available: Table 1.
Hernán, M. A., & Robins, J. M. (2016) · American Journal of Epidemiology · doi:10.1093/aje/kwv254 · Cited by 3,115 · see citing works
Semiparametric Difference-in-Differences Estimators
Abadie, A. (2005) · The Review of Economic Studies · doi:10.1111/0034-6527.00321 · Cited by 2,286 · see citing works
Acemoğlu, D., Naidu, S., Restrepo, P., & Robinson, J. A. (2018) · Journal of Political Economy · doi:10.1086/700936 · Cited by 1,652 · see citing works
Bias-Corrected Matching Estimators for Average Treatment Effects
Abadie, A., & Imbens, G. W. (2011) · Journal of Business & Economic Statistics · doi:10.1198/jbes.2009.07333 · Cited by 1,416 · see citing works
Covariate Balancing Propensity Score
Imai, K., & Ratkovic, M. (2013) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/rssb.12027 · Cited by 1,330 · see citing works
Self-citationRosenbaum, P., & Rubin, D. (1983) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1983.tb01242.x · Cited by 1,264 · see citing works
Diamond, A., & Sekhon, J. S. (2012) · The Review of Economics and Statistics · doi:10.1162/rest_a_00318 · Cited by 1,066 · see citing works
Multivariate Matching Methods That Are Monotonic Imbalance Bounding
Iacus, S., King, G., & Porro, G. (2011) · Journal of the American Statistical Association · doi:10.1198/jasa.2011.tm09599 · Cited by 998 · see citing works
Generalized Synthetic Control Method: Causal Inference with Interactive Fixed Effects Models
Xu, Y. (2017) · Political Analysis · doi:10.1017/pan.2016.2 · Cited by 938 · see citing works
Design-based analysis in Difference-In-Differences settings with staggered adoption
Athey, S., & Imbens, G. W. (2022) · Journal of Econometrics · doi:10.1016/j.jeconom.2020.10.012 · Cited by 917 · see citing works
On the Failure of the Bootstrap for Matching Estimators
Abadie, A., & Imbens, G. W. (2008) · Econometrica · doi:10.3982/ecta6474 · Cited by 800 · see citing works
Toward Causal Inference With Interference
Hudgens, M. G., & Halloran, M. E. (2008) · Journal of the American Statistical Association · doi:10.1198/016214508000000292 · Cited by 768 · see citing works
Difference-in-Differences with Variation in Treatment Timing
Goodman-Bacon, A. (2018) · doi:10.3386/w25018 · Cited by 757 · see citing works
Full Matching in an Observational Study of Coaching for the SAT
Hansen, B. B. (2004) · Journal of the American Statistical Association · doi:10.1198/016214504000000647 · Cited by 648 · see citing works
On the Use of Two-Way Fixed Effects Regression Models for Causal Inference with Panel Data
Imai, K., & Kim, I. S. (2021) · Political Analysis · doi:10.1017/pan.2020.33 · Cited by 623 · see citing works
Self-citationCorrecting for non-compliance in randomized trials using structural nested mean models
Robins, J. M. (1994) · Communication in Statistics- Theory and Methods · doi:10.1080/03610929408831393 · Cited by 534 · see citing works
On causal inference in the presence of interference
Tchetgen, E. J. T., & VanderWeele, T. J. (2010) · Statistical Methods in Medical Research · doi:10.1177/0962280210386779 · Cited by 420 · see citing works
Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis
Doudchenko, N., & Imbens, G. (2016) · doi:10.3386/w22791 · Cited by 410 · see citing works
When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data?
Imai, K., & Kim, I. (2019) · American Journal of Political Science · doi:10.1111/ajps.12417 · Cited by 371 · see citing works
Self-citationTwo-way Fixed Effects Estimators with Heterogeneous Treatment Effects
de Chaisemartin, C., & D'Haultfoeuille, X. (2019) · doi:10.3386/w25904 · Cited by 350 · see citing works
Aronow, P. M., & Samii, C. (2017) · The Annals of Applied Statistics · doi:10.1214/16-aoas1005 · Cited by 347 · see citing works
Matched Sampling for Causal Effects: Contributor Acknowledgments
Rubin, D. (2006) · Cambridge University Press eBooks · doi:10.1017/cbo9780511810725 · Cited by 287 · see citing works
Democracy, War, and Wealth: Lessons from Two Centuries of Inheritance Taxation
Scheve, K. F., & Stasavage, D. (2012) · American Political Science Review · doi:10.1017/s0003055411000517 · Cited by 265 · see citing works
Zubizarreta, J. R. (2012) · Journal of the American Statistical Association · doi:10.1080/01621459.2012.703874 · Cited by 219 · see citing works
Li, Y.-F., Propert, K., & Rosenbaum, P. (2001) · Journal of the American Statistical Association · doi:10.1198/016214501753208573 · Cited by 197 · see citing works
Rosenbaum, P. R., Ross, R. N., & Silber, J. H. (2007) · Journal of the American Statistical Association · doi:10.1198/016214506000001059 · Cited by 163 · see citing works
How to Make Causal Inferences with Time-Series Cross-Sectional Data Under Selection on Observables
Blackwell, M., & Glynn, A. (2018) · American Political Science Review · doi:10.1017/s0003055418000357 · Cited by 131 · see citing works
Estimating Dynamic Treatment Effects in Event Studies With Heterogeneous Treatment Effects
Sun, L., & Abraham, S. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3158747 · Cited by 118 · see citing works
Asymptotic Efficiency in Parametric Structural Models with Parameter-Dependent Support
Hirano, K., & Porter, J. R. (2003) · Econometrica · doi:10.1111/1468-0262.00451 · Cited by 111 · see citing works
Robust Estimation of Inverse Probability Weights for Marginal Structural Models
Imai, K., & Ratkovic, M. (2014) · Journal of the American Statistical Association · doi:10.1080/01621459.2014.956872 · Cited by 89 · see citing works
Self-citationThe Augmented Synthetic Control MethodPreprint
Ben‐Michael, E., Feller, A., & Rothstein, J. M. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3861414 · Cited by 65 · see citing works
Bootstrap Inference of Matching Estimators for Average Treatment Effects
Otsu, T., & Rai, Y. (2016) · Journal of the American Statistical Association · doi:10.1080/01621459.2016.1231613 · Cited by 64 · see citing works
Causal Inference With Interference and Noncompliance in Two-Stage Randomized Experiments
Imai, K., Jiang, Z., & Malani, A. (2020) · Journal of the American Statistical Association · doi:10.1080/01621459.2020.1775612 · Cited by 55 · see citing works
Self-citationSynthetic Controls and Weighted Event Studies with Staggered AdoptionPreprint
Ben‐Michael, E., Feller, A., & Rothstein, J. (2019) · arXiv (Cornell University) · Cited by 12 · see citing works
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West, T. A. P., Wunder, S., Sills, E. O., Börner, J., Rifai, S. W., Neidermeier, A. N., Frey, G., & Kontoleon, A. V. (2023) · Science · doi:10.1126/science.ade3535 · Cited by 430 · see citing works
Liu, L., Wang, Y., & Xu, Y. (2024) · American Journal of Political Science · doi:10.1111/ajps.12723 · Cited by 390 · see citing works
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Lee, B., Zhao, W., Yang, K.-C., Ahn, Y., & Perry, B. L. (2021) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.36687 · Cited by 186 · see citing works
Liu, L., Wang, Y., & Xu, Y. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3555463 · Cited by 142 · see citing works
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Hope, D., & Limberg, J. (2021) · Socio-Economic Review · doi:10.1093/ser/mwab061 · Cited by 103 · see citing works
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Wang, E. H. (2019) · Comparative Political Studies · doi:10.1177/00104140211060276 · Cited by 76 · see citing works
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Bailey, D. H., Jung, A. J., Beltz, A. M., Eronen, M. I., Gische, C., Hamaker, E. L., Kording, K. P., Lebel, C., Lindquist, M. A., Moeller, J., et al. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-01939-z · Cited by 56 · see citing works
A Bayesian Alternative to Synthetic Control for Comparative Case Studies
Pang, X., Liu, L., & Xu, Y. (2022) · Political Analysis · doi:10.1017/pan.2021.22 · Cited by 57 · see citing works
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Arkhangelsky, D., & Imbens, G. (2024) · The Econometrics Journal · doi:10.1093/ectj/utae014 · Cited by 50 · see citing works
Causal Panel Analysis under Parallel Trends: Lessons from a Large Reanalysis Study
CHIU, A., LAN, X., LIU, Z., & XU, Y. (2026) · American Political Science Review · doi:10.1017/s0003055425000243 · Cited by 48 · see citing works
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Li, Z., & Wang, G. (2024) · Management Science · doi:10.1287/mnsc.2021.01010 · Cited by 47 · see citing works
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Li, W., Zhong, H., & Boarnet, M. G. (2024) · Applied Geography · doi:10.1016/j.apgeog.2024.103202 · Cited by 8 · see citing works
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Apeti, A. E., & Edoh, E. D. (2024) · European Journal of Political Economy · doi:10.1016/j.ejpoleco.2024.102571 · Cited by 8 · see citing works
DICKSON, Z. P., & HOBOLT, S. B. (2024) · American Political Science Review · doi:10.1017/s0003055424000741 · Cited by 9 · see citing works
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Merz, L., von Hohenberg, B. C., Bergmann, N. T., Bruskotter, J. T., & Carter, N. (2025) · Science Advances · doi:10.1126/sciadv.adu8945 · Cited by 7 · see citing works
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Wichmann, B., & Wichmann, R. M. (2022) · Economic Modelling · doi:10.1016/j.econmod.2022.105962 · Cited by 7 · see citing works
Vidoli, F., Quintiliani, F., Ivaldi, G., Marinuzzi, G., Porcelli, F., & Tortorella, W. (2023) · Journal of Regional Science · doi:10.1111/jors.12673 · Cited by 7 · see citing works
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Rosenstiel, L. (2024) · American Political Science Review · doi:10.1017/s000305542400011x · Cited by 7 · see citing works
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Reinhardt, R. (2024) · Economics of Disasters and Climate Change · doi:10.1007/s41885-024-00148-2 · Cited by 7 · see citing works
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Cunha, M., Domingos, A. R. M., Rocha, V., & Torres, M. V. D. S. (2021) · Revista de Administração Pública · doi:10.1590/0034-761220200530 · Cited by 7 · see citing works
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Cirulli, V., & Marini, G. (2022) · Annals of Public and Cooperative Economics · doi:10.1111/apce.12374 · Cited by 7 · see citing works
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Egerod, B. C. K. (2023) · The Journal of Politics · doi:10.1086/726957 · Cited by 7 · see citing works
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Pelke, L. (2023) · International Area Studies Review · doi:10.1177/22338659231194945 · Cited by 7 · see citing works
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Nikolov, P., & Adelman, A. (2019) · Social Science Research Network · doi:10.2139/ssrn.3445791 · Cited by 7 · see citing works
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Valentim, A. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3960045 · Cited by 7 · see citing works
Scotti, F., Dell’Agostino, L., Flori, A., & Fabio Pammolli, A. (2023) · Journal of Regional Science · doi:10.1111/jors.12665 · Cited by 6 · see citing works
Stock markets, corporate climate pledges, and the Science-Based Target Initiative
Ko, I., & Prakash, A. (2024) · npj Climate Action · doi:10.1038/s44168-024-00148-8 · Cited by 6 · see citing works
- Authors
- Imai, K., Kim, I. S., & Wang, E. H.
- Affiliations
- Harvard University (US)
- Massachusetts Institute of Technology (US)
- Australian National University (AU)
- Corresponding author
- Imai, Kosuke
- Venue
- American Journal of Political Science
- Publisher
- Wiley
- Published
- 2021-12-11
- Volume
- 67
- Issue
- 3
- Pages
- 587-605
- ISSN
- 0092-5853 (ISSN-L)
- 1540-5907
- OpenAlex
- W4200386818
- Cited by
- 349
- References
- 44
- Citations by year
- 2026: 63 · 2025: 79 · 2024: 80 · 2023: 68 · 2022: 32 · 2021: 13 · 2020: 8 · 2019: 2 · 2018: 1 · 2017: 3
- FWCI
- 35.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Political Science (publishedVersion)
- Funders
- Agence Nationale de la Recherche (ANR-17-EURE-0010)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
- Social Sciences › Sociology and Political Science › Qualitative Comparative Analysis Research
- Keywords
- matching methods, causal inference, time-series cross-sectional data, treatment effect estimation, covariate balance, difference-in-differences, average treatment effect, model dependence, treatment history
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