When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data?
Many researchers use unit fixed effects regression models as their default methods for causal inference with longitudinal data. We show that the ability of these models to adjust for unobserved time-invariant confounders comes at the expense of dynamic causal relationships, which are permitted under...
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| Vydané v: | American journal of political science Ročník 63; číslo 2; s. 467 - 490 |
|---|---|
| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Oxford
Wiley Subscription Services, Inc
01.04.2019
Blackwell Publishing Ltd |
| Predmet: | |
| ISSN: | 0092-5853, 1540-5907 |
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| Abstract | Many researchers use unit fixed effects regression models as their default methods for causal inference with longitudinal data. We show that the ability of these models to adjust for unobserved time-invariant confounders comes at the expense of dynamic causal relationships, which are permitted under an alternative selection-on-observables approach. Using the nonparametric directed acyclic graph, we highlight two key causal identification assumptions of unit fixed effects models: Past treatments do not directly influence current outcome, and past outcomes do not affect current treatment. Furthermore, we introduce a new nonparametric matching framework that elucidates how various unit fixed effects models implicitly compare treated and control observations to draw causal inference. By establishing the equivalence between matching and weighted unit fixed effects estimators, this framework enables a diverse set of identification strategies to adjust for unobservables in the absence of dynamic causal relationships between treatment and outcome variables. We illustrate the proposed methodology through its application to the estimation of GATT membership effects on dyadic trade volume. |
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| AbstractList | Many researchers use unit fixed effects regression models as their default methods for causal inference with longitudinal data. We show that the ability of these models to adjust for unobserved time‐invariant confounders comes at the expense of dynamic causal relationships, which are permitted under an alternative selection‐on‐observables approach. Using the nonparametric directed acyclic graph, we highlight two key causal identification assumptions of unit fixed effects models: Past treatments do not directly influence current outcome, and past outcomes do not affect current treatment. Furthermore, we introduce a new nonparametric matching framework that elucidates how various unit fixed effects models implicitly compare treated and control observations to draw causal inference. By establishing the equivalence between matching and weighted unit fixed effects estimators, this framework enables a diverse set of identification strategies to adjust for unobservables in the absence of dynamic causal relationships between treatment and outcome variables. We illustrate the proposed methodology through its application to the estimation of GATT membership effects on dyadic trade volume. Many researchers use unit fixed effects regression models as their default methods for causal inference with longitudinal data. We show that the ability of these models to adjust for unobserved time‐invariant confounders comes at the expense of dynamic causal relationships, which are permitted under an alternative selection‐on‐observables approach. Using the nonparametric directed acyclic graph, we highlight two key causal identification assumptions of unit fixed effects models: Past treatments do not directly influence current outcome, and past outcomes do not affect current treatment. Furthermore, we introduce a new nonparametric matching framework that elucidates how various unit fixed effects models implicitly compare treated and control observations to draw causal inference. By establishing the equivalence between matching and weighted unit fixed effects estimators, this framework enables a diverse set of identification strategies to adjust for unobservables in the absence of dynamic causal relationships between treatment and outcome variables. We illustrate the proposed methodology through its application to the estimation of GATT membership effects on dyadic trade volume. |
| Author | Kim, In Song Imai, Kosuke |
| Author_xml | – sequence: 1 givenname: Kosuke surname: Imai fullname: Imai, Kosuke – sequence: 2 givenname: In Song surname: Kim fullname: Kim, In Song |
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| Cites_doi | 10.1093/pan/mpl013 10.1007/s11079-005-5329-9 10.1017/CBO9781139025751 10.1257/aer.97.5.2019 10.2307/2526245 10.1111/j.1468-0262.2006.00655.x 10.1146/annurev.polisci.4.1.271 10.1257/000282803321455214 10.3386/w24814 10.1214/ss/1177012032 10.1111/j.0012-9682.2008.00821.x 10.1086/653690 10.1017/CBO9780511810725 10.2307/2529681 10.1017/psrm.2014.7 10.1017/S0003055418000357 10.1257/aer.89.1.215 10.1111/j.1540-5907.2012.00626.x 10.1111/ajps.12185 10.3368/jhr.50.2.301 10.1353/wp.2006.0010 10.1080/01621459.2016.1231613 10.1257/aer.97.5.2005 10.1214/09-STS313 10.1016/j.jeconom.2006.10.009 10.1257/000282804322970724 10.1198/016214506000000636 10.1093/pan/mpl012 10.1111/j.1468-0084.1987.mp49004006.x 10.2307/2297968 10.2307/1912934 10.1515/9781400829828 10.1016/j.jinteco.2006.07.007 10.1093/pan/mpv018 10.1017/CBO9780511803161 10.1017/psrm.2014.32 10.1017/CBO9780511614491.004 10.1097/00001648-200009000-00011 10.1086/691058 10.1080/01621459.2012.682537 10.1162/0034653053970320 |
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| Copyright | 2019 Midwest Political Science Association 2019, Midwest Political Science Association 2019 by the Midwest Political Science Association |
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| Notes | The methods described in this article can be implemented via the open‐source statistical software available through the Comprehensive R Archive Network The initial draft of this article was entitled “On the Use of Linear Fixed Effects Regression Estimators for Causal Inference” (July 2011). We thank Alberto Abadie, Mike Bailey, Neal Beck, Matias Cattaneo, Naoki Egami, Erin Hartman, Danny Hidalgo, Rocio Titiunik, Yuki Shiraito, and Teppei Yamamoto for helpful comments. wfe: Weighted Linear Fixed Effects Estimators for Causal Inference http://cran.r‐project.org/package=wfe ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
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| References | 2006; 74 1980b; 21 1991; 58 2015; 3 2010 2015; 50 2007; 141 2009 1999; 89 2007 2006 2008; 76 2007; 72 2003 2002 2003; 93 2007; 97 2017; 112 2012; 107 2007; 15 2015; 23 2004; 94 2010; 25 2005a; 87 2015; 60 2010; 118 2005b 2013; 57 2001; 4 2018; 112 2000; 11 2017; 79 1973; 29 2018 2013; 82 2017 2015 2005; 16 2006; 101 2005; 57 1990; 5 1980a; 48 1987; 49 e_1_2_9_31_1 e_1_2_9_50_1 e_1_2_9_10_1 e_1_2_9_35_1 e_1_2_9_12_1 e_1_2_9_33_1 e_1_2_9_14_1 e_1_2_9_39_1 e_1_2_9_16_1 e_1_2_9_37_1 e_1_2_9_41_1 e_1_2_9_20_1 e_1_2_9_45_1 e_1_2_9_24_1 e_1_2_9_43_1 e_1_2_9_8_1 e_1_2_9_6_1 e_1_2_9_4_1 e_1_2_9_2_1 e_1_2_9_26_1 e_1_2_9_49_1 e_1_2_9_28_1 e_1_2_9_47_1 e_1_2_9_30_1 e_1_2_9_11_1 e_1_2_9_34_1 Chernozhukov Victor (e_1_2_9_18_1) 2013; 82 e_1_2_9_13_1 e_1_2_9_32_1 Wooldridge Jeffrey M (e_1_2_9_51_1) 2010 Feenstra Robert C (e_1_2_9_22_1) 2003 e_1_2_9_15_1 e_1_2_9_38_1 e_1_2_9_36_1 e_1_2_9_19_1 e_1_2_9_42_1 Duflo Esther (e_1_2_9_21_1) 2007 e_1_2_9_40_1 e_1_2_9_46_1 Brito Carlos (e_1_2_9_17_1) 2002 e_1_2_9_23_1 e_1_2_9_44_1 e_1_2_9_7_1 e_1_2_9_5_1 e_1_2_9_3_1 e_1_2_9_9_1 e_1_2_9_25_1 e_1_2_9_27_1 e_1_2_9_48_1 e_1_2_9_29_1 |
| References_xml | – volume: 49 start-page: 431 issue: 4 year: 1987 end-page: 34 article-title: Computing Robust Standard Errors for Within‐Groups Estimators publication-title: Oxford Bulletin of Economics and Statistics – volume: 89 start-page: 215 issue: 1 year: 1999 end-page: 48 article-title: An Economic Theory of GATT publication-title: American Economic Review – volume: 87 start-page: 385 issue: 2 year: 2005a end-page: 390 article-title: Fixed‐Effects and Related Estimators for Correlated Random‐Coefficient and Treatment‐Effect Panel Data Models publication-title: Review of Economics and Statistics – year: 2009 – volume: 57 start-page: 453 issue: 4 year: 2005 end-page: 78 article-title: An Exclusive Country Club: The Effects of the GATT on Trade, 1950‐94 publication-title: World Politics – volume: 25 start-page: 1 issue: 1 year: 2010 end-page: 21 article-title: Matching Methods for Causal Inference: A Review and a Look Forward publication-title: Statistical Science – volume: 74 start-page: 235 issue: 1 year: 2006 end-page: 67 article-title: Large Sample Properties of Matching Estimators for Average Treatment Effects publication-title: Econometrica – volume: 118 start-page: 433 issue: 3 year: 2010 end-page: 84 article-title: Innovation, Firm Dynamics, and International Trade publication-title: Journal of political economy – volume: 15 start-page: 199 issue: 3 year: 2007 end-page: 236 article-title: Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference publication-title: Political Analysis – volume: 23 start-page: 564 issue: 4 year: 2015 end-page: 77 article-title: Cluster–Robust Variance Estimation for Dyadic Data publication-title: Political Analysis – year: 2003 – volume: 82 start-page: 535 issue: 2 year: 2013 end-page: 80 article-title: Average and Quantile Effects in Nonseparable Panel Models publication-title: Econometrica – volume: 76 start-page: 155 issue: 1 year: 2008 end-page: 74 article-title: Heteroskedasticity‐Robust Standard Errors for Fixed Effects Panel Data Regression publication-title: Econometrica – volume: 58 start-page: 277 issue: 2 year: 1991 end-page: 97 article-title: Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations publication-title: Review of Economic Studies – volume: 16 start-page: 7 year: 2005 end-page: 22 article-title: Does the WTO Make Trade More Stable publication-title: Open Economies Review – volume: 50 start-page: 301 issue: 2 year: 2015 end-page: 16 article-title: What are we weighting for publication-title: Journal of Human Resources – volume: 79 start-page: 964 issue: 3 year: 2017 end-page: 78 article-title: Joining the Club: Accession to the GATT/WTO publication-title: Journal of Politics – volume: 101 start-page: 1398 issue: 476 year: 2006 end-page: 1407 article-title: What Do Randomized Studies of Housing Mobility Demonstrate? Causal Inference in the Face of Interference publication-title: Journal of the American Statistical Association – volume: 15 start-page: 101 issue: 2 year: 2007 end-page: 23 article-title: A Lot More to Do: The Sensitivity of Time‐Series Cross‐Section Analyses to Simple Alternative Specifications publication-title: Political Analysis – year: 2018 – volume: 60 start-page: 250 issue: 1 year: 2015 end-page: 67 article-title: Does Regression Produce Representative Estimates of Causal Effects publication-title: American Journal of Political Science – volume: 97 start-page: 2005 issue: 5 year: 2007 end-page: 18 article-title: Do We Really Know That the WTO Increases Trade? Comment publication-title: The American Economic Review – year: 2010 – volume: 107 start-page: 833 issue: 498 year: 2012 end-page: 43 article-title: A Martingale Representation for Matching Estimators publication-title: Journal of the American Statistical Association – volume: 112 start-page: 1720 issue: 520 year: 2017 end-page: 32 article-title: Bootstrap Inference of Matching Estimators for Average Treatment Effects publication-title: Journal of the American Statistical Association – volume: 48 start-page: 817 issue: 4 year: 1980a end-page: 838 article-title: A Heteroskedasticity‐Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity publication-title: Econometrica – start-page: 27 year: 2005b end-page: 55 – volume: 3 start-page: 133 issue: 1 year: 2015 end-page: 53 article-title: Explaining Fixed Effects: Random Effects Modeling of Time‐Series Cross‐Sectional and Panel Data publication-title: Political Science Research and Methods – volume: 29 start-page: 121 year: 1973 end-page: 30 article-title: Regression toward the Mean in Uncontrolled Clinical Studies publication-title: Biometrics – volume: 3 start-page: 399 issue: 2 year: 2015 end-page: 408 article-title: Should I Use Fixed or Random Effects publication-title: Political Science Research and Methods – volume: 5 start-page: 472 year: 1990 end-page: 80 article-title: Comments on “On the Application of Probability Theory to Agricultural Experiments. Essay on Principles. Section 9” by J. Splawa‐Neyman translated from the Polish and edited by D. M. Dabrowska and T. P. Speed publication-title: Statistical Science – volume: 11 start-page: 550 issue: 5 year: 2000 end-page: 60 article-title: Marginal Structural Models and Causal Inference in Epidemiology publication-title: Epidemiology – volume: 141 start-page: 597 year: 2007 end-page: 620 article-title: Asymptotic Properties of a Robust Variance Matrix Estimator for Panel Data when is Large publication-title: Journal of Econometrics – year: 2006 – volume: 97 start-page: 2019 issue: 5 year: 2007 end-page: 25 article-title: Do We Really Know That the WTO Increases Trade? Reply publication-title: American Economic Review – start-page: 3895 year: 2007 end-page: 3962 – volume: 94 start-page: 98 issue: 1 year: 2004 end-page: 114 article-title: Do We Really Know That the WTO Increases Trade publication-title: American Economic Review – volume: 57 start-page: 504 issue: 2 year: 2013 end-page: 20 article-title: A Framework for Dynamic Causal Inference in Political Science publication-title: American Journal of Political Science – volume: 112 start-page: 1067 issue: 4 year: 2018 end-page: 1082 – volume: 93 start-page: 170 issue: 1 year: 2003 end-page: 92 article-title: Gravity with Gravitas: A Solution to the Border Puzzle publication-title: American Economic Review – start-page: 85 year: 2002 end-page: 93 – volume: 4 start-page: 271 year: 2001 end-page: 93 article-title: Time‐Series‐Cross‐Section Data: What Have We Learned in the Past Few Years publication-title: Annual Review Political Science – year: 2017 – volume: 72 start-page: 151 issue: 1 year: 2007 end-page: 75 article-title: The WTO promotes trade, strongly but unevenly publication-title: Journal of International Economics – volume: 21 start-page: 149 issue: 1 year: 1980b end-page: 70 article-title: Using Least Squares to Approximate Unknown Regression Functions publication-title: International Economic Review – year: 2015 – ident: e_1_2_9_26_1 doi: 10.1093/pan/mpl013 – start-page: 85 volume-title: Proceedings of the 18th Conference of Uncertainty in Artificial Intelligence year: 2002 ident: e_1_2_9_17_1 – ident: e_1_2_9_35_1 doi: 10.1007/s11079-005-5329-9 – ident: e_1_2_9_29_1 doi: 10.1017/CBO9781139025751 – ident: e_1_2_9_36_1 doi: 10.1257/aer.97.5.2019 – ident: e_1_2_9_47_1 doi: 10.2307/2526245 – ident: e_1_2_9_2_1 doi: 10.1111/j.1468-0262.2006.00655.x – ident: e_1_2_9_13_1 doi: 10.1146/annurev.polisci.4.1.271 – ident: e_1_2_9_39_1 – ident: e_1_2_9_4_1 doi: 10.1257/000282803321455214 – ident: e_1_2_9_8_1 doi: 10.3386/w24814 – ident: e_1_2_9_37_1 doi: 10.1214/ss/1177012032 – ident: e_1_2_9_42_1 doi: 10.1111/j.0012-9682.2008.00821.x – start-page: 3895 volume-title: Handbook of Development Economics year: 2007 ident: e_1_2_9_21_1 – ident: e_1_2_9_11_1 doi: 10.1086/653690 – ident: e_1_2_9_38_1 doi: 10.1017/CBO9780511810725 – volume: 82 start-page: 535 issue: 2 year: 2013 ident: e_1_2_9_18_1 article-title: Average and Quantile Effects in Nonseparable Panel Models publication-title: Econometrica – ident: e_1_2_9_27_1 – ident: e_1_2_9_30_1 doi: 10.2307/2529681 – ident: e_1_2_9_14_1 doi: 10.1017/psrm.2014.7 – ident: e_1_2_9_16_1 doi: 10.1017/S0003055418000357 – ident: e_1_2_9_12_1 doi: 10.1257/aer.89.1.215 – ident: e_1_2_9_15_1 doi: 10.1111/j.1540-5907.2012.00626.x – ident: e_1_2_9_9_1 doi: 10.1111/ajps.12185 – ident: e_1_2_9_41_1 doi: 10.3368/jhr.50.2.301 – ident: e_1_2_9_24_1 doi: 10.1353/wp.2006.0010 – ident: e_1_2_9_31_1 doi: 10.1080/01621459.2016.1231613 – ident: e_1_2_9_45_1 doi: 10.1257/aer.97.5.2005 – ident: e_1_2_9_43_1 doi: 10.1214/09-STS313 – ident: e_1_2_9_28_1 – ident: e_1_2_9_25_1 doi: 10.1016/j.jeconom.2006.10.009 – ident: e_1_2_9_34_1 doi: 10.1257/000282804322970724 – ident: e_1_2_9_40_1 doi: 10.1198/016214506000000636 – ident: e_1_2_9_48_1 doi: 10.1093/pan/mpl012 – ident: e_1_2_9_6_1 doi: 10.1111/j.1468-0084.1987.mp49004006.x – ident: e_1_2_9_7_1 doi: 10.2307/2297968 – ident: e_1_2_9_46_1 doi: 10.2307/1912934 – ident: e_1_2_9_5_1 doi: 10.1515/9781400829828 – ident: e_1_2_9_44_1 doi: 10.1016/j.jinteco.2006.07.007 – ident: e_1_2_9_10_1 doi: 10.1093/pan/mpv018 – ident: e_1_2_9_32_1 doi: 10.1017/CBO9780511803161 – ident: e_1_2_9_19_1 doi: 10.1017/psrm.2014.32 – ident: e_1_2_9_50_1 doi: 10.1017/CBO9780511614491.004 – ident: e_1_2_9_23_1 – ident: e_1_2_9_33_1 doi: 10.1097/00001648-200009000-00011 – ident: e_1_2_9_20_1 doi: 10.1086/691058 – volume-title: Econometric Analysis of Cross‐Section and Panel Data year: 2010 ident: e_1_2_9_51_1 – volume-title: Advanced International Trade year: 2003 ident: e_1_2_9_22_1 – ident: e_1_2_9_3_1 doi: 10.1080/01621459.2012.682537 – ident: e_1_2_9_49_1 doi: 10.1162/0034653053970320 |
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| Snippet | Many researchers use unit fixed effects regression models as their default methods for causal inference with longitudinal data. We show that the ability of... Many researchers use unit fixed effects regression models as their default methods for causal inference with longitudinal data. We show that the ability of... |
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| SubjectTerms | AJPS WORKSHOP Causal models Causality Data analysis Economic models Estimation GATT Identification Inference Membership Regression analysis Treatment methods |
| Title | When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data? |
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