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An Introduction to the Augmented Inverse Propensity Weighted Estimator

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  • Glynn, Adam N.
  • Quinn, Kevin M.

Abstract

In this paper, we discuss an estimator for average treatment effects (ATEs) known as the augmented inverse propensity weighted (AIPW) estimator. This estimator has attractive theoretical properties and only requires practitioners to do two things they are already comfortable with: (1) specify a binary regression model for the propensity score, and (2) specify a regression model for the outcome variable. Perhaps the most interesting property of this estimator is its so-called “double robustness.†Put simply, the estimator remains consistent for the ATE if either the propensity score model or the outcome regression is misspecified but the other is properly specified. After explaining the AIPW estimator, we conduct a Monte Carlo experiment that compares the finite sample performance of the AIPW estimator to three common competitors: a regression estimator, an inverse propensity weighted (IPW) estimator, and a propensity score matching estimator. The Monte Carlo results show that the AIPW estimator has comparable or lower mean square error than the competing estimators when the propensity score and outcome models are both properly specified and, when one of the models is misspecified, the AIPW estimator is superior.

Suggested Citation

  • Glynn, Adam N. & Quinn, Kevin M., 2010. "An Introduction to the Augmented Inverse Propensity Weighted Estimator," Political Analysis, Cambridge University Press, vol. 18(1), pages 36-56, January.
  • Handle: RePEc:cup:polals:v:18:y:2010:i:01:p:36-56_01
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    1. Sokbae Lee & Ryo Okui & Yoon†Jae Whang, 2017. "Doubly robust uniform confidence band for the conditional average treatment effect function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1207-1225, November.
    2. Noemi Kreif & Richard Grieve & Rosalba Radice & Zia Sadique & Roland Ramsahai & Jasjeet S. Sekhon, 2012. "Methods for Estimating Subgroup Effects in Cost-Effectiveness Analyses That Use Observational Data," Medical Decision Making, , vol. 32(6), pages 750-763, November.
    3. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2010. "How to Control for Many Covariates? Reliable Estimators Based on the Propensity Score," IZA Discussion Papers 5268, Institute of Labor Economics (IZA).
    4. Pontines, Victor, 2018. "Self-selection and treatment effects: Revisiting the effectiveness of foreign exchange intervention," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 299-316.
    5. Melanie Prague & Rui Wang & Alisa Stephens & Eric Tchetgen Tchetgen & Victor DeGruttola, 2016. "Accounting for interactions and complex inter‐subject dependency in estimating treatment effect in cluster‐randomized trials with missing outcomes," Biometrics, The International Biometric Society, vol. 72(4), pages 1066-1077, December.
    6. Òscar Jordà & Alan M. Taylor, 2016. "The Time for Austerity: Estimating the Average Treatment Effect of Fiscal Policy," Economic Journal, Royal Economic Society, vol. 126(590), pages 219-255, February.
    7. Smale, Melinda & Assima, Amidou & Kergna, Alpha & Thériault, Véronique & Weltzien, Eva, 2018. "Farm family effects of adopting improved and hybrid sorghum seed in the Sudan Savanna of West Africa," Food Policy, Elsevier, vol. 74(C), pages 162-171.
    8. Òscar Jordà & Moritz Schularick & Alan M. Taylor, 2016. "The great mortgaging: housing finance, crises and business cycles," Economic Policy, CEPR;CES;MSH, vol. 31(85), pages 107-152.
    9. Zeqin Liu & Zongwu Cai & Ying Fang & Ming Lin, 2019. "Statistical Analysis and Evaluation of Macroeconomic Policies: A Selective Review," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201904, University of Kansas, Department of Economics, revised Mar 2019.
    10. Konan Alain N'ghauran & Corinne Autant-Bernard, 2020. "Assessing the collaboration and network additionality of innovation policies: a counterfactual approach to the French cluster policy," Working Papers halshs-02482546, HAL.
    11. Bailey, Michael & Hopkins, Daniel J. & Rogers, Todd, 2013. "Unresponsive and Unpersuaded: The Unintended Consequences of Voter Persuasion Efforts," Working Paper Series rwp13-034, Harvard University, John F. Kennedy School of Government.
    12. Pymont, Carly & McNamee, Paul & Butterworth, Peter, 2018. "Out-of-pocket costs, primary care frequent attendance and sample selection: Estimates from a longitudinal cohort design," Health Policy, Elsevier, vol. 122(6), pages 652-659.
    13. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
    14. Moritz Schularick & Ilhyock Shim, 2017. "Household credit in Asia-Pacific," BIS Papers chapters, in: Bank for International Settlements (ed.), Financial systems and the real economy, volume 91, pages 129-144, Bank for International Settlements.
    15. Aloyce R. Kaliba & Anne G. Gongwe & Kizito Mazvimavi & Ashagre Yigletu, 2021. "Impact of Adopting Improved Seeds on Access to Broader Food Groups Among Small-Scale Sorghum Producers in Tanzania," SAGE Open, , vol. 11(1), pages 21582440209, January.
    16. Heigle, Julia & Pfeiffer, Friedhelm, 2019. "An analysis of selected labor market outcomes of college dropouts in Germany: A machine learning estimation approach. Research report," ZEW Expertises, ZEW - Leibniz Centre for European Economic Research, number 222378, February.
    17. Brandon Schaufele, 2013. "Dissent in Parliament as Reputation Building," Working Papers 1301E, University of Ottawa, Department of Economics.
    18. Garriga, Anna & Pennoni, Fulvia, 2017. "The influence of parental divorce, parental temporary separation and parental relationship quality on children’s school readiness," MPRA Paper 82892, University Library of Munich, Germany.
    19. M. Taha Kasim & Benjamin Ukert, 2021. "The impact of WIC participation on tobacco use and alcohol consumption," Contemporary Economic Policy, Western Economic Association International, vol. 39(3), pages 608-625, July.
    20. Mertens, Kewan & Jacobs, Liesbet & Maes, Jan & Kabaseke, Clovis & Maertens, Miet & Poesen, Jean & Kervyn, Matthieu & Vranken, Liesbet, 2015. "The impact of landslides on household income in tropical regions: a case study from the Rwenzori Mountains in Uganda," Working Papers 229008, Katholieke Universiteit Leuven, Centre for Agricultural and Food Economics.
    21. Revilla, Elena & Rodríguez-Prado, Beatriz, 2018. "Bulding ambidexterity through creativity mechanisms: Contextual drivers of innovation success," Research Policy, Elsevier, vol. 47(9), pages 1611-1625.
    22. Long, Wenjin & Pang, Xiaopeng & Dong, Xiao-yuan & Zeng, Junxia, 2020. "Is rented accommodation a good choice for primary school students' academic performance? – Evidence from rural China," China Economic Review, Elsevier, vol. 62(C).

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