IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v197y2017i1p65-75.html
   My bibliography  Save this article

Estimation of average treatment effects with panel data: Asymptotic theory and implementation

Author

Listed:
  • Li, Kathleen T.
  • Bell, David R.

Abstract

Hsiao, Ching and Wan (2012) propose a novel method to estimate the average treatment effect using panel data. In this paper, we accomplish the following: (i) We relax some of the distributional assumptions made in HCW and show that the HCW method works for a much wider range of data generating processes; (ii) We derive the asymptotic distribution of HCW’s average treatment effect estimator which facilitates inference; (iii) When there exists a large number of control units, we propose using the LASSO method to select control units. We show that the LASSO method is computationally more efficient compared to conventional model selection criteria. Moreover, the LASSO method leads to more accurate out-of-sample prediction results than many commonly adopted approaches such as BIC, AIC, AICC and the leave-many-out cross validation methods (Du and Zhang, 2015).

Suggested Citation

  • Li, Kathleen T. & Bell, David R., 2017. "Estimation of average treatment effects with panel data: Asymptotic theory and implementation," Journal of Econometrics, Elsevier, vol. 197(1), pages 65-75.
    • Handle: RePEc:eee:econom:v:197:y:2017:i:1:p:65-75
    DOI: 10.1016/j.jeconom.2016.01.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304407616302019
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jeconom.2016.01.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
    2. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    3. Ashenfelter, Orley C, 1978. "Estimating the Effect of Training Programs on Earnings," The Review of Economics and Statistics, MIT Press, vol. 60(1), pages 47-57, February.
    4. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    5. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    6. Ouyang, Min & Peng, Yulei, 2015. "The treatment-effect estimation: A case study of the 2008 economic stimulus package of China," Journal of Econometrics, Elsevier, vol. 188(2), pages 545-557.
    7. Cheng Hsiao & H. Steve Ching & Shui Ki Wan, 2012. "A Panel Data Approach For Program Evaluation: Measuring The Benefits Of Political And Economic Integration Of Hong Kong With Mainland China," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 705-740, August.
    8. Susan Athey & Guido W. Imbens, 2006. "Identification and Inference in Nonlinear Difference-in-Differences Models," Econometrica, Econometric Society, vol. 74(2), pages 431-497, March.
    9. Bai, ChongEn & Li, Qi & Ouyang, Min, 2014. "Property taxes and home prices: A tale of two cities," Journal of Econometrics, Elsevier, vol. 180(1), pages 1-15.
    10. Ashenfelter, Orley & Card, David, 1985. "Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs," The Review of Economics and Statistics, MIT Press, vol. 67(4), pages 648-660, November.
    11. Du, Zaichao & Zhang, Lin, 2015. "Home-purchase restriction, property tax and housing price in China: A counterfactual analysis," Journal of Econometrics, Elsevier, vol. 188(2), pages 558-568.
    12. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(1), pages 1-19.
    13. Bai, Jushan & Li, Kunpeng, 2010. "Theory and methods of panel data models with interactive effects," MPRA Paper 43441, University Library of Munich, Germany, revised Dec 2012.
    14. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    15. Carrasco, Marine & Chen, Xiaohong, 2002. "Mixing And Moment Properties Of Various Garch And Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 18(1), pages 17-39, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carvalho, Carlos & Masini, Ricardo & Medeiros, Marcelo C., 2018. "ArCo: An artificial counterfactual approach for high-dimensional panel time-series data," Journal of Econometrics, Elsevier, vol. 207(2), pages 352-380.
    2. Shi, Zhentao & Huang, Jingyi, 2023. "Forward-selected panel data approach for program evaluation," Journal of Econometrics, Elsevier, vol. 234(2), pages 512-535.
    3. Carlos Viana de Carvalho & Ricardo Masini & Marcelo Cunha Medeiros, 2016. "The perils of Counterfactual Analysis with Integrated Processes," Textos para discussão 654, Department of Economics PUC-Rio (Brazil).
    4. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Mar 2024.
    5. Zhang, Linling & Long, Ruyin & Chen, Hong, 2019. "Do car restriction policies effectively promote the development of public transport?," World Development, Elsevier, vol. 119(C), pages 100-110.
    6. Li, Xiao & Qiao, Yuanbo & Shi, Lei, 2019. "Has China's war on pollution slowed the growth of its manufacturing and by how much? Evidence from the Clean Air Action," China Economic Review, Elsevier, vol. 53(C), pages 271-289.
    7. Sayoni Roychowdhury & Indrila Ganguly & Abhik Ghosh, 2021. "Robust Estimation of Average Treatment Effects from Panel Data," Papers 2112.13228, arXiv.org, revised Dec 2022.
    8. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    9. Wang, Huiqiang, 2016. "Estimating the health impacts of food safety interventions: Optimal counterfactual selections via information criteria in small samples," Food Policy, Elsevier, vol. 63(C), pages 44-52.
    10. Zhentao Shi & Jingyi Huang, 2019. "Forward-Selected Panel Data Approach for Program Evaluation," Papers 1908.05894, arXiv.org, revised Apr 2021.
    11. Hongjun Li & Zheng Li & Cheng Hsiao, 2023. "Assessing the impacts of pandemic and the increase in minimum down payment rate on Shanghai housing prices," Empirical Economics, Springer, vol. 64(6), pages 2661-2682, June.
    12. Qi Li & Wei Long, 2018. "Do parole abolition and Truth-in-Sentencing deter violent crimes in Virginia?," Empirical Economics, Springer, vol. 55(4), pages 2027-2045, December.
    13. Ke, Xiao & Chen, Haiqiang & Hong, Yongmiao & Hsiao, Cheng, 2017. "Do China's high-speed-rail projects promote local economy?—New evidence from a panel data approach," China Economic Review, Elsevier, vol. 44(C), pages 203-226.
    14. Lechner, Michael, 2011. "The Estimation of Causal Effects by Difference-in-Difference Methods," Foundations and Trends(R) in Econometrics, now publishers, vol. 4(3), pages 165-224, November.
    15. Li, Hongjun & Li, Qi & Shi, Yutang, 2017. "Determining the number of factors when the number of factors can increase with sample size," Journal of Econometrics, Elsevier, vol. 197(1), pages 76-86.
    16. Gao, Yichen & Li, Hongjun & Li, Qi, 2022. "The misalignments in Chinese real effective exchange rate from 1994 to 2020: A counterfactual analysis," China Economic Review, Elsevier, vol. 75(C).
    17. Li, Sujuan & Liu, Jiaguo & Kong, Yudan, 2021. "Pilot free trade zones and Chinese port-listed companies performance: An empirical research based on quasi-natural experiment," Transport Policy, Elsevier, vol. 111(C), pages 125-137.
    18. Fan, Jianqing & Liao, Yuan & Shi, Xiaofeng, 2015. "Risks of large portfolios," Journal of Econometrics, Elsevier, vol. 186(2), pages 367-387.
    19. Du, Zaichao & Yin, Hua & Zhang, Lin, 2022. "Foreign buyer taxes and house prices in Canada: A tale of two cities," Journal of Housing Economics, Elsevier, vol. 55(C).
    20. Volpe Martincus, Christian & Carballo, Jerónimo, 2010. "Beyond the average effects: The distributional impacts of export promotion programs in developing countries," Journal of Development Economics, Elsevier, vol. 92(2), pages 201-214, July.

    More about this item

    Keywords

    Average treatment effects; Asymptotic distribution; LASSO method;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:econom:v:197:y:2017:i:1:p:65-75. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.