IDEAS home Printed from https://ideas.repec.org/a/bpj/causin/v1y2013i2p209-234n3.html
   My bibliography  Save this article

Robust Inferences from a Before-and-After Study with Multiple Unaffected Control Groups

Author

Listed:
  • Wang Pengyuan

    (Yahoo! Lab, 701 1st Ave, Sunnyvale, CA 94085, USA)

  • Traskin Mikhail

    (Amazon.com, 207 Boren Ave. N., Seattle, WA 98109)

  • Small Dylan S.

    (Department of Statistics, University of Pennsylvania, 3730 Walnut Street 400 Jon M. Huntsman Hall, Philadelphia, PA 19104, USA)

Abstract

The before-and-after study with multiple unaffected control groups is widely applied to study treatment effects. The current methods usually assume that the control groups’ differences between the before and after periods, i.e. the group time effects, follow a normal distribution. However, there is usually no strong a priori evidence for the normality assumption, and there are not enough control groups to check the assumption. We propose to use a flexible skew-t distribution family to model group time effects, and consider a range of plausible skew-t distributions. Based on the skew-t distribution assumption, we propose a robust-t method to guarantee nominal significance level under a wide range of skew-t distributions, and hence make the inference robust to misspecification of the distribution of group time effects. We also propose a two-stage approach, which has lower power compared to the robust-t method, but provides an opportunity to conduct sensitivity analysis. Hence, the overall method of analysis is to use the robust-t method to test for the overall hypothesized range of shapes of group variation; if the test fails to reject, use the two-stage method to conduct a sensitivity analysis to see if there is a subset of group variation parameters for which we can be confident that there is a treatment effect. We apply the proposed methods to two datasets. One dataset is from the Current Population Survey (CPS) to study the impact of the Mariel Boatlift on Miami unemployment rates between 1979 and 1982.The other dataset contains the student enrollment and grade repeating data in West Germany in the 1960s with which we study the impact of the short school year in 1966–1967 on grade repeating rates.

Suggested Citation

  • Wang Pengyuan & Traskin Mikhail & Small Dylan S., 2013. "Robust Inferences from a Before-and-After Study with Multiple Unaffected Control Groups," Journal of Causal Inference, De Gruyter, vol. 1(2), pages 209-234, June.
  • Handle: RePEc:bpj:causin:v:1:y:2013:i:2:p:209-234:n:3
    DOI: 10.1515/jci-2012-0010
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/jci-2012-0010
    Download Restriction: no

    File URL: https://libkey.io/10.1515/jci-2012-0010?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
    ---><---

    References listed on IDEAS

    as
    1. Card, David & Krueger, Alan B, 1994. "Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania," American Economic Review, American Economic Association, vol. 84(4), pages 772-793, September.
    2. repec:fth:prinin:315 is not listed on IDEAS
    3. David Card, 1990. "The Impact of the Mariel Boatlift on the Miami Labor Market," ILR Review, Cornell University, ILR School, vol. 43(2), pages 245-257, January.
    4. M. C. Jones & M. J. Faddy, 2003. "A skew extension of the t‐distribution, with applications," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 159-174, February.
    5. Stephen G. Donald & Kevin Lang, 2007. "Inference with Difference-in-Differences and Other Panel Data," The Review of Economics and Statistics, MIT Press, vol. 89(2), pages 221-233, May.
    6. Jörn-Steffen Pischke, 2007. "The Impact of Length of the School Year on Student Performance and Earnings: Evidence From the German Short School Years," Economic Journal, Royal Economic Society, vol. 117(523), pages 1216-1242, October.
    7. Meyer, Bruce D, 1995. "Natural and Quasi-experiments in Economics," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 151-161, April.
    8. David Card & Alan Krueger, 1993. "Minimum Wages and Employment: A Case Study of the Fast Food Industry in New Jersey and Pennsylvania," Working Papers 694, Princeton University, Department of Economics, Industrial Relations Section..
    9. Murray, D.M. & Varnell, S.P. & Blitstein, J.L., 2004. "Design and Analysis of Group-Randomized Trials: A Review of Recent Methodological Developments," American Journal of Public Health, American Public Health Association, vol. 94(3), pages 423-432.
    10. MacKinnon, James G. & White, Halbert, 1985. "Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties," Journal of Econometrics, Elsevier, vol. 29(3), pages 305-325, September.
    11. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:fgv:eesptd:411 is not listed 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. Aydemir, Abdurrahman B. & Kırdar, Murat G., 2017. "Quasi-experimental impact estimates of immigrant labor supply shocks: The role of treatment and comparison group matching and relative skill composition," European Economic Review, Elsevier, vol. 98(C), pages 282-315.
    2. 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.
    3. Dale Belman & Paul Wolfson & Kritkorn Nawakitphaitoon, 2015. "Who Is Affected by the Minimum Wage?," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 54(4), pages 582-621, October.
    4. 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.
    5. Athey, Susan & Imbens, Guido W., 2022. "Design-based analysis in Difference-In-Differences settings with staggered adoption," Journal of Econometrics, Elsevier, vol. 226(1), pages 62-79.
    6. Belman, Dale. & Wolfson, Paul J., 2016. "What does the minimum wage do in developing countries? : A review of studies and methodologies," ILO Working Papers 994893283402676, International Labour Organization.
    7. Roth, Jonathan & Sant’Anna, Pedro H.C. & Bilinski, Alyssa & Poe, John, 2023. "What’s trending in difference-in-differences? A synthesis of the recent econometrics literature," Journal of Econometrics, Elsevier, vol. 235(2), pages 2218-2244.
    8. 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.
    9. Davide Viviano & Jelena Bradic, 2021. "Dynamic covariate balancing: estimating treatment effects over time with potential local projections," Papers 2103.01280, arXiv.org, revised Jan 2024.
    10. van der Klaauw, Bas, 2014. "From micro data to causality: Forty years of empirical labor economics," Labour Economics, Elsevier, vol. 30(C), pages 88-97.
    11. Timothy G. Conley & Christopher R. Taber, 2011. "Inference with "Difference in Differences" with a Small Number of Policy Changes," The Review of Economics and Statistics, MIT Press, vol. 93(1), pages 113-125, February.
    12. Eric James Stokan, 2019. "An Estimate of the Local Economic Impact of State-Level Earned Income Tax Credits," Economic Development Quarterly, , vol. 33(3), pages 170-186, August.
    13. Matthew D. Webb, 2023. "Reworking wild bootstrap‐based inference for clustered errors," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(3), pages 839-858, August.
    14. Committee, Nobel Prize, 2021. "Answering causal questions using observational data," Nobel Prize in Economics documents 2021-2, Nobel Prize Committee.
    15. Pécastaing, Nicolas & Chávez, Carlos, 2020. "The impact of El Niño phenomenon on dry forest-dependent communities' welfare in the northern coast of Peru," Ecological Economics, Elsevier, vol. 178(C).
    16. Kelly Bedard & Peter J. Kuhn, 2013. "Making Nutritional Information Digestible: Effects of a Receipt-Based Intervention on Restaurant Purchases," NBER Working Papers 19654, National Bureau of Economic Research, Inc.
    17. Mustapha Douch & Terence Huw Edwards, 2022. "The bilateral trade effects of announcement shocks: Brexit as a natural field experiment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 305-329, March.
    18. Lewis, Ethan & Peri, Giovanni, 2015. "Immigration and the Economy of Cities and Regions," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 625-685, Elsevier.
    19. Lin, Boqiang & Li, Xuehui, 2011. "The effect of carbon tax on per capita CO2 emissions," Energy Policy, Elsevier, vol. 39(9), pages 5137-5146, September.
    20. James G. MacKinnon, 2019. "How cluster‐robust inference is changing applied econometrics," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 52(3), pages 851-881, August.

    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:bpj:causin:v:1:y:2013:i:2:p:209-234:n:3. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.