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Review on Difference in Differences

Author

Listed:
  • Myoung-jae Lee

    (Korea University)

  • Yasuyuki Sawada

    (Asian Development Bank)

Abstract

Difference in differences (DD) is one of the most popular approaches in economics and other disciplines of social sciences. This paper provides a review on the basics and recent advances in DD from a personal perspective. Details on DD identification and estimation using panel data and repeated cross-sections are provided for various DD cases such as constant/time-varying effect or constant/time-varying treatment timing. Following these basics on DD, topics such as ‘DD in reverse’, fuzzy DD, synthetic control, and triple and generalized differences are examined. Many empirical examples in various areas of economics are provided for illustration.

Suggested Citation

  • Myoung-jae Lee & Yasuyuki Sawada, 2020. "Review on Difference in Differences," Korean Economic Review, Korean Economic Association, vol. 36, pages 135-173.
  • Handle: RePEc:kea:keappr:ker-20200101-36-1-05
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    References listed on IDEAS

    as
    1. Munasib, Abdul & Rickman, Dan S., 2015. "Regional economic impacts of the shale gas and tight oil boom: A synthetic control analysis," Regional Science and Urban Economics, Elsevier, vol. 50(C), pages 1-17.
    2. 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.
    3. William duPont IV & Ilan Noy & Yoko Okuyama & Yasuyuki Sawada, 2015. "The Long-Run Socio-Economic Consequences of a Large Disaster: The 1995 Earthquake in Kobe," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-17, October.
    4. Angrist, Joshua D. & Krueger, Alan B., 1999. "Empirical strategies in labor economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 23, pages 1277-1366, Elsevier.
    5. Matthieu Chemin & Etienne Wasmer, 2009. "Using Alsace-Moselle Local Laws to Build a Difference-in-Differences Estimation Strategy of the Employment Effects of the 35-Hour Workweek Regulation in France," Journal of Labor Economics, University of Chicago Press, vol. 27(4), pages 487-524, October.
    6. Raj Chetty & Adam Looney & Kory Kroft, 2009. "Salience and Taxation: Theory and Evidence," American Economic Review, American Economic Association, vol. 99(4), pages 1145-1177, September.
    7. 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.
    8. Lee, Myoung-jae, 2005. "Micro-Econometrics for Policy, Program and Treatment Effects," OUP Catalogue, Oxford University Press, number 9780199267699.
    9. Brewer Mike & Crossley Thomas F. & Joyce Robert, 2018. "Inference with Difference-in-Differences Revisited," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-16, January.
    10. Young‐sook Kim & Myoung‐jae Lee, 2017. "Ordinal response generalized difference in differences with varying categories: The health effect of a disability program in Korea," Health Economics, John Wiley & Sons, Ltd., vol. 26(9), pages 1123-1131, September.
    11. Sarah Bohn & Magnus Lofstrom & Steven Raphael, 2014. "Did the 2007 Legal Arizona Workers Act Reduce the State's Unauthorized Immigrant Population?," The Review of Economics and Statistics, MIT Press, vol. 96(2), pages 258-269, May.
    12. Minhaj Mahmud & Yasuyuki Sawada, 2018. "Infrastructure and well-being: employment effects of Jamuna bridge in Bangladesh," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 10(3), pages 327-340, July.
    13. Eric Helland & Alexander Tabarrok, 2007. "Does Three Strikes Deter?: A Nonparametric Estimation," Journal of Human Resources, University of Wisconsin Press, vol. 42(2).
    14. Alberto Abadie & Javier Gardeazabal, 2003. "The Economic Costs of Conflict: A Case Study of the Basque Country," American Economic Review, American Economic Association, vol. 93(1), pages 113-132, March.
    15. Nada Eissa & Jeffrey B. Liebman, 1996. "Labor Supply Response to the Earned Income Tax Credit," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(2), pages 605-637.
    16. Ando, Michihito, 2015. "Dreams of urbanization: Quantitative case studies on the local impacts of nuclear power facilities using the synthetic control method," Journal of Urban Economics, Elsevier, vol. 85(C), pages 68-85.
    17. Nikolay Doudchenko & Guido W. Imbens, 2016. "Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis," NBER Working Papers 22791, National Bureau of Economic Research, Inc.
    18. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    19. Campbell, Kayleigh B. & Brakewood, Candace, 2017. "Sharing riders: How bikesharing impacts bus ridership in New York City," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 264-282.
    20. Myoung‐Jae Lee & Young‐Sook Kim, 2014. "Difference In Differences For Stayers With A Time‐Varying Qualification: Health Expenditure Elasticity Of The Elderly," Health Economics, John Wiley & Sons, Ltd., vol. 23(9), pages 1134-1145, September.
    21. 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.
    22. Noémi Kreif & Richard Grieve & Dominik Hangartner & Alex James Turner & Silviya Nikolova & Matt Sutton, 2016. "Examination of the Synthetic Control Method for Evaluating Health Policies with Multiple Treated Units," Health Economics, John Wiley & Sons, Ltd., vol. 25(12), pages 1514-1528, December.
    23. Choi, Seungmoon & Pellen, Alistair & Masson, Virginie, 2017. "How does daylight saving time affect electricity demand? An answer using aggregate data from a natural experiment in Western Australia," Energy Economics, Elsevier, vol. 66(C), pages 247-260.
    24. Xu, Yiqing, 2017. "Generalized Synthetic Control Method: Causal Inference with Interactive Fixed Effects Models," Political Analysis, Cambridge University Press, vol. 25(1), pages 57-76, January.
    25. Matthew J. Kotchen & Laura E. Grant, 2011. "Does Daylight Saving Time Save Energy? Evidence from a Natural Experiment in Indiana," The Review of Economics and Statistics, MIT Press, vol. 93(4), pages 1172-1185, November.
    26. Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097, Elsevier.
    27. Puhani, Patrick A., 2012. "The treatment effect, the cross difference, and the interaction term in nonlinear “difference-in-differences” models," Economics Letters, Elsevier, vol. 115(1), pages 85-87.
    28. Karin Monstad & Carol Propper & Kjell G. Salvanes, 2008. "Education and Fertility: Evidence from a Natural Experiment," Scandinavian Journal of Economics, Wiley Blackwell, vol. 110(4), pages 827-852, December.
    29. Kamhon Kan & Myoung‐Jae Lee, 2018. "The Effects Of Education On Fertility: Evidence From Taiwan," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 343-357, January.
    30. Tzu‐Chun Kuo, 2012. "Evaluating Californian under‐age drunk driving laws: endogenous policy lags," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(7), pages 1100-1115, November.
    31. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    32. Kamhon Kan & Shin-Kun Peng & Ping Wang, 2017. "Understanding Consumption Behavior: Evidence from Consumers' Reaction to Shopping Vouchers," American Economic Journal: Economic Policy, American Economic Association, vol. 9(1), pages 137-153, February.
    33. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(1), pages 1-19.
    34. William duPont IV & Ilan Noy & Yoko Okuyama & Yasuyuki Sawada, 2015. "The Long-Run Socio-Economic Consequences of a Large Disaster: The 1995 Earthquake in Kobe," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-17, October.
    35. Kimin Kim & Myoung-jae Lee, 2019. "Difference in differences in reverse," Empirical Economics, Springer, vol. 57(3), pages 705-725, September.
    36. Besley, Timothy & Case, Anne, 2000. "Unnatural Experiments? Estimating the Incidence of Endogenous Policies," Economic Journal, Royal Economic Society, vol. 110(467), pages 672-694, November.
    37. Hyun Kim & Yong-seong Kim & Myoung-jae Lee, 2012. "Treatment effect analysis of early reemployment bonus program: panel MLE and mode-based semiparametric estimator for interval truncation," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 11(3), pages 189-209, December.
    38. repec:hal:spmain:info:hdl:2441/10198 is not listed on IDEAS
    39. 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.
    40. Hsieh, Chang-Tai & Shimizutani, Satoshi & Hori, Masahiro, 2010. "Did Japan's shopping coupon program increase spending?," Journal of Public Economics, Elsevier, vol. 94(7-8), pages 523-529, August.
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    More about this item

    Keywords

    Difference in Differences (DD); DD in Reverse; Fuzzy DD; Synthetic Control; Triple DD; Generalized DD;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • H00 - Public Economics - - General - - - General
    • I00 - Health, Education, and Welfare - - General - - - General
    • J08 - Labor and Demographic Economics - - General - - - Labor Economics Policies
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

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