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Inference on Difference-in-Differences average treatment effects: A fixed-b approach

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  • Sun, Yu
  • Yan, Karen X.

Abstract

This paper provides an analysis of the standard errors proposed by Driscoll and Kraay (1998) (DK) in linear Difference-in-Differences (DD) models with fixed effects and individual-specific time trends. The analysis is accomplished within the fixed-b asymptotic framework developed by Kiefer and Vogelsang (2005) for heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimator based tests. For both the fixed-N, large-T, and large-N, large-T cases, it is shown that fixed-b asymptotic distributions of test statistics constructed using the DD estimator and the DK standard errors are different from the results found by Kiefer and Vogelsang (2005) and Vogelsang (2012). The newly derived fixed-b asymptotic distributions depend on the date of policy change, individual-specific trend functions as well as the choice of kernel and bandwidth. Monte Carlo simulations illustrate the performance of the fixed-b approximations in practice.

Suggested Citation

  • Sun, Yu & Yan, Karen X., 2019. "Inference on Difference-in-Differences average treatment effects: A fixed-b approach," Journal of Econometrics, Elsevier, vol. 211(2), pages 560-588.
  • Handle: RePEc:eee:econom:v:211:y:2019:i:2:p:560-588
    DOI: 10.1016/j.jeconom.2019.04.001
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    More about this item

    Keywords

    Difference-in-Differences; HAC estimator; Fixed-b asymptotics; Panel data;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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