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Trusting difference-in-differences estimates more: An approximate permutation test
In Bunnenberg and Meyer (2017), we develop a new approach for hypothesis tests in difference-in-differences (DID) regressions. Our approximate permutation test uses simulated placebo interventions to reveal the empirical error distribution of estimated policy effects. In contrast to existing econometric corrections, such as single- or double-clustering, our approach does not impose any parametric form on the data. In comparison to alternative parametric tests, our procedure maintains correct size with simulated and real-world interventions. Simultaneously, it improves power. For further details, please see the working paper.
We invite any interested researcher to apply our procedure to their research problems. For this purpose, we offer an example data set with a commented, self-instructive software code that implements the testing procedure for standard statistical software packages. We thank Kenneth French for providing the data used online. Please feel free to adopt this code for your specific needs. We kindly ask you to quote our working paper in case you apply our procedure in any publication.
- Documentation of the demonstration code as PDF
- Data set and code for STATA
- Data set and code for MATLAB
- Data set and code for R
To execute the example code, please unzip the file and execute the code file in the indicated statistical software.
License and disclaimer
All software provided on the website www.finance.uni-hannover.de (henceforth this webseite) is made available under the terms of the Apache License 2.0. A copy of the license is available at http://www.apache.org/licenses/LICENSE-2.0.
All software available on this website is provided "as is" and any expressed or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed. In no event shall Sebastian Bunnenberg, the Leibniz University Hannover (LUH), or any of their contributors be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised of the possibility of such damage.
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- could include technical or other mistakes, inaccuracies or typographical errors. Sebastian Bunnenberg, LUH and contributors may make changes to the software or documentation made available on its web site.
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The use of the software downloaded through this website is done at your own discretion and risk and with agreement that you will be solely responsible for any damage to your computer system or loss of data that results from such activities. No advice or information, whether oral or written, obtained by you from this website, Sebastian Bunnenberg, LUH, or its contributors shall create any warranty for the software.