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On the Use of Design-Based Simulations

Bruno Ferman

arXiv 11 Mar 2026 · Econometrics

arXiv:2603.11381 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Design-based simulations - procedures that hold realized outcomes fixed and generate variation by resampling treatment assignment or shocks - are widely used in both methodological and applied work to assess inference procedures. This paper studies the extent to which such simulations are informative about inference validity. Focusing on shift-share designs, we show that standard simulations that fix outcomes and resample shocks may rely on a data-generating process that is not aligned with the true one. In particular, these simulations confound true treatment effects with error dependence, potentially overstating inference distortions due to spatial correlation. We propose alternative simulation designs that circumvent this problem and illustrate their use in prominent empirical applications. Our results highlight that the usefulness of design-based simulations depends critically on how closely the simulated data-generating process aligns with the true one.

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17
references
65
in-text mentions
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distinct cited
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Borusyak, K., P. Hull, and X. Jaravel (2021, 06) (2021) Quasi-Experimental Shift-Share Research Designs1.00053100%
2Adão, R., M. Kolesar, and E. Morales (2019, 08) (2019) Shift-Share Designs: Theory and Inference0.91321576%
3Acemoglu, D. and P. Restrepo (2020) Robots and jobs: Evidence from US labor markets0.8558362%
4Autor, D. H., D. Dorn, and G. H. Hanson (2013, October) (2013) The china syndrome: Local labor market effects of import competition in the united states0.8558362%
5Dix-Carneiro, R., R. R. Soares, and G. Ulyssea (2018, October) (2018) Economic shocks and crime: Evidence from the brazilian trade liberalization0.6936250%
6Bertrand, M., E. Duflo, and S. Mullainathan (2004) How much should we trust differences-in-differences estimates?0.64422100%
7Ferman, B. (2019, December) (2019) Assessing Inference Methods self0.64422100%
8Barrios, T., R. Diamond, G. W. Imbens, and M. Kolesar (2012) Clustering, spatial correlations, and randomization inference0.5112250%
9Abadie, A., S. Athey, G. W. Imbens, and J. M. Wooldridge (2020) Sampling-based versus design-based uncertainty in regression analysis0.51121100%
10Abadie, A., S. Athey, G. W. Imbens, and J. M. Wooldridge (2022, 10) (2022) When Should You Adjust Standard Errors for Clustering?0.51121100%

Showing the top 10 of 17 scored citations.