arXiv 11 Mar 2026 · Econometrics
arXiv:2603.11381 · PDF · DOI · OpenAlex · Extracted main text
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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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Borusyak, K., P. Hull, and X. Jaravel (2021, 06) (2021) Quasi-Experimental Shift-Share Research Designs | 1.000 | 5 | 3 | 100% |
| 2 | Adão, R., M. Kolesar, and E. Morales (2019, 08) (2019) Shift-Share Designs: Theory and Inference | 0.913 | 21 | 5 | 76% |
| 3 | Acemoglu, D. and P. Restrepo (2020) Robots and jobs: Evidence from US labor markets | 0.855 | 8 | 3 | 62% |
| 4 | Autor, D. H., D. Dorn, and G. H. Hanson (2013, October) (2013) The china syndrome: Local labor market effects of import competition in the united states | 0.855 | 8 | 3 | 62% |
| 5 | Dix-Carneiro, R., R. R. Soares, and G. Ulyssea (2018, October) (2018) Economic shocks and crime: Evidence from the brazilian trade liberalization | 0.693 | 6 | 2 | 50% |
| 6 | Bertrand, M., E. Duflo, and S. Mullainathan (2004) How much should we trust differences-in-differences estimates? | 0.644 | 2 | 2 | 100% |
| 7 | Ferman, B. (2019, December) (2019) Assessing Inference Methods self | 0.644 | 2 | 2 | 100% |
| 8 | Barrios, T., R. Diamond, G. W. Imbens, and M. Kolesar (2012) Clustering, spatial correlations, and randomization inference | 0.511 | 2 | 2 | 50% |
| 9 | Abadie, A., S. Athey, G. W. Imbens, and J. M. Wooldridge (2020) Sampling-based versus design-based uncertainty in regression analysis | 0.511 | 2 | 1 | 100% |
| 10 | Abadie, A., S. Athey, G. W. Imbens, and J. M. Wooldridge (2022, 10) (2022) When Should You Adjust Standard Errors for Clustering? | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 17 scored citations.