Irene Botosaru, Raffaella Giacomini, Martin Weidner
arXiv 11 Sep 2023 · Econometrics · 6 citations (OpenAlex)
arXiv:2309.05639 · PDF · DOI · OpenAlex · Extracted main text
We consider estimation and inference of the effects of a policy in the absence of a control group. We obtain unbiased estimators of individual (heterogeneous) treatment effects and a consistent and asymptotically normal estimator of the average treatment effect. Our estimator averages over unbiased forecasts of individual counterfactuals, based on a (short) time series of pre-treatment data. The paper emphasizes the importance of focusing on forecast unbiasedness rather than accuracy when the end goal is estimation of average treatment effects. We show that simple basis function regressions ensure forecast unbiasedness for a broad class of data-generating processes for the counterfactuals, even in short panels. In contrast, model-based forecasting requires stronger assumptions and is prone to misspecification and estimation bias. We show that our method can replicate the findings of some previous empirical studies, but without using a control group.
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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 | Arellano, M. and S. Bonhomme (2012) Identifying distributional characteristics in random coefficients panel data models | 0.928 | 5 | 3 | 80% |
| 2 | Goodman-Bacon, A (2021) Difference-in-differences with variation in treatment timing | 0.843 | 5 | 3 | 60% |
| 3 | Sun, L. and S. Abraham (2020) Estimating dynamic treatment effects in event studies with heterogeneous treatment effects | 0.644 | 3 | 2 | 67% |
| 4 | Chamberlain, G (1992) Efficiency bounds for semiparametric regression | 0.644 | 2 | 2 | 100% |
| 5 | Dufour, J.-M (1984) Unbiasedness of predictions from estimated autoregressions when the true order is unknown | 0.644 | 2 | 2 | 100% |
| 6 | Fuller, W. and D. Hasza (1980) Predictors for the first-order autoregressive process | 0.644 | 2 | 2 | 100% |
| 7 | Graham, B. S. and J. L. Powell (2012) Identification and estimation of average partial effects in “irregular” correlated random coefficient panel data models | 0.644 | 2 | 2 | 100% |
| 8 | White, H (2001) Asymptotic theory for econometricians | 0.644 | 2 | 2 | 100% |
| 9 | Callaway, B. and P. H. C. Sant'Anna (2021) Difference-in-differences with multiple time periods | 0.606 | 6 | 2 | 33% |
| 10 | Shover, C., C. Davis, S. Gordon, and K. Humphreys (2019) Association between medical cannabis laws and opioid overdose mortality has reversed over time | 0.511 | 4 | 2 | 25% |
Showing the top 10 of 100 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Causal inference and policy evaluation without a control group$^*$ | 0.511 | 2 | 1 |
| 2 | Difference-in-differences with as few as two cross-sectional units – A new perspective to the democracy–growth debate | 0.511 | 2 | 2 |