arXiv 14 Feb 2025 · Econometrics
arXiv:2502.10301 · PDF · DOI · OpenAlex · Extracted main text
This paper introduces R-OLS, an estimator for the average partial effect (APE) of a continuous treatment variable on an outcome variable in the presence of non-linear and non-additively separable confounding of unknown form. Identification of the APE is achieved by generalising Stein's Lemma (Stein, 1981), leveraging an exogenous error component in the treatment along with a flexible functional relationship between the treatment and the confounders. The identification results for R-OLS are used to characterize the properties of Double/Debiased Machine Learning (Chernozhukov et al., 2018), specifying the conditions under which the APE is estimated consistently. A novel decomposition of the ordinary least squares estimand provides intuition for these results. Monte Carlo simulations demonstrate that the proposed estimator outperforms existing methods, delivering accurate estimates of the true APE and exhibiting robustness to moderate violations of its underlying assumptions. The methodology is further illustrated through an empirical application to Fetzer (2019).
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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 | Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C… (2018) Double/debiased machine learning for treatment and structural parameters | 1.000 | 7 | 3 | 100% |
| 2 | Fetzer, T (2019) Did austerity cause brexit? | 0.961 | 9 | 4 | 89% |
| 3 | Robinson, P. M (1988) Root-$n$-consistent semiparametric regression | 0.843 | 3 | 3 | 100% |
| 4 | Stein, C. M (1981) Estimation of the mean of a multivariate normal distribution | 0.843 | 3 | 3 | 100% |
| 5 | Graham, B. S. and de Xavier Pinto, C. C (2022) Semiparametrically efficient estimation of the average linear regression function | 0.737 | 3 | 3 | 67% |
| 6 | Kolesár, M. and Plagborg-Møller, M (2024) Dynamic causal effects in a nonlinear world: the good, the bad, and the ugly | 0.511 | 3 | 2 | 33% |
| 7 | Angrist, J. D. and Krueger, A. B (1999) Chapter 23 - empirical strategies in labor economics | 0.511 | 2 | 2 | 50% |
| 8 | Angrist, J. D (1998) Estimating the labor market impact of voluntary military service using social security data on military applicants | 0.511 | 2 | 2 | 50% |
| 9 | Yitzhaki, S (1996) On using linear regressions in welfare economics | 0.511 | 2 | 2 | 50% |
| 10 | Cuesta, J. I., Davis, J. M. V., Gianou, A., and Hoyos, A (2019) Identification of average marginal effects under misspecification when covariates are normal | 0.457 | 7 | 2 | 14% |
Showing the top 10 of 26 scored citations.