arXiv 27 Apr 2020 · Econometrics · 3 citations (OpenAlex)
arXiv:2004.12601 · PDF · DOI · OpenAlex · Extracted main text
We propose a novel method for modeling data by using structural models based on economic theory as regularizers for statistical models. We show that even if a structural model is misspecified, as long as it is informative about the data-generating mechanism, our method can outperform both the (misspecified) structural model and un-structural-regularized statistical models. Our method permits a Bayesian interpretation of theory as prior knowledge and can be used both for statistical prediction and causal inference. It contributes to transfer learning by showing how incorporating theory into statistical modeling can significantly improve out-of-domain predictions and offers a way to synthesize reduced-form and structural approaches for causal effect estimation. Simulation experiments demonstrate the potential of our method in various settings, including first-price auctions, dynamic models of entry and exit, and demand estimation with instrumental variables. Our method has potential applications not only in economics, but in other scientific disciplines whose theoretical models offer important insight but are subject to significant misspecification concerns.
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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 | Fessler, P. and Kasy, M (2019) How to Use Economic Theory to Improve Estimators: Shrinking Toward Theoretical Restrictions | 0.874 | 5 | 2 | 100% |
| 2 | Rust, J (2014) The Limits of Inference with Theory: A Review of Wolpin (2013) | 0.811 | 4 | 2 | 100% |
| 3 | Christensen, T. and Connault, B (2019) Counterfactual Sensitivity and Robustness | 0.737 | 3 | 2 | 100% |
| 4 | Chetty, R (2009) Sufficient Statistics for Welfare Analysis: A Bridge Between Structural and Reduced-Form Methods | 0.644 | 4 | 1 | 100% |
| 5 | Heckman, J. J (2000) Causal parameters and policy analysis in economics: A twentieth century retrospective | 0.644 | 2 | 2 | 100% |
| 6 | Pearl, J (2009) Causality | 0.644 | 2 | 2 | 100% |
| 7 | Pan, S. J. and Yang, Q (2010) A Survey on Transfer Learning | 0.585 | 3 | 1 | 100% |
| 8 | Angrist, J. D. and Pischke, J.-S (2010) The credibility revolution in empirical economics: How better research design is taking the con out of econometrics | 0.511 | 2 | 1 | 100% |
| 9 | Angrist, J. D. and Krueger, A. B (1995) Split-Sample Instrumental Variables Estimates of the Return to Schooling | 0.511 | 2 | 1 | 100% |
| 10 | Arcidiacono, P. and Miller, R. A (2011) Conditional choice probability estimation of dynamic discrete choice models with unobserved heterogeneity | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 75 scored citations.