arXiv 22 Feb 2025 · Econometrics
arXiv:2502.16041 · PDF · DOI · OpenAlex · Extracted main text
This paper presents a novel semiparametric method to study the effects of extreme events on binary outcomes and subsequently forecast future outcomes. Our approach, based on Bayes' theorem and regularly varying (RV) functions, facilitates a Pareto approximation in the tail without imposing parametric assumptions beyond the tail. We analyze cross-sectional as well as static and dynamic panel data models, incorporate additional covariates, and accommodate the unobserved unit-specific tail thickness and RV functions in panel data. We establish consistency and asymptotic normality of our tail estimator, and show that our objective function converges to that of a panel Logit regression on tail observations with the log extreme covariate as a regressor, thereby simplifying implementation. The empirical application assesses whether small banks become riskier when local housing prices sharply decline, a crucial channel in the 2007--2008 financial crisis.
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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 | Fernández-Val and Weidner (2018) Fixed effects estimation of large-T panel data models | 1.000 | 6 | 4 | 100% |
| 2 | Stammann, Heiss, and McFadden (2016) Estimating fixed effects Logit models with large panel data | 1.000 | 5 | 4 | 100% |
| 3 | Gabaix (2009) Power laws in economics and finance | 0.928 | 4 | 3 | 100% |
| 4 | Wang and Tsai (2009) Tail index regression | 0.874 | 7 | 2 | 100% |
| 5 | Honoré and Kyriazidou (2000) Panel data discrete choice models with lagged dependent variables | 0.843 | 3 | 3 | 100% |
| 6 | Gabaix (2016) Power laws in economics: An introduction | 0.811 | 4 | 2 | 100% |
| 7 | de Haan and Ferreira (2006) Extreme Value Theory: An Introduction | 0.811 | 4 | 2 | 100% |
| 8 | Liu, Moon, and Schorfheide (2023) Forecasting with a panel Tobit model | 0.811 | 4 | 2 | 100% |
| 9 | Clauset, Shalizi, and Newman (2009) Power-law distributions in empirical data | 0.737 | 3 | 2 | 100% |
| 10 | Hill (1975) A simple general approach to inference about the tail of a distribution | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 48 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | At-Risk Transformation for U.S. Recession Prediction $ $ | 0.405 | 1 | 1 |
| 2 | A Simple and Powerful Diagnostic Test for Binary Choice Models | 0.405 | 1 | 1 |