arXiv 22 Oct 2024 · Econometrics
arXiv:2410.17153 · PDF · DOI · OpenAlex · Extracted main text
This paper presents a Bayesian inference framework for a linear index threshold-crossing binary choice model that satisfies a median independence restriction. The key idea is that the model is observationally equivalent to a probit model with nonparametric heteroskedasticity. Consequently, Gibbs sampling techniques from Albert and Chib (1993) and Chib and Greenberg (2013) lead to a computationally attractive Bayesian inference procedure in which a Gaussian process forms a conditionally conjugate prior for the natural logarithm of the skedastic function.
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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 | J. H. Albert and S. Chib (1993) Bayesian analysis of binary and polychotomous response data | 1.000 | 6 | 4 | 100% |
| 2 | C. F. Manski (1988) Identification of binary response models | 1.000 | 6 | 3 | 100% |
| 3 | S. Chib and E. Greenberg (2013) On conditional variance estimation in nonparametric regression | 0.928 | 4 | 4 | 100% |
| 4 | J. L. Horowitz (1992) A smoothed maximum score estimator for the binary response model | 0.874 | 6 | 2 | 100% |
| 5 | S. Khan (2013) Distribution free estimation of heteroskedastic binary response models using probit/logit criterion functions | 0.811 | 4 | 2 | 100% |
| 6 | C. F. Manski (1985) Semiparametric analysis of discrete response: Asymptotic properties of the maximum score estimator | 0.811 | 4 | 2 | 100% |
| 7 | C. F. Manski (1975) Maximum score estimation of the stochastic utility model of choice | 0.737 | 3 | 2 | 100% |
| 8 | C. E. Rasmussen and C. K. Williams (2006) Gaussian processes for machine learning, volume 2 | 0.737 | 3 | 2 | 100% |
| 9 | Y. Omori, S. Chib, N. Shephard, and J. Nakajima (2007) Stochastic volatility with leverage: Fast and efficient likelihood inference | 0.585 | 3 | 1 | 100% |
| 10 | S. J. Jun, J. Pinkse, and Y. Wan (2015) Classical laplace estimation for n3-consistent estimators: Improved convergence rates and rate-adaptive inference | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 23 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Binary Classification with the Maximum Score Model and Linear Programming | 0.405 | 1 | 1 |