Gaussian Transforms Modeling and the Estimation of Distributional Regression Functions
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2020
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| _version_ | 1866908326816645120 |
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| author | Spady, Richard Stouli, Sami |
| author_facet | Spady, Richard Stouli, Sami |
| contents | We propose flexible Gaussian representations for conditional cumulative distribution functions and give a concave likelihood criterion for their estimation. Optimal representations satisfy the monotonicity property of conditional cumulative distribution functions, including in finite samples and under general misspecification. We use these representations to provide a unified framework for the flexible Maximum Likelihood estimation of conditional density, cumulative distribution, and quantile functions at parametric rate. Our formulation yields substantial simplifications and finite sample improvements over related methods. An empirical application to the gender wage gap in the United States illustrates our framework. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2011_06416 |
| institution | arXiv |
| publishDate | 2020 |
| record_format | arxiv |
| spellingShingle | Gaussian Transforms Modeling and the Estimation of Distributional Regression Functions Spady, Richard Stouli, Sami Econometrics Methodology We propose flexible Gaussian representations for conditional cumulative distribution functions and give a concave likelihood criterion for their estimation. Optimal representations satisfy the monotonicity property of conditional cumulative distribution functions, including in finite samples and under general misspecification. We use these representations to provide a unified framework for the flexible Maximum Likelihood estimation of conditional density, cumulative distribution, and quantile functions at parametric rate. Our formulation yields substantial simplifications and finite sample improvements over related methods. An empirical application to the gender wage gap in the United States illustrates our framework. |
| title | Gaussian Transforms Modeling and the Estimation of Distributional Regression Functions |
| topic | Econometrics Methodology |
| url | https://arxiv.org/abs/2011.06416 |