Fast inference for quantile regression with tens of millions of observations
Big data analytics has opened new avenues in economic research, but the challenge of
analyzing datasets with tens of millions of observations is substantial. Conventional …
analyzing datasets with tens of millions of observations is substantial. Conventional …
Noisy, non-smooth, non-convex estimation of moment condition models
JJ Forneron - arXiv preprint arXiv:2301.07196, 2023 - arxiv.org
A practical challenge for structural estimation is the requirement to accurately minimize a
sample objective function which is often non-smooth, non-convex, or both. This paper …
sample objective function which is often non-smooth, non-convex, or both. This paper …
Kernel-Based Stochastic Learning of Large-Scale Semiparametric Monotone Index Models with an Application to Aging and Household Risk Preference
Q Yao - arXiv preprint arXiv:2309.06693, 2023 - arxiv.org
This paper studies semiparametric estimation of monotone index models in a data-rich
environment, where the number of covariates ($ p $) and sample size ($ n $) can both be …
environment, where the number of covariates ($ p $) and sample size ($ n $) can both be …
[PDF][PDF] The Proximal Bootstrap for Constrained Estimators
J Li - Typescript, University of California, Santa Cruz. URL …, 2023 - people.ucsc.edu
The Proximal Bootstrap for Constrained Estimators ∗ Page 1 The Proximal Bootstrap for
Constrained Estimators ∗ Jessie Li† May 5, 2024 We demonstrate how to use the proximal …
Constrained Estimators ∗ Jessie Li† May 5, 2024 We demonstrate how to use the proximal …