Information theoretic approach to high-dimensional multiplicative models: Stochastic discount factor and treatment effect

• 成果类型: Article
• 署名作者: Qiu, Chen; Otsu, Taisuke
• 署名单位: Cornell University; University of London; London School Economics & Political Science
• 刊物名称: QUANTITATIVE ECONOMICS
• ISSN/ISSBN: 1759-7323
• DOI: 10.3982/QE1603
• 发表日期: 2022
• 页码: 63-94
• 关键词: Information theoretic approach; high-dimensional model; stochastic discount factor; treatment effect; C12; C14

摘要

This paper is concerned with estimation of functionals of a latent weight function that satisfies possibly high-dimensional multiplicative moment conditions. Main examples are functionals of stochastic discount factors in asset pricing, missing data problems, and treatment effects. We propose to estimate the latent weight function by an information theoretic approach combined with the l(1)-penalization technique to deal with high-dimensional moment conditions under sparsity. We study asymptotic properties of the proposed method and illustrate it by a theoretical example on treatment effect analysis and empirical example on estimation of stochastic discount factors.