Open AccessInformation theoretic approach to high‐dimensional multiplicative models: Stochastic discount factor and treatment effect
Author(s) -
Qiu Chen,
Otsu Taisuke
Publication year - 2022
Publication title -
quantitative economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.062
H-Index - 27
eISSN - 1759-7331
pISSN - 1759-7323
DOI - 10.3982/qe1603
Subject(s) - stochastic discount factor , multiplicative function , empirical likelihood , mathematics , moment (physics) , econometrics , mathematical optimization , estimation , function (biology) , capital asset pricing model , asset (computer security) , computer science , economics , statistics , mathematical analysis , physics , management , computer security , classical mechanics , estimator , evolutionary biology , biology
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.