Information theoretic approach to high dimensional multiplicative models: Stochastic discount factor and treatment effect
Taisuke Otsu and Chen Qiu
Published 4 January 2018
This paper is concerned with estimation of functionals of a latent weight function that satisfies possibly high dimensional multiplicative moment conditions. Main examples are missing data problems, treatment effects, and functionals of the stochastic discount factor in asset pricing. We propose to estimate the latent weight function by an information theoretic approach combined with the 1-penalization technique to deal with high dimensional moment conditions under sparsity. We derive asymptotic properties of the proposed estimator, and illustrate the proposed method by a theoretical example on treatment effect analysis and empirical example on the stochastic discount factor.
Paper Number EM/2018/595:
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JEL Classification: C12; C14