Cookies?
Library Header Image
LSE Research Online LSE Library Services

Inference on conditional moment restriction models with generated variables

Kimoto, Ryo and Otsu, Taisuke (2022) Inference on conditional moment restriction models with generated variables. Economics Letters, 215. ISSN 0165-1765

[img] Text (Generated3) - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (334kB)

Identification Number: 10.1016/j.econlet.2022.110454

Abstract

A seminal work by Domínguez and Lobato (2004) proposed a consistent estimation method for conditional moment restrictions, which does not rely on additional identification assumptions as in the GMM estimator using unconditional moments and is free from any userchosen number. Their methodology is further extended by Domínguez and Lobato (2015, 2020) for consistent specification testing of conditional moment restrictions, which may involve generated variables. We follow up this literature and derive the asymptotic distribution of Domínguez and Lobato’s (2004) estimator that involves generated variables. Our simulation result illustrates that ignoring proxy errors in the generated variables may cause severer distortions for the coverage or size properties of statistical inference on parameters.

Item Type: Article
Official URL: https://www.sciencedirect.com/journal/economics-le...
Additional Information: © 2022 Elsevier B.V.
Divisions: Economics
Subjects: H Social Sciences > HB Economic Theory
Q Science > QA Mathematics
JEL classification: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods
Date Deposited: 07 Mar 2022 10:51
Last Modified: 07 Apr 2024 22:48
URI: http://eprints.lse.ac.uk/id/eprint/114264

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics