Inference on conditional moment restriction models with generated variables

Kimoto, Ryo and Otsu, Taisuke ORCID: 0000-0002-2307-143X (2022) Inference on conditional moment restriction models with generated variables. Economics Letters, 215. ISSN 0165-1765

Text (Generated3) - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (334kB)

• Author

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:	12 Dec 2024 02:53
URI:	http://eprints.lse.ac.uk/id/eprint/114264

Actions (login required)

View Item