Arellano (J Econ 42:247-265, 1989a) showed that valid equality restrictions on covariance matrices could result in efficiency losses for Gaussian PMLEs in simultaneous equations models. We revisit his two-equation example using finite normal mixtures PMLEs instead, which are also consistent for mean and variance parameters regardless of the true distribution of the shocks. Because such mixtures provide good approximations to many distributions, we relate the asymptotic variance of our estimators to the relevant semiparametric efficiency bound. Our Monte Carlo results indicate that they systematically dominate MD and that the version that imposes the valid covariance restriction is more efficient than the unrestricted one.

PML versus minimum ?(2): the comeback / Amengual, D; Fiorentini, G; Sentana, E. - In: SERIES. - ISSN 1869-4187. - ELETTRONICO. - 14:(2023), pp. 253-300. [10.1007/s13209-023-00280-4]

PML versus minimum ?(2): the comeback

Fiorentini, G;
2023

Abstract

Arellano (J Econ 42:247-265, 1989a) showed that valid equality restrictions on covariance matrices could result in efficiency losses for Gaussian PMLEs in simultaneous equations models. We revisit his two-equation example using finite normal mixtures PMLEs instead, which are also consistent for mean and variance parameters regardless of the true distribution of the shocks. Because such mixtures provide good approximations to many distributions, we relate the asymptotic variance of our estimators to the relevant semiparametric efficiency bound. Our Monte Carlo results indicate that they systematically dominate MD and that the version that imposes the valid covariance restriction is more efficient than the unrestricted one.
2023
14
253
300
Goal 8: Decent work and economic growth
Amengual, D; Fiorentini, G; Sentana, E
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1322757
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