Computing semiparametric efficiency bounds in linear models with nonparametric regressors

Andrés Aradillas-López

doi:10.1016/j.econlet.2019.108673

Computing semiparametric efficiency bounds in linear models with nonparametric regressors

Andrés Aradillas-López

Economics

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

We use the computational method proposed by Severini and Tripathi (2001) to obtain semiparametric efficiency bounds in linear models with nonparametric regressors in the form of conditional expectations. Examples include social-interaction models. Explicit efficiency bounds for these models, with the degree of generality assumed here, had not been described before.

Original language	English (US)
Article number	108673
Journal	Economics Letters
Volume	185
DOIs	https://doi.org/10.1016/j.econlet.2019.108673
State	Published - Dec 2019

All Science Journal Classification (ASJC) codes

Finance
Economics and Econometrics

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10.1016/j.econlet.2019.108673

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abstract = "We use the computational method proposed by Severini and Tripathi (2001) to obtain semiparametric efficiency bounds in linear models with nonparametric regressors in the form of conditional expectations. Examples include social-interaction models. Explicit efficiency bounds for these models, with the degree of generality assumed here, had not been described before.",

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Computing semiparametric efficiency bounds in linear models with nonparametric regressors

Abstract

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