The purpose of an estimator is what it does: Misspecification, estimands, and over-identification

Fuente: arXiv
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Autori principali: Andrews, Isaiah, Chen, Jiafeng, Tecchio, Otavio
Natura: Preprint
Pubblicazione: 2025
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author Andrews, Isaiah
Chen, Jiafeng
Tecchio, Otavio
author_facet Andrews, Isaiah
Chen, Jiafeng
Tecchio, Otavio
contents In over-identified models, misspecification -- the norm rather than exception -- fundamentally changes what estimators estimate. Different estimators imply different estimands rather than different efficiency for the same target. A review of recent applications of generalized method of moments in the American Economic Review suggests widespread acceptance of this fact: There is little formal specification testing and widespread use of estimators that would be inefficient were the model correct, including the use of "hand-selected" moments and weighting matrices. Motivated by these observations, we review and synthesize recent results on estimation under model misspecification, providing guidelines for transparent and robust empirical research. We also provide a new theoretical result, showing that Hansen's J-statistic measures, asymptotically, the range of estimates achievable at a given standard error. Given the widespread use of inefficient estimators and the resulting researcher degrees of freedom, we thus particularly recommend the broader reporting of J-statistics.
format Preprint
id arxiv_https___arxiv_org_abs_2508_13076
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The purpose of an estimator is what it does: Misspecification, estimands, and over-identification
Andrews, Isaiah
Chen, Jiafeng
Tecchio, Otavio
Econometrics
Methodology
In over-identified models, misspecification -- the norm rather than exception -- fundamentally changes what estimators estimate. Different estimators imply different estimands rather than different efficiency for the same target. A review of recent applications of generalized method of moments in the American Economic Review suggests widespread acceptance of this fact: There is little formal specification testing and widespread use of estimators that would be inefficient were the model correct, including the use of "hand-selected" moments and weighting matrices. Motivated by these observations, we review and synthesize recent results on estimation under model misspecification, providing guidelines for transparent and robust empirical research. We also provide a new theoretical result, showing that Hansen's J-statistic measures, asymptotically, the range of estimates achievable at a given standard error. Given the widespread use of inefficient estimators and the resulting researcher degrees of freedom, we thus particularly recommend the broader reporting of J-statistics.
title The purpose of an estimator is what it does: Misspecification, estimands, and over-identification
topic Econometrics
Methodology
url https://arxiv.org/abs/2508.13076