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Bibliographic Details
Main Author: Blankmeyer, Eric
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2508.15969
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author Blankmeyer, Eric
author_facet Blankmeyer, Eric
contents Linear least squares regression is subject to bias due to an omitted variable, a mismeasured regressor, or simultaneity. A simple test to detect the bias is proposed and explored in simulation and in real data sets.
format Preprint
id arxiv_https___arxiv_org_abs_2508_15969
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A bias test for heteroscedastic linear least-squares regression
Blankmeyer, Eric
Econometrics
Linear least squares regression is subject to bias due to an omitted variable, a mismeasured regressor, or simultaneity. A simple test to detect the bias is proposed and explored in simulation and in real data sets.
title A bias test for heteroscedastic linear least-squares regression
topic Econometrics
url https://arxiv.org/abs/2508.15969