Powerful t-Tests in the presence of nonclassical measurement error.

Autor/inn/en	Kim, Dongwoo; Wilhelm, Daniel
Titel	Powerful t-Tests in the presence of nonclassical measurement error.
Quelle	[London]: Cemmap, Centre for Microdata Methods and Practice, The Institute for Fiscal Studies, Department of Economics, UCL (2023), ca. 50 S. PDF als Volltext kostenfreie Datei (1); PDF als Volltext kostenfreie Datei (2) Link als defekt meldenVerfügbarkeit
Reihe	Cemmap working paper. 22/23
Beigaben	Illustrationen
Sprache	englisch
Dokumenttyp	online; Monographie; Graue Literatur
DOI	10.47004/wp.cem.2023.2223
Schlagwörter	Test; Bildungsertrag; Fehler; Regressionsanalyse; Statistik; Simulation; Großbritannien
Abstract	This paper proposes a powerful alternative to the t-test of the null hypothesis that a coefficient in linear regression is equal to zero when a regressor is mismeasured. We assume there are two contaminated measurements of the regressor of interest. We allow the two measurement errors to be nonclassical in the sense that they may both be correlated with the true regressor, they may be correlated with each other, and we do not require any location normalizations on the measurement errors. We propose a new maximal t-statistic that is formed from the regression of the outcome onto a maximally weighted linear combination of the two measurements. Critical values of the test are easily computed via a multiplier bootstrap. In simulations, we show that this new test can be significantly more powerful than t-statistics based on OLS or IV estimates. Finally, we apply the proposed test to a study of returns to education based on twins data from the UK. With our maximal t-test, we can discover statistically significant returns to education when standard t-tests do not.
Erfasst von	ZBW - Leibniz-Informationszentrum Wirtschaft, Kiel
Update	2024/1