Linear regression with many controls of limited explanatory power

We consider inference about a scalar coefficient in a linear regression model. One previously considered approach to dealing with many controls imposes sparsity, that is, it is assumed known that nearly all control coefficients are (very nearly) zero. We instead impose a bound on the quadratic mean...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Quantitative economics 2021-05, Vol.12 (2), p.405-442
Hauptverfasser:	Li, Chenchuan Mark, Müller, Ulrich K
Format:	Artikel
Sprache:	eng
Schlagworte:	Bias C12 C21 Confidence intervals Econometrics Fines & penalties High dimensional linear regression Hypotheses invariance to linear reparameterizations L2 bound Monte Carlo simulation Power Regression analysis Sparsity Variables
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!