Template-Type: ReDIF-Paper 1.0
Series: Tinbergen Institute Discussion Papers
Creation-Date: 2015-05-22
Number: 15-061/III
Author-Name: Giuseppe De Luca
Author-Workplace-Name: University of Palermo, Italy
Author-Name: Jan Magnus
Author-Workplace-Name: VU University Amsterdam, the Netherlands
Author-Name: Franco Peracchi
Author-Workplace-Name: University of Tor Vergata, Rome, Italy
Title: On the Ambiguous Consequences of Omitting Variables
Abstract: This paper studies what happens when we move from a short regression to a long regression (or vice versa), when the long regression is shorter than the data-generation process. In the special case where the long regression equals the data-generation process, the least-squares estimators have smaller bias (in fact zero bias) but larger variances in the long regression than in the short regression. But if the long regression is also misspecified, the bias may not be smaller. We provide bias and mean squared error comparisons and study the dependence of the differences on the misspecification parameter.
Classification-JEL: C13, C51, C52
Keywords: Omitted variables, Misspecification, Least-squares estimators, Bias, Mean squared error
File-Url: https://papers.tinbergen.nl/15061.pdf
File-Format: application/pdf
File-Size: 161986 bytes
Handle: RePEc:tin:wpaper:20150061