Hypothesis Testing in Econometrics
Institute for Empirical Research in Economics University of Zurich Working Paper No. 444
40 Pages Posted: 25 Sep 2009
There are 2 versions of this paper
Hypothesis Testing in Econometrics
Hypothesis Testing in Econometrics
Date Written: September 24, 2009
Abstract
This paper reviews important concepts and methods that are useful for hypothesis testing. First, we discuss the Neyman-Pearson framework. Various approaches to optimality are presented, including finite-sample and large-sample optimality. Then, some of the most important methods are summarized, as well as resampling methodology which is useful to set critical values. Finally, we consider the problem of multiple testing, which has witnessed a burgeoning literature in recent years. Along the way, we incorporate some examples that are current in the econometrics literature. While we include many problems with wellknown successful solutions, we also include open problems that are not easily handled with current technology, stemming from issues like lack of optimality or poor asymptotic approximations.
Keywords: asymptotics, multiple testing, optimality, resampling
JEL Classification: C12
Suggested Citation: Suggested Citation
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