Hypothesis Testing in Econometrics

Joseph P. Romano, Azeem M. Shaikh () and Michael Wolf ()
Additional contact information
Michael Wolf: Departments of Economics and Statistics, Stanford University, Stanford, California 94305

Annual Review of Economics, 2010, vol. 2, issue 1, pages 75-104

Abstract: This article 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, we summarize some of the most important methods, 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 many problems with well-known successful solutions are included, we also address open problems that are not easily handled with current technology, stemming from such issues as lack of optimality or poor asymptotic approximations.

Keywords: asymptotics; multiple testing; optimality; resampling (search for similar items in EconPapers)
JEL-codes: C12 (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link)
http://www.annualreviews.org/doi/abs/10.1146/annurev.economics.102308.124342 (application/pdf)
Full text downloads are only available to subscribers. Visit the abstract page for more information.

Related works:
Working Paper: Hypothesis testing in econometrics (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:anr:reveco:v:2:y:2010:p:75-104

Ordering information: This journal article can be ordered from
http://www.annualreviews.org/action/ecommerce

Access Statistics for this article

More articles in Annual Review of Economics from Annual Reviews
Address: Annual Reviews 4139 El Camino Way Palo Alto, CA 94306, USA
Series data maintained by http://www.annualreviews.org ().