EconStor >
Forschungsinstitut zur Zukunft der Arbeit (IZA), Bonn >
IZA Discussion Papers, Forschungsinstitut zur Zukunft der Arbeit (IZA) >

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10419/34121
  
Title:Testing dependence among serially correlated multi-category variables PDF Logo
Authors:Pesaran, Mohammad Hashem
Timmermann, Allan
Issue Date:2006
Series/Report no.:IZA Discussion Papers 2196
Abstract:The contingency table literature on tests for dependence among discrete multi-category variables is extensive. Existing tests assume, however, that draws are independent, and there are no tests that account for serial dependencies - a problem that is particularly important in economics and finance. This paper proposes a new test of independence based on the maximum canonical correlation between pairs of discrete variables. We also propose a trace canonical correlation test using dynamically augmented reduced rank regressions or an iterated weighting method in order to account for serial dependence. Such tests are useful, for example, when testing for predictability of one sequence of discrete random variables by means of another sequence of discrete random variables as in tests of market timing skills or business cycle analysis. The proposed tests allow for an arbitrary number of categories, are robust in the presence of serial dependencies and are simple to implement using multivariate regression methods. Monte Carlo experiments show that the proposed tests have good finite sample properties. An empirical application to survey data on forecasts of GDP growth demonstrates the importance of correcting for serial dependencies in predictability tests.
Subjects:contingency tables
canonical correlations
serial dependence
tests of predictability
JEL:C12
C22
C42
C52
Document Type:Working Paper
Appears in Collections:IZA Discussion Papers, Forschungsinstitut zur Zukunft der Arbeit (IZA)

Files in This Item:
File Description SizeFormat
514746963.pdf384.49 kBAdobe PDF
No. of Downloads: Counter Stats
Download bibliographical data as: BibTeX
Share on:http://hdl.handle.net/10419/34121

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.