This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

A Monte Carlo Study of the Necessary and Sufficient Conditions for Weak Separability

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Hjertstrand, Per () (Department of Economics, Lund University)
Abstract

Weak separability is an important concept in many fields of economic theory. This paper uses Monte Carlo experiments to investigate the performance of newly developed nonparametric revealed preference tests for weak separability. A main finding is that the bias of the sequentially implemented test for weak separability proposed by Fleissig and Whitney (A New PC-Based Test for Varian’s Weak Separability Conditions, Journal of Business and Economic Statistics 21, 133-143, 2003) is low. The theoretically unbiased Swofford and Whitney test (A revealed preference test for weakly separable utility maximization with incomplete adjustment, Journal of Econometrics 60, 235-249, 1994) is found to perform better than all sequentially implemented test procedures, but is found to suffer from an empirical bias, most likely because of the complexity in executing the test procedure. As a further source of information, we also perform sensitivity analyses on the nonparametric revealed preference tests. It is found that the Fleissig and Whitney test seems to be sensitive to measurement.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.nek.lu.se/publications/workpap/Papers/WP08_10.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Lund University, Department of Economics in its series Working Papers with number 2008:10.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 26 pages
Date of creation: 14 Jan 2008
Date of revision: 11 Sep 2008
Publication status: Published in Advances in Econometrics - Measurement Error: Consequences, Applications and Solutions , Binner, Jane, Edgerton, David, Elger, Thomas (eds.), 2009, pages 151-182, Emerald Group Publishing Ltd.
Handle: RePEc:hhs:lunewp:2008_010

Contact details of provider:
Postal: Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund,Sweden
Phone: +46 +46 222 0000
Fax: +46 +46 2224613
Web page: http://www.nek.lu.se/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (David Edgerton).

Related research
Keywords: GARP; LP test; Monte Carlo simulations; NONPAR; Weak separability; Swofford and Whitney test;

Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

This paper has been announced in the following NEP Reports:

Statistics
Access and download statistics

Did you know? LogEc provides statistical analysis about downloads from this service (and others).

This page was last updated on 2009-12-2.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.