Revealed preference analysis with normal goods: Application to cost of living indices

Principal Investigator(s): View help for Principal Investigator(s) Laurens Cherchye, KU Leuven; Thomas Demuynck, Université libre de Bruxelles; Bram De Rock, Université libre de Bruxelles; Khushboo Surana, KU Leuven; Matthew Richardson, ICPSR; Re Testing, PuMUS

Version: View help for Version V10

Name	File Type	Size	Last Modified
Data-and-Codes			08/03/2019 06:46:AM
Readme.pdf	application/pdf	112.5 KB	09/02/2019 12:31:AM
collegeCompletion.txt	text/plain	1.1 MB	09/24/2019 04:53:AM

Project Citation:

Cherchye, Laurens, Demuynck, Thomas, De Rock, Bram, Surana, Khushboo, Richardson, Matthew, and Testing, Re. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-09-24. https://doi.org/10.17889/E110942V10

Project Description

Summary: We present a revealed preference methodology for nonparametric demand analysis under the assumption of normal goods. Our methodology is flexible in that it allows for imposing normality on any subset of goods. We show the usefulness of our methodology for empirical welfare analysis through cost of living indices. An illustration to US consumption data drawn from the Panel Study of Income Dynamics (PSID) demonstrates that mild normality assumptions can substantially strengthen the empirical analysis. It obtains considerably tighter bounds on cost of living indices, and a significantly more informative classification of better-off and worse-off individuals after the 2008 financial crisis.

Funding Sources: NIH (231956)

Scope of Project

Subject Terms: TEST; another test

Time Period(s): 9/13/2019 – 9/13/2019

Collection Date(s): 9/24/2019 – 9/24/2019

Methodology

Response Rate: 0%

Scales: test scale

Geographic Unit: household

Related Publications

Download this project

Published Versions

Export Metadata

Dublin Core

DDI 2.5

Report a Problem

Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.

This material is distributed exactly as it arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.