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Title:

Examining Estimation Bias and Efficiency for Pseudopanel Data in Travel Demand Analysis

Accession Number:

01472367

Record Type:

Component

Availability:

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Order URL: http://www.trb.org/Main/Blurbs/169731.aspx

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Order URL: http://worldcat.org/isbn/9780309286701

Abstract:

Pseudopanel data have been increasingly applied in travel demand analysis to investigate the long-run travel demand when genuine panel data are unavailable. However, conventional estimation techniques have typically been used without a careful consideration of some unique properties of pseudopanel data. This paper shows that ignoring these properties potentially leads to estimation bias or inefficiency not observed in genuine panel data. The method used is a Monte Carlo experiment with scenarios designed to generate various data possessing pseudopanel data characteristics under conditions of limited observations; the performance of various estimator is evaluated with the use of the simulation results. This research found that the large between-group variation of the exogenous variable and the variance of unobserved group effects in pseudopanel data are the primary causes of estimation bias and inefficiency. Other factors such as cohort sizes and nonspherical errors have a smaller effect on the estimators’ performance. An empirical application using Sydney Household Travel Survey data is also presented to illustrate the simulation findings.

Monograph Accession #:

01496622

Report/Paper Numbers:

13-0538

Language:

English

Authors:

Tsai, Chi-Hong (Patrick)
Leong, Waiyan
Mulley, Corinne
Clifton, Geoffrey

Pagination:

pp 1–8

Publication Date:

2013

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 2354
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

9780309286701

Media Type:

Print

Features:

References (23) ; Tables (7)

Subject Areas:

Administration and Management; Data and Information Technology; Highways; I70: Traffic and Transport

Files:

PRP, TRIS, TRB, ATRI

Created Date:

Feb 5 2013 12:14PM

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