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

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.

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References

Deaton

Panel Data from Time Series of Cross-Sections. Journal of Econometrics, Vol. 30, No. 1-2, 1985, pp. 109–126.

Ortúzar

J. d. D.

, Armoogum

, Madre

J.-L.

, and Potier

Continuous Mobility Surveys: The State of Practice. Transport Reviews, Vol. 31, No. 3, 2011, pp. 293–312.

Dargay

J. M.

, and Vythoulkas

P. C.

Estimation of Dynamic Car Ownership Model: A Pseudo-Panel Approach. Journal of Transport Economics and Policy, Vol. 33, No. 3, 1999, pp. 287–302.

Dargay

J. M.

Determinants of Car Ownership in Rural and Urban Areas: A Pseudo-Panel Analysis. Transportation Research Part E, Vol. 38, No. 5, 2002, pp. 351–366.

Dargay

The Effect of Prices and Income on Car Travel in the UK. Transportation Research Part A, Vol. 41, No. 10, 2007, pp. 949–960.

Huang

The Use of Pseudo Panel Data for Forecasting Car Ownership. Birkbeck College, University of London, 2007.

Weis

, and Axhausen

K. W.

Induced Travel Demand: Evidence from a Pseudo Panel Data Based Structural Equations Model. Research in Transportation Economics, Vol. 25, No. 1, 2009, pp. 8–18.

Plümper

, and Troeger

V. E.

Efficient Estimation of Time-Invariant and Rarely Changing Variables in Finite Sample Panel Analyses with Unit Fixed Effects. Political Analysis, Vol. 15, No. 2, 2007, pp. 124–139.

Plümper

, and Troeger

V. E.

Fixed-Effects Vector Decomposition: Properties, Reliability, and Instruments. Political Analysis, Vol. 19, No. 2, 2011, pp. 147–164.

10.

Parks

R. W.

Efficient Estimation of a System of Regression Equations When Disturbances Are Both Serially and Contemporaneously Correlated. Journal of the American Statistical Association, Vol. 62, No. 318, 1967, pp. 500–509.

11.

Beck

, and Katz

J. N.

What to Do (and Not to Do) with Time-Series Cross-Section Data. The American Political Science Review, Vol. 89, No. 3, 1995, pp. 634–647.

12.

Chen

, Lin

, and Reed

W. R.

A Monte Carlo Evaluation of the Efficiency of the PCSE Estimator. Applied Economics Letters, Vol. 17, No. 1, 2009, pp. 7–10.

13.

Reed

W. R.

, and Ye

Which Panel Data Estimator Should I Use?

Applied Economics, Vol. 43, No. 8, 2011, pp. 985–1000.

14.

Nickell

Biases in Dynamic Models with Fixed Effects. Econometrica, Vol. 49, No. 6, 1981, pp. 1417–1426.

15.

Anderson

T. W.

, and Hsiao

Estimation of Dynamic Models with Error Components. Journal of the American Statistical Association, Vol. 76, No. 375, 1981, pp. 598–606.

16.

Arellano

, and Bond

Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies, Vol. 58, No. 2, 1991, pp. 277–297.

17.

Kiviet

J. F.

On Bias, Inconsistency, and Efficiency of Various Estimators in Dynamic Panel Data Models. Journal of Econometrics, Vol. 68, No. 1, 1995, pp. 53–78.

18.

Beck

, and Katz

J. N.

Time-Series-Cross-Section Issues: Dynamics. Working paper. The Society for Political Methodology, Washington University in Saint Louis, Mo., 2004.

19.

Verbeek

, and Nijman

Can Cohort Data Be Treated as Genuine Panel Data?

Empirical Economics, Vol. 17, No. 9, 1992, pp. 9–23.

20.

Blundell

, and Bond

Initial Conditions and Moment Restrictions in Dynamic Panel Data Models. Journal of Econometrics, Vol. 87, No. 1, 1998, pp. 115–143.

21.

McKenzie

D. J.

Asymptotic Theory for Heterogeneous Dynamic Pseudo-Panels. Journal of Econometrics, Vol. 120, No. 2, 2004, pp. 235–262.

22.

Inoue

Efficient Estimation and Inference in Linear Pseudo-Panel Data Models. Journal of Econometrics, Vol. 142, No. 1, 2008, pp. 449–466.

23.

Judson

R. A.

, and Owen

A. L.

Estimating Dynamic Panel Data Models: A Guide for Macroeconomists. Economics Letters, Vol. 65, No. 1, 1999, pp. 9–15.