Gravity model estimation with proxy variables and the impact of endogeneity on transportation planning

Transportation Research Part A: Policy and Practice

Volumn 43, Issue 2, 2009, Pages 105-116

  de Grange, Louis ^a   Troncoso, Rodrigo ^a   Ibeas, Angel ^b   González, Felipe ^b  

^a UNIVERSIDAD DIEGO PORTALES   (Chile)

^b UNIVERSITY OF CANTABRIA   (Spain)

Author keywords

Bias; Consumer surplus; Endogeneity; Gravity model; Proxy variables

Indexed keywords

LEAST SQUARES APPROXIMATIONS; LINEAR REGRESSION;

BIAS; CONSUMER SURPLUS; ENDOGENEITY; GRAVITY MODEL; PROXY VARIABLES;

URBAN TRANSPORTATION;

ESTIMATION METHOD; LEAST SQUARES METHOD; MULTIPLE REGRESSION; STATISTICAL ANALYSIS; TRANSPORTATION PLANNING; TRANSPORTATION SYSTEM; URBAN TRANSPORT;

EID: 58149389958     PISSN: 09658564     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.tra.2008.07.002     Document Type: Article

References (21)

1. Abrahamsson T., and Lundqvist L. Formulation and estimation of combined network equilibrium models with applications to Stockholm. Transportation Science 33 (1999) 80-100
2. Anas A. The estimation of multinomial logit models of joint location and mode choice from aggregated data. Journal of Regional Science 21 2 (1981) 223-242
3. Alonso, W., 1973. National Interregional Demographic Accounts: A Prototype. Monograph 17, Institute of Urban and Regional Development, University of California, Berkeley.
4. Alonso, W., 1986. Systemic and Log-linear Models: From Here to There, Then to Now, and This to That. Discussion Paper 86-10, Centre for Population Studies, Harvard University.
5. Bikker J.A. Internal and external trade liberalization in the EEC: an econometric analysis of international trade flows. Economie Appliquee 45 3 (1992) 91-119
6. De vos, A.F., Bikker, J.A., 1982. Interdependent Multiplicative Models for Allocation and Aggregates; A Generalization of Gravity Models. Onderzoeksverslag IAWE-80, Vrije Universiteit, Amsterdam.
7. De vries, J., Nijkamp, P., Rietveld, P., 2000. Alonso's General Theory of Movement. TI 2000-062/3 Tinbergen Institute Discussion Paper.
8. Fang S.C., and Tsao S.J. Linearly-constrained entropy maximization problem with quadratic cost and its applications to transportation planning problems. Transportation Science 29 4 (1995) 353-365
9. Fernández, J.E., De Cea, J., De Grange, L., 2007. A Consolidate Approach for the Formulation and Calibration of Entropic Trip Distribution Models. 11th WCTR, June 24-28, University of California, Berkeley.
10. Fotheringham A.S. A new set of spatial interaction models: the theory of competing destinations. Environment and Planning A 15 (1983) 15-36
11. Gonçalves M., and Souza J.E. Parameter estimation in a trip distribution model by random perturbation of a descent method. Transportation Research Part B 35 (2001) 137-161
12. Green W.H. Econometric Analysis. fifth ed. (2003), Prentice Hall Inc
13. Hausman J. Specification tests in econometrics. Econometrica 46 (1978) 1251-1271
14. Morrison W.I., and Thumann R.G. Lagrangian multiplier approach to the solution of a special constrained matrix problem. Journal of Regional Science 20 3 (1980) 279-292
15. Orpana T., and Lampinen J. Building spatial choice models from aggregate data. Journal of Regional Science 43 2 (2003) 319-347
16. Ortuzar de J.D., and Willumsen L.G. Modelling Transport (2001), John Wiley & Sons, Chichester
17. Pindyck R.S., and Rubinfeld D.L. Econometric Models and Econometric Forecast (1998), McGraw-Hill Companies Inc
18. Sen A., and Matuszewsky Z. Maximum likelihood estimates of gravity model parameters. Journal of Regional Science 31 4 (1991) 469-486
19. Williams H.C. Travel demand models, duality relations and user benefit analysis. Journal of Regional Science 16 (1976) 147-166
20. Wilson A.G. Entropy in Urban and Regional Modeling (1970), Pion, London
21. Wooldridge J. Econometric Analysis of Cross Section and Panel Data (2002), The MIT Press