Controlling for observed and unobserved site characteristics in RUM models of recreation demand

American Journal of Agricultural Economics

Volumn 94, Issue 5, 2012, Pages 1070-1093

  Abidoye, Babatunde O ^a   Herriges, Joseph A ^b   Tobias, Justin L ^c  

^a UNIVERSITY OF PRETORIA   (South Africa)

^b IOWA STATE UNIVERSITY   (United States)

^c PURDUE UNIVERSITY   (United States)

Author keywords

alternative specific constants; Bayesian econometrics; recreation demand

Indexed keywords

BAYESIAN ANALYSIS; COMPUTER SIMULATION; ESTIMATION METHOD; LOGIT ANALYSIS; NUMERICAL MODEL; RECREATIONAL ACTIVITY; TRAVEL BEHAVIOR;

EID: 84866292537     PISSN: 00029092     EISSN: 14678276     Source Type: Journal    
DOI: 10.1093/ajae/aas056     Document Type: Article

References (34)

1. Berry, S. (1994). Estimating Discrete-Choice Models of Product Differentiation,RAND Journal of Economics, 25 (2), 242-262.
2. Berry, S., J. Levinsohn and A. Pakes (1995). Automobile Prices in market Equilibrium, Econometrica, 63 (4), 841-890.
3. Berry, S., O. Linton, and A. Pakes (2004). LimitTheorems for Estimating the Parameters of Differentiated Product Demand Systems, Review of Economic Studies 71: 613-654.
4. Bockstael, N.E., W.M. Hanemann, and I.E. Strand (1986) Measuring the Benefits of Water Quality Improvements Using Recreation Demand Models, report presented to the Environmental Protection Agency under cooperative agreeement CR-811043-01-0,Washington,D.C.
5. Casella, G. and E. I. George (1992). Explaining the Gibbs Sampler, The American Statistician, 46 (3) (August), 167-174.
6. Chen, H.Z., F. Lupi, and J.P. Hoehn (1999). An Empirical Assessment of Multinomial Probit and Logit Models for Recreation Demand, in: Valuing Recreation and the Environment: Revealed Preference Methods in Theory and Practice (ed. Herriges, J.A., and C.L. Kling), Cheltenham, UK: Edward Elgar, pp. 141-161.
7. Chib,S andB.P. Carlin (1999).OnMCMCsampling in hierarchical longitudinal models, Statistics and Computing, (9), 17-26.
8. Egan, K.J., J.A. Herriges, C.L. Kling and J.A Downing (2009). Valuing Water Quality as a Function of Water Quality Measures, American Journal of Agricultural Economics., 91 (1) (Feb.), 106-123.
9. Freeman, A.M (1979). The Benefits of Air and Water Pollution Control: A Review and Synthesis of Recent Estimates, Report Prepared for the Council on Environmental Quality, Bowdoin College, Brunswick, maine, December.
10. George, E.I.,and R. E. McCulloch (1993),Variable Selection Via Gibbs Sampling. Journal of the American Statistical Association 88(423): 881-89.
11. Geweke, J. (1991). Efficient simulation from the multivariate Normal and Student-t distributions subject to linear constraints, in: Computer Science and Statistics: Proceedings of the Twenty-Third Symposium on the Interface (ed. E. Keramidas), Interface Foundation of North America, Inc., Fairfax, 571-578.
12. Hanemann, W.M (1981). Water Quality and the Demand for Recreation, Department of Agricultural & Resource Economics, UCB. CUDARE Working Paper 164, March.
13. Hausman, J., G. Leonard, and D. McFadden (1995). A Utility-Consistent, Combined Discrete Choice and Count Data Model Assessing Recreational Use Losses Due To Natural Resource Damage, Journal of Public Economics, 56:1-30.
14. Herriges, J., and D. Phaneuf (2002). Inducing Patterns Correlation and Substitution in Repeated Logit Model of Recreation Demand,American Journal of Agricultural Economics, 84, 1076-1090.
15. Herriges, J.A, C.L. Kling and D. Phaneuf (1999). Corner Solution Models of Recreation Demand: A Comparison of Competing Frameworks in: Valuing Recreation and the Environment: Revealed Preference Methods inTheory and Practice (ed. Herriges, J.A., and C.L. Kling), Cheltenham, UK: Edward Elgar, pp. 141-161. 163-197.
16. Jiang, R., P. Manchanda and P.E. Rossi (2009). Bayesian analysis of random coefficient logit models using aggregate data, Journal of Econometrics, 149, 136-148.
17. Klaiber, H.A. and R. H. von Haefen (2008). Incorporating Random Coefficients and Alternative Specific Constants into Discrete Choice Models: Implications for In-Sample Fit and Welfare Estimates. Working paper, March.
18. Koop, G. (2003). Bayesian Econometrics, Inc NetLibrary, NetLibrary, Inc, Published by J.Wiley.
19. Koop, G., D.J. Poirier and J.L. Tobias (2007). Bayesian Econometric Methods, Cambridge, Cambridge University Press.
20. Koop,G., and J. L.Tobias (2006) Semiparametric Bayesian Inference in Smooth Coefficient Models,Journal of Econometrics,134: 283-315.
21. Lancaster, T. (2004). An Introduction to Modern Bayesian Econometrics, Published by Blackwell Publishing Ltd, pp 294-295.
22. Lindley, D. and A. F. M. Smith (1972). Bayes estimates for the linear model, Journal of the Royal Statistical Society, Series B, 34, 1-41.
23. Madigan, D.M. and Raftery, A.E. (1994). Model selection and accounting for model uncertainty in graphical models using Occam's Window. Journal of the American Statistical Association, 89, 1335-1346.
24. Moeltner, K., and J. E. Englin (2004). Choice behavior under time-variant quality: State dependence versus 'playing-it-by-ear' in selecting ski resorts, Journal of Business & Economic Statistics 22(2): 214-224.
25. Morey, E.R., R.D. Rowe, and M. Watson (1993). A Repeated Nested-Logit Model of Atlantic Salmon Fishing, American Journal of Agricultural Economics, 75 (August), 578-592.
26. Murdock, J. (2006). Handling unobserved site characterisitics in random utility models of recreation demand, Journal of Environmental Economics and Management, 51, 1-25.
27. Parsons, G.R., E.C. Helm, and T. Bondelid (2003). Measuring the Economic Benefits of Water Quality Improvements to Recreational Users in Six Northeastern States:An Application to the Random Utility Maximization Model. Working Paper, University of Delaware, July.
28. Phaneuf, D.J., C.L. Kling, and J.A. Herriges (2000). Estimation and Welfare Calculations in a Generalized Corner Solution Model with an Application to Recreation Demand, The Review of Economics and Statisitcs, 82 (1) (February), 83-92.
29. Provencher, W., and R. Bishop (1997). An Estimable Dynamic Model of Recreation Behavior with an Application to Great Lakes Angling, Journal of Environmental Economics and Management, 33, pp. 107-27.
30. Rossi, P.E., G. M. Allenby, and R. McCulloch (2005). Bayesian Statistics and Marketing, JohnWiley & Sons Ltd.
31. Tihansky, D.P. (1975). A Survey of Empirical Studies, in: Cost Benefit Analysis andWater Pollution Policy (ed. H.R. Peskin and E.P. Sesking), 127-144.
32. Train, K. (2009). Discrete Choice Methods with Simulation, Cambridge University Press, 2nd edition, 2009.
33. von Haefen, R., and D. J. Phaneuf (2008), "Identifying Demand Parameters in the Presence of Unobservables: A Combined Revealed and Stated Preference Approach," Journal of Environmental Economics and Management, 56: 19-32.
34. Yang, S., Y. Chen, and G. Allenby (2003). Bayesian Analysis of Simultaneous Supply and Demand, Quantitative Marketing and Economics, (1), 251-275.