Englin, J., T. A. Cameron, and D. Poisson Regression Analyses with Individual Panel (1996) “Augmenting Travel Cost Models with Contingent Behavior Data,” Environmental and Resource Economics, 7 (2), 133-47.
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Hensher, D., J. Louviere, and J. Swait (1999) “Combining sources of preference data,” Journal of Econometrics, 89 (1-2), 197-221.
This paper brings together several research streams and concepts that have been evolving in random utility choice theory: (1) it reviews the literature on stated preference (SP) elicitation methods and introduces the concept of testing data generation process invariance across SP and revealed preference (RP) choice data sources; (2) it describes the evolution of discrete choice models within the random utility family, where progressively more behavioural realism is being achieved by relaxing strong assumptions on the role of the variance structure (specifically, heteroscedasticity) of the unobserved effects, a topic central to the issue of combining multiple data sources; (3) particular choice model formulations incorporating heteroscedastic effects are presented, discussed and applied to data. The rich insights possible from modelling heteroscedasticity in choice processes are illustrated in the empirical application, highlighting its relevance to issues of data combination and taste heterogeneity. (C) 1999 Elsevier Science S.A. All rights reserved. JEL classification: C25.
Heyes, C., and A. Heyes (1999) “Willingness to pay versus willingness to travel: Assessing the recreational benefits from Dartmoor National Park,” Journal of Agricultural Economics, 50 (1), 124-139.
Liston-Heyes, C., and A. Heyes (1999) “Recreational benefits from the Dartmoor National Park,” Journal of Environmental Management, 55 (2), 69-80.
The travel cost method (TCM) is commonly used by Government agencies to evaluate the benefits users derive from access to parks and other recreational sites. The results of such studies can provide useful input into policy-design, in informing park designation decisions and in helping guide management on issues such as visitor access. The authors investigate various aspects of the application of the methodology in the context of a case study of the Dartmoor National Park in England. (C) 1999 Academic Press.
Nestor, D. V. (1998) “Policy evaluation with combined actual and contingent response data,” American Journal of Agricultural Economics, 80 (2), 264-276.
The City of Marietta, Georgia, experimentally switched from flat fee financing to volume-based pricing for its trash services in January 1994. Both before and during the experiment, detailed data on individuals' observed responses to the actual introduction and contingent behavioral responses to a hypothetical introduction of volume-based pricing were collected. This study applies these data, and investigates the methodology of collecting contingent behavior data and their use in policy analysis. In particular, this study empirically evaluates the effect of experience with the policy on responses to contingent behavior questions, and tests for potential bias in the contingent behavior data.
Loomis, J. B. (1997) “Panel estimators to combine revealed and stated preference dichotomous choice data,” Journal of Agricultural and Resource Economics, 22 (2), 233-245.
Combining stated and revealed preference data often involves multiple responses from the same individual. Panel estimators are appropriate to jointly model the decision to actually visit at current trip costs, the intention to visit at hypothetically higher trip costs, and the intention to visit at proposed quality levels. To incorporate data on all three choices, the random effects probit model is used to estimate the economic value of changes in instream flow. This model illustrates how the complementarity of revealed and stated preference data allows including of instream flow as a covariate in the model and calculating value under alternative flow regimes.
Huang, J. C., T. C. Haab, and J. C. Whitehead (1997) “Willingness to pay for quality improvements: Should revealed and stated preference data be combined?,” Journal of Environmental Economics and Management, 34 (3), 240-255.
In this article we propose theoretically consistent welfare measurement of use and nonuse values for an improvement in environmental duality with revealed and stated preference data. An analytical model based on the comparative static analysis of the variation function that describes the relationship between recreation demand and dichotomous choice contingent valuation models is estimated. Our results show that revealed and stated data should not be combined under the same assumed preference structure unless the two decisions imply the same change in behavior induced by the quality change. In addition, our results indicate scope effects in willingness to pay measures estimated with stated preference data. (C) 1997 Academic Press.
Cameron, T. A., et al. (1996) “Using actual and contingent behavior data with differing levels of time aggregation to model recreation demand,” Journal of Agricultural and Resource Economics, 21 (1), 130-149.
A model of recreation demand is developed to determine the role of water levels in determining participation at and frequency of trips taken to various federal reservoirs and rivers in the Columbia River Basin. Contingent behavior data are required to break the near-perfect multicollinearities among water levels at some waters. We combine demand data for each survey respondent at different levels of time aggregation (summer months, rest of year, and annual), and our empirical models accommodate the natural heteroskedasticity that results. Our empirical results show it to be quite important to control carefully for survey nonresponse bias.