No abstract

We consider alternative econometric strategies for addressing serial nonparticipation, that is, repeated choice of the same alternative or same type of alternative across a series of choice occasions, in data typically analyzed within the repeated discrete choice framework. Single and double hurdle variants of the repeated discrete choice model are developed and applied to choice experiment and multisite seasonal recreation demand data. Our results suggest that hurdle models can generate significant improvements in statistical fit and qualitatively different policy implications, particularly in choice experiment applications where the proper treatment of serial nonparticipation is relatively more ambiguous. Copyright 2005, Oxford University Press.

We estimate a random utility model of recreation demand accounting for choice set familiarity and favorite sites. Our approach differs from existing approaches by retaining all sites in estimating the parameters of site utility. Familiar and unfamiliar sites are specified with different utility functions. Favored sites are assumed to have higher utility than nonfavored sites in estimation.

and internal review of a final rule by the EPA; OMB review of the final rule; publication of the final rule in the Federal Register; and, finally, implementation of the rule. If the rule is expected to have an impact on the U.S. economy of $100 million per year or more, then it is deemed "economically significant" 1 and must be accompanied by a formal BCA at both the proposal and final stages (Fraas, 1991). This process can be time-consuming. To give an example, the EPA's regulations concerning discharges from Concentrated Animal Feeding Operations (CAFOs) were formally proposed two years after they were initially conceived and the rule was finalized three years after proposal (USEPA, 2009). In another illustrative case, the EPA's Steam Electric effluent guidelines were proposed four years after their conception, and finalized two years after the proposal (USEPA, 2015a). Within such timelines an iterative sequence of data collection, analysis, review, and revision must be conducted in compliance with a series of internally and externally imposed intermediate deadlines. The process begins with collecting large amounts of data. (In the case of the Steam Electric rule, for example, a nearly-400-page questionnaire was distributed to each manufacturing facility that might be subject to the new regulation.) The collected data are then used to develop policy options. Environmental engineers then estimate changes in pollution emissions, and water quality scientists produce estimates of changes in ambient water quality levels associated with each option. Economists use these predictions, as well as other information, to estimate the benefits and costs of each option considered for the proposed rule. After the rule is formally proposed, the process pauses for a public comment period-usually lasting between 60 and 120 daysduring which interested parties submit comments on the proposal to the EPA. Often a large portion of the public comments are submitted by the regulated industry, and these may include new data and analyses. The EPA then must respond to all submitted public comments and modify the rule options and analyses accordingly. Before a rule can be proposed or finalized, it also must pass through several rounds of internal review, plus external review by other federal agencies and OMB. While the overall time from conception to proposal of a rule, and then from proposal to finalization may stretch into years, the time to conduct a BCA may be more constrained. At each stage of review, EPA staff may be required to analyze new options for the rule on relatively short turnaround times. Furthermore, the policy options as originally configured might be partially or wholly obsolete before a rule-making is completed, and EPA analysts must be prepared to make rapid adjustments to the analysis in response to evolving requests from managers as the rulemaking proceeds. 2 These factors create a demand for flexible and timely benefit analysis approaches. In addition to the time pressure benefit-cost analysts may find themselves un...