A Random Parameter Model with Onsite Sampling for Recreation Site Choice: An Application to Southern California Shoreline Sportfishing
A Random Parameter Model with Onsite Sampling for Recreation Site Choice: An Application to Southern California Shoreline Sportfishing
复制标题
用于休闲地点选择的现场采样随机参数模型:在南加州海岸线钓鱼运动中的应用
DOI:
10.1007/s10640-013-9640-4
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发表时间:
2013
影响因子:
5.9
通讯作者:
Michael Hanemann
中科院分区:
文献类型:
--
作者:
Kuriyama;Koichi;James Hilger; Michael Hanemann
Estimation of consistent parameter estimates for recreational demand models faces challenges arising from the choice-based nature of the data collected primarily for resource management purposes. As an alternative to randomized respondent-based sampling, choice-based onsite sampling can provide information on actual choices made by a subset of the population where participation has a low incidence. While the literature has shown that under specific restrictions the estimation of choice models from onsite sampling data yields unbiased fixed parameter estimates for the conditional logit model, this result does not carry over to estimation of the random parameter logit model. We propose an estimator for the unbiased estimation of the random parameter model using choice-based data; our estimator uses weights based on information about the level of sampling effort. An empirical application of the standard and weighted discrete choice RUM models to onsite sample data on recreational fishing illustrates the advantages of the proposed estimator. The estimation results indicate the compensating variation associated with an decrease, or increase, of 50 % in expected catch rates for a recreational shoreline sportfishing trip to a man-made structure in southern California is $$-{\$}2.80$$ or $${\$}3.54$$ per trip, respectively.
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