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The effect of choice set misspecification on welfare measures in random utility models

机译:选择集错误指定对随机效用模型中福利措施的影响

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摘要

Random utility models have been widely employed in environmental valuation. But stochastic choice set formation models in the random utility framework are rarely applied in this literature, although previous research has shown that ignoring choice set formation (when it exists) leads to biased parameter estimates and welfare measures. This paper conducts Monte Carlo (MC) experiments to investigate the directionality and magnitude of welfare measure bias arising from ignoring or misspecifying choice set formation. We find that when attribute cutoff-based choice set formation exists in the data generation process, typical RUM models ignoring or misspecifying choice set formation underestimate welfare measures by 30-50%. Models that approximate choice set formation may produce unbiased welfare measures, but constitute a promising area for future research. This paper illustrates the importance of applying choice set formation in environmental valuation and provides practical guidance about the usage of stochastic choice set formation models. (C) 2015 Elsevier B.V. All rights reserved.
机译:随机效用模型已广泛用于环境评估中。但是,尽管先前的研究表明,忽略选择集形成(如果存在)会导致参数估计和福利测度产生偏差,但随机效用框架中的随机选择集形成模型很少在该文献中应用。本文进行了蒙特卡洛(MC)实验,以研究由于忽视或错误指定选择集而引起的福利测度偏差的方向性和大小。我们发现,当在数据生成过程中存在基于属性截止的选择集形成时,忽略或错误指定选择集形成的典型RUM模型低估了福利措施30-50%。近似选择集形成的模型可能会产生公正的福利测度,但构成了未来研究的有希望的领域。本文阐述了在环境评估中应用选择集形成的重要性,并为使用随机选择集形成模型提供了实用指导。 (C)2015 Elsevier B.V.保留所有权利。

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