当用户的相关信息有限时,娱乐随机效用模型中偏好异质性的建模

IF 0.8 Q3 ECONOMICS
Aestimum Pub Date : 2020-06-23 DOI:10.13128/AESTIM-7792
M. Salvo, G. Cucuzza, C. Prato, G. Signorello
{"title":"当用户的相关信息有限时,娱乐随机效用模型中偏好异质性的建模","authors":"M. Salvo, G. Cucuzza, C. Prato, G. Signorello","doi":"10.13128/AESTIM-7792","DOIUrl":null,"url":null,"abstract":"We suggest a novel approach to analyze revealed preference heterogeneity in recreation random utility maximization models when information about users is limited to their place of residence. We assume that recreationists living in the same place act as a “cohort” and that their preferences are hence homogeneous. We adopt a location-specific distribution criterion. We empirically test the suitability of this spatial approach by comparing its econometric performance and welfare estimates with that of the standard individual framework. We use data on hunting in Sicily to empirically test the cohort approach. Results from individual-specific and location-specific mixed logit models suggest that econometric performance improves when modeling heterogeneity with a location-specific conditional distribution. Further, marginal willingness-to-pay mean values and distributions for site characteristics differ significantly.","PeriodicalId":53999,"journal":{"name":"Aestimum","volume":"1 1","pages":"5-17"},"PeriodicalIF":0.8000,"publicationDate":"2020-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modeling preference heterogeneity in recreation random utility models when relevant information about users is limited\",\"authors\":\"M. Salvo, G. Cucuzza, C. Prato, G. Signorello\",\"doi\":\"10.13128/AESTIM-7792\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We suggest a novel approach to analyze revealed preference heterogeneity in recreation random utility maximization models when information about users is limited to their place of residence. We assume that recreationists living in the same place act as a “cohort” and that their preferences are hence homogeneous. We adopt a location-specific distribution criterion. We empirically test the suitability of this spatial approach by comparing its econometric performance and welfare estimates with that of the standard individual framework. We use data on hunting in Sicily to empirically test the cohort approach. Results from individual-specific and location-specific mixed logit models suggest that econometric performance improves when modeling heterogeneity with a location-specific conditional distribution. Further, marginal willingness-to-pay mean values and distributions for site characteristics differ significantly.\",\"PeriodicalId\":53999,\"journal\":{\"name\":\"Aestimum\",\"volume\":\"1 1\",\"pages\":\"5-17\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2020-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Aestimum\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.13128/AESTIM-7792\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aestimum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13128/AESTIM-7792","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 1

摘要

当用户的信息仅限于他们的居住地时,我们提出了一种新的方法来分析娱乐随机效用最大化模型中揭示的偏好异质性。我们假设生活在同一个地方的娱乐主义者是一个“群体”,因此他们的偏好是同质的。我们采用特定地点的分布标准。我们通过将这种空间方法的计量经济表现和福利估计与标准个人框架的比较,实证检验了这种方法的适用性。我们使用西西里岛狩猎的数据来实证检验队列方法。个体特定和地点特定的混合logit模型的结果表明,当用地点特定的条件分布对异质性进行建模时,计量经济性能会提高。此外,边际支付意愿平均值和场地特征分布存在显著差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling preference heterogeneity in recreation random utility models when relevant information about users is limited
We suggest a novel approach to analyze revealed preference heterogeneity in recreation random utility maximization models when information about users is limited to their place of residence. We assume that recreationists living in the same place act as a “cohort” and that their preferences are hence homogeneous. We adopt a location-specific distribution criterion. We empirically test the suitability of this spatial approach by comparing its econometric performance and welfare estimates with that of the standard individual framework. We use data on hunting in Sicily to empirically test the cohort approach. Results from individual-specific and location-specific mixed logit models suggest that econometric performance improves when modeling heterogeneity with a location-specific conditional distribution. Further, marginal willingness-to-pay mean values and distributions for site characteristics differ significantly.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Aestimum
Aestimum ECONOMICS-
CiteScore
2.30
自引率
0.00%
发文量
4
审稿时长
12 weeks
期刊介绍: Aestimum is a peer-reviewed Journal dedicated to the methodological study of appraisal and land economics. Established in 1976 by the Italian Association of Appraisers and Land Economists, which was legally recognized by Ministerial Decree, March 1993. Topics of interests comprise rural, urban and environmental appraisal, evaluation of public investments and land use planning. All the areas under discussion are addressed to the International scene. The interdisciplinary approach is one of the mainstays of this editorial project and all of the above mentioned topics are developed taking into consideration the economic, legal and urban planning aspects. Aestimum is biannual Journal and publishes articles both in Italian and English. Articles submitted are subjected to a double blind peer review process.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信