Investigating preference heterogeneity in a repeated discrete-choice recreation demand model of Atlantic salmon fishing
Abstract: Estimating a demand system under the assumption that preferences are homogeneous may lead to biased estimates of parameters for any specific individual and significantly different expected consumer surplus estimates. This paper investigates several different parametric methods to incorpora...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.138.2053 2023-05-15T15:30:36+02:00 Investigating preference heterogeneity in a repeated discrete-choice recreation demand model of Atlantic salmon fishing William S. Breffle Edward R. Morey The Pennsylvania State University CiteSeerX Archives 2000 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.138.2053 http://www.colorado.edu/economics/morey/papers/het.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.138.2053 http://www.colorado.edu/economics/morey/papers/het.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.colorado.edu/economics/morey/papers/het.pdf preference heterogeneity random parameters recreation demand discrete-choice travel cost model complete demand system logit Atlantic Salmon fishing text 2000 ftciteseerx 2016-01-07T14:47:52Z Abstract: Estimating a demand system under the assumption that preferences are homogeneous may lead to biased estimates of parameters for any specific individual and significantly different expected consumer surplus estimates. This paper investigates several different parametric methods to incorporate heterogeneity in the context of a repeated discrete-choice model. The first is the classic method of assuming utility to be a function of individual characteristics. Second, a random parameters method is proposed, where preference parameters have some known distribution. Random parameters logit causes the random components to be correlated across choice occasions and, in a sense, eliminates IIA. Simulation noise is discussed. Finally, methods are proposed to relax the assumption that the unobserved stochastic component of utility is identically distributed across individuals. For example, randomization of the logit scale, which is a new method, allows noise levels to vary across individuals, without the added burden of explaining the source using covariates. The application is to Atlantic salmon fishing, and expected compensating variations and changes in trip patterns are compared across the models for three policy-relevant changes in fishing conditions at the Penobscot River, the best salmon fishing site in Maine. Text Atlantic salmon Unknown |
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English |
topic |
preference heterogeneity random parameters recreation demand discrete-choice travel cost model complete demand system logit Atlantic Salmon fishing |
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preference heterogeneity random parameters recreation demand discrete-choice travel cost model complete demand system logit Atlantic Salmon fishing William S. Breffle Edward R. Morey Investigating preference heterogeneity in a repeated discrete-choice recreation demand model of Atlantic salmon fishing |
topic_facet |
preference heterogeneity random parameters recreation demand discrete-choice travel cost model complete demand system logit Atlantic Salmon fishing |
description |
Abstract: Estimating a demand system under the assumption that preferences are homogeneous may lead to biased estimates of parameters for any specific individual and significantly different expected consumer surplus estimates. This paper investigates several different parametric methods to incorporate heterogeneity in the context of a repeated discrete-choice model. The first is the classic method of assuming utility to be a function of individual characteristics. Second, a random parameters method is proposed, where preference parameters have some known distribution. Random parameters logit causes the random components to be correlated across choice occasions and, in a sense, eliminates IIA. Simulation noise is discussed. Finally, methods are proposed to relax the assumption that the unobserved stochastic component of utility is identically distributed across individuals. For example, randomization of the logit scale, which is a new method, allows noise levels to vary across individuals, without the added burden of explaining the source using covariates. The application is to Atlantic salmon fishing, and expected compensating variations and changes in trip patterns are compared across the models for three policy-relevant changes in fishing conditions at the Penobscot River, the best salmon fishing site in Maine. |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
William S. Breffle Edward R. Morey |
author_facet |
William S. Breffle Edward R. Morey |
author_sort |
William S. Breffle |
title |
Investigating preference heterogeneity in a repeated discrete-choice recreation demand model of Atlantic salmon fishing |
title_short |
Investigating preference heterogeneity in a repeated discrete-choice recreation demand model of Atlantic salmon fishing |
title_full |
Investigating preference heterogeneity in a repeated discrete-choice recreation demand model of Atlantic salmon fishing |
title_fullStr |
Investigating preference heterogeneity in a repeated discrete-choice recreation demand model of Atlantic salmon fishing |
title_full_unstemmed |
Investigating preference heterogeneity in a repeated discrete-choice recreation demand model of Atlantic salmon fishing |
title_sort |
investigating preference heterogeneity in a repeated discrete-choice recreation demand model of atlantic salmon fishing |
publishDate |
2000 |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.138.2053 http://www.colorado.edu/economics/morey/papers/het.pdf |
genre |
Atlantic salmon |
genre_facet |
Atlantic salmon |
op_source |
http://www.colorado.edu/economics/morey/papers/het.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.138.2053 http://www.colorado.edu/economics/morey/papers/het.pdf |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766361059334029312 |