Combining Aggregate Demand and Discrete Choice Data with Application to Deer License Demand in Indiana.
Estimating demand for licenses for recreational activities is complicated because of a lack of meaningful variation across time, space, buyer types, and license attributes, including price. Prior work uses discrete choice experiments (DCEs) to overcome this challenge, but the resulting demand models...
| Publicado en: | Land Economics Vol. 99; no. 4; pp. 477 - 490 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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University of Wisconsin Press
Nov2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=173052324&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 173052324 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00237639 LAE jtl: Land Economics issn: 00237639 maglogo: N pubinfo: dt: Nov2023 vid: 99 iid: 4 pid: 249 pub: University of Wisconsin Press artinfo: ui: 173052324 10.3368/le.99.4.120621-0144r1 ppf: 477 ppct: 13 formats: tig: atl: Combining Aggregate Demand and Discrete Choice Data with Application to Deer License Demand in Indiana. aug: au: Reeling, Carson Erickson, Dane Kim, Yusun Lee, John G. Widmar, Nicole J. O. su: Indiana Prices Aggregate demand Demand function Deer Market share sug: subj: Prices Indiana All other miscellaneous animal production All Other Animal Production Aggregate demand Demand function Deer Market share keyword: Q21 Q26 Q21 Q26 ab: Estimating demand for licenses for recreational activities is complicated because of a lack of meaningful variation across time, space, buyer types, and license attributes, including price. Prior work uses discrete choice experiments (DCEs) to overcome this challenge, but the resulting demand models are unlikely to replicate observed demands in the absence of ad hoc calibration procedures. We use a generalized method of moments–based approach that combines DCE data with observed market share data to estimate a choice model that yields demand functions that much more closely replicate observed data. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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