000264979 001__ 264979
000264979 005__ 20180123012308.0
000264979 037__ $$a1901-2017-5566
000264979 041__ $$aeng
000264979 084__ $$aQ51
000264979 084__ $$aC35
000264979 245__ $$aPartially observable latent class analysis (POLCA): An application to serial participation in mosquito control in Madison, WI
000264979 260__ $$c2016
000264979 269__ $$a2016-11-01
000264979 300__ $$a43
000264979 336__ $$aWorking or Discussion Paper
000264979 490__ $$aCEnREP Working Paper No. 16-015
000264979 520__ $$aSerial nonparticipation in nonmarket valuation using choice data is a frequently observed pattern of behavior in which an individual always appears to choose the status quo or ‘no program’ alternative. In choice models serial nonparticipation may be viewed as belonging to a class of deterministic choice patterns, other examples of which include serial participation and lexicographic preferences. While common in the context of environmental goods unfamiliar to respondents, logit-based choice models are ill-equipped for identifying such preferences, because predicted choice probabilities cannot take a value of zero or one. We extend latent class analysis (LCA) of preference heterogeneity to address this issue, for each class specifying a subset of alternatives that are avoided with certainty. We are then able to partially observe class membership, knowing with certainty that an individual does not belong to a class if she selects any alternatives excluded by that class. We apply our model to a discrete choice experiment on mosquito control programs to reduce West Nile virus risk and nuisance disamenities in Madison, Wisconsin. We find that partially observable latent class analysis (POLCA) obtains the same goodness of fit as LCA with fewer parameters. Adjusting for the need to re-specify the reference alternative when the status quo is excluded, our relative valuation measures are significantly different than those obtained from LCA. We argue that our model is useful for detecting and addressing alternative-specific nonidentification in a given dataset, thus reducing the risk of invalid inference from discrete choice data.
000264979 542__ $$fBy depositing this Content ('Content') in AgEcon Search, I agree that  I am solely responsible for any consequences of uploading this Content to AgEcon Search and making it publicly available, and I represent and warrant that: I am either the sole creator and the owner of the copyrights and all other rights in the Content; or, without obtaining another’s permission, I have the right to deposit the Content in an archive such as AgEcon Search. To the extent that any portions of the Content are not my own creation, they are used with the copyright holder’s express permission or as permitted by law. Additionally, the Content does not infringe the copyrights or other intellectual property rights of another, nor does the Content violate any laws or another’s rights of privacy or publicity. The Content contains no restricted, private, confidential, or otherwise protected data or information that should not be publicly shared. I understand that AgEcon Search will do its best to provide perpetual access to my Content. In order to support these efforts, I grant the Regents of the University of Minnesota ('University'), through AgEcon Search, the following non-exclusive, irrevocable, royalty-free, world-wide rights and licenses: to access, reproduce, distribute and publicly display the Content, in whole or in part, in order to secure, preserve and make it publicly available, and to make derivative works based upon the Content in order to migrate the Content to other media or formats, or to preserve its public access. These terms do not transfer ownership of the copyright(s) in the Content. These terms only grant to the University the limited license outlined above.
000264979 546__ $$aEnglish
000264979 650__ $$aEnvironmental Economics and Policy
000264979 6531_ $$arandom utility models
000264979 6531_ $$apreference heterogeneity
000264979 6531_ $$alatent class analysis
000264979 6531_ $$apartial observability
000264979 6531_ $$aserial nonparticipation
000264979 6531_ $$aserial participation
000264979 6531_ $$adeterministic choice patterns
000264979 6531_ $$aE-M algorithm
000264979 700__ $$aBrown, Zachary
000264979 700__ $$aDickinson, Katherine L.
000264979 700__ $$aPaskewitz, Susan
000264979 8560_ $$fenviro_econ@ncsu.edu
000264979 8564_ $$s1194986$$uhttp://ageconsearch.umn.edu/record/264979/files/WP-2016-015.pdf
000264979 8564_ $$s1748053$$uhttp://ageconsearch.umn.edu/record/264979/files/WP-2016-015.pdf?subformat=pdfa$$xpdfa
000264979 909CO $$ooai:ageconsearch.umn.edu:264979$$pGLOBAL_SET
000264979 980__ $$a1901