Count Data Models and the Problem of Zeros in Recreation Demand Analysis

Tim Haab and Kenneth McConnell ()

American Journal of Agricultural Economics, 1996, vol. 78, issue 1, 89-102

Abstract: In this paper we develop a count data model for consumer demand which explicitly allows for a large number of zero observations for the dependent variable, and separation of the participation versus quantity decisions. The advantages of the model over traditional censored and count demand models are brought out, and the appropriate consumer surplus measures are derived. By introducing a random error term into the traditional count model demand function, the appropriate measure of expected consumer surplus for count models is derived. The model is illustrated using a recreational survey of the general population. Copyright 1996, Oxford University Press.

Date: 1996
References: Add references at CitEc
Citations: View citations in EconPapers (46)

Downloads: (external link)
http://hdl.handle.net/10.2307/1243781 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:ajagec:v:78:y:1996:i:1:p:89-102

Access Statistics for this article

American Journal of Agricultural Economics is currently edited by Madhu Khanna, Brian E. Roe, James Vercammen and JunJie Wu

More articles in American Journal of Agricultural Economics from Agricultural and Applied Economics Association Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().