2006
DOI: 10.1016/j.jeem.2006.03.002
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Multivariate count data regression models with individual panel data from an on-site sample

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Cited by 59 publications
(75 citation statements)
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“…Therefore, our model specification includes a dummy variable representing those observations elicited using our stated preference methodology. This allows our model to account for and measure any hypothetical bias that might be present in the stated preference trip counts (Egan and Herriges 2006;Whitehead 2005). …”
Section: Conceptual Frameworkmentioning
confidence: 99%
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“…Therefore, our model specification includes a dummy variable representing those observations elicited using our stated preference methodology. This allows our model to account for and measure any hypothetical bias that might be present in the stated preference trip counts (Egan and Herriges 2006;Whitehead 2005). …”
Section: Conceptual Frameworkmentioning
confidence: 99%
“…Overall, the strengths of both approaches can be exploited through joint estimation of RP/SP data. Essentially, joint estimation has the advantage of allowing the measurement of preferences outside of an individual's historical experience while anchoring the stated preference responses to actual behavior (Rosenberg and Loomis 1999;Grijalva et al 2002;Whitehead 2005;Egan and Herriges 2006). Our RP/SP approach enables us to not only measure the effect of a future deployment of a large ship artificial reef on diving behavior, but also to consider the deployment effect under two different sinking depth scenarios to investigate whether, from a policy perspective, deployment depth is an influential component of diving demand.…”
Section: Introductionmentioning
confidence: 99%
“…The recreation analysis shown uses a transferable trip generation function to estimate the number of visits which would occur if a forest was created in a given location and a separate meta-analysis to estimate per-visit values (with aggregate values being given by multiplying per-visit values by the estimated number of visits). For a superior RUM approach to travel cost analysis see Herriges et al (2004), Egan and Herriges (2006) and Bateman et al (2010c). shadow values is in sharp contrast with the actual distribution of forests as illustrated in the final map. The latter is driven by market forces alone and hence ignores the carbon storage and recreation values instead being driven solely by the market values of agriculture (the left hand panel of Fig.…”
Section: Figmentioning
confidence: 99%
“…If these random components are allowed to be correlated across equations, the net result is a mixed count model that allows correlation across outcomes. Such a model can be estimated using classical or Bayesian simulation techniques (Egan andHerriges, 2006, Chib andWinkelmann, 2001). An important problem with this approach, however, is that the use of the Poisson or negative binomial distribution as the underlying kernel for mixing restricts "the amount of probability mass that can be accommodated at any one point" (see Herriges et al, 2008).…”
Section: Introductionmentioning
confidence: 99%