| Abstract: |
We develop econometric models to jointly estimate revealed preference (RP) and
stated preference (SP) models of recreational fishing behavior and preferences
using survey data from the 2007 Alaska Saltwater Sportfishing Economic Survey.
The RP data are from site choice survey questions, and the SP data are from a
discrete choice experiment. Random utility models using only the RP data may
be more likely to estimate the effect of cost on site selection well, but
catch per day estimates may not reflect the benefits of the trip as perceived
by anglers. The SP models may be more likely to estimate the effects of trip
characteristics well, but less attention may be paid to the cost variable due
to the hypothetical nature of the SP questions. The combination and joint
estimation of RP and SP data seeks to exploit the contrasting strengths of
both. We find that there are significant gains in econometric efficiency, and
differences between RP and SP willingness to pay estimates are mitigated by
joint estimation. We compare a number of models that have appeared in the
environmental economics literature with the generalized multinomial logit
model. The nested logit “trick” model fails to account for the panel nature of
the data and is less preferred to the mixed logit error components model that
accounts for panel data and scale differences. Naïve (1) scaled, (2) mixed
logit, and (3) generalized multinomial logit models produced similar results
to a generalized multinomial logit model that accounts for scale differences
in RP and SP data. Willingness to pay estimates do not differ across these
models but are greater than those in the mixed logit error components model.
Key Words: discrete choice experiment, generalized multinomial logit model,
hypothetical bias, revealed preference, stated preference, travel cost method |