Joint Estimation of Revealed Preference Site Selection and Stated Preference Choice Experiment Recreation Data Considering Attribute Non-Attendance

We estimate demand models with revealed preference (RP) site selection and stated preference (SP) discrete choice experiment marine recreational fishing data. We combine RP data from the Marine Recreational Information Program (MRIP) creel survey with SP survey data from 2003/04. RP and SP data combination is motivated by two factors. Catch rate information in the RP data are often thin, and use of SP scenarios for changes in catch can improve variation while minimizing multicollinearity. The SP data can suffer from hypothetical bias, which often manifests itself as bias in the cost coefficient. There are eight SP trip decisions and one RP trip decision for each of 1928 anglers who provided enough information to be analyzed. Joint RP-SP generalized multinomial logit models are estimated. We find that the SP travel cost coefficient is much lower than the RP travel cost coefficient in absolute value, suggesting hypothetical bias in the SP data. This difference is reflected in the willingness to pay estimates, where the SP estimates for improved catch are much higher than the RP estimates. Attribute non-attendance (ANA) arises when survey respondents ignore choice experiment attributes. We use inferred ANA methods to identify respondents who may be ignoring the SP cost variable. The generalized multinomial logit model accounting for ANA is statistically preferred. The SP cost coefficient accounting for ANA is much higher in absolute value than the SP coefficient from the model that does not account for ANA. The ANA model indicates much more consistency between the RP and SP data. The smaller difference in the travel cost coefficients is also reflected in the willingness to pay estimates