Addressing Onsite Sampling in Recreation Site Choice Models

Abstract

Independent experts and politicians have criticized statistical analyses of recreation behavior that rely upon onsite samples due to their potential for biased inference, prompting some to suggest support for these efforts should be curtailed. The use of onsite sampling usually reflects data or budgetary constraints but can lead to two primary forms of bias in site choice models. First, the strategy entails sampling site choices rather than sampling anglers – a form of bias called endogenous stratification. Under these conditions, sample choices may not reflect the site choices of the true population. Second, the exogenous attributes of the recreational users sampled onsite may differ from the attributes of users in the population – the most common form in recreation demand is avidity bias. We propose addressing these biases by combining two existing methods, Weighted Exogenous Stratification Maximum Likelihood Estimation (WESMLE) and propensity score estimation. We use the National Marine Fisheries Service’s (NMFS) Marine Recreational Fishing Statistics Survey (MRFSS) to illustrate methods of bias reduction employing both simulation and empirical applications. We find that propensity score based weights can significantly reduce bias in estimation. Our results indicate that failure to account for these biases can overstate anglers’ willingness to pay for additional fishing catch.