Estimating the economic effects of climate change on nature-based tourism: a comparison of revealed- and stated-preference methods

Abstract

Exogenous effects of a changing climate may influence visitation for nature-based recreation sites such as national parks, and in turn, may impact the regional economy of a gateway community and the net economic benefits of recreation. The studies herein represent the examination of the economic effects of climatic change on nature-based tourism.

The first paper explores the use of revealed-preference data in the measurement of the relative effects of climate variables on visitation at Rocky Mountain National Park (RMNP) and the economy of its gateway community. Historical data are used to estimate a multiple regression of the past effects of climate variability on park visitation. Temperature was found to have a positive and statistically significant effect on visitation. Visitation effects, along with forecasts of climate variables and regional population, are then used with an input-output model to forecast the impact to the economy of the gateway community of Estes Park, Colorado. The results of the statistical model are used to estimate prediction intervals for the regional effects, including employment and income. Prediction intervals allow for testing the relative effects of climate change and population growth on future estimates of visitation; from this, population growth was found to be the only significant determinant of future park visitation.

The second paper is an application of a contingent behavior analysis in the measurement of the effects of climate and resource variables on park visitation. A visitor survey at RMNP included descriptions of hypothetical climate scenarios (depicting both weather- and resource-related variables), and questions about how respondents’ visitation behavior would change contingent upon the scenarios. Survey responses are used to estimate the impact of climate change on park visitation and to test for the relative significance among scenarios. A relatively small proportion of respondents indicated that their behavior would change under the hypothetical climate scenarios, and the effect on visitation is positive. Both direct (weather-related) and indirect (resource-related) climate scenario variables are found to be statistically significant determinants of contingent behavioral changes. The results of the stated-preference analysis are compared with the revealed-preference results for methodological assessment, and we find that they are in close agreement.

The third paper uses the contingent valuation method (CVM) to estimate the effects of daily weather variables on recreation economic benefits (net willingness to pay) at RMNP. A visitor survey was used to gather responses to a dichotomous-choice CVM question about visitors’ willingness to pay for their recreation experience. CVM responses were analyzed with daily weather data to measure the degree to which temperature, precipitation, and cloud cover influence recreation benefits. Both temperature and precipitation had a positive and statistically significant effect on the estimated recreation benefits per trip.

In each analysis, climate variables are found to have statistically significant effects on visitation, local economic measures, and net recreation benefits, but the estimated economic effects of predicted climate change are quite small.