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Testing the convergent validity of approaches for valuing national park visitation

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Abstract

Recreation values are necessary to inform a variety of planning and management decisions affecting national parks and other public lands. Standard visitor surveys often collect data that can facilitate estimation of such values through either revealed or stated preference approaches. However, several issues can arise when using such data, such as selection of the appropriate per mile rate to apply in travel cost models, limited variation in the number of trips taken to the site in the past year, and limitations in response formats for contingent valuation questions. To explore these issues, we use visitor survey data from Glacier National Park to estimate consumer surplus for a park visit, comparing mean estimates and percentile confidence intervals from several approaches. Exploring convergent validity across these approaches provides some support for the exclusion of depreciation costs when selecting a per mile travel cost rate and caution in using alternative dependent variable specifications in travel cost models.

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Data availability

Data are available by the authors upon request.

Notes

  1. Additional park-specific studies not included in this database are Sinclair et al. (2020), Richardson et al. (2017), Benson et al. (2013), and Melstrom (2013, 2015), who estimate the value of visiting Pearl Harbor National Memorial, Katmai National Park, Yellowstone National Park, and several national battlefields, respectively. A more recent study by Parsons et al (2021) applies a unique site-portfolio model to visitation at seven national parks in the southwestern U.S. and estimates welfare losses associated with the closure of one or more of those sites.

  2. For more information about the SEM, see https://www.nps.gov/subjects/socialscience/socioeconomic-monitoring.htm.

  3. The national wildlife refuge surveys are available at https://u.osu.edu/dietsch.29/. For national parks with primarily day visitors, the same bid amounts as those in the national wildlife refuge surveys were used. For national parks with a higher percentage of visitors staying overnight, such as Glacier NP, these bid amounts were adjusted upward.

  4. Respondents that did not answer survey questions regarding their place of residence or trip purpose tended to leave much of the survey blank and were excluded from the analysis. One respondent reported taking 100 trips to the park in the past 12 months, more than three times the next highest reported number of trips (30). This was considered an outlier and was excluded from the analysis.

  5. All models are estimated in STATA 14. The travel cost models are estimated using the nbstrat command and the CV model is estimated using the intreg command.

  6. Interestingly, this estimate is nearly identical if using the midpoint of the payment card interval ($471.35) or the random variable approach outlined in Sect. 3.1 ($471.20). Further, when accounting for the full subset of respondents that answered the CV question, the interval regression results in an estimate of $474.47.

  7. As pointed out by a reviewer, a comparison could be made following the approach of Heberling and Templeton (2009) and Martínez-Espiñeira and Amoako-Tuffour (2008). In this case, the CS estimate from the persontrips model can be converted to a CS estimate per individual per year, then divided by the number of trips taken per year by the average individual. Following a similar approach, but focusing on the number of people splitting trip expenses as opposed to group size for consistency with our model, this results in a value per trip of $1260 based on the low cost per mile and $1482 based on the high cost per mile.

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Authors and Affiliations

  1. Economist, National Park Service, Social Science Program, 1201 Oakridge Drive, Fort Collins, CO, USA

    Leslie Richardson & Matthew Flyr

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  1. Leslie Richardson
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  2. Matthew Flyr
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Correspondence to Leslie Richardson.

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Richardson, L., Flyr, M. Testing the convergent validity of approaches for valuing national park visitation. Environ Econ Policy Stud 26, 101–120 (2024). https://doi.org/10.1007/s10018-023-00378-w

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