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Browsing by Author "Burkhardt, Jesse, advisor"

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    Exploring the use of credit/debit card transaction data in estimating national park visitor spending: a Mount Rushmore case study
    (Colorado State University. Libraries, 2024) Stockmoe, Evan, author; Burkhardt, Jesse, advisor; Bayham, Jude, committee member; Komarek, Tim, committee member
    Visitor spending refers to trip-related expenditures made by tourists. Estimates of visitor spending are needed for national park economic contribution studies, and are an essential component in evaluating tourism-related economic activity [Thomas et al., 2019, Wilton and Nickerson, 2006]. Traditional methods for estimating visitor spending rely on visitor surveys, which are costly and subject to multiple forms of survey bias [Stynes and White, 2006, Sinclair et al., 2023, Wilton and Nickerson, 2006]. Using Mount Rushmore National Memorial as a case study, I explore the use of granular credit and debit card transaction data to estimate visitor spending without the need for survey data. I use Safegraph Spend as the source of credit and debit card transaction data. I gather transaction data at stores within 100 miles of Mount Rushmore for the period 2019-2023. Combining this data and Mount Rushmore visitation data from the National Park Service, I develop and compare multiple models that use fixed effect regressions to estimate average spending per visit in the Accommodation, Food Service, Retail, and Arts/Entertainment/Recreation sectors. Using results from the best performing model, for 2022, I estimate Mount Rushmore visitor spending to be $41.0 million in the Accommodation sector, $38.4 million in the Food Service sector, $154.8 million in the Retail sector, and $6.4 million in the Arts/Entertainment/Recreation sector. I compare these estimates with NPS survey-based Mount Rushmore visitor spending estimates. I find that model estimates for the Food Service and Retail sectors are statistically indifferent to NPS estimates, however, model estimates for the Accommodation and Arts/Entertainment/Recreation sectors are below NPS estimates. I find several strengths and weaknesses in the credit/debit card transaction models. One strength is the use of observed spending data rather than stated spending data. Another strength is the representation of yearly visitor spending habits. A third strength is the ability to provide measures of estimate precision, like standard errors. One weakness is the inability to identify park-specific visitor spending when other nearby tourist attractions have similar visitation. Another weakness is the failure to account for visitor trip purpose. Additionally, I find that Safegraph Spend underrepresents spending in the Accommodation sector since vacation rental websites (like Airbnb) are not reflected in the data. Looking forward, further research should focus on methodological refinement and the integration of other data sources to improve visitor spending estimation using credit/debit card transaction data.
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    Heterogeneity in the price elasticity of demand for commercial water
    (Colorado State University. Libraries, 2018) Flyr, Matthew, author; Burkhardt, Jesse, advisor; Goemans, Chris, committee member; Shields, Martin, committee member
    The gap between projected future water demand and supply are increasing the importance of conservation policies. Commercial users are a major source of utility withdrawals, heightening the need for increased understanding of commercial responsiveness to utility policies. Despite an abundance of empirical studies on residential water demand, there are limited commercial sector studies exploring demand elasticity heterogeneity. In this paper, we estimate commercial water demand elasticity for firms served by a local utility, employing a novel instrumental variables approach. We then present evidence that firms respond to one period lagged average price rather than marginal price. Finally, we find notable differences in elasticity among different categories of businesses and among businesses of different consumption variance levels. The findings in this paper are particularly important as utility providers across the country consider how to cope with growing demand and limited water supply.
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    The recreational value and social cost of national parks: an application of the travel cost method
    (Colorado State University. Libraries, 2023) Lallement, Luc, author; Burkhardt, Jesse, advisor; Richardson, Leslie, committee member; Bayham, Jude, committee member; Iverson, Terry, committee member
    Studies that value the natural resources and recreational opportunities of a National Park have been explored for some time. Of the myriad techniques used to determine these values, our study uses the Travel Cost Method (TCM) to estimate the consumer surplus (CS) value per-visit for several National Parks surveyed in 2022. Previous studies have typically been conducted for one site or region at a time. Our data is novel in that it contains survey results from five different National Parks as part of the first year of the Socioeconomic Monitoring Survey conducted by the National Park Service (NPS). The parks range in size, purpose, and popularity, and we examine heterogeneity in CS estimates across these differences. Many of our CS estimates are new to the TCM literature, and some provide an update to existing estimates. In addition, we use the Social Cost of Carbon (SCC) to calculate the social cost of trips to the surveyed parks. These results are used to determine the total social cost of visitation, how costs would change if social costs were incorporated into the travel cost, and finally how visitation would change in this scenario. Our methodology builds on previous literature in the TCM space by incorporating econometric techniques to address multi-purpose visitors and on-site data collection. We find that our CS estimates are in line with previous TCM estimates. When social costs are incorporated, we estimate that there would be fewer visitors to the parks when social costs exceed an individual's estimated willingness to pay, if social costs were hypothetically incorporated via a carbon tax. Our study contributes to both the methodology of TCM studies and CS estimates of use-value for natural resources and can inform future authors on how to incorporate outside data (such as the SCC) to a well-established field. In addition, our estimates can be used by the NPS to inform policy decisions and benefit-cost analysis.