An Empirical Study of the Influences of Recreational Park Visitation: The Case of US National Park Service Sites

McIntosh, Christopher S.; Wilmot, Neil A.

doi:10.5367/te.2011.0036

Cited by 17 publications

(16 citation statements)

References 10 publications

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“…The existing literature on economic valuation of UNESCO World Heritage parks (Alexandrakis et al, 2019) such as GNP is relatively scarce. Certainly, there are no comprehensive studies on the economic values of attributes found in the Galapagos Islands (Peñaherrera et al, 2012), and there is a lack of information on tourist preferences in UNESCO parks and policy guidelines or suggestions to better allocate their resources (McIntosh and Wilmot, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

Economic valuation of recreational attributes using a choice experiment approach: An application to the Galapagos Islands

2019

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Despite the increasing number of visitors to Galapagos National Park, the tourism industry pays little attention to the distinct preferences of tourists toward park attributes, including both its natural resources and managerial emphasis. To “monetize” the benefits of these attributes requires utilizing nonmarket valuation techniques. Using a stated preference questionnaire, we estimated the economic value of the park’s recreational attributes. The following five attributes were selected: endangered species, prevalence of garbage, site infrastructure, air quality, and entrance fees. The results of this study demonstrate that tourists place the highest willingness to pay values on increased protection of animal species (US$26.9) and garbage reduction (US$111.2). These results highlight the economic contributions for park management, with a potential for value improvement of US$38.1 per tourist if the park’s combined attributes are upgraded from the present condition to the optimum condition.

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Section: Literature Reviewmentioning

confidence: 99%

Economic valuation of recreational attributes using a choice experiment approach: An application to the Galapagos Islands

2019

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“…Finally, given the demonstrated significance of the terrorist attack against the US (McIntosh & Wilmot, 2011), several dummy variables were constructed to capture the potential impact/"structural change" from this event. The first dummy variable (TDY) takes the value 1 after 2001 terrorist attack (TDY = 1 in 2002-2006, 0 otherwise), while TDUM equals 1 at the time of the terrorist attack (TDUM = 1 in 2001, 0 otherwise).…”

Section: Wilmot and Mcintoshmentioning

confidence: 99%

“…The basis for the inclusion of economic variables derives from the work of McIntosh and Wilmot (2011). Many of the macroeconomic variables were obtained from the Federal Reserve Economic Database (Federal Reserve Bank of St. Louis, 2010), including real disposable personal income (RDPI) (series: DPIC 96), exchange rates (ERATE) (series: TWEXBANL), and population (POP) (series: POPTHM).…”

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confidence: 99%

Forecasting Recreational Visitation at US National Parks

Wilmot¹,

McIntosh²

2014

Tourism Analysis

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This study evaluates forecasting accuracy among several competing methodologies, including time series and econometric methods, on visitation to 255 US National Park Service (NPS) sites. The performance of these models is contrasted with the model currently in use by the NPS. One-yearahead, 2-year-ahead, and combined (1-and 2-year-ahead) forecasting performance at the individual park level is examined utilizing several measures of forecasting accuracy, including root mean square error (RMSE) and mean absolute percentage error (MAPE). Results indicate incorporating economic variables can significantly improve forecasts, particularly for large and small parks. For medium size parks the naive forecast errors were typically lowest. Furthermore, the naive model performed well, often producing the best forecast, followed by the econometric model. Regionally, the naive and econometric models preform best, with the Pacificwest region being the exception. Utilizing the most accurate model for each park leads to a 24% improvement over current forecasts (1-year horizon) and suggests that a mixed model approach is optimal. Pergrams and Zaradic (2006) demonstrate that per capita use of US national parks has declined since the late 1980s. Additionally, The Economist (2008) has highlighted the fact that Americans are retreating from such outdoor activities. The significant economic impacts of, and potential downward trends in, national park visitation combine to make the accuracy of visitation forecasts a principal concern. The US NPS currently provides forecast estimates for approximately 350 parks, and understanding future demand is critical to the provision of services, appropriate application of funds, and budgeting concerns.

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“…These equations offer justification for the estimation of regression equations outlined in the empirical model (to be discussed in the next section). To explain the above-derived quantity of recreational goods (that is, the park visit), we started with the typical demand model of national park visitation, commonly used in tourism economics literature (Johnson andSuits, 1983, McIntosh andWilmot, 2011). This model, explains the number of park visits as a function of both the destination characteristics (accessibility, season, air quality, etc) and the characteristics of the social and economic characteristics of potential visitors (transportation cost, consumer confidence, relative price of other goods, etc).…”

Section: Max U(x)mentioning

confidence: 99%

“…Following Johnson and Suits (1983) and McIntosh and Wilmot (2011), we measured the dependent variable as the total monthly recreational visits to a national park. One limitation in such quantitative models of tourism flow and park visitation demand is the identification of appropriate independent variables (Chen et al, 2008).…”

Section: Max U(x)mentioning

confidence: 99%

Estimating the Impact of Impaired Visibility on the Demand for Visits to National Parks

Poudyal

Paudel²,

Green

2013

Tourism Economics

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The authors fitted a number of time-series econometric models to monthly visitation data of a national park to examine the effect of impaired visibility on visitation demand. Using a polynomial distributed lag model, the long-run elasticity of demand with respect to visibility in the Great Smoky Mountain National Park (GSMNP) was estimated. The GSMNP, the most visited national park in the USA, has significant air quality issues. Although the park has observed some fluctuation in visitation, the results indicate that the demand for visitation in general and for specific recreational visits are mean reverting and highly stable. Further, park visitation in a given month is significantly affected by the cumulative effect of the visibility condition in both the current and preceding months. Estimated elasticity reveals that a programme aiming to improve the average visibility by 10% (5.5 km) from the current level could result in an increase of roughly one million recreational visits annually, and that the increase would be higher for overnight visitors than for day visitors because of overnight visitors' relatively elastic demand. This demand model could assist park managers in their planning as they weigh the anticipated benefits of a visibility improvement programme against increased visitation and its associated costs.

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An Empirical Study of the Influences of Recreational Park Visitation: The Case of US National Park Service Sites

Cited by 17 publications

References 10 publications

Economic valuation of recreational attributes using a choice experiment approach: An application to the Galapagos Islands

Economic valuation of recreational attributes using a choice experiment approach: An application to the Galapagos Islands

Forecasting Recreational Visitation at US National Parks

Estimating the Impact of Impaired Visibility on the Demand for Visits to National Parks

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