Literature DB >> 23716008

Valuation of national park system visitation: the efficient use of count data models, meta-analysis, and secondary visitor survey data.

Christopher Neher1, John Duffield, David Patterson.   

Abstract

The National Park Service (NPS) currently manages a large and diverse system of park units nationwide which received an estimated 279 million recreational visits in 2011. This article uses park visitor data collected by the NPS Visitor Services Project to estimate a consistent set of count data travel cost models of park visitor willingness to pay (WTP). Models were estimated using 58 different park unit survey datasets. WTP estimates for these 58 park surveys were used within a meta-regression analysis model to predict average and total WTP for NPS recreational visitation system-wide. Estimated WTP per NPS visit in 2011 averaged $102 system-wide, and ranged across park units from $67 to $288. Total 2011 visitor WTP for the NPS system is estimated at $28.5 billion with a 95% confidence interval of $19.7-$43.1 billion. The estimation of a meta-regression model using consistently collected data and identical specification of visitor WTP models greatly reduces problems common to meta-regression models, including sample selection bias, primary data heterogeneity, and heteroskedasticity, as well as some aspects of panel effects. The article provides the first estimate of total annual NPS visitor WTP within the literature directly based on NPS visitor survey data.

Entities:  

Mesh:

Year:  2013        PMID: 23716008     DOI: 10.1007/s00267-013-0080-2

Source DB:  PubMed          Journal:  Environ Manage        ISSN: 0364-152X            Impact factor:   3.266


  6 in total

1.  Application of non-market valuation to the Florida Keys marine reserve management.

Authors:  Mahadev G Bhat
Journal:  J Environ Manage       Date:  2003-04       Impact factor: 6.789

2.  Quantifying and reporting uncertainty from systematic errors.

Authors:  Carl V Phillips
Journal:  Epidemiology       Date:  2003-07       Impact factor: 4.822

3.  Recreation demand analysis under truncation, overdispersion, and endogenous stratification: an application to Gros Morne National Park.

Authors:  Roberto Martínez-Espiñeira; Joe Amoako-Tuffour
Journal:  J Environ Manage       Date:  2007-09-04       Impact factor: 6.789

4.  Multi-destination and multi-purpose trip effects in the analysis of the demand for trips to a remote recreational site.

Authors:  Roberto Martínez-Espiñeira; Joe Amoako-Tuffour
Journal:  Environ Manage       Date:  2009-01-31       Impact factor: 3.266

5.  Estimating the economic value of national parks with count data models using on-site, secondary data: the case of the great sand dunes national park and preserve.

Authors:  Matthew T Heberling; Joshua J Templeton
Journal:  Environ Manage       Date:  2008-05-28       Impact factor: 3.266

6.  What weight should be assigned to future environmental impacts? A probabilistic cost benefit analysis using recent advances on discounting.

Authors:  Carmen Almansa; José M Martínez-Paz
Journal:  Sci Total Environ       Date:  2011-01-16       Impact factor: 7.963

  6 in total
  1 in total

1.  Who visits a national park and what do they get out of it?: a joint visitor cluster analysis and travel cost model for Yellowstone National Park.

Authors:  Charles Benson; Philip Watson; Garth Taylor; Philip Cook; Steve Hollenhorst
Journal:  Environ Manage       Date:  2013-08-22       Impact factor: 3.266

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.