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Confidence Intervals for Welfare Measures with Application to a Problem of Truncated Counts

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Author Info
Creel, Michael D
Loomis, John B

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Abstract

Demand for deer hunting trips was estimated using statistical models based on the normal, Poisson, and negative binomial probability laws. Some of the models accounted for existing sampling truncation. Estimates of Marshallian and Hicksian welfare measures are presented, accompanied by 90 percent confidence intervals based on Krinsky and Robb's procedure. For each of the statistical models, the Hicksian measures are found to be very close to the Marshallian measures, with similar confidence intervals. Accounting for the truncation of the dependent variable has a statistically significant effect on the resulting estimates of welfare measures. Copyright 1991 by MIT Press.

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Publisher Info
Article provided by MIT Press in its journal Review of Economics & Statistics.

Volume (Year): 73 (1991)
Issue (Month): 2 (May)
Pages: 370-73
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Handle: RePEc:tpr:restat:v:73:y:1991:i:2:p:370-73

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  1. Ram Shrestha & John Loomis, 2003. "Meta-Analytic Benefit Transfer of Outdoor Recreation Economic Values: Testing Out-of-Sample Convergent Validity," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 25(1), pages 79-100, May. [Downloadable!] (restricted)
  2. O. Ashton Morgan & D. Matthew Massey & William L. Huth, 2009. "Demand for Diving on Large Ship Artificial Reefs," Working Papers 09-09, Department of Economics, Appalachian State University. [Downloadable!]
  3. Isabel Mendes & Isabel Proença, 2009. "Measuring the Social Recreation Per-Day Net Benefit of Wildlife Amenities of a National Park: A Count-Data Travel Cost Approach," Working Papers 2009/35, Department of Economics at the School of Economics and Management (ISEG), Technical University of Lisbon.. [Downloadable!]
  4. Roberto Martinez-Espineira & Joe Amoako-Tuffour, 2005. "Recreation Demand Analysis under Truncation, Overdispersion, and Endogenous Stratification: An Application to Gros Morne National Park," Econometrics 0511007, EconWPA. [Downloadable!]
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