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Measurement error and functional form: implications for welfare estimates

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  • Natalie Stoeckl

Abstract

This paper describes a series of Monte Carlo simulations which investigate the accuracy of final estimates generated from the travel cost model (TCM). The results are of interest to all applied researchers who: (a) cannot select functional form on theoretical grounds; and (b) wish to use Ordinary Least Squares (OLS) estimates for further calculations. This is because the simulations indicate that certain types of measurement error decrease the probability that researchers will be able to determine the correct functional form of the estimating equation on the basis of goodness of fit statistics. While this does not necessarily mean that slope (partial coefficient) estimates will be biased, it can cause substantial and unpredictable bias in welfare estimates.

Suggested Citation

  • Natalie Stoeckl, 2003. "Measurement error and functional form: implications for welfare estimates," Applied Economics Letters, Taylor & Francis Journals, vol. 10(5), pages 259-270, April.
    • Handle: RePEc:taf:apeclt:v:10:y:2003:i:5:p:259-270
    DOI: 10.1080/1350485031000112673
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    References listed on IDEAS

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    1. Common, Mick S. & Bull, Tim & Stoeckl, Natalie, 1999. "The Travel Cost Method: an empirical investigation of Randall's Difficulty," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 43(4), pages 1-21, December.
    2. Alan Randall, 1994. "Difficulty with the Travel Cost Method," Land Economics, University of Wisconsin Press, vol. 70(1), pages 88-96.
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    Cited by:

    1. Akbar Marvasti, 2010. "A welfare estimation of beach recreation with aggregate data," Applied Economics, Taylor & Francis Journals, vol. 42(3), pages 291-296.
    2. Prabha Prayaga & John Rolfe & Jack Sinden, 2006. "A Travel Cost Analysis of the Value of Special Events: Gemfest in Central Queensland," Tourism Economics, , vol. 12(3), pages 403-420, September.

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