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Valuation of Landmass Degradation Using Fuzzy Hedonic Method: A Case Study of National Capital Region

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  • Rakesh Paliwal
  • Gejo Geevarghese
  • P. Ram Babu
  • P. Khanna

Abstract

A Hedonic model to determine the revealed willingness to pay for landmass of different suitability classes, based on landmass functional characteristics obtained through subjective assessments, is developed for the National Capital Region in India. The inherent non-specificity involved in subjective evaluation is minimized using fuzzy logic based regression technique. The proposed fuzzy regression involves regression using central values of triangular fuzzy number and minimization of non-specificity using linear programming. The revealed willingness-to-pay for landmass of different suitability classes is used for valuation of disbenefits due to urban expansion on landmass of different agricultural suitability classes in National Capital Territory of Delhi. Appropriate pricing policies to prevent the future inappropriate landuse practices are developed using the landmass valuation. Copyright Kluwer Academic Publishers 1999

Suggested Citation

  • Rakesh Paliwal & Gejo Geevarghese & P. Ram Babu & P. Khanna, 1999. "Valuation of Landmass Degradation Using Fuzzy Hedonic Method: A Case Study of National Capital Region," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 14(4), pages 519-543, December.
    • Handle: RePEc:kap:enreec:v:14:y:1999:i:4:p:519-543
    DOI: 10.1023/A:1008357705800
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    1. Lili Sun & G. Kooten, 2009. "Comparing Fuzzy and Probabilistic Approaches to Preference Uncertainty in Non-Market Valuation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 42(4), pages 471-489, April.
    2. Lili Sun & G. Cornelis van Kooten, 2005. "Fuzzy Logic and Preference Uncertainty in Non-market Valuation," Working Papers 2005-11, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.

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