Estimating the Subjective Value of Decreasing the Environmental Pollution of the Beshar River, Yasuj

Document Type : Research

Authors

1 Assistant professor, Economy department, Payam Noor University

2 Assistant Professor, Agricultural Sciences and Natural Resources University, Gorgan, Iran

3 Assistant professor, Department of range and Watershed Management, Faculty of Agricultural sciences, Fasa University, Fasa, Iran

4 Assistant professor, agriculture department, Payam Noor University

5 Research Division of Agriculture economic, Kohgiluyeh and Boyerahmad Agricultural and Natural Resources Research and Education Center, AREEO, Yasooj, Iran

Abstract

Economic valuation of natural resources and patterns of payments for ecosystem services may help reduce environmental degradation and its consequences. The aim of this research was to estimate the value of decreasing environmental pollution in the Beshar River using conditional valuation method. The Logistic regression model was used to measure the willingness to pay of the individuals. The model's parameters were estimated based on the maximum likelihood method. The number of individuals who had been selected randomly in the city of yasuj and filled the questionnaires was 388. Results showed that 229 individuals (about 60.7%) were willingness to pay a fee to reduce the environmental pollution of the river. Also, the results of estimating Logit model indicated that the coefficient of variables of financial ability, being well-informed about the items in the questionnaire, gender, household income, the recreational activities in the river, and bid were significant at the 0.05 level, the responsibility variable was significant at the 0.01 level. The willingness to pay of each household for reducing the environmental pollution of the river according to the Logit model was 61819 Rls per month, and the monthly value of the pollution reduction in the Beshar River was estimated at 2493.16 million Rls.

Keywords

References

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History

  • Receive Date: 22 January 2018
  • Revise Date: 27 April 2018
  • Accept Date: 12 June 2018

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