Application of nested logit model in ecosystem services valuation (Case study: Ganjname recreational site)

Document Type : Research Paper

Authors

1 Econometrics PhD Candidate, University of Isfahan, I.R. Iran

2 Associate Professor, Economic Department, University of Tehran, I.R. Iran

3 Professor, Economic Department, University of Isfahan, I.R. Iran

4 MA Graduated of Economics, Isfahan University, IRAN

Abstract

Today, environment is an important part of any country's economy. One of the main issues in environmental economics is non-market value estimation. Recognizing the importance of environmental and tourism of recreational sites, the purpose of this study is economic valuation of Ganjname recreational ecosystem attributes, estimation of implicit price, impact assessment of socio- economic variables such as age, marriage status, indigenous status, family size and education stand on the mentioned values and analyzing welfare and compensation variation due to variation of hypothetical policy and movement from a hypothetical policy to another one. It has been used choice experiment approach that it is subset of choice modeling procedure and stated preferences methods. Data needed extracted from six different choice experiment questionnaires filled out by 300 random households in Hamedan city. Each questionnaire contained 72 hypothetical policies, 36 choice sets, 1296 observations and 3888 rows of data. In order to estimation of visitors willingness to pay for improving attribute levels for Ganjnameh site, nested logit models and full information maximum likelihood method were used which is on the basis of multinomial discrete choice analysis of preferences, Lancaster's theory of value and the theory of random utility function. Results showed that the visitors have willingness to pay for conservation of forest diversity, preservation of monument and environmental health by sequence 17810, 33518, 36121 Rial, while no positive willingness to pay for reduction of overcrowding. Some socio- economic variables have a positive impact on willingness to pay.

Keywords

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