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Determinant Factors of Farmer’s Willingness to Pay for Sustainable Land Management Practices Evidence with Homosha Benishangul Gumuz Region: Application with Multinomial Logit Model, Mixed Logit Model, and Conditional Logit Model
Melaku Tarekegn Takele
University of Gondar College of Business and Economics
Corresponding Author
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This work is licensed under a CC BY 4.0 License. Read Full License
The study examines factors affecting farmer’s willingness to pay for sustainable land management practices in Ethiopia, The study uses primary data collected from 200 households randomly selected from four kebeles of districts in Ethiopia’s Benishangul-Gumuz regional state with 4,800 observations (eight choices for each household). The choice experiment design was done using the R software to efficiently generate an attribute and level combination using fractional factorial design. Data were analyzed using discrete choice models including multinomial logit model, mixed logit model, and conditional logit model using STAT-14. The findings showed that households were aware of the effects of using SLM and benefits of using a bundle of SLM. However, they were challenged by the costs of implementing a bundle of SLM and technologies related to it. Moreover, mean willingness to pay estimates is about 844 to 2540 birr and in case of total willingness to pay households is not less than 66% for a bundle of SLM. Crop-rotation attributes levels are negatively and significantly affect decision for SLM, while conserve-agriculture positively and significantly affects households' decision to adopt a bundle of SLM. Socio-economic (the type of crop, land size, land form, livestock, awareness about SLM and technologies) variables are found to be factors that determine decision to adopt SLM.
Keywords
Sustainable land management’s, willingness to pay, discrete choice experiment, crop-rotation, conserve-agriculture, terracing
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This is a preprint. It has not completed peer review.
Research
Determinant Factors of Farmer’s Willingness to Pay for Sustainable Land Management Practices Evidence with Homosha Benishangul Gumuz Region: Application with Multinomial Logit Model, Mixed Logit Model, and Conditional Logit Model
Melaku Tarekegn Takele
University of Gondar College of Business and Economics
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 11 Aug, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Agricultural Economics & Policy
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The study examines factors affecting farmer’s willingness to pay for sustainable land management practices in Ethiopia, The study uses primary data collected from 200 households randomly selected from four kebeles of districts in Ethiopia’s Benishangul-Gumuz regional state with 4,800 observations (eight choices for each household). The choice experiment design was done using the R software to efficiently generate an attribute and level combination using fractional factorial design. Data were analyzed using discrete choice models including multinomial logit model, mixed logit model, and conditional logit model using STAT-14. The findings showed that households were aware of the effects of using SLM and benefits of using a bundle of SLM. However, they were challenged by the costs of implementing a bundle of SLM and technologies related to it. Moreover, mean willingness to pay estimates is about 844 to 2540 birr and in case of total willingness to pay households is not less than 66% for a bundle of SLM. Crop-rotation attributes levels are negatively and significantly affect decision for SLM, while conserve-agriculture positively and significantly affects households' decision to adopt a bundle of SLM. Socio-economic (the type of crop, land size, land form, livestock, awareness about SLM and technologies) variables are found to be factors that determine decision to adopt SLM.
Figure 1
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.