Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/303596 
Year of Publication: 
2022
Citation: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 10 [Issue:] 1 [Article No.:] 2041261 [Year:] 2022 [Pages:] 1-17
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
This study aims to analyze farmers' willingness to contribute labor for the ongoing natural resource rehabilitation interventions in watershed development in East and West Belesa Districts, Amhara region. The aim of the study to assesses farmers' intervention in natural resource rehabilitation activities and examines the mean willingness to pay family labor required for public watershed development activities from the two districts; a total of 501 households were selected by using a multistage sampling technique. The collected data were analyzed using a descriptive and econometrics model. In the econometric part, the mixed logit model is used to analyze the mean willingness to contribute to family labor. The descriptive result showed that farmers have to improve the watershed ecosystem service through soil and water conservation, area enclosure, forestation, and reforestation natural resource management intervention methods. The mean willingness to pay contribution results from the mixed logit, revealing that the sampled households are willing to contribute for livestock fodder availability 0.79 labors per month means Farmer's Contribute 8 daily labors per months for watershed management activity for stabilizing spring water flow 0.80 labors per month, for reduced soil erosion 0.14 labors per month, and increase crop productivity 0.09 labors per month, respectively. The results important for policymakers and extension workers not to expect all farmers' have homogeneous daily labor contribute to public watershed development activity.
Subjects: 
willingness to pay in labor time
watershed ecosystem services
mixed logit
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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