Journal of Earth & Environmental Waste Management
- ISSN: 3065-8799
Genesha Mada , Agena Anjulo and Abren Gelaw
The study aimed to set “a new valuation metrics” to compensate the degraded plantation forests via the choice method, daily laborer vs. money. The people in the catchment were poor agrarian and relied on nonagricultural economic activities and ecosystem services of plantation forests, and caused for degradation. However, none of degradation state, restoration prices and willingness of users to restore the degraded plantation hadn’t assessed and valued interms of money and other metrics. The purposive sampling was implemented to select kebeles while simple random sampling methods was applied to drawn the sampled respondents. The utility difference model was used so as to rank from dichotomous pay data; the correlation coefficient was applied to estimate the relationship between their willingness to restore and socioeconomic backgrounds; multinomial regression model was used to predict the likelihood of socioeconomic backgrounds of users and
minimum willingness to accept restoration costs. The respondents had a demand for restoring the degraded plantation forests via money and daily laborer. However, more than half of respondents ranked to compensate in terms of daily labor [51.3%; significant at P<0.05], while the remaining were via money [48.7%; significant at P<0.05]. The multinomial regression model results predict that if the number of people who are not write and read, economically poor and medium, and age group of adults in the target population increases, there will be an increase in demand to compensate via daily laborers. If people have primary education, high school, and certified, are economically rich; the age group of young and old increases, there will have an increase in demands to compensate [restore] in terms of money. To concluded that implementing different accounting metrics likely to increase the opportunity of restoration capability and incorporating users regardless of socioeconomic background difference although further testing of different restoration cost metrics is interesting