Abstract Detail


Kemigisha, Esther [1], Angelsen, Arild [2].

Opportunity versus Necessity: What drives Environmental Reliance?

This study addresses the uneven distribution of environmental income across rural households in developing countries. We investigate whether environmental reliance – measured as the environmental income’s share of total household income - can be better understood if household categories are identified based on their level of environmental reliance, rather than the prevalent approaches that are based on what they earn (total income) or own (assets). We use cross-sectional household data from 268 households of private forest owners in Hoima and Kibale districts in Uganda. We apply the quantile regression model to predict environmental reliance across and within four household group (quantiles). We found significantly different coefficients between the least and most reliant on environment, indicating heterogeneity in the factors driving households into environmental reliance. Particularly, environmental reliance among the most reliant on the environment was reduced by more agricultural land and other household assets. Environmental reliance among the least reliant was reduced by remoteness from the road and increased by remoteness from the market. We suggest for the most reliant on environmental income, their reliance is driven by necessity and lack of options for survival, while environmental reliance among the least reliant on the environment is opportunity driven. Understanding such differences and therefore households differentiated response to changing economic conditions and policy measures, have implications for the design of effective poverty reducing and conservation policies. 

1 - Makerere University, Department of Environmental management, Makerere University road, Kampala, Uganda
2 - Norwegian University of Life Sciences, Universitetstunet 3,, 1430 ├ůs, Norway

Environmental reliance
Environmental income
Quantile regression

Presentation Type: Oral Paper
Session: ETH1, Ethnobotany
Location: Virtual/Virtual
Date: Tuesday, July 28th, 2020
Time: 4:00 PM
Number: ETH1005
Abstract ID:457
Candidate for Awards:Economic Botany Section best student paper

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