Asset, Property Rights and Forest Dependency: Evidence From Machine Learning Analysis - June 2019

Authors

Dambala Gelo, University of Pretoria
Daniela Lamparelli, University of the Witwatersrand, Johannesburg

Document Type

Spring 2019 Meeting Presentation - Manchester, England

Publication Date

6-2019

Subjects

Environmental economics, Conservation of natural resources -- Economic aspects, Payments for ecosystem services

Abstract

In many poor regions, the poor heavily depend on the income derived from the natural resource base. This presentation tests the forest-dependency-asset poverty hypotheses; looks at the impacts of credit constraint on forest dependency; and using machine learning approach resolves the problems of model selection uncertainty and structural parameters identification.

Description

Presented at the Sixth Biannual Meeting of the Environment for Development (EfD) Forest Collaborative Manchester, UK. June 25-26, 2019.

Persistent Identifier

https://archives.pdx.edu/ds/psu/29455

Citation Details

Gelo, Dambala and Lamparelli, Daniela, "Asset, Property Rights and Forest Dependency: Evidence From Machine Learning Analysis - June 2019" (2019). Forest Collaborative Research. 14.
https://archives.pdx.edu/ds/psu/29455