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How to Frequently and Accurately Measure Poverty and Forest Dependence?
Author(s) -
Emilie Perge,
Raisa Behal
Publication year - 2019
Publication title -
world bank, washington, dc ebooks
Language(s) - English
Resource type - Book series
DOI - 10.1596/32802
Subject(s) - measure (data warehouse) , poverty , geography , psychology , economics , computer science , data mining , economic growth
The relationship between forest dependence and welfare remains partially explored, partially due to a lack of data. Data collection of household consumption and poverty correlates has been constrained by time consuming and costly tools, such as multipage household and community surveys. Forest-SWIFT is a complementary tool to a traditional household survey, developed to simultaneously measure poverty as well as forest dependence, using a 15-question country specific mini-survey. Forest-SWIFT was piloted in Turkey, where the forest-dwelling population is also the poorest. The tool used recent data from the Household Budget Survey 2013 as well as the Socio-Economic Household Survey 2016 tracking poverty and forest-dependence across 100 forest villages in Turkey in 2017. Forest-SWIFT estimated poverty at 23.2 percent in rural forest villages, and forest dependence as 15 percent, the latter echoing findings from previous literature. Forest-SWIFT is efficient to bring more data on the relationship between poverty and forest activities and to monitor how this relationship evolves with the goal to have a tangible effect on policymaking.

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