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Forest-SWIFT Methodology for High-Frequency Forest-Poverty data collection

CHALLENGE

Around 1.3 billion people – most of them living on less than $1.25 a day - rely on forests for some part of their livelihood. However, detailed, country-specific data is still lacking when it comes to forests’ socio-economic contributions and their role in poverty alleviation. Without this information, forests may be overlooked in national development strategies.

This activity aims to contribute to knowledge on forest’s contribution to movements out of poverty by using a new and innovative approach to forest-poverty data collection.

APPROACH

A new tool, Forest-SWIFT (Survey of Wellbeing via Instant and Frequent Tracking) is being developed to collect information to document who the poor are, where they live and how they rely on forests. Forest-SWIFT combines the latest statistical methods with in-person interviews using smart phones or tablets, and also functions offline where mobile coverage or technology is limited. Survey data is collected on a central server, where it can be rapidly accessed, analyzed, and used to design more effective projects or policies. 

The tool consists of 10-15 questions to strongly estimate forest reliance, a set of 10-15 questions to strongly estimate poverty, and a set of questions on governance. The tool methodology was developed by (i) modeling income (cash and non-cash) from forest to estimate forest reliance; (ii) modeling consumption/income models to estimate poverty; and (iii) identifying forest governance data.  The tool is being field tested in Turkey, Argentina and Mozambique.

Forest-SWIFT can be used to complement the Living Standards Measurement Study (LSMS) Forestry Module. The LSMS Forestry Module is carried out every three years, and Forest-SWIFT can easily be carried out in the interim two years, to create a rich and comprehensive knowledge base on forests and poverty. Forest-SWIFT promises improved monitoring of forest projects, better targeting of beneficiaries of forest interventions, and more effective programs and policies that help to reduce poverty and enhance the economic, social and environmental benefits derived from forests.

RESULTS

A first version of Forest-SWIFT is being implemented in Turkey to collect data about poverty and forest reliance. The SWIFT model for poverty was done using SILC data provided by the Poverty Economist. Household income per capita was modeled as a function of most important determinants. This model shows that household income per capita is explained by household size, dependency ratio, characteristics of household head, type of fuel, water system in the household, quality of the dwelling, holdings of different assets, ownership the house, and educational levels of household members. However, the data used presents some issues and a new dataset from the Global Poverty Working Group is being used to re-model income. Forest reliance has been modeled using forest income data from a survey done in spring 2016. The final version of Forest-SWIFT for Turkey will be launched in April.

In Argentina, instruments and sampling strategy are being identified to use Forest-SWIFT for an impact evaluation. Discussions are also underway in Mozambique to implement Forest-SWIFT there.

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Last Updated : 10-04-2017

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