{{menu_nowledge_desc}}.

CIFOR–ICRAF publishes over 750 publications every year on agroforestry, forests and climate change, landscape restoration, rights, forest policy and much more – in multiple languages.

CIFOR–ICRAF addresses local challenges and opportunities while providing solutions to global problems for forests, landscapes, people and the planet.

We deliver actionable evidence and solutions to transform how land is used and how food is produced: conserving and restoring ecosystems, responding to the global climate, malnutrition, biodiversity and desertification crises. In short, improving people’s lives.

Household dataset of the Global Comparative Study on REDD+ (GCS REDD+) Module 2

The Global Comparative Study on REDD+ (GCS REDD+) was launched in 2009 by the Center for International Forestry Research (CIFOR) to ensure that policy-makers and practitioner communities have access to – and use – the information, analyses and tools they need to: design and implement REDD+ and other forest-based mitigation strategies in effective, efficient and equitable ways that also promote social and environmental co-benefits; and rigorously assess to what degree REDD+ has delivered. Module 2 (Subnational REDD+ and low emissions development initiatives) focuses on assessing the performance of subnational REDD+ and other low-emission development initiatives, including subnational jurisdictional programmes and local-level projects. Module 2 evaluated the impacts of 23 REDD+ project and program sites in six countries: Brazil, Cameroon, Indonesia, Peru, Tanzania and Vietnam. The research uses a before–after/control–intervention (BACI) approach. In this approach, identical data are collected both before and after the initiative starts, and in an ‘intervention’ area (that is, the location that is impacted by the REDD+ initiative) and a ‘control’ area (that is, a location that has similar characteristics to the intervention area, but is not impacted by the REDD+ initiative). Data collection for the ‘before’ period was carried out in 2010/11 (hereafter referred as ‘Phase 1’), and for the ‘after’ period in 2013/14 (hereafter referred as ‘Phase 2’). At each site, four intervention villages and four control villages were surveyed. In each village, three types of data collection instruments were implemented in Phase 1 and Phase 2: a Household Questionnaire; a Village Questionnaire; and a Women’s Questionnaire. The Household dataset corresponds to the Household Questionnaire, which is used to: 1.Measure the potential effect of REDD+ on household well-being on the basis of objective metrics (livelihood, assets and income in the course of 12 months) and subjective metrics (perceived well-being status and the reasons for change for those who experience change); 2.Measure the potential effect of REDD+ on land and resource use at the level of the household; 3.Measure household knowledge of and involvement in the process of establishing and implementing REDD+. The Household Questionnaire is divided into 5 main sections: 1. Basic information on household members; 2. household assets; 3. household income; 4. perceptions of wellbeing and wellbeing change in last two years; and, 5. involvement in and assessment of forest conservation interventions. The Household Questionnaire was carried out in 18 of the 23 subnational initiatives. The Household dataset includes 4524 households in phase 1 and 3988 in phase 2, of which 3529 were interviewed twice (not all the phase 1 households could be interviewed again in phase 2 due to attrition). Variables from Phase 1 start with P1H_section&question number, and variables from Phase 2 start with P2H_section&question number. The research design and methods are further described in Sunderlin et al. (2016) as well as in several GCS REDD+ publications (see ‘Related publications’).

Dataset's Files

Global_Codebook_Public.pdf
MD5: 99e1a7cbc49de1b5d63dcf105ac23e47
This file provides a list of all the codes used in the dataset files and answers options of questionnaire form. It includes generic codes for answers, countries code, products, forest type, land use classification, units of measurement, livelihood by category and causes of change code of forest area.

Other datasets you might be interested in