Numbers of households and population by Local Government Areas, Districts, and Settlements, 2013, The Gambia

The dataset consists of socio-economic data obtained from the survey of 409 farm households in the Bongo, Kassena Nankana East and Kassena Nankana West Districts in Upper East Ghana. It also includes constructed data from the main dataset for the analysis of the drivers and impacts of farmer innovation. A description of all the variables in the data is also included.

This dataset describe household survey conducted in the Vea watershed of Ghana between the periods May 2013 to February 2014. It describes several household characteristics such as age, gender, income sources, agricultural production levels, Occurrence of droughts and floods as well as the impact of these hazards. The data also include several derived parameters such as household income, household size in adult equivalent scale, Tropical livestock units and poverty prevalence.

Innovation is essential for agricultural and economic development, especially in today’s rapidly changing global environment. While farmers have been recognised as one of the key sources of innovation, many studies on agricultural innovations continue to consider farmers as adopters of externally-driven technologies only. This thesis, in contrast, analyses the innovation-generating behaviour among rural farmers. Specifically, the study looks at the determinants, impacts and identification of farmer innovation. The study is based on primary data obtained from a survey of 409 smallholder farm households in the Upper East region of northern Ghana. Additional data were collected through an innovation contest and a stakeholder workshop conducted in the region. Employing recursive bivariate probit and endogenous treatment-regression models which control for selection bias, it was found that participation in Farmer Field Fora − a participatory extension approach with elements of the innovation systems perspective − is a key determinant of innovation behaviour in farm households. Other important determinants are education, climate shocks and risk preferences. These results are robust to alternative specifications and estimation techniques. The study also found no spillover effect of FFF on farmers’ innovation capacity and discussed its implications. Using endogenous switching regression and propensity score matching techniques, the effect of farmer innovation on household welfare was analysed. The results show that farmer innovation significantly improves both household income and consumption expenditure for innovators. It also contributes significantly to the reduction of food insecurity among innovative households by increasing household food consumption expenditure, reducing the length of food shortages, and decreasing the severity of hunger. However, the findings show that the positive income effects of farmer innovation do not significantly translate into nutritious diet, measured by household dietary diversity. The results also indicate that though households innovate mainly to increase production, their innovations indirectly contribute to building their resilience to climate shocks. Overall, the results show positive and significant welfare effects of farmer innovation. Through an innovation contest that rewards farmers’ creativity and a household survey, 48 outstanding innovations developed by smallholder farmers were identified in the study region. The innovations are largely extensive modification of existing practices or combination of different known practices in unique ways to save costs or address crop and livestock production constraints. While some of the identified innovations can be recommended or disseminated to other farmers, most of them may require further validation or research. The multi-criteria decision making analysis − based on expert judgement ¬− is proposed as a simple and useful method that can be applied in prioritising high-potential innovations. Using this method, it was found that among the most promising innovations involve the control of weeds, pest and diseases using plant residues and extracts, and the treatment of livestock diseases using ethnoveterinary medicines. In conclusion, this study provides empirical evidence that smallholder farmers develop diverse and spectacular innovations to address the myriad challenges they face. These innovations also contribute significantly to household well-being, hence, need to be recognised and promoted. An institutional arrangement that permits interactions and learning among stakeholders may be a potential option for strengthening farmers’ innovation capacity.

Household survey conducted in the Vea watershed of Burkina Faso between the periods May 2013 to February 2014. It describes several household characteristics such as age, gender, income sources, agricultural production levels, Occurrence of droughts and floods as well as the impact of these hazards. The data also include several derived parameters such as household income, household size in adult equivalent scale, Tropical livestock units and poverty prevalence.

Household socio-economic, population and migration dynamics in the Vea catchment.

This dataset is the seventh of a series of datasets addressing farmers' adaptation to climate change in West-Africa, specifically in Dano, Burkina Faso and Dassari, Benin. This data was obtained by interviews with 118 people from communities in Dano. It provides information on the household level in regard to biophisical and socio-economic data for agroforestry systems.

This dataset is the eighth of a series of datasets addressing farmers' adaptation to climate change in West-Africa, specifically in Dano, Burkina Faso. Data includes randomly sampled pasture/soil measurments, transcripts of 22 qualitative interviews (anonymized), and a questionnaire with 128 corresponding results focused on livestock systems and climate change adaptation but also with socio-economic information.

This dataset is the seventh of a series of datasets addressing farmers' adaptation to climate change in West-Africa, specifically in Dano, Burkina Faso and Dassari, Benin. This data was obtained by interviews with 137 people from 17 communities in Dassari. It provides information on the household level in regard to biophysical and socio-economic data for agroforestry systems.

This dataset is the fourth of a series of datasets addressing farmers' adaptation to climate change in West-Africa, specifically in Dano, Burkina Faso and Dassari, Benin. This Data was obtained by interviews with 137 people from 17 communities,in Dassari. It provides information on the household level in regard to the aspects; challenges and behavioral change.