Year Published
- 2008 (0)
- 2009 (0)
- 2010 (4) Apply 2010 filter
- 2011 (2) Apply 2011 filter
- 2012 (1) Apply 2012 filter
- (-) Remove 2013 filter 2013
- 2014 (0)
- 2015 (0)
- 2016 (2) Apply 2016 filter
- (-) Remove 2017 filter 2017
- 2018 (0)
- (-) Remove 2019 filter 2019
- 2020 (0)
- 2021 (0)
Research Topics
Populations
Types of Research
- Data Analysis (3) Apply Data Analysis filter
- Literature Review (0)
- Portfolio Review (0)
- Research Brief (1) Apply Research Brief filter
Geography
- East Africa Region and Selected Countries (3) Apply East Africa Region and Selected Countries filter
- Global (0)
- South Asia Region and Selected Countries (2) Apply South Asia Region and Selected Countries filter
- Southern Africa Region and Selected Countries (0)
- Sub-Saharan Africa (0)
- West Africa Region and Selected Countries (2) Apply West Africa Region and Selected Countries filter
Dataset
Current search
- (-) Remove 2017 filter 2017
- (-) Remove Other Datasets filter Other Datasets
- (-) Remove Technology filter Technology
- (-) Remove 2013 filter 2013
- (-) Remove Farmer First filter Farmer First
- (-) Remove 2019 filter 2019
- (-) Remove Agricultural Productivity, Yield, & Constraints filter Agricultural Productivity, Yield, & Constraints
Studies of improved seed adoption in developing countries almost always draw from household surveys and are premised on the assumption that farmers are able to self-report their use of improved seed varieties. However, recent studies suggest that farmers’ reports of the seed varieties planted, or even whether seed is local or improved, are sometimes inconsistent with the results of DNA fingerprinting of farmers' crops. We use household survey data from Tanzania to test the alignment between farmer-reported and DNA-identified maize seed types planted in fields. In the sample, 70% of maize seed observations are correctly reported as local or improved, while 16% are type I errors (falsely reported as improved) and 14% are type II errors (falsely reported as local). Type I errors are more likely to have been sourced from other farmers, rather than formal channels. An analysis of input use, including seed, fertilizer, and labor allocations, reveals that farmers tend to treat improved maize differently, depending on whether they correctly perceive it as improved. This suggests that errors in farmers' seed type awareness may translate into suboptimal management practices. In econometric analysis, the measured yield benefit of improved seed use is smaller in magnitude with a DNA-derived categorization, as compared with farmer reports. The greatest yield benefit is with correctly identified improved seed. This indicates that investments in farmers' access to information, seed labeling, and seed system oversight are needed to complement investments in seed variety development.
In this report we analyze three waves nationally-representative household survey data from Kenya, Uganda, Tanzania, Nigeria, Pakistan, Bangladesh, India, and Indonesia to explore sociodemographic and economic factors associated with mobile money adoption, awareness, and use across countries and over time. Our findings indicate that to realize the potential of digital financial services to reach currently unbanked populations and increase financial inclusion, particular attention needs to be paid to barriers faced by women in accessing mobile money. While policies and interventions to promote education, employment, phone ownership, and having a bank account may broadly help to increase mobile money adoption and use, potentially bringing in currently unbanked populations, specific policies targeting women may be needed to close current gender gaps.
Consumer attitudes are a key component in private sector market segmentation. Knowledge about consumers’ tastes can lead to better product design and more effective communication with target markets. Similarly, evidence suggests that farmers’ attitudes influence whether they adopt productivity-increasing technologies. Using consumer insights from the private sector, agricultural intervention programs can use market research, product development, and communication strategies to better understand farmers as consumers and best target interventions. This brief provides an overview of how farmers' attitudes affect their willingness to adopt new technology, and how knowledge of farmer attitudes can improve program design and implementation.