Year Published
- 2008 (0)
- 2009 (0)
- (-) Remove 2010 filter 2010
- 2011 (5) Apply 2011 filter
- 2012 (6) Apply 2012 filter
- 2013 (3) Apply 2013 filter
- 2014 (1) Apply 2014 filter
- 2015 (2) Apply 2015 filter
- (-) Remove 2016 filter 2016
- 2017 (5) Apply 2017 filter
- 2018 (0)
- 2019 (1) Apply 2019 filter
- 2020 (0)
- 2021 (0)
Research Topics
Populations
- Countries/Governments (0)
- Rural Populations (0)
- Smallholder Farmers (0)
- Women (0)
Types of Research
- (-) Remove Data Analysis filter Data Analysis
- Literature Review (3) Apply Literature Review filter
- Portfolio Review (0)
- Research Brief (10) Apply Research Brief filter
Geography
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
- Global (1) Apply Global filter
- (-) Remove South Asia Region and Selected Countries filter South Asia Region and Selected Countries
- Southern Africa Region and Selected Countries (1) Apply Southern Africa Region and Selected Countries filter
- Sub-Saharan Africa (2) Apply Sub-Saharan Africa filter
- (-) Remove West Africa Region and Selected Countries filter West Africa Region and Selected Countries
Dataset
- ASTI (0)
- FAOSTAT (0)
- Farmer First (0)
- LSMS & LSMS-ISA (2) Apply LSMS & LSMS-ISA filter
- Other Datasets (2) Apply Other Datasets filter
Current search
- (-) Remove East Africa Region and Selected Countries filter East Africa Region and Selected Countries
- (-) Remove Data Analysis filter Data Analysis
- (-) Remove Market & Value Chain Analysis filter Market & Value Chain Analysis
- (-) Remove Household Well-Being & Equity filter Household Well-Being & Equity
- (-) Remove Labor & Time Use filter Labor & Time Use
- (-) Remove Technology filter Technology
- (-) Remove West Africa Region and Selected Countries filter West Africa Region and Selected Countries
- (-) Remove South Asia Region and Selected Countries filter South Asia Region and Selected Countries
- (-) Remove 2010 filter 2010
- (-) Remove Agricultural Productivity, Yield, & Constraints filter Agricultural Productivity, Yield, & Constraints
- (-) Remove 2016 filter 2016
There is a wide gap between realized and potential yields for many crops in Sub-Saharan Africa (SSA). Experts identify poor soil quality as a primary constraint to increased agricultural productivity. Therefore, increasing agricultural productivity by improving soil quality is seen as a viable strategy to enhance food security. Yet adoption rates of programs focused on improving soil quality have generally been lower than expected. We explore a seldom considered factor that may limit farmers’ demand for improved soil quality, namely, whether farmers’ self-assessments of their soil quality match soil scientists’ assessments. In this paper, using Tanzania National Panel Survey (TZNPS) data, part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA), we compare farmers’ own assessments of soil quality with scientific measurements of soil quality from the Harmonized World Soil Database (HWSD). We find a considerable “mismatch” and most notably, that 11.5 percent of survey households that reported having “good” soil quality are measured by scientific standards to have severely constrained nutrient availability. Mismatches between scientific measurements and farmer assessments of soil quality may highlight a potential barrier for programs seeking to encourage farmers to adopt soil quality improvement activities.
Labor is one of the most productive assets for many rural households in developing countries. Despite the importance of labor—and time use more generally—little research has empirically examined the quality of time-use data in household surveys. Many household surveys rely on respondent recall, the reliability of which may decrease as recall length increases. In addition, respondents often report on time allocation for the entire household, which they may not know or recall as clearly as their own time allocation. Finally, simultaneous activities such as tending children while preparing dinner, may lead to the systematic underestimation of certain activities, particularly those that tend to be performed by women. This paper examines whether the identity of the survey respondent affects estimates of time allocation within the household. Drawing on the Ugandan LSMS-ISA household survey, we find that individuals responding for themselves report higher levels of time use over the previous week than when responding for other household members. Moreover, male respondents tend to underreport time allocation for females over the age of 15 as compared to female respondents, especially time spent on domestic activities. In addition, an analysis of the effects of two economics shocks—having a baby and floods or droughts—suggests that the identity of the respondent can affect substantive conclusions about the effects of shocks on household time use.
Mobile technology is associated with a variety of positive development and social outcomes, and as a result reaching the “final frontier” of uncovered populations is an important policy issue. We use proprietary 2012 data on mobile coverage from Collins Bartholomew to estimate the proportion of the population living in areas without mobile coverage globally and in selected regions and countries, and use spatial analysis to identify where these populations are concentrated. We then compare our coverage estimates to data from previous years and estimates from the most recent literature to provide a picture of recent trends in coverage expansion, considering separately the trends for coverage of urban and rural populations. We find that mobile coverage expansion rates are slowing, as easier to reach urban populations in developing countries are now almost entirely covered and the remaining uncovered populations are more dispersed in rural areas and therefore more difficult and costly to reach. This analysis of mobile coverage trends was the focus of an initial report on mobile coverage estimates. In a follow-up paper prepared for presentation at the 2016 APPAM International Conference, we investigate the assumption that levels of mobile network coverage are related to the degree of market liberalization at the country level.