Year Published
- 2008 (3) Apply 2008 filter
- 2009 (3) Apply 2009 filter
- 2010 (8) Apply 2010 filter
- 2011 (5) Apply 2011 filter
- 2012 (1) Apply 2012 filter
- 2013 (0)
- 2014 (3) Apply 2014 filter
- (-) Remove 2015 filter 2015
- 2016 (4) Apply 2016 filter
- 2017 (5) Apply 2017 filter
- 2018 (1) Apply 2018 filter
- (-) Remove 2019 filter 2019
- 2020 (0)
- 2021 (0)
Research Topics
Populations
- Countries/Governments (0)
- Rural Populations (0)
- Smallholder Farmers (1) Apply Smallholder Farmers filter
- Women (0)
Types of Research
- (-) Remove Data Analysis filter Data Analysis
- (-) Remove Literature Review filter Literature Review
- Portfolio Review (0)
- Research Brief (1) Apply Research Brief filter
Geography
- East Africa Region and Selected Countries (1) Apply East Africa Region and Selected Countries filter
- Global (1) Apply Global filter
- South Asia Region and Selected Countries (0)
- Southern Africa Region and Selected Countries (0)
- Sub-Saharan Africa (0)
- West Africa Region and Selected Countries (0)
Dataset
- ASTI (0)
- FAOSTAT (0)
- Farmer First (0)
- LSMS & LSMS-ISA (0)
- Other Datasets (1) Apply Other Datasets filter
Current search
- (-) Remove Food Security & Nutrition filter Food Security & Nutrition
- (-) Remove Health filter Health
- (-) Remove Labor & Time Use filter Labor & Time Use
- (-) Remove Research & Development filter Research & Development
- (-) Remove Data Analysis filter Data Analysis
- (-) Remove Literature Review filter Literature Review
- (-) Remove 2015 filter 2015
- (-) Remove 2019 filter 2019
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.
We review the current body of literature exploring the theories behind holistic human development measurements and the tradeoffs of different methodologies for the construction of human development indices. Through a systematic review of published and grey literature in the fields of human, international, and economic development we identify 22 current indices that aggregate measures from multiple dimensions of human development. We then analyze these indices to identify tradeoffs related to their unique characteristics and construction methodologies, considering ease of calculation, coverage of different measures of human development, ease of interpretation, comparability, and novelty. The report is accompanied by an appendix of summary tables for each index with further details regarding background information, methodology, index components, and evaluation criteria addressed within the report.
This report reviews the current body of peer-reviewed scholarship exploring the impacts of morbidity on economic growth. This overview seeks to provide a concise introduction to the major theories and empirical evidence linking morbidity – and the myriad different measures of morbidity – to economic growth, which is defined primarily in terms of gross domestic product (GDP) and related metrics (wages, productivity, etc.). Through a systematic review of published manuscripts in the fields of health economics and economic development we further identify the most commonly-used pathways linking morbidity to economic growth. We also highlight the apparent gaps in the empirical literature (i.e., theorized pathways from morbidity to growth that remain relatively untested in the published empirical literature to date).