Year Published
- 2008 (0)
- (-) Remove 2009 filter 2009
- 2010 (0)
- 2011 (1) Apply 2011 filter
- 2012 (0)
- 2013 (1) Apply 2013 filter
- 2014 (0)
- 2015 (1) Apply 2015 filter
- 2016 (2) Apply 2016 filter
- 2017 (3) Apply 2017 filter
- (-) Remove 2018 filter 2018
- 2019 (2) Apply 2019 filter
- 2020 (0)
- 2021 (0)
Research Topics
Populations
- Countries/Governments (1) Apply Countries/Governments filter
- (-) Remove Rural Populations filter Rural Populations
- (-) Remove Smallholder Farmers filter Smallholder Farmers
- Women (5) Apply Women filter
Types of Research
- (-) Remove Data Analysis filter Data Analysis
- Literature Review (5) Apply Literature Review filter
- Portfolio Review (0)
- (-) Remove Research Brief filter Research Brief
Geography
- East Africa Region and Selected Countries (1) Apply East Africa Region and Selected Countries filter
- Global (0)
- 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 (1) Apply LSMS & LSMS-ISA filter
- Other Datasets (0)
Current search
- (-) Remove Household Well-Being & Equity filter Household Well-Being & Equity
- (-) Remove Information & Mobile Technology filter Information & Mobile Technology
- (-) Remove Smallholder Farmers filter Smallholder Farmers
- (-) Remove Data Analysis filter Data Analysis
- (-) Remove Market & Value Chain Analysis filter Market & Value Chain Analysis
- (-) Remove Monitoring & Evaluation filter Monitoring & Evaluation
- (-) Remove Agricultural Productivity, Yield, & Constraints filter Agricultural Productivity, Yield, & Constraints
- (-) Remove Rural Populations filter Rural Populations
- (-) Remove Research Brief filter Research Brief
- (-) Remove 2009 filter 2009
- (-) Remove 2018 filter 2018
Precise agricultural statistics are necessary to track productivity and design sound agricultural policies. Yet, in settings where intercropping is prevalent, even crop yield can be challenging to measure. In a systematic survey of the literature on crop yield in low-income settings, we find that scholars specify how they estimate the yield denominator in under 10% of cases. Using household survey data from Tanzania, we consider four alternative methods of allocating land area on plots that contain multiple crops, and explore the implications of this measurement decision for analyses of maize and rice yield. We find that 64% of cultivated plots contain more than one crop, and average yield estimates vary with different methods of calculating area planted. This pattern is more pronounced for maize, which is more likely than rice to share a plot with other crops. The choice among area methods influences which of these two staple crops is found to be more calorie-productive per ha, as well as the extent to which fertilizer is expected to be profitable for maize production. Given that construction decisions can influence the results of analysis, we conclude that the literature would benefit from greater clarity regarding how yield is measured across studies.
Presentation slides summarizing agriculture growth and development information sourced from the World Development Report and two academic papers provided by the Bill and Melinda Gates Foundation. Slides convey information in a non-academic format. Slides are organized into: agricultural pro-poor growth, agriculture as an engine for development, who benefits from agriculture, and the effects and policy impacts of the Green Revolution.