Year Published
- 2008 (0)
- (-) Remove 2009 filter 2009
- 2010 (0)
- (-) Remove 2011 filter 2011
- 2012 (1) Apply 2012 filter
- 2013 (1) Apply 2013 filter
- 2014 (0)
- 2015 (0)
- 2016 (3) Apply 2016 filter
- (-) Remove 2017 filter 2017
- 2018 (0)
- 2019 (0)
- 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
- Literature Review (1) 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 (1) Apply Global filter
- South Asia Region and Selected Countries (0)
- Southern Africa Region and Selected Countries (0)
- Sub-Saharan Africa (1) Apply Sub-Saharan Africa filter
- West Africa Region and Selected Countries (0)
Dataset
Current search
- (-) Remove Household Well-Being & Equity filter Household Well-Being & Equity
- (-) Remove 2017 filter 2017
- (-) Remove 2009 filter 2009
- (-) Remove 2011 filter 2011
- (-) Remove Agricultural Productivity, Yield, & Constraints filter Agricultural Productivity, Yield, & Constraints
- (-) Remove Farmer First filter Farmer First
- (-) Remove Data Analysis filter Data Analysis
- (-) Remove Technology Adoption filter Technology Adoption
- (-) Remove FAOSTAT filter FAOSTAT
- (-) Remove Research Brief filter Research Brief
An ongoing stream of EPAR research considers how public good characteristics of different types of research and development (R&D) and the motivations of different providers of R&D funding affect the relative advantages of alternative funding sources. For this project, we seek to summarize the key public good characteristics of R&D investment for agriculture in general and for different subsets of crops, and hypothesize how these characteristics might be expected to affect public, private, or philanthropic funders’ investment decisions.
This brief explores agricultural data for Tanzania from the LSMS-ISA and Farmer First household surveys. We first present the differences in the LSMS and Farmer First survey design and in basic descriptives from the two data sources. We then present the results of our initial LSMS data analysis using the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), focusing on the agricultural data, before presenting our analysis of farmer aspirations and of gender differences using the Farmer First data.
This brief presents an in depth analysis of the FAO’s methodology behind their calculations for hunger. The analysis includes a review of the key assumptions made by the FAO in their calculations, critiques of their methodology, and recommendations for future research. The critiques include opinions from the literature on the subject as well as from the authors of the request.