Types of Research
- (-) Remove Agricultural Productivity, Yield, & Constraints filter Agricultural Productivity, Yield, & Constraints
- (-) Remove Health filter Health
- (-) Remove Smallholder Farmers filter Smallholder Farmers
- (-) Remove Aid & Other Development Finance filter Aid & Other Development Finance
- (-) Remove Technology filter Technology
- (-) Remove LSMS & LSMS-ISA filter LSMS & LSMS-ISA
- (-) Remove FAOSTAT filter FAOSTAT
- (-) Remove Food Security & Nutrition filter Food Security & Nutrition
- (-) Remove Monitoring & Evaluation filter Monitoring & Evaluation
- (-) Remove Information & Mobile Technology filter Information & Mobile Technology
Common estimates of agricultural productivity rely upon crude measures of crop yield, typically defined as the weight harvested of a crop divided by the area harvested. But this common yield measure poorly reflects performance among farm systems combining multiple crops in one area (e.g., intercropping), and also ignores the possibility that farmers might lose crop area between planting and harvest (e.g., partial crop failure). Drawing on detailed plot-level data from Tanzania’s National Panel Survey, our research contrasts measures of smallholder productivity using production per hectare harvested and production per hectare planted.
An initial analysis (Research Brief - Rice Productivity Measurement) looking at rice production finds that yield by area planted differs significantly from yield by area harvested, particularly for smaller farms and female-headed households. OLS regression further reveals different demographic and management-related drivers of variability in yield gains – and thus different implications for policy and development interventions – depending on the yield measurement used. Findings suggest a need to better specify “yield” to more effectively guide agricultural development efforts.
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.