Types of Research
- (-) Remove ASTI filter ASTI
- (-) Remove LSMS & LSMS-ISA filter LSMS & LSMS-ISA
- (-) Remove Research Brief filter Research Brief
- (-) Remove Agricultural Productivity, Yield, & Constraints filter Agricultural Productivity, Yield, & Constraints
- (-) Remove Rural Populations filter Rural Populations
- (-) Remove Data Analysis filter Data Analysis
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.