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Maize Yield and Crop Area Allocation among Tanzanian Farmers

EPAR TECHNICAL REPORT #326

Thu, 06/01/2017

AUTHORS: Travis Reynolds, C. Leigh Anderson, Margaret Beetstra, Pierre Biscaye, Katie Panhorst Harris

ABSTRACT: 

By examining how farmers respond to changes in crop yield, we provide evidence on how farmers are likely to respond to a yield-enhancing intervention that targets a single staple crop such as maize. Two alternate hypotheses we examine are: as yields increase, do farmers maintain output levels but change the output mix to switch into other crops or activities, or do they hold cultivated area constant to increase their total production quantity and therefore their own consumption or marketing of the crop? This exploratory data analysis using three waves of panel data from Tanzania is part of a long-term project examining the pathways between staple crop yield (a proxy for agricultural productivity) and poverty reduction in Sub-Saharan Africa. 

Previous EPAR research identified a high level of year-to-year change in crop portfolios by farmers, as well as large-magnitude changes in cultivated area, particularly for smallholders. This implies that farmers may be open to changes in crop mix influenced by development interventions targeting certain crops. Many agricultural development interventions focus on increasing land productivity, in particular relying on crop-focused strategies that emphasize raising yields of major cereal crops. Such interventions often assume that as farmers become more productive, they will specialize increasingly in their most productive crop, while relatively less productive farmers will shift to other crops, or shift out of farming into other rural employment, or migrate to look for urban employment. However, many smallholder farmers in Sub-Saharan Africa face constraints that also shape their livelihood decisions and may result in different farmer responses to land productivity changes than expected.

We use panel data from three waves of the Tanzania National Panel Survey (TNPS) between 2008 and 2012 to examine patterns in how Tanzanian farmers adjust their land allocation to maize following changes in their on-farm maize yields. We first consider whether households that experienced increasing maize yield from 2008-2010 (yield increasers) versus those experiencing decreasing maize yield (yield decreasers) exhibit any shared baseline household, farm, or livelihood characteristics. We then use OLS and ordinal logistic regression to analyse how changes in maize yield within a given household might be associated with changes in cropland allocation to maize versus other crops, controlling for household, farm, and geographic characteristics. We find that higher baseline maize yields in 2008 or 2010 are positively associated with increases in maize land allocation from 2010-2012, both in terms of increasing total land area (ha) and increasing proportion of total farm landholdings (%) – suggesting that on average higher-yield maize farmers are more likely to expand maize production than lower-yield maize farmers. A better understanding of the ways farmers respond to increases in maize yields will allow for better-informed and better-targeted investments in agriculture, and could inform ongoing structural transformation debates.

This report is being prepared for submission to a peer-reviewed publication. A research poster that was presented at the Evans School Research Symposium includes some of our initial results. Findings from this report were presented at the ICABR Conference in Berkeley, CA in June 2017.

Learn more about our ongoing research on yield and area allocation and explore our data with this interactive visualization, which we presented at the Global Open Data for Agriculture and Nutrition (GODAN) 2016 Summit. The code for this visualization is a available in a GitHub repository.

TYPE OF RESEARCH: Data Analysis

RESEARCH TOPIC CATEGORY: Sustainable Agriculture & Rural Livelihoods; Agricultural Productivity, Yield, & Constraints; Agricultural Inputs & Farm Management; Risk, Preferences, & Decision-Making

POPULATION(S): Smallholder Farmers

GEOGRAPHIC FOCUS: East Africa Region and Selected Countries

DATASET(S): LSMS & LSMS-ISA

Downloadable Documents

Presentation Poster

Presentation Slides

GitHub Code Repository – Data Visualization