Research Topics

Geography

EPAR Technical Report #363
Publication Date: 02/10/2019
Type: Data Analysis
Abstract

Studies of improved seed adoption in developing countries almost always draw from household surveys and are premised on the assumption that farmers are able to self-report their use of improved seed varieties. However, recent studies suggest that farmers’ reports of the seed varieties planted, or even whether seed is local or improved, are sometimes inconsistent with the results of DNA fingerprinting of farmers' crops. We use household survey data from Tanzania to test the alignment between farmer-reported and DNA-identified maize seed types planted in fields. In the sample, 70% of maize seed observations are correctly reported as local or improved, while 16% are type I errors (falsely reported as improved) and 14% are type II errors (falsely reported as local). Type I errors are more likely to have been sourced from other farmers, rather than formal channels. An analysis of input use, including seed, fertilizer, and labor allocations, reveals that farmers tend to treat improved maize differently, depending on whether they correctly perceive it as improved. This suggests that errors in farmers' seed type awareness may translate into suboptimal management practices. In econometric analysis, the measured yield benefit of improved seed use is smaller in magnitude with a DNA-derived categorization, as compared with farmer reports. The greatest yield benefit is with correctly identified improved seed. This indicates that investments in farmers' access to information, seed labeling, and seed system oversight are needed to complement investments in seed variety development.

EPAR Technical Report #140
Publication Date: 03/17/2011
Type: Data Analysis
Abstract

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. 

EPAR Technical Report #121
Publication Date: 01/10/2011
Type: Literature Review
Abstract

The purpose of this literature review is to identify the linkages between increases in agricultural productivity and poverty reduction. The relevant literature includes economic theory and evidence from applied growth and multiplier models as well as micro-level studies evaluating the impact of specific productivity increases on local poverty outcomes. We find that cross-country and micro-level empirical studies provide general support for the theories of a positive relationship between growth in agricultural productivity and poverty alleviation, regardless of the measures of productivity and poverty that are used. The evidence also suggests multiple pathways through which increases in agricultural productivity can reduce poverty, including real income changes, employment generation, rural non-farm multiplier effects, and food prices effects. However, we find that barriers to technology adoption, initial asset endowments, and constraints to market access may all inhibit the ability of the poorest to participate in the gains from agricultural productivity growth.