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Recent research has used typologies to classify rural households into categories such as “subsistence” versus “commercialized” as a means of targeting agricultural development interventions and tracking agricultural transformation. Following an approach proposed by Alliance for a Green Revolution in Africa, we examine patterns in two agricultural transformation hallmarks – commercialization of farm output, and diversification into non-farm income – among rural households in Ethiopia, Nigeria, and Tanzania from 2008-2015. We classify households into five smallholder farm categories based on commercialization and non-farm income levels (Subsistence, Pre-commercial, Transitioning, Specialized Commercial, and Diversified Commercial farms), as well as two non-smallholder categories (Largeholder farms and Non-farm households). We then summarize the share of households in each of these categories, examine geographic and demographic factors associated with different categories, and explore households’ movement across categories over time. We find a large amount of “churn” across categories, with most households moving to a different (more or less commercialized, more or less diversified) category across survey years. We also find many non-farm households become smallholder farmers – and vice versa – over time. Finally, we show that in many cases increases in farm household commercialization or diversification rates actually reflect decreased total farm production, or decreased total income (i.e., declines in the denominators of the agricultural transformation metrics), suggesting a potential loss of rural household welfare even in the presence of “positive” trends in transformation indicators. Findings underscore challenges with using common macro-level indicators to target development efforts and track progress at the household level in rural agrarian communities.
This is "Section B" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of household characteristics by gender and by administrative zone, considering landholding size, number of crops grown, yields, livestock, input use, and food consumption.
This is "Section E" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of livestock and livestock by-product characteristics by gender of household head and by zones, as well as our analyses of livestock disease, vaccines, and theft.
This is "Section F" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of soil characteristics and soil management, of input use by crop and gender at the plot and household levels, and of improved variety seeds and water management.
This is "Section D" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of basic farm characteristics, land and labor productivity, crop sales, yield measures, intercropping, and pre- and post-harvest losses, including comparisons by gender of household head and by zone.
This is the introductory section of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present an overview of report sections, as well as an executive summary of findings on crops and livestock, constraints to productivity, and productivity and nutrition outcomes.
This presentation summarizes the biotic (insects, viruses, fungi, bacteria, weeds, and post-harvest pests) and abiotic (drought and soil nutrients) stresses that may be addressed or countered in order to improve crop yield in Sub-Saharan Africa and South Asia. Data is sourced from FAOSTAT, GAEZ, a series of academic papers by Waddington & Dixon, and IMPACT model estimates. Slides compare area harvested, yield, and yield gap percentage with total calories per year, the 2005 value of production, and projected growth between 2005-2030.
This research brief synthesizes evidence on the effects of policy incentives on agricultural productivity. The evidence discussed is primarily drawn from documents provided to EPAR by the Bill and Melinda Gates Foundation. We review the role of policy and institutions in the Asian Green Revolution, a detailed case study on how policy changes have removed smallholder productivity constraints and contributed to growth, and the theory on the connection of policy incentives to productivity growth.
This brief presents selected material from the Fourth African Agricultural Markets Program (AAMP) policy symposium, Agricultural Risks Management in Africa: Taking Stock of What Has and Hasn’t Worked, organized by the Alliance for Commodity Trade in Eastern and Southern Africa and the Common Market for Eastern and Southern Africa that took place in Lilongwe, Malawi, September 6-10, 2010. We draw almost exclusively from Rashid and Jayne’s summary, “Risk Management in African Agriculture: A review of experiences.” This article summarizes across the background papers, with major findings grouped into three broad categories: cross cutting, government-led policies, and modern instruments.
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.