Research Topics

EPAR Research Brief #187
Publication Date: 07/11/2012
Type: Data Analysis
Abstract

This brief present our analysis of maize cultivation in Tanzania using data 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 find that Maize was the most commonly grown crop in Tanzania – cultivated by 83% of farming households. Eighty-two percent of agricultural households reported consuming maize flour during the week prior to being surveyed. About half of those households grew nearly all of the maize they consumed, making maize production an integral part of the farming household diet. A separate appendix includes details on our analyses.

EPAR Research Brief #188
Publication Date: 07/11/2012
Type: Data Analysis
Abstract

This brief presents our analysis of rice paddy cultivation in Tanzania using data 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 find that Paddy was the sixth most commonly cultivated priority crop. Nationally, paddy was cultivated by 17% of farming households, with male- and female-headed households cultivating paddy at a similar rate.2 Cultivation rates varied widely across zones, ranging from 51% of households in Zanzibar to only 5% in the Northern Zone. A separate appendix includes additional detail on our analyses.

EPAR Research Brief #189
Publication Date: 04/09/2012
Type: Data Analysis
Abstract

This brief presents our analysis of legume cultivation in Tanzania using data 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 find that Tanzanian farmers reported growing eight different varieties of food legumes: beans, groundnuts, cowpeas, mung beans, chickpeas, bambara nuts, field peas, soya beans, and pigeon peas. Fifty-seven percent of households in Tanzania grew at least one of these crops during the long and/or short rainy seasons.  A separate appendix includes details on our analyses.

EPAR Research Brief #190
Publication Date: 03/30/2012
Type: Data Analysis
Abstract

This brief presents a comparative analysis of men and women and of male- and female-headed households in Tanzania using data 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 compare farm activity, productivity, input use, and sales as well as labor allocations by gender of the respondent and of the household head. In households designated “female-headed” a woman was the decision maker in the household, took part in the economy, control and welfare of the household, and was recognized by others in the household as the head. For questions regarding household labor (both non-farm and farm), the gender of the individual laborer is recorded, and we use this to illustrate the responsibilities of male and female household members. An appendix provides the details for our analyses.

EPAR Research Brief #167
Publication Date: 10/07/2011
Type: Data Analysis
Abstract

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.

EPAR Technical Report #163
Publication Date: 10/03/2011
Type: Data Analysis
Abstract

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.

EPAR Technical Report #161
Publication Date: 10/01/2011
Type: Data Analysis
Abstract

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.

EPAR Technical Report #133
Publication Date: 03/07/2011
Type: Literature Review
Abstract

This report provides a summary of Tanzania’s agriculture sector, crop production, agricultural productivity and yield levels, risks, and policies and reforms. This review uses resources found on the University of Washington Libraries system and Google Scholar, as well as the websites of the Government of Tanzania, FAO, and World Bank. We find that Tanzanian agriculture workers comprise 80% of the population and farm a wide variety of crops, ranging from staple crops such as maize, cassava, and rice, to export crops such as coffee, cotton, tobacco, tea, and sugar. Smallholder farmers face increasing risks from climate change, pests, diseases, and land degradation, among others. While they have some resources available, such as farmer groups and limited access to ICTs, they lack important resources such as credit and inputs. We find that Tanzania’s land tenure and agriculture policies may further complicate the lives of smallholders through increased taxes and administrative processes. Through the Agricultural Sector Development Programme (ASDP) reform, however, the Government of Tanzania hopes to empower farmers and improve service delivery.  

EPAR Technical Report #100
Publication Date: 09/28/2010
Type: Literature Review
Abstract

Without availability and access to a variety of foods, populations in the developing world are suffering from deficiencies in iron, zinc, iodine, vitamin A, and other micronutrients in addition to deficiencies in energy and protein. Supplementation and fortification programs have demonstrated effectiveness, but there is an increasing interest in potentially more sustainable solutions via agricultural interventions. The review examines the literature regarding agricultural interventions and pathways to diet diversification and whether desired nutritional outcomes are achieved.  We find a strong sentiment that agricultural interventions can improve dietary diversity, and that dietary diversity can improve nutrition and related health outcomes. The programs with demonstrated ability to improve nutrition outcomes are most often cross-cutting interventions, borrowing from the agriculture, nutrition, and public health traditions. While these multi-platform programs can be costly to evaluate and difficult to implement, the evidence supports their potential to create sustainable quality-of-life improvements in target regions. The pathways by which agricultural interventions achieve impact are not fully clear, however. The greatest knowledge gaps are directly related to the lack of integration between program design and evaluation. Many evaluations are based on small sample sizes, lack control groups or baseline data, are subject to selection bias, or face other challenges to rigorous statistical analysis. 

EPAR Technical Brief #96
Publication Date: 09/02/2010
Type: Literature Review
Abstract

The purpose of this literature review is to examine research and decision-making tools that model the impacts of agricultural interventions. We begin with a short explanation of what model features are being described. We then review decision-support tools and user-end modeling tools (menu-driven tools with an interface designed for easy use), as well as academic and professional research models for assessing the potential impacts of agricultural interventions. This review also includes decision tools and models for analyzing agricultural and environmental policies outside of technology impacts in Sub-Saharan Africa and South Asia. The other tools mentioned here, for example a tool that considers nutritional intervention impacts, are included to help provide a broader understanding of the structure and availability of user-end, decision-making tools. In the final section of this brief, we review the most complex models used more in academic research than for in-field decision-making.