Geography

EPAR Technical Report #335
Agricultural Development Indicator Curation
Publication Date: 11/21/2017
Type: Data Analysis
Abstract
EPAR has developed Stata do.files for the construction of a set of agricultural development indicators using data from the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA). We are sharing our code and documenting our construction decisions both to facilitate analyses of these rich datasets and to make estimates of relevant indicators available to a broader audience of potential users. 
Presentation Slides
Code, Code, Code, Code
EPAR Technical Report #317
Digital Financial Services & Gender: An Analysis of Correlates of Awareness, Adoption, and Use
Publication Date: 11/16/2017
Type: Data Analysis
Abstract

In this report we analyze three waves nationally-representative household survey data from Kenya, Uganda, Tanzania, Nigeria, Pakistan, Bangladesh, India, and Indonesia to explore sociodemographic and economic factors associated with mobile money adoption, awareness, and use across countries and over time. Our findings indicate that to realize the potential of digital financial services to reach currently unbanked populations and increase financial inclusion, particular attention needs to be paid to barriers faced by women in accessing mobile money. While policies and interventions to promote education, employment, phone ownership, and having a bank account may broadly help to increase mobile money adoption and use, potentially bringing in currently unbanked populations, specific policies targeting women may be needed to close current gender gaps.

Technical Report
Code
EPAR Technical Report #218
China Agricultural Machinery
Publication Date: 01/13/2013
Type: Literature Review
Abstract

This desk study reports on the small-scale machinery sector in China and a selection of SSA countries: Ethiopia, Tanzania, Nigeria, Burkina Faso, and Uganda. The report is organized into three sections. Section 1 discusses the current state of small-scale agricultural machinery in SSA for crop and livestock production in each of the SSA countries identified. It also seeks to identify major areas of need in terms of agricultural mechanization and major constraints to agricultural machinery adoption, dissemination and maintenance. Section 2 focuses on the agricultural machinery sector in China and Chinese Africa relationships in agricultural development. It also identifies the major government players in the Chinese agricultural machinery sector. Section 3 is a “directory” of small-scale agricultural machinery manufactured in China with potential relevance for SSA smallholder farmers. We divide machines by function (e.g. threshing) although many Chinese machines are multi-function and can serve multiple purposes. We also note applicable crops, if listed by the manufacturers, and technical specifications as available.

Literature Review
EPAR Technical Report #201
Drivers of Inorganic Fertilizer Use in Tanzania: A Comparison of the TZNPS and FF Datasets
Publication Date: 09/12/2012
Type: Data Analysis
Abstract

This brief explores how two datasets – The Tanzania National Panel Survey (TZNPS) and the TNS-Research International Farmer Focus (FF) – predict the determinants of inorganic fertilizer use among smallholder farmers in Tanzania by using regression analysis. The (TZNPS) was implemented by the Tanzania National Bureau of Statistics, with support from the World Bank Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) team and includes extensive information on crop productivity and input use. The FF survey was funded by the Bill and Melinda Gates Foundation and implemented by TNS Research International and focuses on the on the behaviors and attitudes of smallholder farmers in Tanzania. The two datasets produce relatively comparable results for the primary predictors of inorganic fertilizer use: agricultural extension and whether or not a household grows cash crops. However, other factors influencing input use produce results that vary in magnitude and direction of the effect across the two datasets. Distinct survey instrument designs make it difficult to test the robustness of the models on input use other than inorganic fertilizer. This brief uses data inorganic fertilizer use, rather than adoption per se. The TZNPS did not ask households how recently they began using a certain product and although the FF survey asked respondents how many new inputs were tried in the past four planting seasons, they did not ask specifically about inorganic fertilizer.

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