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Realizing "Tanzania Vision 2025" through Livestock

Evidence from the 2012/13 National Panel Survey








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    Brochure, flyer, fact-sheet
    Realizing "Uganda Vision 2040" through Livestock
    Evidence from the 2011/12 National Panel Survey
    2015
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    How many households keep livestock in rural and urban areas? What are their major production and husbandry practices, and their constraints to increase livestock productivity? This infographics presents an analysis of one of the largest datasets on livestock at household level available throughout sub-Saharan Africa: the Uganda 2011/12 National Panel Survey. In Uganda, the majority of rural households depend on livestock for their livelihoods; a binding constraint to increase livestock productiv ity is their limited utilization of extension services. While technical-fixes are important, it is as much as if not more important that policies and investments also address the so-called “last-mile challenge”, with the objective to ensure that livestock farmers are informed and have incentives to adopt improved livestock technologies and more efficient production and husbandry practices.
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    Mobilizing the Data Revolution
    Experimenting with livestock data in Tanzania and Uganda
    2015
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    The data revolution must address three major challenges in order to contribute to sustainable development: increasing the quantity and quality of data; making the data usable; and ensuring their use by decision-makers. This infographic shows how the data revolution can be mobilized, with an example from the livestock sector. In collaboration with FAO, the governments of Tanzania and Uganda have increased the quantity and quality of livestock data available to decision-makers – currently the two countries have possibly the largest datasets on livestock at household level available throughout Africa - and have analyzed them to refine and reshape their policies and investments in the livestock sector.
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    Investing in the livestock sector: Why Good Numbers Matter
    A Sourcebook for Decision Makers on How to Improve Livestock Data
    2014
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    This Sourcebook on livestock data summarizes the activities and outputs of the Livestock in Africa: Improving Data for Better Policies Project. It provides guidance to decision makers responsible to collect and analyze livestock data from differ¬ent perspectives on how to systematically address livestock data-related issues within the context of the national agri-cultural statistical system. In particular, it first develops the skeleton of a sound livestock statistical system, consistent with th e demand of livestock information by stakehold¬ers and the principles of the Global Strategy to Improve Agricultural and Rural Statistics (World Bank, 2011) , which represents the foundation for producing good livestock data. It then presents a sample of methods and tools and associated examples designed to improve the quantity and quality of livestock data available to decision makers. These tools and methods target household and farm level data for example, trade data and the role of expert in formants to generate statistics are not dealt with in the Sourcebook and to a large extent have been tested in the context of the implementation of Living Standards Measurement Studies and small-scale data collection exercises in Niger, Tanzania and Uganda. They were jointly identified and developed based on dialogue between the Livestock in Africa: Improving Data for Better Policies Project and users and suppliers of livestock data and statistics at country level, including the Ministry respons ible for livestock development, the National Statistical Authority, and other national and pan-African public and private sector data stakeholders. As such, they address data issues which are of broad interest to livestock stakeholders: the 23rd session of the African Commission for Agricultural Statistics (AFCAS, December 2013) recommend¬ed country governments in the continent adopt some of the tools and methods presented in the following chapters to improve the quantity and quality of the live stock information available to decision makers.

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