Skip to main navigation Skip to search Skip to main content

Integrating livestock into agricultural statistics: The AU-IBAR, FAO, ILRI, WB Data Innovation Project

Ugo Pica-Ciamarra, Derek Baker, Berhanu Bedane, Thomas Emwanu, Nancy Morgan

Research output: Contribution to conferencePaperpeer-review

Abstract

The growing demand for food of animal origin developing countries, stimulated by population growth, gains in real per capita income and urbanization, represents an opportunity for some livestock dependent poor to escape poverty. However, because of the dearth of livestock-related data, the linkages between livestock, economic development and poverty reduction remain to a large extent unclear, which constrains the design, implementation and monitoring of pro-poor livestockrelated policies and investments. This paper provides an introduction to the Gates-funded Livestock in Africa: Improving Data for Better Policies Project being implemented by AU-IBAR, FAO, ILRI and WB. This project has the overarching objective to assist African governments in better collecting and analyzing data which support public and private investments in the livestock sector that benefit the less well-to-do.

A variety of livestock-related data can be collected at country level, but the current limited understanding of the livestock-poverty interface makes it difficult to identify priority data to gather and process for formulating policies and investments which promote equitable growth of the livestock sector. In addition, the role and mandate of the public sector in providing specific information is often unclear, and stakeholders tend to look for data and indicators which support specific investments or government objectives - such as, for example, the number of livestock to be vaccinated or prices for live animals in major regional markets - often disregarding the broader livestock-poverty interface. There are also technical difficulties associated with 'measuring livestock', due to the existence of hundreds of breeds; regular and irregular herd mortality and reproduction rate; livestock movements; impact of livestock age and animal diseases on productivity; and others.

The Livestock in Africa: Improving Data for Better Policies Project will inventory existing livestock-poverty data and data sources in Uganda, Tanzania and a West African country to be decided, and establish communications amongst users and suppliers of livestock statistics to pilot new methods for collection, validation and analysis of data and dissemination of indicators, which facilitate both public and private investments in the livestock sector. In developing new methods and approaches, the Project will (a) combine production, value chain and consumption data to better understand the livestock-poverty linkages; (b) identify key indicators that provide insights not only on production and productivity but also on other livelihood-supporting services provided by livestock; (c) take a demand-driven approach and design a targeted communication and advocacy strategy to support the mainstreaming of key livestock data / indicators into national statistical systems. What matters, in fact, is not the one-off generation and analysis of data, but the continuous availability of livestock statistics to identify good investment opportunities, either for the public and the private sector.

Original languageEnglish
Pages1-10
Publication statusPublished - 2010
EventICAS V: Fifth International Conference on Agricultural Statistics - Speke Resort & Conference Centre, Kampala, Uganda
Duration: 12 Dec 200714 Dec 2007

Conference

ConferenceICAS V: Fifth International Conference on Agricultural Statistics
CityKampala, Uganda
Period12/12/0714/12/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 1 - No Poverty
    SDG 1 No Poverty
  2. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  3. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth

Fingerprint

Dive into the research topics of 'Integrating livestock into agricultural statistics: The AU-IBAR, FAO, ILRI, WB Data Innovation Project'. Together they form a unique fingerprint.

Cite this