Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/30472
Title: Improving Methods for Estimating Livestock Production and Productivity
Contributor(s): Baker, Derek  (project team member)orcid ; Morley, Philip  (project team member); Al-Moadhen, Hussain (project team member); Downey, Rebecca (project team member); Yusuf, Eva (project team member); Longin, Nsiima (project team member); Baleseng, Leonard Boitumelo (project team member); Makgekgenene, Alec (project team member); Coleman, Michael  (project team member)orcid ; Moss, Jonathan  (project team member)orcid 
Publication Date: 2017
Handle Link: https://hdl.handle.net/1959.11/30472
Abstract: This project seeks methods of improving the quality of livestock data. It supports the Global Strategy on Agricultural and Rural Statistics, and focuses on production-level livestock: specifically the measurement of production and productivity at household level.
The project seeks opportunities to improve livestock data collection methods across a range of species. It also addresses the definition of target variables, methods of collection, procedures for benchmarking, and institutional organisation surrounding livestock data collection.
The fieldwork for the project features several stages:
  • Consultation – identifying species and variables for which measurement of production and productivity are most important, and identifying mechanisms by which field tests can be carried out (Feb 2015)
  • Gap analysis – identifying gaps between an "ideal system" and the current reality, and proposing changes that can be tested. This includes a review of existing questionnaires and other collection mechanisms (Feb-March 2015).
  • Communications – formulating new variables and measures, and designing new collection methods which can be tested in selected locations (Feb-April 2015).
  • Testing – field-testing of new collection methods, which can occur alongside existing collection procedures or independently (April-August 2015).
  • Review and validation – examination and discussion of results, and their application in future data collection (through to early 2016).
The field work for the project offers an opportunity to test and improve existing or new activities in livestock data collection, and to improve mechanisms for benchmarking performance.
Publication Type: Report
Publisher: Global Strategy to Improving agricultural and rural statistics (GSARS)
Place of Publication: Rome, Italy
Fields of Research (FoR) 2008: 140201 Agricultural Economics
080609 Information Systems Management
Fields of Research (FoR) 2020: 300208 Farm management, rural management and agribusiness
380101 Agricultural economics
Socio-Economic Objective (SEO) 2008: 919999 Economic Framework not elsewhere classified
890399 Information Services not elsewhere classified
Socio-Economic Objective (SEO) 2020: 280108 Expanding knowledge in economics
280101 Expanding knowledge in the agricultural, food and veterinary sciences
HERDC Category Description: R1 Report
Publisher/associated links: https://www.une.edu.au/research/research-centres-institutes/irf/international-development-research/current-projects/improving-methods-for-estimating-livestock-production-and-productivity
Description: The following reports and working papers are available in relation to this project:
Literature Review (April 2016): Timely and accurate data is critically important for the development of food security programs, agricultural development, poverty reduction policies, investment strategies and natural disaster responses. (Drafted By: Jonathan Moss, Philip Morley, Derek Baker, Hussain Al-Moadhen, Rebecca Downie, and University of New England)
Gap Analysis Report (November 2016): This Gap Analysis Report seeks methods for improving the quality of livestock data across a range of species and focuses on production-level livestock, specifically on the measurement of production and productivity at household level.
Test Stage (November 2016): The test phase of the project Improving Methods for Estimating Livestock Production and Productivity is based on the literature review and gap analysis and was carried out in three countries (Botswana, Tanzania and Indonesia). (Drafted By: Michael Coleman, Phil Morley, Derek Baker and Jonathan Moss)
Methodological Report (May 2017): This Technical Report proposes methods for the collection of data to compile improved measures of selected indicators, based on analyses of existing methods and field-testing of alternatives.
Appears in Collections:Report
School of Environmental and Rural Science
UNE Business School

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