Using The Economic Surplus Model To Measure Potential Returns To International Livestock Research

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Using the Economic Surplus Model to Measure Potential Returns to International Livestock Research

Using the Economic Surplus Model to Measure Potential Returns to International Livestock Research
Author :
Publisher : ILRI (aka ILCA and ILRAD)
Total Pages : 37
Release :
ISBN-10 : 9789291460540
ISBN-13 : 9291460540
Rating : 4/5 (540 Downloads)

Book Synopsis Using the Economic Surplus Model to Measure Potential Returns to International Livestock Research by : Patricia Kristjanson

Download or read book Using the Economic Surplus Model to Measure Potential Returns to International Livestock Research written by Patricia Kristjanson and published by ILRI (aka ILCA and ILRAD). This book was released on 1999-01-01 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study has developed a methodology that builds on the approach to measuring agricultural research returns suggested by Alston et al (1995). We have integrated a herd model to measure the potential size of impact of a new technology, GIS, to predict where this impacts is likely to be felt, and the economic surplus model to estimate some of the costs of trypanosomosis, the potential benefits of controlling it, and potential returns to vaccine research. The advantage of this approach is that it uses field data and GIS analysis to determine where and how much impact research will have on livestock productivity, rather than 'guesstimates' by researchers, as has often been done in previous studies of returns to agricultural research. It is an approach, however, that requires much data and the type of information that is still scarce in many developing countries. This includes evidence of the productivity impacts of a given livestock technology at the herd, rather than individual animal level, and access to GIS data at the lowest adminstrative level possible (e.g. district). Ideally, household level survey data are used to complement the GIS data and verify the recommendation domain. Thus this approach will be enhanced in future analyses by the availability of a wider range of data collected at the household level from different livestock production systems to examine more closely the question 'Impact on whom?'


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