Relevant publications
Impact Assessment of Agricultural Research for Development and Poverty Reduction
H. WaibelWorking Paper No. 2Development and Agricultural Economics, Faculty of Economics and Management, University of Hannover, Germany2006This is an overview of the impact of research on agriculture for developing countries; in particular past investments of the International Agricultural Research Centres (IARC) of the Consultative Group on International Agricultural Research (CGIAR) are analysed. The key questions are: (1) has the impact of past agricultural research been significant? (2) have the poor benefited from agricultural research? and (3) what are the challenges ahead? The paper summarizes and interprets major impact assessment studies of the CGIAR. It deals with the question of poverty impact and some of the criteria that need to be fulfilled to improve the poverty impact of agricultural research. Finally emerging opportunities in agricultural research and the challenges that will arise for impact assessment from this research are considered.
11/01/2012
A Meta-Analysis of Rates of Return to Agricultural R&D: Ex Pede Herculem?
J.M. Alston, C. Chan-Kang, M.C.Mara, P.G. Pardey, and T. Wyatt IFPRI Research Report 113 International Food Policy Research Institute, Washington, D.C., USA2000In this study a concerted effort was made to assemble all the available evidence on the returns to investments in agricultural R&D published since 1953. 292 studies reporting a total of 1,886 rate of return estimates—an average of 6.5 estimates per published study. Few (21%) of the published rate of return estimates fall within the range of conventional wisdom of 40–60% per year. Excluding two extreme outlier observations, the average rate of return was 100% per year for research, 85% for extension, 48% for studies that estimated the returns to research and extension jointly, and 81% for all the studies combined. The median of the rate of return estimates was 48.0% per year for research, 62.9% for extension studies, 37% for studies that estimated the returns to research and extension jointly, and 44.3% for all studies combined. This is almost half the corresponding average, indicating significant positive skewness in the distribution of rates of return.
11/01/2012
Measuring the impacts of agricultural research on poverty reduction
J. Alwang and P.B. Siegel Agricultural Economics, 29 (1): 1-14 2003Policymakers are increasingly calling upon agricultural research managers to consider poverty reduction objectives when making resource allocations. The authors present a simple method to measure the impact of agricultural research on the poor. This method has the advantage that it presents the results in a manner consistent with commonly used measures of poverty. This consistency and focus should facilitate and enhance dialogue between policymakers and research managers when deciding on resource allocations and assessing impacts on poverty reduction. An illustrative application is presented using data from Malawi.
11/01/2012
The Economic Impact of Agricultural Research: A Practical Guide
W.A. Masters, B. Coulibaly, D. Sanogo, M. Sidibé, A.Williams, J.H. Sanders and J. Lowenberg-DeBoerDepartment of Agricultural Economics, Purdue University, Indiana, USA1996This first section of the guidebook is intended to introduce the concept of impact assessment; the second explains the economic surplus method. This is followed by a detailed discussion of practical guidelines for the collection and use of field data. Finally, a brief conclusion puts the economic surplus method into perspective, relative to other possible impact-assessment techniques.
11/01/2012
Measuring the Impacts of Science: Beyond the Economic Dimension
B. Godin and C. Doré Paper presented at the Helsinki Institute for Science and Technology Studies, HIST Lecture, 24 August 2007, Helsinki, Finland2005 Most quantitative studies on the impact of science are based on econometric models that correlate R&D expenditures to economic variables such as GDP. This study notes non-economic dimensions that should be included, such as social, cultural, political and organizational outcomes. Health and environmental impacts are also critical. How to develop indicators, and the importance of quantity, duration and frequency are considered.
11/01/2012
Assessing the Impact of Agricultural Research on Poverty Using the Sustainable Livelihoods Framework: Concepts and Methods
M. Adato, M. and R. Meinzen-Dick EPTD Discussion Paper 89 International Food Policy Research Institute, Washington, D.C., USA2002 This paper reports on the approach used in a multicountry study of the poverty impact of research programs under the Consultative Group on International Agricultural Research (CGIAR). The studies use an expanded understanding of poverty that goes beyond income or consumption-based headcounts or severity measures, to consider many other factors that poor people in different contexts define as contributing to their vulnerability, poverty, and well-being. The sustainable livelihoods framework provides a common conceptual approach to examining the ways in which agricultural research and technologies fit (or sometimes do not fit) into the livelihood strategies of households or individuals with different types of assets and other resources, strategies that often involve multiple activities undertaken at different times of the year. This paper reports on the conceptual framework, methods, and findings to date of these studies. The paper describes five case studies: (1) modern rice varieties in Bangladesh; (2) polyculture fishponds and vegetable gardens in Bangladesh; (3) soil fertility management practices in Kenya; (4) hybrid maize in Zimbabwe; and (5) creolized maize varieties in Mexico. Applying the sustainable livelihoods approach highlights the multilayered interactions between technologies and the vulnerability context of households, their asset base, intervening institutions, and livelihood strategies. However, additional aspects of culture, power, and history need to be integrated to understand the role of agricultural research in the lives of the poor, including implications of gender, ethnicity, class, etc.
11/01/2012
Operational guidelines for assessing the impact of agricultural research on livelihoods: Good practices from CIMMYT
R. La Rovere and J. Dixon (Coordinators)International Maize and Wheat Improvement Center (CIMMYT), Mexico City, MexicoMany methods, tools, and standards are available for doing impact assessment (IA), yet there are two essential requirements: (1) IA must be an integral part of the organization’s core business and knowledge management. (2) Formulating the right questions, designing the study, communicating throughout the assessment, and taking action on recommendations are as important as the actual results of an IA. This document focuses on (1) Understanding what is meant by IA and why IA studies are needed and important. (2) Designing IA studies that respond to external and internal demands. (3) Increasing awareness of available approaches. (4) Identifying good practices for quality IA and making informed choices on data and methods. (5) Teaching the key elements of well-designed IA studies or projects with IA elements.
11/01/2012
Impact Assessment of the IFPRI Agricultural Science and Technology Indicators (ASTI) Project
G. W. NortonImpact Assessment Discussion Paper No. 32International Food Policy Research Institute, Washington, D.C., USA2010Assessing research system funding adequacy and staffing, as compared to alternative investments, and allocating research resources within systems require data on agricultural research investments. The Agricultural Science and Technology Indicators (ASTI) initiative at IFPRI is the most comprehensive source of agricultural research statistics for low- and middle-income countries. Since 2001, building on an earlier International Service for National Agricultural Research (ISNAR) effort, ASTI has developed a network of institutional collaborators at national and regional levels who assist in implementing surveys to collect agricultural research investment data in Africa, Asia, the Middle East, and Latin America. ASTI compiles, processes, and publicizes the data at national, regional, and global levels. It has published a broad set of country briefs, notes, and regional synthesis reports that have been cited in national and international policy documents. The primary outputs from ASTI are the country data sets. Data are published for 32 countries in Sub-Saharan Africa, 15 countries in Latin America and the Caribbean, 5 countries in South Asia, 7 countries in East and Southeast Asia, 5 countries in the Middle East and North Africa, and 1 country in the Pacific.
11/01/2012
Challenges for Impact Evaluation of Agricultural Projects
The difficulties of impact assessment are considered. It is concluded that methodological pluralism is needed, including use of Randomized Control Trials as one option in a portfolio of methods and not always as the superior approach. Each case is different. Hence, each case needs to be carefully diagnosed (through case studies, descriptive statistics) to understand in particular who has adopted and why non-adoption occurs.
11/01/2012
Impacts of Agricultural Research on Poverty: Findings of an Integrated Economic and Social Analysis
R. Meinzen-Dick, M. Adato, L. Haddad and P. HazellInternational Food Policy Research Institute, Washington, DC, USA2003This paper reports findings of a CGIAR research project including seven case studies of different types of agricultural research: aggregate investments in agricultural research in China and India; rice, vegetable, and fishpond technologies in Bangladesh; soil fertility replenishment in Kenya; hybrid maize in Zimbabwe, and creolized maize in Mexico. The case studies found adoption was influenced by the technologies’ likelihood to increase or decrease vulnerability, whether the poor have the assets needed to adopt, the nature of disseminating institutions, and cultural factors such as gender roles and taste preferences. This paper identifies lessons that for future impact assessments. These included the identification of factors that should be understood at an early stage, such as the priority poor people put on managing risk; the types of social differentiation (gender; class; ethnicity, etc.) that will affect the uptake and impacts of technologies; the variety of traits that farmers value; and the role of agriculture in livelihood strategies. With regard to methodology, the case studies underscore the need to consider direct and indirect impacts and to avoid restricting analysis to only impacts that can be easily quantified. Mixing disciplines and research methods are essential to conducting impact assessments. Finally, the study concludes that for impact assessment to make a difference, researchers must conduct research and impact assessment in a way that facilitates institutional learning and change.
11/01/2012
Ex Post Evaluation of Economic Impacts of Agricultural Research Programs: A Tour of Good Practice
M. Maredia, D. Byerlee and J. AndersonPaper presented to the Workshop on “The Future of Impact Assessment in CGIAR: Needs, Constraints, and Options”, Standing Panel on Impact Assessment (SPIA) of the Technical Advisory Committee, Rome, May 3-5, Rome, Italy2000For relatively standard productivity-enhancing innovations such as improved cultivars, and improved livestock production methods, fairly standard and accepted methods are available, and are being increasingly applied by both IARCs and national AROs. However, we also conclude that there is much room to improve the quality of these applications. Simplistic assumptions about lags, costs, and supply shifts, together with failure to account for spill-ins, have biased estimated RORs, usually upward. In addition, the emphasis on evaluating individual technologies in an ad hoc manner, rather than research programs on a regular basis has undoubtedly favoured the selection of winners and elsewhere will probably be required to ensure reasonable chances of satisfactory progress on the methods front. For successful impact evaluation it is crucial to: (1) Define minimum data sets, (2) Combine quantitative and qualitative assessment, (3) Decentralize as far as possible (4) Build institutional capacity for ongoing evaluation and (5) Develop mechanisms to integrate information with decision making.
11/01/2012
Recent Advances in Impact Analysis Methods for Ex-post Impact Assessments of Agricultural Technology: Options for the CGIAR
A. de Janvry, A. Dustan and E. SadouletIndependent Science and Partnership Council Secretariat, Consultative Group on International Agricultural Research, Rome, Italy2011The key quantity that impact evaluation studies attempt to estimate is the average effect of adoption on outcomes for those who have adopted, known as the average treatment effect on the treated (ATT). The following steps are suggested: 1. Researchers should use either natural or randomized experiments in which the village or the community is the unit of randomization. 2. When using randomization, researchers should pursue supply-side interventions in which the new technology is introduced to entire villages. 3. Research designs should not be limited to randomized controlled trials (RCTs). Natural experiments can yield reliable estimates of impact even in the absence of controlled, explicit randomization. 4. There may be opportunities to use public–private–civil society partnerships (e.g., agro-dealers) to perform supplyside interventions. 5. Researchers should plan the evaluation before, and conduct it during diffusion of a new technology. While impact analysis is ex-post, evaluation should be planned and begin beforehand. Impact analysis designs are shown for genetically improved farm tilapia, treatment for internal parasites in goats, and drought-tolerant crop varieties. It is important to measure Long-term and aggregate effects, to assess ex-post the aggregate benefit of a technology that has diffused over a large area. As there is no observable counterfactual situation, researchers can do the following: (a) focus on smaller units of observation (such as villages) on the presumption that markets are not well integrated and therefore each unit represents a small ‘economy’. Econometric analyses of observations over time are presumed to identify the causal effect of an uneven development of technological change. (b) use simulation models to extrapolate impacts measured at the micro-level (most often increases in yields) to the level of aggregate effects. This includes the economic surplus method and the computable general equilibrium (CGE) simulation models. However, these simulations are not impact estimations. CGIAR needs to focus on generating rigorous impact estimates. View PDF
11/01/2012
Impact Assessment of Agricultural Research: Context and State Of The Art
Revised Version of a Paper prepared by the Impact Assessment and Evaluation Group (IAEG) of the Consultative Group on International Agricultural Research (CGIAR) for the ASARECA / ECART / CTA Workshop on Impact Assessment of Agricultural Research in Eastern and Central Africa, Uganda, November 1999TAC Secretariat, Food and Agriculture Organization, Rome, Italy2000Funding entities are requiring better and more substantial accountability for their investments. Furthermore, they are emphasizing the need to be output-focused, i.e., on the benefits that research produces and who gets those benefits; and not just with inputs and the levels of expenditure of resources and who pays. There is also a greater awareness among researchers that they are dealing with a dynamic situation where changes increasingly are needed during the execution of research. It is now more widely recognized that monitoring and evaluation (including assessment of impacts) can indicate most appropriate and effective ways to change plans and programmes. Social and environmental impacts must be considered along with the economic impacts. However, such assessments are beyond the time and resources normally available. Thus researchers should focus on some specific social, economic and environmental issues and then to explore the most appropriate methods to address and integrate them within the overall research evaluation and management system within the research organization. It must be institutionalized throughout. Too narrow a focus on generating a number of studies that then end up “on the shelf” will be of little use in policy- or decision making. Impact assessment provides tools to aid in decision-making or policy making, but is not a substitute for making decisions, nor does it replace the need for judgement. View PDF
11/01/2012
Does Research Reduce Poverty? Assessing the Welfare Impacts of Policy-oriented Research in Agriculture
E. Masset, R. Mulmi and A. SumnerIDS Working Papers: 360 Institute of Development Studies, UK2011In the current context of the global financial crisis and its aftermath, resources for development and for research are likely to become scarcer. The set of circumstances generating the resource scarcity is also putting pressure on development gains. More than ever before, every dollar spent on development research will have to count towards sustainable poverty reduction. However, the understanding of the impacts of development research on policy change and on poverty is weak at best, with agriculture being no different. The area of research impact is not a new area of enquiry but an emergent one. The literature is surveyed to identify different ways of assessing the impact of policy-oriented research, with the available literature on agriculture as a specific focus, considering the following: the different types of ‘policy-oriented’ research; the literature on the ‘theories of change‘ for policy research in international development; methodologies for analysing the impact of policy-oriented research; the relevant agriculture literature and outlines the types indicators that can be used for impact assessment of research with examples. View PDF
11/01/2012
Measuring Agricultural Research Investments: A Revised Global Picture
N.M. Beintema and G.J. StadsASTI Background Note International Food Policy Research Institute, Washington, D.C., USA2008Revised calculations of global agricultural research and development (R&D) spending show that the world is investing less in agricultural research than previously thought. In addition, the agricultural R&D spending of developing countries has been revised downward, with the result that high-income countries as a group still invest more in public agricultural R&D than do developing countries. Developing countries are making up ground, but more slowly than previously estimated. This brief presents revised investment trends in global agricultural R&D previously published by the Agricultural Science and Technology Indicators (ASTI) initiative. This revision has been prompted by major World Bank adjustments to its comparative pricing of goods and services across countries, expressed in internationally comparable exchange rates known as purchasing power parity (PPP) indexes. These index adjustments have in turn led to downward revisions of global economic growth figures by the International Monetary Fund (IMF), and an upward revision of developing-country poverty estimates by the World Bank. Furthermore, ASTI recently revised its country classifications to reflect increasing diversity among developing countries. The initiative has also produced new estimates of agricultural R&D investments for Latin America and the Caribbean, and a number of other developed and developing countries. The reduced calculation of total global agricultural R&D spending is largely the result of a downward adjustment of total spending for China and India. The PPP indexes for the United States, Japan, and other high-income countries did not undergo major revisions. However, due to large downward PPP adjustments in many other countries as well as the reclassification of non-OECD high-income countries, the share of high-income countries as a group in 2000 increased to 57%.
11/01/2012
Agricultural R&D Capacity and Investments in the Asia–Pacific Region
N.M. Beintema and G.J. StadsResearch Brief No. 11 International Food Policy Research Institute, Washington, D.C., USA 2008This brief reviews major institutional developments and investment and human resource trends in agricultural research and development (R&D) in 11 countries of the Asia–Pacific region. The brief draws on a set of country briefs, reports, and underlying datasets developed by the Agricultural Science and Technology Indicators (ASTI) initiative. ASTI worked with regional partners to collect detailed quantitative and qualitative information on research capacity and investment trends within agricultural R&D agencies. These data were then linked with investment and human resource data from the Chinese government and other secondary sources to provide a broader regional and global context.
11/01/2012
Public Agricultural Research in Latin America and the Caribbean: Investment and Capacity Trends
G.-J. Stads and N.M. BeintemaASTI Synthesis ReportInternational Food Policy Research Institute, Washington, D.C., USA2009In 2006, LAC employed 19,000 FTE researchers in agriculture, investing 3.0 billion in agricultural R&D (in 2005 constant prices): 1.14% of the region’s total agricultural output. However, 70% was by Argentina, Brazil, and Mexico: the remainder’s investment would be 0.72%. Regionwide investments grew by 1.1% per year during 1981–2006. During 1996–2006, agricultural research spending in countries like Argentina, Costa Rica, and Uruguay rose markedly, whereas expenditures in countries like Chile, El Salvador, Guatemala, Honduras, and Paraguay contracted. Brazil, the region’s largest country, also experienced a modest decline in its agricultural R&D investments since the mid-1990s. Argentina, Brazil, and Mexico each have large and comparatively complex systems employing thousands of scientists, whereas capacity in the Caribbean and Central American is much smaller. Average qualifications of agricultural scientists vary across the region, and while qualification improved in the past decade, the pool of scientists is ageing. Most agricultural R&D in LAC is funded by national governments, but sources differ widely across countries, and competitive funding mechanisms are more popular. Donor dependency for the LAC region is much lower than in Sub-Saharan Africa, although very high in countries like Nicaragua and Honduras. Internally generated resources and private funding play an important role in financing agricultural research in the region as well. In addition to financing research directly, national and multinational private enterprises also carry out their own research in some countries. Some of the poorer, agriculture-dependent countries (such as Guatemala, El Salvador and Paraguay) experienced sharp cuts in their agricultural research expenditures and intensity ratios over the past decade (affecting ability to generate new technology and varieties). More economically advanced countries (such as Argentina and Mexico) experienced growth and benefit from the spillover of technologies from high-income countries with similar agroclimatic conditions. Sustainable financial support for agricultural R&D is crucial regionwide, in support of revenue-generating export crops and much-needed food crops and development initiatives to alleviate rural poverty. View document
11/01/2012
Mapping research systems in developing countries: Essential Bibliography: S&T in African countries
J. Mouton and L. LorenzenUniversity of Stellenbosch, South AfricaThis bibliography details key international publications and then lists those focusing on S&T development in specific African countries. Many of these relate to agricultural research and development, S&T policy and impact assessment.
11/01/2012
Evaluating impact of agricultural research and development: Future Harvest Research Centre approaches
P. Kristjanson, P.K. Thornton, B. Douthwaite, J. Watts, R.S. Reid and L. WithersInternational Livestock Research Institute, Nairobi, Kenya, International Institute for Tropical Agriculture, Ibadan, Nigeria and International Plant Genetic Resource Institute, Rome, ItalyPaper presented at the African Evaluation Association Conference, June 10-14, 2002, Nairobi. 2002One area that needs strong improvement is inclusion of environmental and socio-cultural impacts within economic/productivity impact assessments; stronger evaluation of trade-offs is also needed. The ‘building blocks’ of these integrated assessments often exist in Centres and NARS in the work of agro-ecologists and anthropologists, but this expertise needs to be strengthened and brought into mainstream economic/productivity efforts. Many of the assessments described in this paper are now being improved by expanding more traditional approaches through valuation of ecosystem goods and services. Socio-cultural impacts, however, are rarely brought into these assessments, even though these impacts (though improvement of social capital) may be crucial for reducing poverty. We also need to more explicitly acknowledge that processes and relationships are as important as tangible/material products/outputs. The poor can benefit from the development of a new high-yielding variety of a crop. They can also benefit, arguably in a more sustainable way, from a changed institutional environment that supports self-reliance in developing new locally-adapted varieties, through access to and application of skills and raw materials that are included in their livelihood assets. Achieving this change is a complex undertaking and its monitoring and evaluation will require tools and methods that reflect that complexity. Needless to say, this needs to be achieved without adding significantly to the cost of impact assessment.
11/01/2012
Science and Innovation for African Agricultural Value Chains: lessons learned in transfer of technologies to smallholder farmers in sub-Saharan Africa
New Growth InternationalMeridian Institute, Washington, D.C., USA2009This report comprises two broad segments: (1) A summary analysis on “do’s and don’ts” of technology development and deployment for smallholder farmers. The analytical framework guiding the analysis is presented in the next section. Features of successful innovations and a typology of such innovations are described in the next two sections, respectively. Key lessons related to policy, institutional, incentive, and scalability dimensions of agricultural innovation are then set out. A summary of the “do’s and don’ts” rounds out the analysis. (2) Six specific case studies of “successful” and “unsuccessful” technology introductions to illustrate key lessons learned in more detail. These case studies are not intended to be representative of innovations in Africa’s agricultural value chains. Rather, they are selected and developed aiming to expand on, highlight, and complement the findings in the summary analysis, given the guiding framework.
11/01/2012
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