DATASETS

× Food policy research plays a crucial role in guiding agricultural transformation in developing countries. To achieve food security goals, countries need to strengthen their capacity to conduct food policy research. Strong local policy research institutions help shaping evidence-based policymaking. Measuring national capacity for food policy research is important for identifying capacity gaps in food policy research and guiding the allocation of resources to fill those gaps. “Food policy research capacity” is defined as the ability to do socioeconomic or policy-related research in the areas of food, agriculture, nutrition, or natural resources. To measure this capacity, the International Food Policy Research Institute (IFPRI) has developed a set of indicators for the quantity and quality of policy research at the country level.
IFPRI created the Food Policy Research Capacity Indicators (FPRCI) database in 2010 and has since continued to expand and refine it. Data are currently collected for 33 countries; data for Myanmar was added in 2017. A consistent methodology is followed to enable a comparison of values across time and countries. The database was most recently updated with numbers for 2019.
Analysts/researchers counts the professionals employed at local organizations whose work involves food policy research or analysis. To introduce some uniformity, IFPRI also presents a modified quantification of this headcount: full-time equivalent analysts/researchers with PhD. To obtain an indicator of per capita food policy research capacity, this research capacity is then divided by the country’s rural population (full-time equivalent researchers per million rural residents). This helps to illustrate the impact of local food policy research in a country. This indicator was last updated in 2015.
The quality of a country’s food policy research capacity is estimated by tallying the number of relevant international publications in peer-reviewed journals over a five-year period. IFPRI views this as a reflection of the local enabling intellectual environment for food policy research. This indicator allows for comparison across countries, as it ensures an internationally accepted standard of quality for publications. The final indicator is derived by dividing the number of international publications by the number of full-time equivalent researchers with a PhD, providing a measure of productivity.

× Increasing the efficiency of agricultural production—getting more output from the same amount of resources—is critical for improving food security. To measure the efficiency of agricultural systems, we use total factor productivity (TFP). TFP is an indicator of how efficiently agricultural land, labor, capital, and materials (agricultural inputs) are used to produce a country’s crops and livestock (agricultural output)—it is calculated as the ratio of total agricultural output to total production inputs. When more output is produced from a constant amount of resources, meaning that resources are being used more efficiently, TFP increases. Measures of land and labor productivity—partial factor productivity (PFP) measures—are calculated as the ratio of total output to total agricultural area (land productivity) and to the number of economically active persons in agriculture (labor productivity). Because PFP measures are easy to estimate, they are often used to measure agricultural production performance. These measures normally show higher rates of growth than TFP, because growth in land and labor productivity can result not only from increases in TFP but also from a more intensive use of other inputs (such as fertilizer or machinery). Indicators of both TFP and PFP contribute to the understanding of agricultural systems needed for policy and investment decisions by allowing for comparisons across time and across countries and regions.
The data include estimates of TFP and land and labor productivity measures for developing countries and regions for three-sub-periods between 2000 and 2016. These use the most recent data on outputs and inputs from the Economic Research Service of the US Department of Agriculture (ERS-USDA), an internationally consistent and comparable dataset on production and input quantities built using data from the FAOSTAT database of the Food and Agriculture Organization of the United Nations (FAO), supplemented with data from national statistical sources (for more on data and methodology- https://www.ers.usda.gov/data-products/international-agricultural-productivity/ ).

× Increasing the efficiency of agricultural production—getting more output from the same amount of resources—is critical for improving food security. To measure the efficiency of agricultural systems, we use total factor productivity (TFP). TFP is an indicator of how efficiently agricultural land, labor, capital, and materials (agricultural inputs) are used to produce a country’s crops and livestock (agricultural output)—it is calculated as the ratio of total agricultural output to total production inputs. When more output is produced from a constant amount of resources, meaning that resources are being used more efficiently, TFP increases. Measures of land and labor productivity—partial factor productivity (PFP) measures—are calculated as the ratio of total output to total agricultural area (land productivity) and to the number of economically active persons in agriculture (labor productivity). Because PFP measures are easy to estimate, they are often used to measure agricultural production performance. These measures normally show higher rates of growth than TFP, because growth in land and labor productivity can result not only from increases in TFP but also from a more intensive use of other inputs (such as fertilizer or machinery). Indicators of both TFP and PFP contribute to the understanding of agricultural systems needed for policy and investment decisions by enabling comparisons across time and across countries and regions.

The data file provides estimates of IFPRI's TFP and PFP measures for developing countries for three-sub-periods between 1991 and 2014(1991-2000,2001-2010 and 2010-2014). These TFP and PFP estimates were generated using the most recent data from Economic Research Service of the United States Department of Agriculture (ERS-USDA), the FAOSTAT database of the Food and Agriculture Organization of the United Nations (FAO), and national statistical sources.

× Policy makers, analysts, and civil society face increasing challenges to reducing hunger and improving food security in a sustainable way. Modeling alternative future scenarios and assessing their outcomes can help inform policy choices. The International Food Policy Research Institute's IMPACT model is an integrated system of linked economic, climate, water, and crop models that allows for the exploration of such scenarios.

At IMPACT's core is a partial equilibrium, the multimarket economic model that simulates national and international agricultural markets. Links to climate, water, and crop models support the integrated study of changing environmental, biophysical, and socioeconomic trends, allowing for in-depth analysis of a variety of critical issues of interest to policy makers at national, regional, and global levels. IMPACT benefits from close interactions with scientists at all 15 CGIAR research center through the Global Futures and Strategic Foresight (GFSF) program, and with other leading global economic modeling efforts around the world through Agricultural Model Intercomparison and Improvement Project (AgMIP).

This dataset summarizes results from the latest IMPACT projections to 2030 and 2050. Results are included for production, consumption, and for the population at risk of hunger, by region and for selected countries. The projections are for two "baseline scenarios"-one considers the impacts of climate change, while the assumes no climate change (for comparison).

× Policymakers recognize that increased investment in agricultural research is key to increasing agricultural productivity. Despite this, many low- and middle-income countries struggle with capacity and funding constraints in their agricultural research systems.

Agricultural Science and Technology Indicators (ASTI), facilitated by the International Food Policy Research Institute (IFPRI) within the portfolio of the CGIAR Research Program on Policies, Institutions, and Markets, works with national, regional, and international partners to collect time series data on the funding, human resource capacity, and outputs of agricultural research in low- and middle-income countries. Based on this information, ASTI produces analysis, capacity-building tools, and outreach products to help facilitate policies for effective and efficient agricultural research.

“Agricultural research” includes government, higher education, and nonprofit agencies, but excludes the private for-profit sector. Total agricultural research spending includes salaries, operating and program costs, and capital investments for all agencies, excluding the private for-profit sector, involved in agricultural research in a country. Expenditures are adjusted for inflation and expressed in 2011 prices. Purchasing power parities (PPPs) measure the relative purchasing power of currencies across countries by eliminating national differences in pricing levels for a wide range of goods. PPPs are relatively stable over time, whereas exchange rates fluctuate considerably. In addition to looking at absolute levels of agricultural research investment and capacity, another way of comparing commitment to agricultural research is to measure research intensity—that is, total agricultural research spending as a percentage of agricultural output (AgGDP).

“Total agricultural researchers” (excluding the private for-profit sector) are reported in full-time equivalents (FTEs) to account for the proportion of time researchers actually spend on research activities. A critical mass of qualified agricultural researchers is crucial for implementing a viable research agenda, for effectively communicating with stakeholders, and for securing external funding. Therefore, it is important to look at the share of PhD-qualified researchers. Gender balance in agricultural research is important, given that women researchers offer different insights and perspectives that can help research agencies more effectively address the unique and pressing challenges of female farmers. Age imbalances among research staff should be minimized to ensure the continuity of future research as researchers retire.

× Policy makers, analysts, and civil society face increasing challenges to reducing hunger and improving food security in a sustainable way. Modeling alternative future scenarios and assessing their outcomes can help inform their choices. The International Food Policy Research Institute's IMPACT model is an integrated system of linked economic, climate, water, and crop models that allows for the exploration of such scenarios.

At IMPACT's core is a partial equilibrium, the multimarket economic model that simulates national and international agricultural markets. Links to climate, water, and crop models support the integrated study of changing environmental, biophysical, and socioeconomic trends, allowing for in-depth analysis of a variety of critical issues of interest to policy makers at national, regional, and global levels. IMPACT benefits from close interactions with scientists at all 15 CGIAR research center through the Global Futures and Strategic Foresight (GFSF) program, and with other leading global economic modeling efforts around the world through Agricultural Model Intercomparison and Improvement Project (AgMIP).

This dataset summarizes results from the latest IMPACT projections to 2030 and 2050. Results are included for production, consumption, and trade of major food commodity groups, by regions and country. The projections are for two "baseline scenarios"-one considers the impacts of climate change, while the assumes no climate change (for comparison).

× The Statistics on Public Expenditures for Economic Development (SPEED) database is a resource of the International Food Policy Research Institute (IFPRI) that contains information on agricultural and other sectoral public expenditures in 147 countries from 1980 to 2016.

Policymakers, researchers, and other stakeholders can use this robust database to examine both historical trends and the allocation of government resources across sectors. It also allows for comparisons with other countries within a region or at a similar level of development. Because the SPEED database covers many countries for a long time period, it allows analysts of government spending to examine national policy priorities, as reflected in the allocation of public expenditures, and track development goals and the cost-effectiveness of public spending both within and across countries.

Indicators reported in this data study include total agricultural expenditure, agricultural spending per capita, and the ratio of agricultural spending to the agricultural gross domestic product (GDP) for years 1995, 2000, and 2016. IFPRI researchers have compiled data from multiple sources, including the International Monetary Fund, World Bank, United Nations, and national governments, and conducted extensive data checks and adjustments to ensure consistent spending measurements over time that are free of exchange-rate fluctuations and currency denomination changes.

× Food policy research plays a crucial role in guiding the agricultural development of countries. To achieve food security goals, countries need to strengthen their capacity to conduct food policy research. Strong local policy research institutions help in shaping an evidence-based policy-making process. Measuring national capacity for food policy research is important for identifying capacity gaps in food policy research and guiding the allocation of resources to fill those gaps. Food policy research capacity is defined as any socioeconomic or policy-related research capacity in the area of food, agriculture, or natural resources. To measure this capacity, the International Food Policy Research Institute (IFPRI) developed a set of indicators of the quantity and quality of policy research at the country level.

IFPRI created a database for food policy research capacity in 2010 and has continued to expand and refine it. The data presented are currently collected for 33 countries; data for Myanmar were added in 2017. A consistent methodology is followed to enable comparison of values across time and countries. The database was most recently updated with numbers for 2018.

“Analysts/researchers” is a head count of professionals employed at local organizations whose work involves food policy research or analysis. To introduce some uniformity, IFPRI also presents a modified quantification of the headcount: "full-time equivalent analysts/researchers with the Ph.D. equivalent." To obtain an indicator of per capita food policy research capacity, this research capacity is then divided by the country’s rural population ("full-time equivalent researchers per million rural residents"). This helps to illustrate the impact of local food policy research in a country. This indicator was last updated in 2015.

The quality of a country’s food policy research capacity is estimated by tallying the number of relevant international publications in peer-reviewed journals over a five-year period. IFPRI views this as a reflection of the local enabling environment for food policy research. This indicator allows for comparison across countries, as it ensures an internationally accepted standard of quality for publications. The final indicator ("publications per full-time equivalent researcher") is derived by dividing the number of international publications by the number of full-time equivalent researchers with a Ph.D., providing a measure of productivity.

× Using a variety of inputs, IFPRI's Spatial Production Allocation Model (SPAM) uses a cross-entropy approach to make plausible estimates of crop distribution within disaggregated units. Moving the data from coarser units such as countries and sub-national provinces, to finer units such as grid cells, reveals spatial patterns of crop performance, creating a global gridscape at the confluence between geography and agricultural production systems. Improving spatial understanding of crop production systems allows policymakers and donors to better target agricultural and rural development policies and investments, increasing food security and growth with minimal environmental impacts

× The 2019 Statistics on Public Expenditures for Economic Development (SPEED) database contains public expenditure data for 164 countries from 1980 to 2017 for ten sectors: agriculture, communication, education, defense, health, mining, social protection, fuel and energy, transport, and transport and communication combined as one sector. Indicators reported include percentage of sector expenditure in total expenditure, percentage of total expenditure to total gross domestic product, and per capita sector and total expenditure in constant prices.

The data were compiled from multiple sources, including the International Monetary Fund, the World Bank, and national governments, and conducted extensive data checks and adjustments to ensure consistent spending measurements over time that are free of exchange-rate fluctuations and currency denomination changes.

SPEED is a user-friendly tool that could help governments to better allocate their resources to be consistent with their policy objectives, and citizens’ needs and priorities. Because of the wide coverage of time periods, countries, and sectors, it could help policymakers and researchers to better understand the linkages between different types of public expenditure and development. It could also help examine historical trends and compare those to other countries.