ASTI collects and processes its datasets according to the standard procedures and definitions developed by the Organisation for Economic Co-operation and Development (OECD) and the United Nations Educational, Science, and Cultural Organization (UNESCO), as described in the Frascati Manual, the Oslo Manual, and the Canberra Manual.
The Frascati Manual, originally published in 1963, has become the global standard for national and international organizations and has been revised numerous times. It should be noted, however, that the manual was devised by and for industrialized countries and hence is not always directly applicable to the developing world. As a result, ASTI has found it necessary to make some adjustments, particularly in the institutional classifications of agricultural research agencies.
Financial Years
ASTI collects actual spending data, not budgeted or projected data, in thousands of current local currency units. If the financial year differs from the calendar year, spending is reported in the calendar year that covers the majority of the financial year in question. For example, if the 2014/15 financial year begins April 1, 2014, all costs for that year are reported as 2014; if the financial year begins July 1, 2014, all costs for that year are reported as 2015.
Adjusting Expenditures for Inflation
Inflation is often a significant component of apparent growth in any series measured in local currency units. By adjusting for inflation, you uncover the real growth, if any. This involves revaluing every annual spending figure to a chosen year’s prices (a base year). The choice of base year does not affect percentage change calculations, but it will affect the absolute change figure. ASTI collects all its financial timeseries data in local currency units and converts these into constant prices using official World Bank GDP deflators. Currently, ASTI expresses its financial data in 2011 prices.
Purchasing Power Parity Exchange Rates
Comparing economic data across countries is a highly complex process due to important differences in price levels across countries and over time. ASTI collects data on national agricultural research spending in local currency units, which must then be converted into a common currency before national and regional comparisons can be made. Standard market exchange rates are the logical choice for conversions when measuring financial flows across countries; however, they are far from perfect when comparing economic data. Official exchange rates tend to understate the values of economies with relatively low price levels and overstate those with relatively high price levels. The largest components of a country’s agricultural research expenditures are staff salaries and local operating costs (rather than internationally traded capital investments). The wages of a field laborer or lab assistant at a research facility, for example, are much lower in India than in any European country, and locally made office furniture in Kenya is considerably cheaper than a similar set of furniture purchased in the United States.
At present, the preferred method for calculating the relative size of economies or other economic data, such as agricultural research spending, is purchasing power parity (PPP) conversion. PPP exchange rates measure the relative purchasing power of currencies for a wide range of goods and services, converting current GDP prices of individual countries into a common currency. PPP conversion offers two main advantages over market exchange rates: First, PPP exchange rates are relatively stable over time, whereas market exchange rates fluctuate considerably, and second, PPP exchange rates take nontraded goods and services into account, whereas market exchange rates are affected by traded goods and capital flows only. Many international organizations—such as the World Bank, the International Monetary Fund, and the Organisation for Economic Co-operation and Development—present their economic data in PPP dollars as well, and by maintaining consistency with these organizations ASTI is able to make broader (macro)economic comparisons.
Cost Categories
ASTI collects detailed expenditure data under three categories of costs as follows:
- Salaries, which include all remuneration-related expenditures, such as wages, pension/retirement fund contributions, insurance premiums, child education, housing allowances, and so on. This category also includes the cost of contract and other temporary work, such as long-term consultants and day laborers
- Operating and program expenditures, including water, electricity, gasoline/petrol, stationary, books, staff training. This category also includes the cost of maintaining buildings, cars, and equipment
- Capital investments, which includes expenditures related to the purchase or long-term rental (more than a year) of items such as equipment, furniture, computers, and vehicles. This category also includes the purchase or rental of land and buildings, as well as any associated depreciation costs or interest charges.
Funding Sources
ASTI collects data on all funding received within a given financial year, not budgeted or projected funding. Funding sources are categorized as follows:
- Core government allocations from the central government budget, such as through a ministry or the treasury for salaries or operating expenses
- Other government allocations, such as through competitive funding sources
- Loans from multilateral or bilateral donors
- Grants from multilateral or bilateral donors
- Allocations derived from commodity levies or producer organizations
- Revenues derived from the sale of goods and services
- Funding derived from other sources
Full-Time Equivalents (FTEs)
ASTI calculates its human resource and financial data in full-time equivalents or FTEs. This method takes into account the proportion of time researchers spend on research compared with other nonresearch activities. University employees, for example, spend the bulk of their time on teaching, administration, and student supervision rather than on research. As a result, four faculty members estimated to spend 25 percent of their time on research would individually represent 0.25 FTEs and collectively be counted as 1.0 FTE.
Sample surveys
ASTI’s primary data surveys differ according to the type of organization being surveyed. The following are downloadable examples of ASTI’s surveys in pdf format:
- Government and nonprofit organizations
Download Survey Form (Spreadsheet) - Higher education agencies
Download Survey Form (Spreadsheet) - Private, for-profit companies
Download Survey Form (Spreadsheet)
FAQ
Why is the ASTI database important, and who are the main users of ASTI data?
Quantitative information is fundamental to understanding the contribution of agricultural science and technology (S&T) to agricultural growth. Indicators derived from such information allow the performance, inputs, and outcomes of agricultural S&T systems to be measured, monitored, and benchmarked. These indicators assist S&T stakeholders in formulating policy, setting priorities, and undertaking strategic planning, monitoring, and evaluation. They also provide information to governments, policy research institutes, universities, and private-sector organizations involved in public debate on the state of agricultural S&T at national, regional, and international levels.
How does ASTI collect its data?
ASTI datasets are collected and processed using internationally accepted definitions and statistical procedures developed by the Organisation for Economic Co-operation and Development and the United Nations Educational, Science, and Cultural Organization. ASTI relies on its in-country partners to identify all agencies involved in agricultural research, to disseminate ASTI survey forms to each of them, and to coordinate the necessary followup. Three different survey forms were developed—one for government agencies and nonprofit institutions, one for university faculties and schools, and one for the private sector—to reflect fundamental differences in agency categories. The three forms have different sets of questions, and those for government agencies and nonprofit institutions request the most detail. The primary indicators are collected for a series of years, whereas the secondary indicators cover a single year only—usually the year prior to the year in which the benchmark survey is conducted. Over the years, the list of indicators has been amended and improved based on accumulating experience and consultations with partners.
Does ASTI collect data for high-income countries?
ASTI’s primary focus is low- and middle-income countries. Nevertheless, ASTI does maintain access to relevant developed-country datasets for comparative purposes. From time to time, ASTI publicizes updates on global agricultural research spending in which it links its own dataset to secondary data sources.
Why is ASTI’s coverage of the private sector so limited?
Agricultural research investment data for private-sector enterprises are very hard to come by. For reasons of confidentiality, many private companies are reluctant to provide information on their resources and investments in agricultural research. In addition, private research activities in many low- and middle-income countries are often small-scale and ad hoc, making it difficult to capture accurate information.
Why does ASTI report most of its financial data in purchasing power parity (PPP) dollars?
Comparing economic data across countries is a highly complex process due to important differences in price levels across countries. ASTI collects data on national agricultural research spending in local currency units, which must be converted into a common currency before national and regional comparisons can be made. Standard market exchange rates are the logical choice for conversions when measuring financial flows across countries; however, they are far from perfect currency converters for comparing economic data. Official exchange rates tend to understate the values of economies with relatively low price levels and overstate those with relatively high price levels. No fully satisfactory method has yet been devised to compare consumption or expenditure trends among countries.
At present, the preferred conversion method for calculating the relative size of economies or other economic data, such as agricultural research spending, is the purchasing power parity (PPP) index. PPPs measure the relative purchasing power of currencies for a wide range of goods and services, converting current GDP prices of individual countries into a common currency.
In addition, many international organizations—such as the World Bank, the International Monetary Fund, and the Organisation for Economic Co-operation and Development—present their economic data in PPP dollars, and by maintaining consistency with these organizations ASTI is able to make broader (macro)economic comparisons.
The largest components of a country’s agricultural research expenditures are staff salaries and local operating cost (rather than internationally traded capital investments). The wages of a field laborer or lab assistant at a research facility, for example, are much lower in India than in any European country, and locally made office furniture in Kenya is considerably cheaper than a similar set of furniture purchased in the United States. This being the case, PPP indexes offer two main advantages over market exchange rates. First, PPPs are relatively stable over time, whereas exchange rates fluctuate considerably. Second, PPP indexes take nontraded goods and services into account, whereas market exchange rates are affected by traded goods and capital flows only.
Why are ASTI data always a few years old?
ASTI data collection and analysis is highly labor intensive. Rather than relying on ready-made data from national government or other sources, ASTI publishes its country and regional data after a comprehensive survey process. In countries with large numbers of geographically dispersed agricultural research agencies, this can be a time-consuming and logistically challenging process. Time and cost factors also mean that ASTI can focus on only one or two regions at a time. Moreover, given ASTI's comprehensive data collection methods, a minimum one-year lag occurs before data is available for analysis.
Why are certain low- and middle-income countries excluded from the ASTI database?
ASTI aims to achieve good data coverage for each country and region, but this, unfortunately, is not always possible due to factors like political unrest, funding constraints, problems establishing in-country collaborators, and so on. Nevertheless, ASTI ensures that a representative sample of countries is included in regional survey rounds so that regional and global agricultural research investment and capacity trends can be accurately estimated.
What is ASTI’s current schedule for updating its dataset for a certain region or country?
Future updates for regions and countries depend on the availability of funding. Two consecutive data collection and analysis rounds in Sub-Saharan Africa and South Asia will be fully funded until 2018.
ASTI is working with various partners to secure funding to set up similar data compilation systems in Southeast Asia, Latin America, and the Middle East and North Africa as well. It also aims to secure funding to further develop its analytical capacity and activities.
