- Procedures and Definitions
- Financial Years
- Adjusting Expenditures for Inflation
- Purchasing Power Parity Exchange Rates
- Cost Categories
- Funding Sources
- Full-Time Equivalents (FTEs)
Procedures and Definitions
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 R&D agencies.
Financial Years2017/18, 2017, 2018
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 2017/18 financial year begins April 1, 2017, all costs for that year are reported as 2017; if the financial year begins July 1, 2017, all costs for that year are reported as 2018.
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 R&D 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 R&D 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 R&D 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.
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.
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 R&D 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.