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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.

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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 R&D, 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.

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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 R&D spending in which it links its own dataset to secondary data sources.


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Why is ASTI’s coverage of the private sector so limited?

Agricultural R&D 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.

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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 R&D 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 R&D 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 R&D 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.

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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 R&D 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.

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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 R&D investment and capacity trends can be accurately estimated.

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