- •Foreword
- •Table of Contents
- •1.1. A preliminary word to the user of R&D data
- •1.2. Coverage of the Manual and the uses of R&D statistics
- •Table 1.1. OECD methodological manuals
- •1.4. R&D input and output
- •1.5. R&D and related activities
- •1.5.1. Research and experimental development (R&D)
- •1.5.2. Scientific and technological activities (STA)
- •1.5.3. R&D and technological innovation
- •1.5.4. The identification of R&D in software, social sciences and service activities
- •1.5.5. R&D administration and other supporting activities
- •1.6. R&D in all fields of science and technology is covered
- •1.7. Measures of R&D inputs
- •1.7.1. R&D personnel
- •1.7.2. R&D expenditures
- •1.7.3. R&D facilities
- •1.7.4. National R&D efforts
- •1.9. Classification systems for R&D
- •1.9.1. Institutional classifications
- •1.9.2. Functional distribution
- •1.10. R&D surveys, reliability of data and international comparability
- •1.11. Government budget appropriations or outlays for R&D (GBAORD)
- •1.12. Topics of special interest
- •1.13. A final word to the user of R&D data
- •2.1. Research and experimental development (R&D)
- •2.2. Activities to be excluded from R&D
- •2.2.1. Education and training
- •2.2.2. Other related scientific and technological activities
- •2.2.3. Other industrial activities
- •2.2.4. Administration and other supporting activities
- •2.3. The boundaries of R&D
- •2.3.1. Criteria for distinguishing R&D from related activities
- •2.3.2. Problems at the borderline between R&D and education and training
- •Table 2.2. Borderline between R&D and education and training at ISCED level 6
- •2.3.3. Problems at the borderline between R&D and related scientific and technological activities
- •2.3.4. Problems at the borderline between R&D and other industrial activities
- •Table 2.3. Some cases at the borderline between R&D and other industrial activities
- •2.3.5. Problems at the borderline between R&D administration and indirect supporting activities
- •2.4.1. Identifying R&D in software development
- •2.4.2. Identifying R&D in the social sciences and humanities
- •2.4.3. Special problems for identifying R&D in service activities
- •3.1. The approach
- •3.2. The reporting unit and the statistical unit
- •3.2.1. The reporting unit
- •3.2.2. The statistical unit
- •3.3. Sectors
- •3.3.1. Reasons for sectoring
- •3.3.2. Choice of sectors
- •3.3.3. Problems of sectoring
- •3.4. Business enterprise sector
- •3.4.1. Coverage
- •3.4.2. The principal sector sub-classification
- •3.4.3. Other institutional sub-classifications
- •3.5. Government sector
- •3.5.1. Coverage
- •3.5.2. The principal sector sub-classification
- •3.5.3. Other institutional sub-classifications
- •3.6.1. Coverage
- •3.6.2. The principal sector sub-classification
- •Table 3.2. Fields of science and technology
- •3.6.3. Other institutional sub-classifications
- •3.7. Higher education sector
- •3.7.1. Coverage
- •3.7.2. The principal sector sub-classification
- •3.8. Abroad
- •3.8.1. Coverage
- •3.8.2. The principal sector sub-classification
- •3.8.3. Other institutional sub-classifications
- •3.8.4. Geographic area of origin or destination of funds
- •4.1. The approach
- •Table 4.1. Utility of functional distributions
- •4.2. Type of R&D
- •4.2.1. Use of distribution by type of R&D
- •4.2.2. The distribution list
- •4.2.3. Criteria for distinguishing between types of R&D
- •Table 4.2. The three types of research in the social sciences and humanities
- •4.3. Product fields
- •4.3.1. Use of distribution by product fields
- •4.3.2. The distribution list
- •4.3.3. Criteria for distribution
- •4.4. Fields of science and technology
- •4.4.1. Use of distribution by field of science and technology
- •4.4.2. The distribution list
- •4.4.3. The criteria for distribution
- •4.5. Socio-economic objectives
- •4.5.2. Minimum recommended breakdown
- •4.5.3. The distribution list
- •4.5.4. The criteria for distribution
- •5.1. Introduction
- •Table 5.1. R&D and indirect support activities
- •5.2. Coverage and definition of R&D personnel
- •5.2.1. Initial coverage
- •5.2.2. Categories of R&D personnel
- •5.2.3. Classification by occupation
- •5.2.4. Classification by level of formal qualification
- •5.2.5. Treatment of postgraduate students
- •5.3. Measurement and data collection
- •5.3.1. Introduction
- •5.3.2. Headcount data
- •5.3.3. Full-time equivalence (FTE) data
- •5.3.4. Recommended national aggregates and variables
- •5.3.5. Cross-classified data by occupation and qualification
- •Table 5.4. R&D personnel classified by occupation and by formal qualification
- •5.3.6. Regional data
- •6.1. Introduction
- •6.2. Intramural expenditures
- •6.2.1. Definition
- •6.2.2. Current costs
- •6.2.3. Capital expenditures
- •6.3. Sources of funds
- •6.3.1. Methods of measurement
- •6.3.2. Criteria for identifying flows of R&D funds
- •6.3.3. Identifying the sources of flows of R&D funds
- •6.4. Extramural expenditures
- •6.6. Regional distribution
- •6.7. National totals
- •6.7.1. Gross domestic expenditure on R&D (GERD)
- •Table 6.1. Gross domestic expenditure on R&D (GERD)
- •6.7.2. Gross national expenditure on R&D (GNERD)
- •Table 6.2. Gross national expenditure on R&D (GNERD)
- •7.1. Introduction
- •7.2. Scope of R&D surveys
- •7.3. Identifying target population and survey respondents
- •7.3.1. Business enterprise sector
- •7.3.2. Government sector
- •7.3.3. Private non-profit sector
- •7.3.4. Higher education sector
- •7.3.5. Hospitals
- •7.4. Working with respondents
- •7.4.2. Operational criteria
- •7.5. Estimation procedures
- •7.5.1. Unit and item non-response
- •7.5.2. Estimation procedures in the higher education sector
- •7.6. Reporting to the OECD or to other international organisations
- •8.1. Introduction
- •8.2. Relationship with other international standards
- •8.3. Sources of budgetary data for GBAORD
- •8.4. Coverage of R&D
- •8.4.1. Basic definition
- •8.4.2. Fields of science and technology
- •8.4.3. Identifying R&D
- •8.5. Definition of government
- •8.6. Coverage of government budget appropriations and outlays
- •8.6.1. Intramural and extramural expenditures
- •8.6.2. Funding and performer-based reporting
- •8.6.3. Budgetary funds
- •8.6.4. Direct and indirect funding
- •8.6.5. Types of expenditure
- •8.6.6. GBAORD going to R&D abroad
- •8.7.1. Criteria for distribution
- •8.7.2. Distribution of budgetary items
- •8.7.3. The distribution
- •8.7.4. Socio-economic objectives – SEO
- •Table 8.1. Standard key between NABS 1992 and previous OECD GBAORD objectives
- •Table 8.2. Standard key between NABS 1992 and Nordforsk GBAORD objectives
- •8.7.5. Principal areas of difficulty
- •8.8. Main differences between GBAORD and GERD data
- •8.8.1. General differences
- •8.8.2. GBAORD and government-financed GERD
- •8.8.3. GBAORD and GERD by socio-economic objectives
- •Table 1. Summary of sectors in the SNA and in the Frascati Manual
- •Table 2. Sectors and producers in the SNA
- •Table 5. Gross output and total intramural R&D
- •Table 1. Identifying health-related R&D in GBAORD
- •Table 2. Health-related R&D from performer-reported data: business enterprise sector
- •Table 3. Identifying health-related R&D by field of science and socio-economic objective
- •Table 2. Current classification of French, UK and US terminology in the Frascati Manual
- •Acronyms
- •Bibliography
- •Index by Paragraph Number
7 SURVEY METHODOLOGY AND PROCEDURES
serve as a valuable source of hypothetical examples and may help countries to develop more uniform classification practices.
7.5.Estimation procedures
463. In the process of compiling R&D statistics, various estimation procedures are used. Results from sample surveys have to be grossed up, using various methods, to correspond to the total target population. Especially in surveys of the business enterprise and government sectors, there are problems of unit and item non-response. In the higher education sector, statistics in most countries are based on a combination of surveys and estimation procedures.
7.5.1. Unit and item non-response
464.In practice, responses to R&D surveys are often incomplete, irrespective of the survey method used. Two types of missing values can be distinguished: item and unit non-responses. Unit non-response means that a reporting unit does not reply at all. The surveying institute may not be able to reach the reporting unit or the reporting unit may refuse to answer. For item non-response, a unit does answer but leaves at least one question blank or even, in an extreme case, leaves all questions but one blank.
465.Item and unit non-responses would be less of a problem if missing values were randomly distributed over all sampling units and all questions. In reality, however, both types of missing values are biased with respect to certain characteristics of the population and the questionnaire. Item nonresponse is more likely when the question is (or seems to be) difficult. Examples are the breakdown of R&D investments (land and buildings and equipment) or of R&D by type of R&D.
466.These non-responses clearly affect the comparability of the results of national and international R&D surveys. Appropriate methods to overcome this problem have to be developed and used. As different methods may lead to different results, some general recommendations should be followed. Otherwise, differences in results over time and/or among countries may arise from using different concepts to reduce the bias of item and unit nonresponses.
467.For practical as well as theoretical reasons, one recommended way to overcome the problem of item non-response is a group of methods called “imputation methods” for estimating missing values on the basis of additional information. The easiest method is to use the previous answer for the same enterprise. Another possibility is to use statistical techniques such as “hot decking”, using information from the same survey, or “cold decking”, using information from previous surveys.
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7 SURVEY METHODOLOGY AND PROCEDURES
468. In the case of unit non-response, past R&D data at firm level can be used to estimate the R&D expenditures for the same firm for the current period. The evolution of sales and or employment can be used to adapt the previous figures. In cases where no previous R&D data at firm level are available, as R&D is a metric variable correlated to a certain degree with sales, a recommended method is to use the relation between the sales of the total population and the sales of the realised sample for each cell in the sample. Another method is to use employment as a variable. This procedure is based on the assumption that the ratios of R&D to sales or R&D personnel to total personnel of responding and non-responding units are identical. This assumption can be tested through non-response analysis of a representative sample of non-responding units. Even if the assumption is wrong, the bias introduced can be disregarded as long as the fraction of non-responding units is fairly small.
7.5.2. Estimation procedures in the higher education sector
469.
It is recommended that information on R&D in this sector should be based on surveys of the perform ing units, supplemented, if necessary, by estimations.
470. Often over half of the funding of R&D is given as general university funds, not earmarked for research but given for the general functioning of the university. The R&D share of these funds is often unknown to the universities themselves. To determine which part should be devoted to R&D, a variety of methods have been used:
–Central estimates not based on empirical knowledge of how time is spent on different activities.
–Time-use surveys/studies concerning the distribution of time by various categories of personnel.
–Time-use surveys/studies based on researchers’ own evaluation of their working time.
471. From the time-use studies, research coefficients are derived for use in calculating full-time equivalents on R&D (FTEs) and R&D labour costs. Other R&D costs should primarily be estimated on the basis of purpose. For example, the acquisition of research equipment and expenditures for a research laboratory should be put under research, while maintenance of teaching facilities should be put under teaching. For expenditures not clearly attributable to either research or teaching, an estimate can be made using the research coefficients as the basis of calculation.
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