Advancing Concepts and Models for Measuring Innovation Proceedings of a Workshop (2017) / Chapter Skim
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2 Assessing Innovation Measurement
2 Assessing Innovation Measurement
Pages 9-24
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From page 9... ...
Where might administrative or big data become more prominent in meeting demand for new metrics? • What is the path forward for measuring innovation (a difficult measurement process)
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From page 10... ...
However, due to falling survey response rates and increasing costs, there is a growing sense that some data might be better collected using administrative and other passive methodologies that utilize data created as a matter of course for operational or other (nonresearch) purposes.
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One approach used for measuring innovative activities is the growth accounting framework, Hall explained. This framework is used for measuring R&D, which is only a subset of innovative activities in the National Income and Product Accounts (NIPAs)
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Hall concluded that to address gaps in data coverage, improving the ability to link sources, to generate timely data, and to produce information on capital for financing innovation (much of which is privately held) should be top priorities for the statistical agencies.
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Reiterating a point made by Hall, he noted that outdated measures are often maintained due to the appeal to researchers of consistent time series. When NCSES redesigned its R&D survey in the early 1990s to send to a much larger group of firms, the change required extra work to interpret trends spanning the pre- and post-change periods.
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From page 14... ...
Pointing to the challenges now being faced, Martin identified the need to conceptualize, define, and devise methods for measuring dark innovation. Some solutions may be facilitated by opportunities created in an era of big data.
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spoke to a range of issues: developing new indicators to capture the changing nature of innovation; policy and other uses of innovation data and indicators; and international comparisons. His approach to the challenge posed by the workshop -- to identify questions that cannot now be answered but could be with additional data that have a reasonable chance of being collected -- was to compare what can be done within the existing definition of innovation in the Oslo Manual with what could be done if changes were made to the definition and new data sources were then developed.4 The current definition in the Oslo Manual is as follows: An innovation is the implementation of a new or significantly improved product (good or service)
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The Community Innovation Survey (CIS) -- a series of harmonized surveys based on the Oslo Manual and fielded by national statistical offices throughout the European Union -- provides data on sources of informa
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From page 17... ...
and household sectors, in a way that makes it possible to examine how innovation links together economy wide. He suggested a new definition might take the following form: An innovation is the implementation of a new or significantly changed product or process.
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As he and Gault outlined, the OECDEurostat Oslo Manual embodies, as the outcome of a global consensusbuilding exercise, a number of measurement choices reflecting sectoral scope, perspective on the unit of interest, data sources, who is performing the measurement, and who benefits from the data. Galindo-Rueda's presentation focused on the role of international standards for measuring innovation and the scope for extending them in order to facilitate the international benchmarking of U.S.
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From page 19... ...
The Oslo Manual provides guidelines oriented toward the measurement of innovation through statistical surveys based on self-reported measures from respondents (who are typically managers within firms)
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From page 20... ...
Some of these measurement avenues could be the object in the future of standardization, but it is important to note that not all areas are equally mature for that purpose, bearing in mind the OECD criteria for endorsing statistical guidelines. In considering new kinds of data and guideline development, OECD will no doubt demand quality assessment along the lines described by Hall and Jaffe (2012)
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Price changes that are not explained by a weighted average of input costs also indicate multifactor productivity growth. The faster prices fall, the more rapid will be measured multifactor productivity growth.
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Once a revised semiconductor price measure is fed into the broad system of productivity measurement, the inferred rates of innovation change sharply. Sichel noted that the blue bars in Figure 2-2 are rates of multifactor productivity growth within the semiconductor sector by period, using official price measures.
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From page 23... ...
Even though the broad analytical framework is a bit of a black box, Sichel noted, it is important to try to make progress to improve the sorts of inferences about innovation made from that broad system. He suggested that to improve the accuracy of multifactor productivity measurement and, in turn, inferences about innovation in key sectors, work on improving measures of prices within key sectors needs to continue and to be incorporated into the measurement programs that feed into official statistics.
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From page 24... ...
Building on this exchange, Wesley Cohen (Duke University) pointed out that bridging the microlevel view often used by innovation researchers with the multifactor productivity view of macroeconomists reveals a need to measure additional multiple dimensions of productive processes.
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