The problem noted in the previous post on how to measure productivity in the internet age is just one example of the problems with measuring most aspects of the economy in the, so-called, knowledge economy.
This is a problem that I have written a little on. There is a section on this problem, called “Mr Bean(counter) measures the economy”, in Oxley, Walker, Thorns and Wang (2008). It is written,
Much time and effort is expended by many national and international organisations in an attempt to measure the economy or economies of the world.
While the measuring of the “standard” economy is funny enough, when we move to the measurement of the “knowledge economy” measurement goes from the mildly humorous to the outright hilarious. Most attempts to measure, or even define, the information or knowledge economy border on the farcical: the movie version should be called, “Mr Bean(counter) Measures the Economy”.
There are substantial challenges to be overcome in any attempt to measure the knowledge societyeconomy. These are at both the theoretical and the method level. A more consistent set of definitions are required as are more robust measures that are derived from theory rather than from what is currently or conveniently available. In order to identify the size and composition of the KBE one inevitably faces the issue of quantifying its extent and composition. Economists and national statistical organisations are naturally drawn to the workhorse of the ‘System of National Accounts’ as a source of such data. Introduced during WWII as a measure of wartime production capacity, the change in Gross Domestic Product (GDP) has become widely used as a measure of economic growth. However, GDP has significant difficulties in interpretation and usage (especially as a measure of wellbeing) which has led to the development of both ‘satellite accounts’ – additions to the original system to handle issues such as the ‘tourism sector’; ‘transitional economies’ and the ‘not-for-profit sector’ and alternative measures for example, the Human Development Indicator and Gross National Happiness . GDP is simply a gross tally of products and services bought and sold, with no distinctions between transactions that add to wellbeing, and those that diminish it. It assumes that every monetary transaction adds to wellbeing, by definition. Organisations like the ABS and OECD have adopted certain implicitexplicit definitions, typically of the Information Economy-type, and mapped these ideas into a strong emphasis on impacts and consequences of ICTs. The website (http://www.oecd.org/sti/information-economy) for the OECD’s Information Economy Unit states that it:
“. . . examines the economic and social implications of the development, diffusion and use of ICTs, the Internet and e-business. It analyses ICT policy frameworks shaping economic growth productivity, employment and business performance. In particular, the Working Party on the Information Economy (WPIE) focuses on digital content, ICT diffusion to business, global value chains, ICT-enabled off shoring, ICT skills and employment and the publication of the OECD Information Technology Outlook.”
Furthermore, the OECD’s Working Party on Indicators for the Information Society has
“. . . agreed on a number of standards for measuring ICT. They cover the definition of industries producing ICT goods and services (the “ICT sector”), a classification for ICT goods, the definitions of electronic commerce and Internet transactions, and model questionnaires and methodologies for measuring ICT use and e-commerce by businesses, households and individuals. All the standards have been brought togetherin the 2005 publication, Guide to Measuring the Information Society . . . “ (http://www.oecd.org/document/22/0,3343,en_2649_201185_34508886_1_1_1_1, 00.html)
The whole emphasis is on ICTs. For example, the OECD’s “Guide to Measuring the Information Society” has chapter headings that show that their major concern is with ICTs. Chapter 2 covers ICT products; Chapter 3 deals with ICT infrastructure; Chapter 4 concerns ICT supply; Chapter 5 looks at ICT demand by businesses; while Chapter 6 covers ICT demand by households and individuals. As will be shown below several authors have discussed the requirements for, and problems with, the measurement of the knowledgeinformation economy. As noted above most of the data on which the measures of the knowledge economy are based comes from the national accounts of the various countries involved. This does raise the question as to whether or not the said accounts are suitably designed for this purpose. There are a number of authors who suggest that in fact the national accounts are not the appropriate vehicle for this task. Peter Howitt argues that:
“. . . the theoretical foundation on which national income accounting is based is one in which knowledge is fixed and common, where only prices and quantities of commodities need to be measured. Likewise, we have no generally accepted empirical measures of such key theoretical concepts as the stock of technological knowledge, human capital, the resource cost of knowledge acquisition, the rate of innovation or the rate of obsolescence of old knowledge” (Howitt 1996: 10).
Howitt goes on to make the case that because we can not measure correctly the input to and the output of, the creation and use of knowledge, our traditional measure of GDP and productivity give a misleading picture of the state of the economy. Howitt further claims that the failure to develop a separate investment account for knowledge, in much the same manner as we do for physical capital, results in much of the economy’s output being missed by the national income accounts.
In Carter (1996) six problems in measuring the knowledge economy are identified:
1) The properties of knowledge itself make measuring it difficult,
2) Qualitative changes in conventional goods: the knowledge component of a good or service can change making it difficult to evaluate their “levels of output” over time,
3) Changing boundaries of producing units: for firms within a knowledge economy, the boundaries between firms and markets are becoming harder to distinguish,
4) Changing externalities and the externalities of change: spillovers are increasingly important in an knowledge economy,
5) Distinguishing ‘meta-investments’ from the current account: some investments
are general purpose investments in the sense that they allow all employees to be more efficient,
6) Creative destruction and the “useful life” of capital: knowledge can become
obsolete very quickly and as it does so the value of the old stock drops to zero.
Carter argues that these issues result in it being problematic to measure knowledge at the level of the individual firm. This results in it being difficult to measure knowledge at the national level as well since the individual firms’ accounts are the basis for the aggregate statistics and thus any inaccuracies in the firms’ accounts will compromise the national accounts.
Haltiwanger and Jarmin (2000) examine the data requirement for the proper measurement of the information economy. They point out that changes are needed in the statistical accounts which countries use if we are to deal with the informationknowledge economy. They begin by noting that improved measurement of many “traditional” items in the national accounts is crucial if we are to understand fully Information Technology (IT’s) impact on the economy. It is only by relating changes in traditional measures such as productivity and wages to the quality and use of IT that a comprehensive assessment of IT’s economic impact can be made. For them, three main areas related to the information economy require attention:
1) The investigation of the impact of IT on key indicators of aggregate activity, such as productivity and living standards,
2) The impact of IT on labour markets and income distribution and
3) The impact of IT on firm and on industry structures.
Haltiwanger and Jarmin outline five areas where good data are needed:
1) Measures of the IT infrastructure,
2) Measures of e-commerce,
3) Measures of firm and industry organisation,
4) Demographic and labour market characteristics of individuals using IT, and
5) Price behaviour.
In Moulton (2000) the question is asked as to what improvements we can make to the measurement of the information economy. In Moulton’s view additional effort is needed on price indices and better concepts and measures of output are needed for financial and insurance services and other “hard-to-measure” services. Just as serious are the problems of measuring changes in real output and prices of the industries that intensively use computer services. In some cases output, even if defined, is not directly priced and sold but takes the form of implicit services which at best have to be indirectly measured and valued. How to do so is not obvious. In the information economy, additional problems arise. The provision of information is a service which in some situations is provided at little or no cost via media such as the web. Thus on the web there may be less of a connection between information provision and business sales. The dividing line between goods and services becomes fuzzier in the case of e-commerce. When Internet prices differ from those of brick-and-mortar stores do we need different price indices for the different outlets? Also the information economy may affect the growth of Business-to-Consumer sales, new business formation and in cross-border trade. Standard government surveys may not fully capture these phenomena. Meanwhile the availability of IT hardware and software results in the variety and nature of products being provided changing rapidly. Moulton also argues that the measures of the capital stock used need to be strengthened, especially for high-tech equipment. He notes that one issue with measuring the effects of IT on the economy is that IT enters the production process often in the form of capital equipment. Much of the data entering inventory and cost calculations are rather meagre and needs to be expanded to improve capital stock estimates. Yet another issue with the capital stock measure is that a number of the components of capital are not completely captured by current methods, an obvious example being intellectual property. Also research and development and other intellectual property should be treated as capital investment though they currently are not. In addition to all this Moulton argues that the increased importance of electronic commerce means that the economic surveys used to capture its effects need to be expanded and updated.
In Peter Howitt’s view there are four main measurement problems for the knowledge economy:
1) The “knowledge-input problem”,
2) The “knowledge-investment problem”,
3) The “quality improvement problem”,
4) The “obsolescence problem”.
To deal with these problems Howitt makes a call for better data. But it’s not clear that better data alone is the answer, to both Howitt’s problems and the other issues outlined here. Without a better theory of what the “knowledge economy” is and the use of this theory to guide changes to the whole national accounting framework, it is far from obvious that much improvement can be expected in the current situation.
One simple question is to which industry or industries andor sector or sectors of the economy can we tie knowledgeinformation production? When considering this question several problems arise. One is that the “technology” of information creation, transmission and communication pervades all human activities so cannot fit easily into the national accounts categories. It is language, art, shared thought, and so on. It is not just production of a given quantifiable commodity. Another issue is that because ICT exists along several different quantitative and qualitative dimensions production can not be added up. In addition if much of the knowledge in society is tacit, known only to individuals, then it may not be possible to measure in any meaningful way. If on the other hand knowledge is embedded in an organisation via organisational routines, see Becker (2004) for a review of this literature, then again it may not be measurable. Organisational routines may allow the knowledge of individual agents to be efficiently aggregated, much like markets aggregate information, even though no one person has a detailed understanding of the entire operation. In this sense, the organisation “possesses” knowledge which may not exist at the level of the individual member of the organisation. Indeed if, as Hayek can be interpreted as saying, much of the individual knowledge used by the organisation is tacit, it may not even be possible for one person to obtain the knowledge embodied in a large corporation.
There has also been considerable effort made to measure the informationknowledge society by national and international organisation such as UNESCO, the UN and the EU. That these efforts differ in their outcomes reflects, to a certain degree, different understandings of what the knowledge society is and thus different ways of modelling it. Some documents follow the process of knowledge production to sort out indicators, themes and tend to include measures on i) prerequisites for knowledge production (information infrastructure, knowledge, skill and human capital) and ii) knowledge production (R&D) itself. For example, in “Advancement of the Knowledge Society: Comparing Europe, the US and Japan” (European Foundation for the Improvement of Living and Working Conditions 2004), all indicators are sorted by whether they measure a prerequisite for the advancement of the knowledge society or whether they measure the outcomes of a knowledge society.
Other documents use different criteria to select indicators. The UN model initiated in “Understanding Knowledge Societies in Twenty Questions and Answers with the Index of Knowledge Societies” (Department of Economic and Social Affairs 2005), for example, categorises indicators along three dimensions: assets, advancement and foresightedness. When putting together its “Knowledge Society Barometer” (European Foundation for the Improvement of Living and Working Conditions 2004a), ‘The European Foundation for the Improvement of Living and Working Conditions’ considers notions such as information, knowledge, knowledge-value societies and sustainable development as parts of a ‘jigsaw puzzle’ which makes up their knowledge society framework. It seems to indicate that the knowledge society is viewed as a result of the integration of concerns of the previous conceptualisation of societies. Thus, the different frameworks also suggest the influence of organisational agendapriorities in defining the knowledge society.
Despite the difference in frameworks and indicators, there are some common themes. These include human capital, innovation, ICT development and the context dimension. The human capital theme includes variables on the levels of people’s skills and education which reflect the size of the pool of educated people. Included in the innovation theme are variables showing innovation investment, procedures, capacities and networks. There are diverse indicators under the ICT theme; yet, they can be categorised as either resources or access. The former refers to the information infrastructure while the latter is related to the accessibility of information in people’s life and work. The context dimension always includes variables on socio-economic, political and institutional conditions for knowledge production.
Obviously, these themes are crucial for measuring the knowledge society. However, these measures are not without their pitfalls. One basic problem for these measures is caused by the “knowledge problem”. In some cases, knowledge is understood partially and information and knowledge are treated as exchangeable terms. As a result, some documents focused entirely on measuring the information economy while talking about the knowledge economy and society. Other documents mentioned the difference between tacit and explicit knowledge, the distinction between information and knowledge, and thus, the distinction between the information society and the knowledge society while they failed to employ appropriate variables to reflect the distinctions, due to data availability. Among these documents, we do see a gradually shifting understanding and discourse on the knowledge society. For example, “UNESCO World Report: Towards Knowledge Societies” could be seen as a leading document in initiating the paradigm shift from the information society to the knowledge one. It acknowledges that “the idea of the information society is based on technological breakthroughs. The concept of knowledge societies encompasses much broader social, ethical and political dimensions” (UNESCO 2005: 17). At the same time, another document prepared by UNESCO on statistical challenges shows difficulties in identifying the relevant data within the existing measurement frameworks.
In addition, the knowledge problem raises other issues to do with the choice of indicators in each of the major themes. For example, human capital is measured according to people’s formal education and skills based on human capital approaches. This inevitably ignores people’s tacit knowledge and knowledge between people. There are a number of sociological studies which show that even within the economic domain people are not rational actors but their economic performance is signicantly affected by social, cultural and political structures in which they are embedded.
Similarly, the measurement of innovation in these documents seems to focus mainly on the production of scientific knowledge in laboratories. This is inconsistent with the Mode-2 knowledge production initiated by Gibbons (1994) in the knowledge society in which science and society co-evolve. Also the measurement of innovation fails to distinguish the role of inventions from that of innovations. Consequently, it is difficult to see how they can measure the economic value of innovation and at the same time attach a social value to it. Regarding ICTs, it seems that the widely accepted practice is to enumerate the physical infrastructure or, at best, measure access to information. There is a misunderstanding on the relationship between technology and human beings here. It is not technology but human beings and their interactions that constitute so-called society and its institutions. Thus, the function of ICTs is not only their capacity to provide additional new connections but also their potential for opening or closing forms of personal, social and economic capacities, relationships and power-plays (Dutton, 2004). Mansell and Wehn’s (1998) INEXSK approach would be a valuable endeavour to integrate the dimension of human beings, their knowledge and ICTs in the knowledge society measurement (Mansell and Wehn 1998).
Another problem with measures of the knowledge society is confusing the knowledge economy with the knowledge society. Generally, there are two kinds of documents on the measurement of the knowledge society. One group focuses on measuring the knowledge economy although they mention the concept of the knowledge society. The foci of the measurement are human capital, innovation and ICT development. A representative document is “Measuring a Knowledge-based Economy and Society: An Australian Framework” prepared by the Australian Bureau of Statistics. The document’s author claims that this framework
“does not attempt to cover all knowledge in the economy and society . . . [and] offer a comprehensive treatment of a knowledge-based society although it does address those social elements which potentially affect economic change or are affected by it” (Australian Bureau of Statistics 2002: 15)
Another group of documents considers both economic and technological features and social conditions and outcomes of the knowledge society. Two representative documents here would be, “Advancement of the Knowledge Society: Comparing Europe, the US and Japan” (European Foundation for the Improvement of Living and Working Conditions 2004) and “Knowledge Society Barometer” (European Foundation for the Improvement of Living and Working Conditions 2004a) published by the European Foundation for the Improvement of Living and Working Conditions. There are some variables reflecting social issues such as social inclusion, quality of life and gender equality in the two documents. However, they failed to see that both the economic and the social are equally important and integrated components in the measurement frameworks. Instead, the social is still treated as the ‘leftover’ after having identified ‘significant’ and ‘measurable’ components for national accounting.
In light of these issues it would seem that a necessary first step along the path towards the correct measurement of the knowledge societyeconomy would entail the development of a theory of the knowledge societyeconomy. Such a theory would tell us, among other things, what the knowledge economy is, how – if at all – the knowledge economyknowledge society differ, how they change and grow, and what the important measurable characteristics are. Based on this, a measurement framework could be developed to deal with, at least some of, the problems outlined above.
All the references in the above can be found in Oxley, Walker, Thorns and Wang (2008).
- Oxley, Les, Walker, Paul, Thorns, David, Wang, Hong (2008). ‘The knowledge economy/society: the latest example of “Measurement without theory”?’, The Journal of Philosophical Economics, II:1 , 20-54.