~~Eurostat - ISTAT Seminar~~

~~Bologna, February 7, 1996~~

Introduction

This paper addresses two questions: What are the major forces shaping the modern economy ? What are the implications of those forces for statistics and statisticians ?

In short, my answers to those questions are as follows. The defining trend of the modern economy is the shift to the intangible. The economic landscape is no longer moulded by physical flows of material goods and products but by intangible streams of data, images and symbols. The source of economic value and wealth is no longer the production of material goods but the creation and manipulation of dematerialised content. We live in the intangible economy.

Non-linear and non-deterministic, the intangible economy raises a whole series of measurement issues. More fundamentally, it changes the role, the function, and the perception of economic measurement data. Because information is its key resource and output, the intangible economy is highly data-sensitive and intrinsically self-reflective. Official agencies no longer have the monopoly of economic data: a lively and diversified measurement and monitoring industry has emerged. Statisticians need to undertake a comprehensive appraisal of their business. Adapting to the new environment will require major changes in three key areas: conceptual foundations, modus operandi and temporal outlook.

Before developing these points in greater detail, let me make some remarks about the scope of the paper and our approach:

- Our perspective is economic. We focus on production, consumption and transaction processes and structures. We shall not discuss here political, social or cultural implications of the emergence of the intangible economy

- Our objective is not a formally rigorous demonstration backed by incontrovertible data. Rather, it is to outline a coherent conceptual framework, which sheds a new light on key economic trends and issues. We seek to stimulate constructive discussion of fundamental assumptions that underlie and guide the work of statisticians.

- This paper relies on a wide assortment of references and data, some of which could be considered somewhat unorthodox. It is however an incontrovertible fact that some of the best information about, and the most penetrating analysis of, the key economic trends come from such unconventional sources as management consultants, journalists, financial analysts or advertising agencies.

- This is not a futuristic “crystal ball” exercise. We shall not venture into scenarios about the world in 2010 or 2050. Forces that will shape the economy of the 21st Century are at work today and therefore we shall focus on the present.

EMergence of the intangible economy

Fundamental change: Incontrovertible yet misunderstood

We should begin by stating the obvious: the fundamental change in the economy has become conventional wisdom. Books, articles, speeches by economists, sociologists, management consultants and politicians about revolutionary change, new paradigms, earthshaking upheavals, megatrends, technotrends... are so numerous that they can no longer be counted let alone read and analysed in depth.

Three key trends

From this great variety of descriptions and analysis, we can highlight three key trends:

· The changing profile of employment and output structure. While the numbers may vary from country to country, the overall trend is definite: the share of industry and agriculture, whether in total output or in employment, has been falling steadily and now represents for instance less than forty percent of the total in the EU countries. Services represent the lion’s share of both employment and output and constitute the principal, for many countries the only, source of employment growth.

· Globalization. Foreign trade has been growing more rapidly than the world’s output for decades. The difference between trade and output growth rates decreased somewhat between 1971 and 1985 (3.7% vs. 3.2%) but since the mid-1980s it has increased again (5.9% for the former and 2.5% for the latter, between 1986 and 1996). The World Bank estimates that world trade will continue to grow at roughly twice the rate of world output [World Bank, 1995].

The international trade of final goods is accompanied by a massive crossborder deployment of production facilities, distribution networks, technologies and people. Global deployment of supply resources has been growing at an even higher rate. According to the World Bank, during the 1980s, total inward foreign direct investment (FDI) stock rose by 14 percent a year in high-income countries and by 11 percent in developing countries.

A key feature of globalization is the increased mobility of people, driven by increased demand for international labour and leisure. The mobility has created a huge travel and tourism (T&T) business. According to an association of leading T&T firms, the World Travel and Tourism Council (WTTC), it is the world’s largest industry. WTTC defines T&T as comprising five groups of activities: transportation, accommodation, catering/retail, recreation/culture and travel related services. With the assistance of WEFA, an economic consultancy, WTTC has estimated that in 1991 T&T generated over 10% of the world’s GDP (3 400 billion dollars), employed over 10% of the global labour force (204 million people) and accounted for 11% of gross investment [WTTC, 1994]. [1]

· The ubiquity of Information Technology. Information Technology (IT), which includes computers, telecommunications, and associated products and services (such as semiconductors or software), is recognised as a structural vector that influences all economic activities. According to Tom Stewart from Fortune Magazine, since 1991 we have entered the Information Age. That year, US capital investment in Information Technology exceeded investment in traditional machinery and equipment [Stewart, 1994a]. [2]

The impact of IT cannot be overestimated or overemphasised. The speed and the magnitude of technical progress are staggering and combine tremendous increases in quality with a continuing decline in prices. According to Gordon Moore, founder of Intel, the dominant supplier of microprocessors, the processing power of a microprocessor doubles every 18 months.[3] Thus, in 1980 a microprocessor chip had 30 000 transistors, in 1995, 3.3 millions. At the same time, the cost of hardware is falling at a rate of about 20% a year. A Pentium-based PC offers today several thousand times as much processing power as the mainframe of the 1970s, at a price that is less than 1% of 1% of the latter.

The development of IT has engendered a huge and rapidly growing new economic domain, whose global size is estimated at between 600 and 1100 billion dollars [EIT0, 1995, Banks, 1994]. [4] Furthermore, it profoundly affects all other economic sectors, no matter how traditional and well-established. IT is markedly different from other vector technologies, such as transportation and energy, which provided enabling infrastructure for the industrial revolution. Pervasive and ubiquitous, Information Technology cannot be reduced to infrastructure: it is simultaneously raw material, processing infrastructure, intermediate good and final product. It penetrates workspace, home and all other areas of social interaction. While transport and energy modified our physical capacity and our mechanical skills, IT touches these and more: it directly affects our mental and sensory capabilities [Solomon, 1989].

Inconclusive controversies

And yet, while there is broad agreement on the existence of these three trends, there is no real consensus on their magnitude, their underlying drivers, their structural causes and, more importantly, on their meaning. Actually, each trend has triggered fierce but rather inconclusive controversies.

For mainstream economists and statisticians, and for many politicians, the shift to services is a puzzling occurrence that is inconsistent with their basic view of the economy. This view, which has historical roots going all the way back to Adam Smith, postulates that the central activity of an economy and the source of wealth is the production of physical goods [Giarini, 1984]. How can technological progress and economic growth result in a shift to a relatively less attractive output and employment mix, weighted toward subsidiary and less productive activities ? There is a vocal and articulate school of thought which asserts that “manufacturing matters, “ that industry remains the true vector of the economy. To buttress their assertion, its proponents marshal data on the lower productivity of services and lower quality of service jobs [Cohen and Zysman, 1992; Taddei and Corniat, 1993]. Yet, other studies and data, based in particular on the recent employment trends in the US, suggest that services can generate high productivity and create high quality jobs [McKinsey, 1992, 1994].

The underlying problem is the tremendous heterogeneity of services. They comprise low paying, low productivity, labour-intensive and local activities such as restaurants as well as highly paid, high productivity, capital-intensive and global activities such as financial trading. Some services are immobile and non-tradable, others are extremely mobile and highly tradable. Certain services are subject to diseconomies of scale (household services), while others are the prime beneficiaries of economies of scale (telecommunications for instance). This heterogeneity makes it difficult to agree on a meaningful definition: a service can be an output, a production factor or an activity. According to an UK economist, Phedon Nicolaides [Nicolaides, 1989]:

" More intensely services are studied, the less certainty there is about how they can be defined and classified."

Service confusion is also a key element of controversies about globalization and Information Technology.

The conventional view of services contends that they are less tradable than physical goods. For instance, the French Statistical Institute, INSEE [INSEE, 1993], characterises services as

" generally not storable [and which] are produced in direct contact with the consumer."

This view is apparently corroborated by international trade statistics, based on IMF balance of payments data, showing that services represent some 20% of the world trade. For OECD, this a relatively stable share, even if market services (excluding government services) grow faster than merchandise trade [OECD, 1993].

This picture is highly misleading. There is compelling evidence that trade in services not only grows much more rapidly than goods but also constitutes the bloodline of globalization. Let us take just one example: international telecommunications. According to the International Telecommunications Union, the international voice traffic has been growing at some 16% a year and in 1992 represented 41 billion minutes, some 70 minutes per subscriber [ITU, 1994]. And the voice ~~communication~~ is only one aspect of international telecommunications. Based on anecdotal information, the data traffic, not only from the Internet but also from corporate data networks, is growing much more rapidly than voice. And let not forget the flood of global images from TV satellite broadcasting.

Finance is another quintessential service activity, yet it is excluded from international services trade data. According to British Invisibles, London-based trade group which promotes international activities of UK based financial institutions and business services, investment income flows approximately equal service trade flows. Taken together, in 1994 services and income flows represented over 35% of the total trade (vs. 32% in 1984) [British Invisibles, 1995].

And this is still an incomplete picture of the relative magnitude of global flows, as it does not take into account financial transactions. Those utterly dominate physical flows: the value of foreign currency trading alone was 1.3 trillion dollars in 1995 a day, more than sixty times greater than the daily physical trade volume of approximately 20 billion dollars. Furthermore, financial transactions experience explosive growth: between 1992 and 1995, the foreign currency trading market has grown by 47%, after growing by 42% between 1989 and 1992 [BIS, 1995]. Yet despite their size, visibility and persistence, global financial flows remain at the periphery of conventional economic measurement framework. Many economists and business decision makers tend to dismiss them as a speculative epiphenomenon, pointing out that only 5% of transactions are connected to “real” commercial operations undertaken by customers [Guth, 1993]. Others seek to introduce a distinction between the “good” investment flows and the “bad” portfolio flows, a rather futile effort, in light of an inextricable intertwining of the two categories. One of the most intensively watched and analysed economic activities, the international finance remains a block box.

Information Technology, on the other hand, appears as a black hole. The IT controversy revolves around the question: where has all the money gone ? This is what Robert Solow called a “computer paradox”: the price of computer equipment has been falling dramatically, businesses have invested massive amounts into computing equipment and yet, the results are not there [Griliches, 1992]. Actually, the period of massive IT investment in the 1980s has coincided with a significant productivity slowdown, which was particularly apparent in services [Baily et al., 1993]. In a 1991 study, based on Department of Commerce data, Stephen Roach, Chief Economist of Morgan Stanley, has calculated that the productivity in services during the 1980s has been growing at an annual rate of 0.5% per year, compared to 2.3% in manufacturing. Yet, during the same period the service sector invested massively in Information Technology, to the tune some 800 billion dollars [Roach, 1991].

The computer paradox prompted a huge variety of studies, many of which were based on detailed and custom-generated data at sectoral and firm levels. Yet, despite the wealth of evidence, opinions remain as polarised at ever. One group of analysts affirms that the computer paradox is simply a by-product of inadequate data and that detailed studies show a significant technology pay-off. Columbia Business School Professor Frank Lichtenberg [Lichtenberg, 1994] studied IT use in several hundred manufacturing and service industries and concluded that IT investments were highly effective. While they accounted for 10% of labour~~labor~~ costs and 15% of capital expenditures, they contributed over 20% of the output of the companies studied. Two MIT researchers, Erik Brynjolfsson and Lorin Hitt, have analysed the impact of IT investment in 400 large firms in the United States between 1987 and 1991. They calculated that the average return on investment was close to 70% [Brynjolfsson and Hitt, 1993]. A survey of French firms, carried by a French computer magazine 01 Informatique published in June 1993, also concluded that the IT impact was highly positive [01 Informatique, 1993]. After reviewing new data, Roach changed his views radically and in 1992 asserted that IT investment in services had significantly improved productivity [Roach, 1992; Gleckman, 1993].

On the other hand, proponents of the computer paradox persevere. In a heavily documented book published in 1995, Thomas Landauer argues that the paradox not only exists but will persist in the absence of radical changes in the way computers are designed and used [Landauer, 1995].

Measurement gap

A common thread runs across the three controversies: the weakness of data and the inadequacy of measurement methodologies. The problem is severe. Zvi Griliches of Harvard University, argues that the share of the economy which is measured by official statistics with a degree of accuracy is declining [Griliches, 1994]. Between 1947 and 1990, the fraction of the economy for which productivity data can be deemed reasonably accurate fell from close to 50% to about 30%. As a result:

“ Our ability to interpret changes in aggregate total factor productivity has declined, and major portions of actual technical change have eluded our measurement framework entirely. “

Furthermore, data weaknesses have been most pronounced in the areas and sectors which are most dynamic and most indicative of new trends such as Information Technology, new services or finance. This measurement gap contributes to the continuing inability of the economic profession to provide answers to such essential questions as:

- What are the determinants of long-term growth ? What is the relationship between growth and inflation ?

- What is the impact of the diffusion of Information Technology on productivity and employment ?

- What is the role of financial markets in the economy ?

Charges of data weaknesses and methodological inadequacy are not limited to official statistics. They are also levelled at financial accounting data and the underlying conceptual framework. The title of an influential book published in 1987 by two Harvard Business School professors, Thomas Johnson and Robert Kaplan, is explicit in this regard: “Relevance Lost, The Rise and Fall of Management Accounting.” [Johnson and Kaplan, 1987]. The main thesis of the book is that the traditional accrual-based systems are at best obsolete and often harmful. For Robert Kaplan, traditional measures for corporate performance are so misleading that they condemn managers to fly blind. In fast-moving sectors, such as computer software or entertainment, accounting statements have simply ceased to be a relevant indicator of business value and performance.

The existence of the measurement gap is not a recent discovery. Problems of official statistics are well known and have been extensively studied. Statisticians have constantly sought to improve the national accounts framework [SNA, 1993].

Nevertheless, the prevailing feeling is that the progress has been painfully slow and uneven. In his 1994 Presidential Address to the American Economic Association, Griliches [Griliches, 1994] asks an obvious question:

“ Why we don’t know more after years of research done by so many good people [?] What is it about our data and data acquisition structure, and possibly our intellectual framework, that prevents us from making more progress on this topic ?

For Griliches, the main problem is the quality of data, which stems from an inadequate attention to their generation methods and to the quality of the sources. But one has to wonder whether this is a sufficient explanation.

It can be argued that the measurement gap is provoked by a tension between the stable statistical apparatus and the dynamic economy. Statistics are meant to facilitate comparisons across space and time and therefore have to emphasise continuity: long time series, stable indices, rigid classifications, taxonomic approach... On the other hand, a major characteristic of the new economy is the permanent shifting of borders and boundaries. Consumption baskets, production functions and sectoral classifications are changing all the time, thus rendering major aggregates obsolete or even meaningless.

In our view, beyond data accuracy and tension arguments, the core measurement issue is the relevance of underlying conceptual models and assumptions. In their 1995 book on Statistics for 21^st century, two well-known economists-statisticians, Joseph Duncan and Andrew C. Gross [Duncan and Gross, 1995], declare:

“ As the 21^st Century approaches, it is increasingly clear that our current conceptual net, designed for earlier realities, does not cover current realities very well.”

The crucial assumptions of national accounts - focus on physical goods production and trade, choice of a nation as the main reference, stable sectoral groupings and classifications, neglect of non-material transborder flows - are grounded in a specific vision of the economy, which has not fundamentally changed since Adam Smith’s time and which postulates the production of physical goods as the main source of value.

These assumptions and the underlying vision can no longer be considered universally valid. While they may be seriously flawed, other conceptual approaches have not gained enough internal consistency and external recognition to provide a credible basis for the development of an alternative measurement framework. Two best known approaches are the service economy and the information economy. They share the same problem. Both terms are well known, to the point of becoming buzzwords. Yet, little progress has been made in making them conceptually more robust and operationally more relevant. They remain largely on the periphery of mainstream economics and statistics.

The service economy

The contrast is particularly striking for the service economy. On the one hand, after years of neglect, services have begun to gain political weight. They have now been officially recognised by statisticians and economists. International organisations such as the IMF, OECD and the World Bank have undertaken several projects to improve measurement of services, particularly in international trade [IMF, 1993, Arkell, 1995]. More importantly, services were a key item on the agenda of the Uruguay round, resulting in the adoption of General Agreement on Trade in Services (GATS), and constitute a priority for the World Trade Organization (WTO).

And yet, on the conceptual level, the service economy has made little progress. This lack of progress can be attributed to two crippling weaknesses:

- The first one is the original sin of a residual approach.

- The second, more~~second,more~~ recent and potentially more worrisome, is the loss of operational relevance.

Work on the service economy started in the early forties, with the seminal work by a prominent British economist, Collin Clark [Clark, 1940]. It was Clark who defined services as a residual category comprising all activities that cannot be classified as either manufacturing or agriculture. This definition entailed a structural heterogeneity of services, which became more pronounced as their range expanded. Such heterogeneity largely explains the difficulties of definition. In turn, these difficulties make it difficult to define boundaries and meaningful classifications. Existing service classifications lack economic intelligibility. In its 1991 survey of service business, INSEE acknowledges that it covers “heterogeneous activities, whose only common point is that they are neither industrial nor financial (banks and insurance).” [INSEE, 1993]. New services classifications, such as the one proposed by the IMF in its 5th edition of the Balance of Payment Manual, suffer from similar flaws [IMF, 1993]. For instance, telecommunications and computer services data appear in different categories, making it difficult to capture the development of telecommunications data networks, such as Internet, one of the most significant technological and economic trends of this turn of the century.

More ominously, product/service output or manufacturing/service activity distinctions appear increasingly irrelevant in the real economy. Services have been industrialised and service has become a key product component [Levitt, 1976, 1981]. Large industrial firms such as General Electric or General Motors generate more than a third of their revenues in financial services. Consumer electronics firms, Philips and Sony for instance, control leading audio-visual entertainment content producers. Acknowledging this interpenetration, Fortune magazine decided in 1995 to integrate its previously separate rankings of Fortune 500 Industrial and Fortune 500 services. It justified this decision by the obliteration of “once valid distinctions between industrial and service businesses and between services”[Stewart, 1995a].

The information economy

The lack of progress on the information economy is puzzling. Nobody would argue that the notion of information is becoming less relevant. Information can be quantified, stored and manipulated. Furthermore, a pioneering work has been carried out by Mark Porat in the mid 1970s seeking to integrate information activities in a statistical framework [Porat, 1977]. This work was published by the Department of Commerce and is widely known. Yet it has spawned little operational follow-up in the United States or elsewhere and thus remains a one-off effort.

One explanation is timing: Porat’s work came too early and therefore did not attract a constituency capable of pushing the work forward. This was aggravated by Porat’s outsider status (he was a Ph.D. student and later went on to other things, such as joining Apple and founding General Magic, an innovative software company).

There is however a more fundamental problem with the information economy. It is the schizophrenic way in which economists define information and approach the fundamental relationship between information and uncertainty. For classical economic theory, the role of information is to reduce uncertainty: more information means less uncertainty. Given its focus on physical goods as store of value, the theory does not address the issue of information as a tradable good. Yet, this is a primary concern for financial economists such as Charles Goodhart [Goodhart, 1975], who seek to understand the functioning of financial markets. From their perspective, the relationship needs to be inverted: it is uncertainty that determines the value of information. The higher the uncertainty, the higher the value of information. This view is consistent with the Communication Theory of Claude Shannon [Shannon and Weaver, 1947], which provides the theoretical underpinning for the development of modern telecommunications and informatics. This theory postulates that uncertainty creates information.

More generally, economists have difficulties coming to grips with the polymorphic and ubiquitous nature of information, simultaneously a good, a production asset and a market attribute.

The continuing spread of Information Technology, which raises a host of new economic issues, has given the information economy a new, if still fragile, momentum. It is fragile because it remains largely confined to academia. Major American universities such as University of California at Berkeley, Stanford, Columbia or MIT have created dedicated educational and research units. Current work on information economy tends to focus on specific issues: telecommunications network pricing or the use of information resources such as libraries [CERSI, 1995].[5]

Defining trend: shift to the intangible

The need for a new conceptual framework for the modern economy remains paramount. Such a framework should build upon the contributions of the service and information economy approaches but should be broader to encompass other significant trends such as the financial markets explosion.

We would like to propose an alternative framework, based on a single defining trend: the shift from tangible to intangible. The economic landscape of the present and future is no longer shaped by physical flows of material goods and products but by ethereal streams of data, images and symbols. The well-known three stages (Collin Clark) or three waves (Alvin Toffler) theories of economic evolution can thus be reformulated. At the core of the agricultural economy, there was a relationship between man, nature and natural products. The core relationship of the industrial economy was between man, machine and machine-created artificial objects. The intangible economy is structured around relationships between man and ideas and symbols. The source of economic value and wealth is no longer the production of material goods but the creation and manipulation of intangible content.

The shift to the ethereal is general and long-lasting. It affects all sectors and all aspects of economic life. According to Peter Drucker, the relative share of raw materials in the manufacturing output has been decreasing at an annual rate of about 1% a year since the end of World War II. Since 1950, the relative share of energy input has been declining at the same rate. Conversely, since the 1880s, the relative contribution of information and knowledge to manufacturing output has been growing at the same rate [Drucker, 1992a]. The result is that today, for instance, intangible inputs account for over 70% of the value added in the car production [CES, 1994]. Somewhat more surprisingly, 70% of the cost of producing butter are due to intangible factors [Blanc and Breton, 1994].

The intangible economy is not synonymous with information and knowledge. It is as much an economy of “useful” information and knowledge as it is of “futile” entertainment and distraction. One of its key features, for instance, is the explosive growth of entertainment activities, comprising toys, sporting goods, VCR equipment, records, books, newspapers and magazines, gambling, amusement parks, home computers, live entertainment and spectator sports. According to a lead Business Week article in March 1994, entertainment is “the growth industry of the 1990s.” Using Department of Commerce data, Business Week journalists estimated the 1993 US market size of the entertainment industry at $341 billion. In the US, entertainment employs more people than the automobile industry and in 1993 it accounted for 12% of all job creation [Mandel, Landler and Grover, 1994].

Although Information Technology is a cardinal vector of the intangible economy, it is not the only one. The emergence of the intangible economy owes at least as much to basic trends in consumer behaviour and in business environment. Secular shift toward higher relative demand for leisure, information and knowledge, on the one hand, and business innovations such as brand-driven competition and unbundling of hardware and software, on the other hand, played a major role in the advent of the intangible economy. The point here is not to argue a specific causality chain, an extremely arduous task, but rather to avoid a fallacy that the intangible economy is technology-push driven and its course technology-determined. Such a fallacy is quite widespread and leads many observers to equate intangible with digital. The intangible economy is thus seen as the triumph of bits over atoms [Negroponte, 1995].[6] This is a dangerous oversimplification. Not only are analogue technologies, such as radio or television, an integral part of the intangible economy. More importantly, the intangible economy transcends the opposition between bits and atoms the same way that quantum physics transcends the opposition between particles and waves. While the technological trend toward digitalisation is unmistakable, its economic and business impact remains unclear and the range of potential outcomes is wide open.

The intangible economy presents us with the “bicycle dilemma”: it is easier to practice than to explain.[G1] By definition, intangible phenomena are elusive. Not limited by physical constraints, they do not fit into standard economic categories. Their characteristics often defy common sense and intuition: they can simultaneously be durable and ephemeral, lumpy and infinitely divisible, unique and ubiquitous, scarce and abundant.

To understand the intangible economy, we propose to approach it from three different perspectives [Goldfinger, 1994]:

- Demand perspective: Intangible artefacts: final output for consumption.

- Supply perspective: Intangible assets, used by firms to establish and maintain their competitive position and survival. They include: the brand, the intellectual property, the human capital, Research and development information and know-how.

- Economic system perspective: Logic of dematerialisation: an interrelated set of trends and forces that affect all economic activities, changing the nature of economic transactions and market structures.

Intangible artefacts

Intangible artefacts include different forms of information and communication, high and low culture, audio-visual media, entertainment and leisure, without forgetting finance, the ultimate intangible.

All artefacts are joint products. They combine intangible content with physical support or a set of supports: song with a magnetic tape for an audiocassette; history and a building site for a classical monument. The use of the term “support” clearly indicates the value relationship: the content is more important than the support.

In the traditional economy, content and support were tightly linked, making them either unique or reproducible on a small-scale only. The development of technologies of storage and replication of content has loosened the links: the same content can now be easily and cheaply replicated and associated with various physical supports. Like a witch in the enchanted forest, artefacts with an identical content appear in various disguises and shapes: a news item can be printed, shown on television, spoken over a radio network, distributed via an on-line network and so on. A financial payment can be made in cash, by cheque, via card or wire transfer. Not only is the cost of replication very low, and getting lower over time, but the replication devices are readily available to the consumer. The dissociation of content and support has led to the proliferation of intangible artefacts in two ways. First, it has lifted capacity constraints limiting a large-scale consumption of intangibles. A theatrical show or a sports game could be only watched by those who could physically attend the theatre or the stadium. Today, television can multiply the number of spectators ad infinitum. One could argue that a stadium attendance and a TV watching of a sport event are two different artefacts, with different consumption, distribution and pricing characteristics. That is precisely the second dimension of proliferation: the same content provides a source for a family of artefacts: a book can be offered as a hardcover, as a paperback, as a CD-ROM or on-line. The ability to generate such families is what makes companies such as Disney successful: each film idea, Aladdin or Lion King, generates not only movies but also videos, park attractions, books, toys and other sources of revenues.[7]

The consumption of intangible artefacts displays specific and interrelated properties:

- It is joint (always consumed with other products, tangibles or intangibles).

- It is non-destructive: the same artefact can be consumed repetitively either by a same consumer or by a different one.

- It is non-subtractive (or non-rival): one’s consumption does not reduce anyone else’s consumption. In other terms, the opportunity cost of sharing is zero.

Intangibles such as information are often presented as a “public good,” such as fresh air or national defence, whose consumption cannot be limited to a single consumer and therefore is inherently collective [Olson, 1973]. While this is undoubtedly true, the “public good ” notion has a connotation that takes us away from the main focus of our argument. For instance, many economists define public goods as goods which, because of their inherent qualities, cannot be left to private suppliers and have to be produced by the public sector [Musgrave, 1959]. Thus, rather than to engage into an extraneous discussion about the role of the public sector, we prefer to use the term “shared good.”

Sharing in effect is the notable property of intangible artefacts. Although they are often produced for the use of a specific consumer, the exclusivity cannot be durably maintained. Sharing can be sequential or simultaneous. However, simultaneity in time does not mean simultaneity in space, as demonstrated by television or on-line networks. Intangible artefacts create their own space-time which lifts the constraints of geography.

On the other hand, sharing does not signify homogeneity. A same artefact can be consumed by very different groups, as anybody who has attended a football match in the UK can testify.

Sharing affects not only consumption but also production. Many intangible artefacts are produced through interaction between consumers and producers. Consumers not only often provide elements of content but they create their own combination of content as well as a content-support association. Facilitated by the low cost and the availability of replication technology and the content-support dissociation, such interaction is increasingly frequent and widespread.

Sharing also affects other aspects of intangible artefacts transactions such as the allocation of property rights. While a seller of a physical good loses his property rights to it, a seller of an intangible artefact continues to hold them. Sharing is thus a fundamental attribute of intellectual property.

The pervasiveness of sharing creates extensive externalities. Our willingness to consume and to pay is affected by consumption or non-consumption of others. Moreover, the traditional equality “purchase equals consumption," which is the cornerstone of consumer behaviour measurements in the market economy, is no longer universal. For intangible artefacts, purchase does not equal consumption ( how many people read all the books they buy ?) and consumption does not necessarily imply purchase: in newspapers or in broadcast television, the number of “free riders” far exceeds that of paying consumers.

Economic characteristics of intangible artefacts render conventional pricing and transaction mechanisms largely inadequate to capture their economic value. The two standard approaches are difficult to apply. Production costs cannot be used as guide for pricing as there is no proportionality between inputs and the output. Mass consumption does not imply mass production. Economies of scale for intangible artefacts are determined by consumption not by production. Yet the willingness to pay approach also has serious pitfalls, given the ease of replication and sharing and associated externalities. Another problem, which particularly affects informational artefacts, is what Joseph Stiglitz called the “infinite regress”: it is impossible to determine whether it is worthwhile to obtain a given piece of information without having this information [Stiglitz, 1985].

Traditionally, the pricing of intangibles was a function of convenience and was based on the support rather than on the content. Thus, the price of a book was determined by its thickness and the printing quality. This meant that pricing largely ignored the content variation: the price for an excellent book was the same as the price of a bad one.

The advance of dissociation created opportunities for unbundling: content can now be priced separately from the support. Price discrimination, based on the estimated value of content, becomes more common. Commercial on-line services, for instance, differentiate between standard and premium services, which are sold at higher prices. Yet, bundling has its advantages, in particular the simplicity of administration. It facilitates pricing of composite artefacts, comprising several types of content (multimedia software or amusement parks). Bundling also allows cross-subsidies between artefacts that are profitable and those which are less profitable but nevertheless desirable or essential for a full service offering. In financial services for instance, equity research is bundled into brokerage commissions. Thus, the range of intangibles pricing schemes is getting broader and more complex. Furthermore, depending on the supplier-consumer relationship, different pricing arrangements can apply to apparently similar artefacts~~artifacts~~. Computer software can be sold as a stand-alone product or it can bundled with hardware or be distributed as a shareware or freeware over a network [Dyson, 1992; Varlan, 1994, 1995].

And things are not getting any simpler. On-line networks and Internet provide a fascinating laboratory of various approaches to pricing through various combinations of selling, sharing and giving away. The debate about the respective merits of those approaches is quite lively. Some argue that the development of technologies such as metering, which measure the detailed use of a given software, makes feasible a fully variable usage-driven pricing [Cox, 1994]. Others plead in favour of a fixed access charge, independent of the actual use. Still another group considers that the ease of replication makes content practically free and therefore the only feasible approach is to charge for ancillary services [Dyson, 1995].

As pricing of intangibles focuses more on content, it highlights a fundamental issue: the inherent volatility of valuation. Although physical goods also show variation in price, the amplitude of changes is considerably larger for intangible artefacts. Their value is highly time-sensitive and can change dramatically: the same artefact can be valued very differently by the same user - financial information can be worth millions of dollars in the morning and nothing in the afternoon. Economists have grappled with this issue and came up with theoretical solutions. However, their implementation may be costly, due to the need for demand data, thus raising the issue of the trade-off between allocative efficiency and operational cost-effectiveness [Mitchell and Vogelsang, 1991].

V~~The v~~aluation problems have serious implications for ~~the~~ estimates of the consumption of intangible artefacts, resulting in all likelihood in underestimates~~ing~~ of its importance. For instance, ~~Most of the information consumed is free.~~ iIf one looks closely ~~for instance~~ at household entertainment expenditures, one can see discrepancies between time spent and monetary outlays. In 1992, each American spent on average 3 262 hours consuming different forms of entertainment, close to 9 hours a day [Veronis Suhler, 1994].Of these, the lion’s share, close to 5 hours a day, was spent on television and radio. Yet the bulk of this time (excluding cable television and pay-per view) was “free”, funded by advertising and thus did not show up as consumer expenditures.

Intangible assets

The shift to the ethereal is not limited to demand. The ascent of intangible artefacts is accompanied and stimulated on the supply side by the growing importance of intangible assets.

At first glance, intangible assets appear better known and better defined than intangible artefacts. Statisticians and accountants have long recognised that ~~the~~ capital accumulation and asset deployment means more than the acquisition of physical plant and equipment.

At the aggregate level, intangible investment comprises R&D, training, marketing, computer software and services. The French Statistical Institute (INSEE) in its 1992 National Accounts [INSEE, 1993] defines intangible investment as:

“ Those business expenditures, which develop the production capacity and enhance the value of the firm by creating a capital which could be depreciated or long-term tradable assets. ”

It is not surprising that in the intangible economy, the share of intangible investment is expanding relative to physical investment. According to INSEE, intangible investment represented 30% of the total investment in 1992 in France and was growing at a quicker rate than fixed assets. Partial evidence suggests that in other countries, such as the UK, the percentage is even higher [Norman, 1991, OECD, 1992]. Let us note again the paucity of data. Despite the recognised importance of intangible investment, the official investment statistics continue to report only the fixed asset accumulation. For instance, periodic announcements about an increase or fall in IT investments refer mainly to business purchases of computer equipment and include extremely partial data on software and services expenditures.

At the firm level, intangible assets are defined by Arthur Andersen [Arthur Andersen, 1992] as:

“…Resources controlled by the enterprise […] which possess the following attributes:

- non physical in nature

- capable of producing future economic net benefits

- protected legally or through de facto right.”

Arthur Andersen proposes a four parts classification of intangible assets: brands, intellectual property, publishing rights and licences. This is a commonly accepted classification and yet it is far from exhaustive. It excludes what many consider the most critical asset: ~~the~~ human capital, the quality of firm’s workforce. It also ignores the company culture, its accumulated knowledge (which is often informal and unprotected) and its network of relationships with customers and suppliers. These omissions have spurred the emergence of alternative approaches, such as the Intellectual Capital movement. According to its leading proponent, Leif Edvinsson from Skandia, Intellectual Capital is the sum of Human Capital and Structural Capital, which he defines as “all that is left when the staff has gone home, i.e. brand, customer databases, software systems “.” [Edvinsson, 1995; Stewart, 1994b].

The notion that the intangible assets are more important to business performance and survival than the physical assets is now conventional wisdom. The acknowledgement of their importance is more than a lip service or a fad. For consumer goods companies, Coca-Cola, Philip Morris, Nestle or Danone, brand management is the top priority guiding all their strategies. Brand is also essential for Information Technology companies such as Intel and Compaq, which are spending substantial sums to build it. Leading marketing specialists, such as David Aaker, consider brand an integral part of firm’s equity [Aaker, 1991]. Attempts are often made to quantify this “brand equity.” An American business monthly, Financial World, publishes each year a brands survey, which value them on the basis of their sales, profitability and growth potential. For leading brands such as Coca-Cola, Marlboro or Intel, this valuation largely exceeds the total balance sheet of parent companies.

A~~The a~~cknowledgement of the importance of intangible assets is not limited to brands. Intellectual property - patents, trademark, technological know-how - is considered as a critical competitive weapon, particularly in software, in electronics and in biotechnology. The control of intellectual property rights is often a matter of life and death for companies. It is through intellectual property litigation that Polaroid has driven Kodak out of instant photography market and AMD managed to preserve its foothold in microprocessors, despite Intel’s domination. In merger and acquisition transactions, the book value has become largely irrelevant to the company valuation, which is determined primarily by intangible assets [Petersens and Bjurstrom, 1991]. Thus, the apparently extravagant amount paid for media assets, such as~~particularly~~ ~~the~~ Hollywood studios or newspapers, can be explained by the crucial role attributed to brands, contents and publishing rights in the emerging realm of infotainment, combining information and entertainment [The Economist, 1994].

The problem of intangible assets is not the dearth of measurement. Rather, it is the consistency of approaches. While managers live and die by intangible assets, many accountants still refuse to recognise them and to include them in official accounts. Thus, the total amount of intangible assets in the published 1992 accounts of Coca Cola was 300 million dollars, while its brand was valued by Financial World at 35 billion dollars. The 1992 vValue of Intel brand, as measured by Financial World, wais more than 200% higher than the total value of its 1992 balance sheet, 8 billion dollars. Intel carries no intangibles on its balance sheet. Similarly, Microsoft considers ~~the~~ software development, its core competence, as an expense and writes it off in the year incurred. English football clubs do not include the value of their players in their accounts. Were they to do so, their aggregated value would increase by 250 million pounds, according to Touche Ross [Touche Ross, 1993].[8] In its 1994 Annual Report, Reuters [Reuters, 1995], the leading provider of electronic information, acknowledges that its balance sheet does not include the “following strengths and resources:

- Reuters independence […]

- goodwill attached to the Reuter name

- software and other intellectual property

- global databases of financial information

- integrated global organisation including skilled workforce.”[9]

Is it therefore surprising that the market value of Reuters representeds in 1994 and 1995 some 600% of its book value ?

The main reason for ~~the~~ non-inclusion is the lack of agreement among experts on how to treat intangible assets. Just as~~The same way that~~ intangible artefacts differ markedly from material goods, intangible assets are not like tangible assets.

First, they are highly heterogeneous, not only between categories but also within a given category: one hour of software programming does not equal another hour of programming. The rRevenue-generating capacity of an intangible asset is much more uncertain than that of a physical investment. When a plant adds another machine, it can easily quantify the potential increase in output. On the other hand, when a computer department hires another programmer, it cannot predict with certainty either the quantity or, more importantly, the quality of his/her contribution.

Intangible assets are difficult to separate, thus violating one of the cardinal rules of traditional asset valuation [OECD, 1992]. First, it is difficult to separate intangible assets from current expenditures. Whether an advertising expenditure can be classified as current expenditure or investment depends on its purpose. Similarly, not all training or software expenditures can be treated as investment.

More importantly, intangible assets often interact with each other, making it difficult to identify their separate contribution. When, in October 1992, Intel decided to give its new microprocessor a recognisable name, Pentium, rather than a number, 80586, it was because it wanted to establish a brand name and simultaneously to reinforce intellectual property protection.

Because intangible assets are, by definition, non-physical, they do not follow the classical progressive depreciation rules. Some assets depreciate very rapidly, others, like a good wine, appreciate with age, stills others follow non-linear and often unpredictable life cycles.

Thus traditional ways of valuing assets cannot be applied. The historical cost of acquiring or creating an intangible asset is largely irrelevant. Opportunity costs are difficult to apply in light of asset heterogeneity. A market or transaction-based approach also has serious pitfalls. For most intangible assets, markets are very narrow and extremely imperfect. This approach also raises the issue of separability. Market transactions only rarely concern just one category of intangible assets. Usually what is being bought or sold is a bundle of assets. Most frequently, the transaction concerns the control of the firm, in which case it is extremely difficult to isolate contributions of brands, intellectual property or publishing rights as distinct from the “pure” control premium paid by the acquirer. Finally, transaction-based values are subject to wide fluctuations.

In light of the shortcomings of cost-based and transaction-based valuation approaches, another approach is being recommended, which seeks to determine the economic value of an asset based on its cash generating potential, through the Discounted Cash Flow (DCF) method. A lLeading proponent of the economic value approach is Arthur Andersen which considers the DCF method “conceptually superior” to other approaches [Arthur Andersen, 1992]. The International Accounting Standards Committee also endorsed DCF in its 1994 Draft Statement of Principles on Intangible Assets [IASC, 1994].

However, the DCF method is far from universally accepted. Proponents of the transaction-based valuation have developed new approaches, which seek to~~aiming at~~ create~~ing~~ dedicated markets for some classes of intangible assets such as rights to operate telecommunication networks. The FCC auction of licences for a new category of mobile networks, PCS, in March 1995 is an example, deemed very successful, of such an approach [Kotelka, 1995]. Thus, as in the case of intangible artefacts, the range of methods used to value of intangible assets is getting larger, making the consensus on measurement of their value ever more elusive.

Dematerialisation logic

The impact of the intangible economy is not limited to intangible artefacts and assets. The logic of dematerialisation is pervasive and ubiquitous and affects all sectors and activities. It profoundly transforms economic relationships and interactions, the ways firms and markets are organised and transactions are carried out.

D~~The d~~ematerialisation logic is unsettling. It runs squarely against some of the key tenets of the conventional logic of economics. The conventional logic is concerned with scarcity, the dematerialisation logic with abundance. The former stresses equilibrium, the latter disequilibrium. Obsolescence, redundancy and volatility, which have been perceived in the past as pernicious epiphenomena, detrimental to growth and development, now constitute essential and necessary vectors which shape consumption patterns and supply resource deployment.

The three fundamental features of dematerialisation logic are: abundance, interpenetration and indeterminacy.

Abundance

Intangible economy is structurally abundant. Abundance, of course, is not a new phenomenon. The productive potential of the industrial economy is enormous and clearly exceeds the demand absorption capacity. However, physical goods are subject to physical decay and their consumption marks the beginning of the end of their economic life. Intangible artefacts, on the other hand, are not only extremely cheap to replicate but furthermore are not eliminated through consumption. Contrary to a popular belief, intangible does not automatically signify ephemeral. The lifecycle of popular intangible artefacts is considerably longer than that of material goods: we will forever read Shakespeare, listen to Mozart or watch Fellini. The intangible economy superimposes on the abundance of production the abundance of accumulation. The imbalance between supply and demand expands dramatically.

For intangible activities, whether they are entertainment or information related, the gap is so huge that it has created an “information overload’, also called “infoglut” or “infobog: ” the inability to absorb the torrential and continuously swelling flood of data, images, messages and transactions” [Tetzeli, 1994]. The on-going deregulation of markets for intangibles along withnd the technological evolution continue to aggravate the overload. For instance, the number of television channels in the European Union has increased from 40 in 1980 to 150 in 1994. Progress in transmission and distribution techniques makes it feasible to increase the number of channels to 500 or even more [Heilemann, 1994]. Moreover, the overload is self-perpetuating: to navigate through it we need catalogues, indexes, documentation, whose very proliferation calls for more cross-references, hypertext links and so on. Efficient management of infoglut requires more rather than less information. Information about information is a growing business.

Abundance and the resulting overload confront consumers with a dilemma. On the one hand, they want to take advantage of the increased choice of products and artefacts. On the other hand, they seek to minimise the cost of search.

In response to the first objective, new modes of consumption have emerged: zapping, surfing or browsing. They are characterised by a short attention span, latency, high frequency of switching and capriciousness. They blur the distinction between consumption and non-consumption, rendering pricing problems even more intractable.

The expanded range of output makes consumer choice more difficult, by continuously raising the cost of acquiring information about the output. To minimise this cost, the choice is increasingly determined by criteria other than product characteristics such as brand familiarity or mimicking and fashion [Bikchandani and al., 1993; Veblen, 1899]. These criteria are discretionary, generating rapid and massive shifts in demand, which are hard to anticipate. The result is an uneasy coexistence of stability, for products and artefacts~~artifacts~~ associated with a strong brand, and volatility for the others. The trend is clearly toward the latter.

B~~The b~~rand and fashion--driven demand forces suppliers to continuously renew their offerings and to actively manage their product portfolio. Product cycle is becoming shorter. Obsolescence is no longer an external constraint, it becomes an instrumental variable. In certain areas, such as personal computers, obsolescence leads to cannibalisation: new products are introduced to replace products that are still successful. Intel and Compaq are particularly skilful in the use of cannibalisation to keep their competitors off balance [Chreiki, 1995; Allen, 1992].

Wager economy

A fundamental implication of the supply imbalance is the increasing frequency of product failures. Flops are the rule, successes, an exception. In Hollywood, one movie is made out of a hundred scenarios under development, and only one in six movies released makes money. The flop rule is not limited to intangibles. In the pharmaceutical industry, only one in 4000 synthesised compounds ever makes it to market and only 30% of those recover their development costs [Moore, 1995]. In consumer goods industry, over 80% of new products launched in the United States fail within two years [Powers, 1993]. Furthermore, the cost of launching new products is rising rapidly: 50 million dollars for a movie, 250 millions for a new drug, several billions for a new car.

And yet, despite this dismal outlook, the pace of introduction of new products has not slackened. This has become a wager economy: higher and higher stakes against lower and lower odds.

The wager analogy helps to explain why most of companies continue to generate new products at a rapid rate. As long as a player remains at the table, he has a non-zero probability to recoup his losses. Only if he walks away, his loss becomes final. Also, what really matters is not so much how many times one plays but the overall magnitude of the gain (or loss).

There are of course other factors. One is the need for brand preservation. New products can be considered as visible signals of both brand continuity and renewal. Another factor, which ap~~plies~~ particularly applies to ~~the~~ intangible artefacts, is what can be called a “bookstore” effect. The best bookstore is the one that offers the widest choice. Furthermore, a well-stocked bookstore stimulates browsing which leads to greater book consumption. It is however not enough to have a wide assortment, it is also important to keep it current, hence the need for continuing introduction of new products. The bookstore effect explains for example while Reuters maintains 20 000 pages of data in its on-line financial information services, while the overwhelming majority of its clients use only four or five. The value of its databases is derived not only from particular pieces of information but also from the total inventory of data.

Management specialists have extensively studied companies such as Hewlett-Packard, Sony or 3M, which have been consistently successful in new product introduction, in order to discover their secrets. Their findings and recommendations are somewhat disappointing, bordering on the obvious: listen to the customer, have a long-term vision, use interdisciplinary teams...[Deschamps and Ranganath, 1995; Clark and Wheelwright, 1995]. Their main problem is the fallacy of composition: the experience of product development champions cannot be extended to all firms. Making product development generally more efficient will increase the supply of new products and thus further contribute to the imbalance and lower the odds of success. There is no escape from the rule of the wager economy.

If this view is accepted, the main product management challenge is not how to increase the probability of success but rather how to capitalise on it, how to transform hits into megahits. In this respect, the true champions are Hollywood studios such as Disney, which are extraordinarily adept in spinning out ancillary products - videotapes, computer games, toys, clothing, etc. - from their hit movies. These products generate, on ~~the~~ average, two to three times more revenues than ~~the~~ movie attendance [Goldman, 1995].

Structural abundance has also a major impact on the notion of capacity and the use of productive assets. Redundancy and excess capacity become the rule. For instance, according to Ian Valliance, chairman of British Telecom, telephone lines in the BT network lie idle 99.4% of the time [Valliance, 1995]. Despite this extremely low utilisation rate, BT is highly profitable with an operating margin of 20% and a 15% return on capital. While in the industrial economy, excess capacity is synonymous with costly inefficiency ~~and costliness~~, to be avoided, in the intangible economy it is widespread, functional and inexpensive. It is functional, even necessary, because it enables users and producers to cope with demand volatility and to accommodate the new consumption modes.

Excess capacity is inexpensive because in the intangible economy the key flows are that of information rather of physical goods. The economics of adding additional capacity for information flows are very different from that for physical goods handling. The latter is clearly subject to diminishing returns and thus its marginal costs are high. In the realm of Information Technology, there y might be diminishing returns at some point but they are unlikely to be reached in the foreseeable future. The long-term trend is for an exponential progression mode and for a dramatic fall in unit processing and transmission costs. The ongoing shift from 32 bit to 64 bit processors will increase the addressable memory ability by a factor of four billion. In telecommunications, fibre~~fiber~~ optic cable offers ten10 orders of magnitude greater bandwidth than copper wire with ten orders of magnitude lower bit-error rate. According to George Gilder [Gilder 1995], one of the keenest analysts of Information Technology trends,

“ Such feats plausible support the assertion that, as practical matter, the spectrum is free.”

Interpenetration

The second defining feature of the logic of dematerialisation is interpenetration.

The intangible economy undermines traditional frontiers and distinctions. Sectoral boundaries are crumbling: previously separate activities of telecommunication, informatics, electronics and audio-visual entertainment are now overlapping. Time-honoured distinctions between work and leisure, home and work-place, intermediate good and final output, consumer and producer, product and service, become blurred.

This is not a one-off effect of transition to a new environment but a fundamental trend. The iIntangible economy does not follow the rules of binary logic of exclusivity but that of fuzzy logic of overlapping. Not only are the boundaries porous and overlaying, they are unstable.

The interpenetration profoundly changes the nature of the firm and its relationships with the environment. Internal links, between firm and its employees, become weaker; external links, between firms and its suppliers, become stronger. While employees are told to work at home, suppliers are invited to work on premises.

Many of functions traditionally considered as central to the very existence of the firm are now subcontracted or outsourced. This leads to the advent of the “virtual corporation” [Davidow and Malone, 1992]. Nike, leader in sport shoes, does not manufacture any shoes. Nor does Dell, a leading supplier of computers, own any industrial plant. In the semi-conductor industry, many leading firms are “fabless, ”and subcontract their production [Rapaport and Halevi, 1991]. In computer services, outsourcing is one of the highest growth sectors.

This development suggests that the traditional rationale for the existence of the firm, articulated by Ronald Coase as, the minimisation of transaction costs, is no longer universally valid [Coase, 1937, Williamson and Winter, 1993]. Not only has Information Technology dramatically reduced transaction costs, but the intangible economy has altered the nature of the markets (see p. 132221 below) and enlarged the range of transaction mechanisms, blurring the well-known distinctions between markets, hierarchies and networks. An alternative and broader rationale for the firm needs to be developed, which would stress the brand umbrella, the intellectual property repository and the control of distribution channels ~~control~~ as key cohesion factors and functions of the firm.

Traditional inter-firm linkages have been governed by the subcontractor-production-distribution-service relationships, which can be modelled by input/output analysis to measure their economic impact. The intangible economy adds another linkage, which can be called the monitoring linkage. Abundance of products and services stimulates the development of activities, whose purpose is to monitor, evaluate and explain their characteristics and performance. Monitoring linkages are not captured by the traditional input/output analysis. Yet, their impact can be substantial. Th~~us, th~~e growth of personal computer industry has been accompanied and stimulated by the emergence of a specialised press and publishing. To take just one example, on the very day, August 24 1995, that Microsoft Windows 95 software was launched, some 450 books were available on the subject [Galloni, 1995]. Another example of the importance of monitoring linkages: in the press magazines sector, by far the largest segment is the TV-related press, which provides data about programs.

Another significant aspect of changing economic relationships is a shift in ~~the~~ market power and in the resulting ability to capture a larger share of the value chain. In the industrial economy, the central position in the value chain was that of a final product assembly, while the position of subcontractor was subordinate. Despite ~~that~~ the fact that Michelin contributed more to the development of the automobile, by facilitating road travel with maps, signs and guides, than Renault or Citroen, the latter gained greater market power: few people ever buy their cars in function of the brand of its tires. In the intangible economy, a subcontractor often assumes a dominant position. Thus, in personal computers, Intel and Microsoft, are in a considerably stronger position than IBM or Compaq, whicho control final assembly. Their dominance is due to their ability to establish intellectual property rights over key product components, in this instance microprocessor architecture and operating system software.

These changes in the value chain structure reflect a fundamental trend: the weight of the value chain is moving closer to the consumer. Peter Drucker [Drucker, 1992b] observed that

“ Power in the economies of developed countries is rapidly shifting from manufacturers to distributors and retailers.”

This trend has led to the emergence of “power retailers” such as Wal Mart in the US, Marks and Spencer in the UK, Galleries Lafayette in France or Ikea in Sweden. They are not only distribute~~ing~~ products made by others and decide which products are put on the scarce real estate of store shelves. They also set prices and become increasingly involved in product design. One visible sign of their increasing power is the development of own-label brands. According to Boston Consulting Group estimates [Reid, 1995], own-label brands represent close to 30% of total grocery sales in the UK, 25% in Germany, over 20% in France, and their share is growing.

The power shift toward distributors is clearly apparent in the pharmaceuticals industry. In 1972, drug manufacturers captured 67% of retail price, and the distributor, 33%. By 1992, the ratio has been reversed: 60% to the distributor, 40% to the manufacturer [Stewart, 1995b].

The transfer of market power does not stop at the check-out counter and frequently crosses the producer-consumer divide. In the personal computer industry, between 1986 and 1991, customers captured 49% of value added, against 31% for software and services suppliers and 20% for equipment manufacturers [McKinsey, 1992].

The intangible economy brings about a momentous change in the relationship between suppliers and consumers - the end of information asymmetry. More often than not, the customer knows as much about products and markets as the supplier. This entails not only substantial end-user price falls but also an unbundling of the production and assembly process, which becomes interactive. The unbundling is particularly apparent in the Information Technology area. Software applications and corporate data networks are often designed and built by customers, using inputs from different suppliers. Of course, they can also be created by suppliers with inputs from customers. “Make-or-buy” decisions are becoming more prevalent and more convoluted. The nature of competition changes: for computer services suppliers, their biggest competitors are not the other suppliers but their clients.

The changing nature of markets

Changes in the consumption mode, in the production function and, in interfirm relationships necessarily entail - and also reflect - a change in the nature of the markets. This change can be stated fairly simply: the main purpose of markets is no longer to support the trading of physical goods but to facilitate exchanges of intangibles. This does not mean that markets for physical goods have disappeared or became irrelevant. They are alive, well and growing. However, markets for intangibles are growing considerably faster. Furthermore, the evolution of physical goods markets is heavily influenced by the logic of intangibles trading.

Is not a notion of markets for intangibles an oxymoron ? In physical goods markets, it is easy to identify discrete transactions. Buyers and sellers are usually distinct. This is not universally true in markets for intangibles. There, transactions form a continuous process. For many artefacts, the distinction between buyers and sellers is tenuous. Academics exchanging data over Internet or financial institutions on a trading network are in turn producers and consumers of information. We have seen above the difficulties of establishing appropriate pricing mechanisms for intangibles. Give-aways, subsidies, cross-subsidies, indirect (third-party) payments or bundled prices are the a rule rather than an exception. The peculiar characteristics of intangibles lead many analysts to argue that they should not be traded through traditional markets. Ronald Coase, Nobel Prize laureate, attacked this argument and suggested that the market for ideas should be approached in the same manner as the market for goods [Coase, 1974]. We would like to suggest a variation of this suggestion: markets for goods should be treated as a special case of markets for intangibles.

Regardless of the arguments about their nature, markets for intangibles exist and are spreading rapidly. The most visible of those markets are financial markets. As we have seen above, they are enormous and growing explosively. Their explosion disturbs many economists and government officials. They are concerned about market incestuousness: the bulk of transactions is carried out between financial intermediaries rather than between these and non-financial clients. Furthermore, financial markets are highly volatile and their volatility appears to be contagious. Another disturbing fact is that the derivative markets, in futures and options, grow more rapidly than cash markets in the underlying instruments such as stocks and bonds [Scholtes, 1995].

Explaining financial markets by speculative urge and herd instinct may be popular but is not very helpful. Markets are too huge and too diverse and their growth has been too long-lasting to be dismissed as temporary aberrations. The financial explosion is information-driven. The globalization of the economy and the increasing variety of economic transactions have created greater uncertainty and thus generated a strong and continuous demand for information. Financial markets are a web of conduits for displaying and exchanging such information. Exchange of information, viewpoints, judgements and opinions has become their main function. Higher levels of risk and uncertainty also create a strong demand for information about the future. Derivative markets represent an aggregation of collective views about the future [Goldfinger, 1995].

Financial markets pose a major paradox. On the one hand, they represent a real-life incarnation of the theoretical model of a perfect market, liquid, information-rich and cost-effective. Ubiquitous, both local and global, accessible twenty-four hours a day, seven days a week, financial markets are large and very liquid. They supply an incredible wealth of information about the economy, both in the aggregate and in detail. Last but not the least, they are very cost-effective: transaction costs are low and falling.

At the same time, low transaction costs lead to excessive volume of transactions that generate noise rather than useful information. High volatility lead to serious distortions and create doubts about their signalling capacity. In the foreign exchange markets, “overshooting” and “undershooting” (extensive deviations from the rate levels calculated on the purchasing power parity basis) are endemic [De Grauve and Decuper, 1992; Curcio, R. And Goodhart, C, 1992]. Even Milton Friedman, an ardent defender of unfettered markets, acknowledged in April 95 that the mark was “extra-ordinarily overvalued," relative to the dollar [Friedman, 1995].

The vVolatility and the instability of financial markets, and more generally, of markets for intangibles are structural. They are due, first, to the fundamental characteristics of intangible artefacts and, second, to the anticipatory orientation of those markets.

Because intangibles are shared goods, there can be multiple sellers for a single buyer and vice versa. The rapid diffusion of information is conducive to herding: it is dangerous to go against market consensus, to be a single buyer when everyone else is selling or vice versa. Financial markets offer striking examples of herding. For instance, in February 1994, there was a huge crash in the US government bond market, which led to world-wide~~worl~~d~~wide~~ losses estimated at some 1.5 trillion dollars. Following a Federal Reserve decision to increase short term interest rates, long-term rates rose as well, thus lowering the price of long-term bonds. In the aftermath of the crash, Fortune Magazine carried a survey of portfolio managers to find out howho had correctly anticipated the evolution of interest rates and positioned their portfolio accordingly. Out of some 1000 managers surveyed, they found exactly four who were right [Ehrbar, 1994]. The persistence of herding suggests that the greater availability of information does not necessarily lead to a greater dispersion of views and positions. It may actually lead to greater homogeneity, which in turn breeds instability.

Instability is further stimulated by the anticipatory orientation of financial markets. Information about the past is widely known and certain, and its direct value is therefore low. Views about the future, less known and inherently uncertain, are more valuable and thus become the main objects of trading. This explains a paradoxical market behaviour. For instance, the value of ~~some~~ stocks often falls on good news, and ~~while the value of~~ ~~others~~ rises on bad news. The reason being that all ~~these~~ news are compared to prior expectations. If market analysts anticipate that a given company will grow at 50% rate over the next year, and the company achieves only a 40% rate, its stock price will fall when the actual growth rate is announced. And if market expects that another company will experience substantial losses, should the actual losses be lower than the market anticipation, the price of the losing company would rise.

As information about the future is irreducibly uncertain, anticipatory markets are inherently more volatile than the markets that aggregate past information. Thus, the derivative markets, which trade exclusively on anticipations, are more volatile than the cash markets. Also, because information about the future is more valuable than information about the past, demand for the former is relatively greater than ~~the~~ demand for the latter, hence the higher rate of growth of derivative markets. To the extent that the future-oriented markets are more information-rich than the past-oriented ones, the implication is clear: the higher the information content and efficiency of a market, the higher its volatility. This view, while radically different from that offered by traditional economic theory, appears consistent with oobserved market behaviour. It explains for instance not only the persistence of volatility but also the coexistence of volatility and liquidity. Traditional analysis of markets postulates that volatility limits liquidity. While it is true that at extreme levels ~~the~~ volatility leads to market breakdowns, such as the ones seen on the New York Stock Exchange and on the Chicago Mercantile Exchange on October 19, 1987, it can be argued that in the anticipatory markets the volatility is a necessary condition of ~~the~~ liquidity, a fundamental mechanism to cope with the information disequilibrium and uncertainty.

The iInstability of markets for intangibles is further compounded by the strategic behaviour of market participants. Not only do they constantly look for new information, they also seek to anticipate reactions of other participants. This goes well beyond what Keynes described as the “beauty contest” approach: in order to choose the most beautiful girl, a judge needs to consider not only his own preferences but also that of other judges [Keynes, 1936]. Sophisticated players are looking for second and third order derivatives and are not above a surreptitious manipulation of the signalling aspects of their transactions [Orléan, 1989, Thaler, 1991].

Financial markets generate a tremendous variety of price and value indications. Even if they suffer from serious distortions, they are more often right than wrong in their assessment. One can apply to the financial markets the Churchillian definition of democracy: it is the worst solution, except for all the others. Their evolution suggests that the notion of an intrinsic and stable value is largely meaningless in the intangible economy. Value is transaction-dependant and is determined not only by the buyer’s willingness to pay ~~of the buyer~~ but also by the market characteristics and the pricing mechanisms used. The industrial economy introduced price uniformity and stability. The intangible economy favours price differentiation and variability. This trend will be further accentuated by the on-going development of electronic markets and the growing sophistication of pricing mechanisms.

Indeterminacy

The logic of dematerialisation is not deterministic. It does not point to a single optimal trajectory. It actually widens the range of choices and alternatives. Instability and volatility which govern the demand for intangibles become pervasive and affect all aspects of the economy, national competitiveness, business hierarchies and market structures, prompting frequent and massive reversals of judgements and opinions.

In the early 1990s, the conventional wisdom was that the competitiveness of the United States was declining and that of Japan, ~~was~~ increasing. This was, for instance, the verdict of the widely publicised World Competitiveness Report, compiled by the International Institute for Management Development (IMD) in Lausanne. By 1994, the consensus has changed radically: the US is now considered as having the most competitive economy in the world, while Japan is losing ground [IMD, 1992; IMD, 1995].

The hierarchy upheaval is even more dramatic in business. Market dominance can be achieved with unprecedented speed and lost with equal if not greater rapidity, particularly in ~~the~~ fast growing sectors such as telecommunications and computers. How many specialists would subscribe today to a view published in 1984 by Stephan McLennan [McLennan, 1984], one of the most respected industry analysts on the Wall Street, in a book on The Coming Computer Industry Shake-Out:

“ In the world of computers, as in horse racing, there is no such things as a sure thing. But IBM is about as close as we are going to get.” [10]

Out of 500 American corporations that comprised the Fortune 500 ranking in 1980, 40% have disappeared by 1992.

Upheavals in the market place are accompanied by radical reversals of opinions among business watchers. In 1993, business press compared big multinational companies with dinosaurs, condemned to inexorable decline [Solomon, 1993; Loomis, 1993]. In 1995, the Economist headlined its survey of multinationals with a telling title “Big is back”[Wooldridge, 1995]. Similarly, the theme of the emergence of power retailers has now been succeeded by prophecies of death of traditional retailing [Sherman, 1994].

Instability and volatility are not only sequential but also simultaneous. The intangible economy is moulded by contradictory cross-currents: globalization~~globali~~z~~ation~~ and localisation~~localization~~, concentration and fragmentation, vertical integration and horizontal competition. Thus, while the economy is becoming more integrated and more transnational, the political system heads in the opposite directions. The number of new countries has increased in the last fifty years, with twenty having been born between 1989 and 1995. This is what John Naisbitt refers to as a “Global Paradox.” [Naisbitt, 1994; Alesina and Spolane, 1995].

C~~The c~~ontradictory crosscurrents are the strongest in the business area. At times, it appears that the guiding principle of business strategies and economic policy making is the schizophrenia. On the one hand, the competition has never been keener; the fight for market share and shelf space, more brutal; the rivalry between firms, more intense. At the same time, alliances proliferate in all sectors and all areas and management theorists extol the virtues of co-operation and sharing [Badaracco, 1991; Konsynski and McFadden, 1990]. This coexistence of competition and co-operation has prompted Ray Noorda, the founder of Novell, the leading provider of networking software, to coin a new term - the “coopetition.”

Nowhere is ~~the~~ strategic schizophrenia stronger than in the emerging realm of multimedia. There, at least three radically different approaches coexist: “oligopolistic convergence”, “oligopolistic specialisation” and “Internet proliferation”.

The ” oligopolistic convergence” is based on the view that in the new environment, which is being created by the convergence of information, communication and entertainment, economies of scale and vertical integration are the key success factors. Only the biggest companies, controlling various elements of the value chain - programming, distribution, marketing - and all ~~the~~ facets of the multimedia spectrum - movies, TV, records, books, computer software... -, will survive. When the dust settles, the multimedia domain will be ruled by very few, global, vertically and horizontally integrated players. This approach has provided the rationale for the spectacular media mergers such as Disney-ABC and Time Warner - Turner transactions.

“Oligopolistic specialisation” also assumes economies of scale and market concentration. Its proponents are sceptical however about the speed and economic viability of convergence. They view vertical integration, whether between hardware and software or between content and distribution, as somewhat of a mixed blessing, hypothetical virtues of synergy being largely counterbalanced by the heavy administrative overhead and persistent conflicts of interest between different businesses. Under this approach, the key success factor is the ability to focus and to concentrate resources on chosen market segments and customer groups. The September 1995 decision by ATT, the perennial paragon of a vertically integrated information company, to split itself into three parts is an example of a strategy, guided by ~~the~~ oligopolistic specialisation.

The “Internet proliferation” approach assumes that fragmentation will be the dominant feature of the Information Technology landscape. Wide availability of technology and information maintains low barriers to entry and facilitates unbundling. Networks proliferate and interactivity reigns supreme. This entails a fluid market structure with a high degree of specialisation and segmentation, and a numerous and diversified cast of players. Negroponte sees “the monopolistic media empires dissolving into an array of cottage industries“ [Negroponte, 1995]. While the oligopolistic models continue to rule the corporate boardroom, the Internet model has captured ~~the~~ ~~popular~~ imagination foot soldiers in the Information war trenches, and the interest of fund managers, as evidenced by the success of public offerings of Internet companies such as Netscape {in August 95} and their (at least initially) astronomical valuation: three Internet upstarts, Raptor Systems, VocalTec and CyberCash, whose combined 1995 revenues were about 5 million dollars had attained an initial market capitalisation of 850 million dollars ! .

It is difficult to predict which approach will prevail. The empirical evidence is inconclusive. Data can be marshalled to support each approach. Thus, certain segments of Information Technology are utterly dominated by a single supplier: Microsoft and Novell in personal computer software, Intel in microprocessors. Other segments, such as personal computer manufacturing, display a substantial number of players and intense competition. Many specialists point at a strong growth of mergers and acquisitions as ~~the~~ evidence of consolidation and concentration. Yet, the robust pace of Initial Public Offerings (IPO), in the US and in the UK in particular, and of venture capital financings indicates a continuing inflow of newcomers. Since the early 1990s, both mergers and acquisitions and IPO activities are at record levels. Furthermore in this area, the past is a very imperfect guide to the future: the shifts in technology and in consumer preferences can be sudden and sweeping, creating threats for existing leaders and opportunities for audacious entrants. The shifts are also hard to predict: very few experts have anticipated the extent, the speed and the impact of the Internet explosion.

Behind the strategic schizophrenia and the inconclusiveness of data lies a more fundamental and structural ambivalence. At the core of the intangible economy, contradictory forces are at work: economies of scale and increasing returns, on the one hand, value shift to the consumer and market upheaval, on the other hand. These forces will continue to coexist and to interact, thus maintaining ~~the~~ indeterminacy.

Contrary to the industrial economy, economies of scale in the production of intangible artefacts are limited: adding twice as many programmers to a software development project is unlikely to cut in half its completion time or cost, it may actually double it. However, economies of scale in distribution can be significant, due to a combination of high fixed costs of creating the distribution infrastructure and low variable costs of using it. Economies of scale in distribution ~~The existence of economies of scale in distribution~~ arehas ~~been~~ a major factor in the downstream value chain shift. They It also constitutes the main rationale for the wave of mergers in sectors such as banking, retailing and media, whose prime objective. is to create large and ubiquitous distribution networks [Wysocki, 1995].

The impact of economies of scale in distribution is accentuated by the consumption characteristics of intangible artefacts (see pp.11,18 above). Thus the bookstore effect favours a supplier concentration as consumers tend to use a supplier with a largest choice. Sharing leads to network externalities: the value of a given artefact is enhanced by the number of other consumers using it. Large networks tend to grow larger, at the expense of smaller networks. The jJoint~~ness~~ and non-destructive (repetitive)~~cumulative~~ nature of intangibles’ consumption entails what Brian Arthur, Stanford economist and a leading proponent of the increasing returns theory, calls the “lock-in” effect: once a user is committed to a given technology and accumulates artefacts which depend on it, the cost of switching becomes very high. A supplier who manages to impose his technological standard, whether it is VHS for Matsushita or Windows for Microsoft, locks in consumers and grabs practically a 100% market share. For Brian Arthur, the combination of lock-in effect and increasing returns not only leads to monopolistic concentration but also threatens technological progress. This implies the need for government intervention, such the US Department of Justice restrictions on the activities of Microsoft [Arthur, 1995]. ~~{Winner take all society proponents also argue for government intervention].~~

And yet, there are clearly countervailing forces at work. The cardinal one is the shift of the market power to the consumer. Wider availability of information and lower transaction costs eliminate information asymmetry and drastically lowers the search costs. It also reduces the incentive for vertical integration [Huber, 1992]. It is the consumer who acquires the integration capability. {}The rapid pace of technological innovation and the capriciousness of demand limits the “lock-in” effect and favours the emergence of new product families and market segments, which offers scope for new entrants and for the supplier hierarchy reversal. Ultimately, the reduction of supplier monopoly power comes not from an increased competition in the existing segments or from government intervention but from the creation of new markets. So far, the intangible economy has demonstrated an enormous capacity to sustain innovation and generate new markets. There is no reason to doubt its continuing ability to do so. The intangible economy is still in its infancy and has not even begun to fulfil its potential.

Implications for Statistics and statisticians

Changing Measurement data dynamics

Self-reflectiveness

The intangible economy fundamentally changes the role, function, position and perception of measurement data. These are no longer external ~~and~~, neutral or, independent from the facts they calibrate. Because information is its key resource and output, the intangible economy is highly data-sensitive and intrinsically self-reflective [Braman, 1995]. It continuously monitors and measures its own behaviour. It functions in conformity with the Heisenberg uncertainty principle: the very act of observing and measuring changes the measured phenomenon. Thus, the publication of economic data triggers rapid and often massive reactions of economic agents. Moreover, these adjust their behaviour not only in reaction to ~~the~~ already available data but in anticipation of ~~the~~ future data. This kind of attitude may render data less reliable and relevant. It particularly affects financial data such as the monetary growth aggregates, M1, M2 or M3. As soon as authorities announce a monetary aggregate target, financial intermediaries adopt strategies that minimise its pertinence and causality. Alan Greenspan, the chairman of Federal Reserve Board openly recognised in July 1993 that, because of these strategies, monetary aggregates could no longer be considered as dependable signals of future economic growth and price inflation [Ullmann, 1993].

Competition

Increased data sensitivity has triggered the development of a lively measurement and monitoring industry. This industry comprises a variety of actors: private suppliers offering a broad range of information such as Dun & Bradstreet or Reuters, private suppliers of specialised information such as IDG or Dataquest (IT domain data), subsidiaries of advertising agencies (Zenith Media or WPP), research departments of or financial institutions ~~(Veronis Suhler, Broadview Associates)~~, management consultants, sectoral associations such as the World Travel and Tourism Council (WTTC) or European Information Technology Observatory (EITO), etc. The quality of data offered by non-official suppliers can be uneven (and difficult to assess when their methodologies are considered a trade secret and not disclosed) but they often provide a timely and pertinent information about activities and sectors that are inadequately covered by official agencies. Thus, the availability of measurement data and their range increase dramatically.

Official statistical organisations still need to come to terms with the changing environment and fully comprehend the implications of self-reflectiveness and competition. The shortcomings of their data are now scrutinised more closely and they have to fight for recognition and public attention with alternative suppliers, with whom they have not defined clear modus operandi. The dDeliberateness of their reactions and adjustment to change appear as handicaps in a rapidly evolving economy.

Their tasks are becoming wider and more complex at the time when governments are unwilling to increase resources for statistical data gathering.

Specific issues

The emerging economy is non-linear, non-proportional and riddled with discontinuities. It raises a whole series of methodological and conceptual issues for the measurement specialists. Let us mention four~~just a few~~:

- Issue of shifting boundaries.

Intangibles wreak havoc with a taxonomic approach, based on mutually exclusive and exhaustive classifications. They undermine the very principle of stable groupings and set boundaries. Two already discussed examples are the loss of relevance of product/service distinction and convergence/segmentation dynamics of IT activities. Statistics need to find methodologies and approaches to handle shifting and overlapping sectoral boundaries and multidimensional interfirm linkages. They have to learn to cope with fuzzy rather than binary data sets [Kosko, 1993]{~~fuzzy~~. ~~logic)~~

- Issue of imperfectly priced transactions.

In the intangible economy, a great deal of consumption and exchanges between economic agents either are either free or are priced through mechanisms that do not reflect their full value to the consumer. In order to capture them, conventional measurement approaches, based on market transactions, have to be supplemented by metrics capturing the actual use of resources. For instance, ~~the~~ estimates of household consumption should take into account not only ~~the~~ monetary expenditures but also ~~the~~ time budgets. This would allow a better capture of the consumption of entertainment artefacts such as a “free” TV.

- Issue of qualitative change and technical progress.

Because of its critical importance, this issue is well known, which does not make it any simpler to resolve. Benchmark definition, product comparability and discontinuity, appropriate data collection and treatment are only few of the problems encountered. To solve them, statistical skills need to be combined with technical knowledge. The issue has acquired a greater sense of urgency with the implementation of the chain-weight price index methodology for GDP measurement. Unless this methodology is complemented by measures of qualitative change, it may very~~will~~ result in serious underestimatione of living standards and productivity. Stakes are extremely high: according to calculations by Yale economist, William Nordhaus, the failure to capture technological improvements between 1800 and today for products ranging from light bulb~~lamp~~s through cars anand d telephones to zippers resulted in an underestimate of living standards improvement ~~in standards of living~~ of the order of 3.5% to 4% per annum [Nordhaus, 1994]. Similar point has been made by Leonard Nakamura, an economist at the Federal Reserve Bank of Philadelphia, for whom the gap between the real and the official GDP growth has substantially increased since 1974 [Nakamura, 1995].

- Issue of heterogeneity

Heterogeneity is a key hurdle in measuring intangible assets such as human capital. Economists tend to approach it like physical capital, with the view that more is better and thus a higher spending indicates a higher real investment, which entails higher returns in the future. Yet, this is clearly not the case. Take for instance the relationship between the quality of the labour force and training expenditures. Japanese industrial competitiveness is often explained by the quality of its labour force. Conversely, the low productivity of UK labour is blamed on the inadequate training of the UK labour force. Yet, in 1985, ~~the~~ JJapanese companies were spending less than a half of the amount spent by ~~the~~ British companies on training: 0,3% of total remuneration for the former versus 0.7% for the latter [Leadbeater, 1989]. The explanation of this paradox is intuitively simple: a great deal of training in Japan is informal through learning-by-doing, which does not show in quantitative indicators.,

Over the years, economists have explored different ways to measure human capital: some looked at the level of education [Barra and Jong-Wha, 1989], others at the wage structure, which they sought to correlate with ~~the~~ educational achievement [Mulligan and Sala-I-Martin, 1995]. Those attempts are not entirely convincing and fail to overcome two major problems: ~~the~~ differences in the quality of education and an imperfect correlation between education and income levels.

Human capital is generated in variety of ways, formally and informally, in educational establishments, in the workplace andor at home~~in the family~~. Traditional economic and statistical approaches fail to capture this variety and to address the crucial question of the primary purpose of human capital formation: Is it to enhance the marketability and the earning power or is it to respond to other, less tangible yet essential demands, for social integration and personal enrichment. The labour market is not the only market where human capital is traded.

This list is far from exhaustive. It suggests however two important points:

- The need to complement monetary measurements of economic variables (both on the input and the output side) withby other ~~resource use~~ metrics, which measure the resource use and the qualitative change. The pioneering work by Griliches and others on techniques such as hedonic regression need to be pursued and amplified [Griliches, 1992b]. Statistics has to go back to its roots in metrology.

- The need to complement statistical skills by a more specialised technical knowledge, particularly in the area of Information Technology, where the notion and measure of performance are still being heatedly debated [Landauer, 1995].

Way forward: Triple challenge

Beyond tackling specific issues, statisticians need to undertake a comprehensive appraisal of their business. Adapting to the new environment of the intangible economy will require major changes in three key areas of the statistical establishment: conceptual foundations, modus operandi and temporal outlook.

Changing conceptual foundations: Aaccepting the centrality of the intangible

To put it bluntly: if ~~the~~ measurement systems are to capture the essence of the economy of today and tomorrow, intangibles have to move from the periphery to the core of these systems. The bBasic characteristics of intangibles should be better understood and modelled. Markets for intangibles need to be analysed in order to fully grasp ~~fully~~ their transaction dynamics, ~~and~~ their tremendous signalling potential and the new relationship between price and value.. For statisticians, focusing on intangibles implies a shift away from macroeconomic aggregates toward micro-economic processes and transactions.

The magnitude of the necessary conceptual revolution is comparable to the shift from Newtonian to quantum physics. This comparison can quite illuminating, to the extent that it focuses on two contrasting views of the universe. Newtonian physics view it as mechanistic and materialistic, its evolution rigidly defined by a deterministic interplay of immutable forces. In the Newtonian world, as one goes toward more elementary level, things are becoming simpler and better defined, hence its emphasis on the aggregate level. Quantum physics put this view on its head: complexity and indeterminacy are not the result of aggregation of elementary units but a starting point. At a most elementary level, traditional laws of causality no longer apply: the distinction between matter and non-matter, lump and flow, particle and wave, becomes meaningless: space, time and matter converge. The famous Schrödinger quantum cat is simultaneously dead and alive [Zohar & Marshall, 1993]. Seemingly incompatible forces coexist. As we recall, this type of coexistence is at the core of the intangible economy.

The quantum metaphor also highlights that the importance of the uncertainty principle of in the intangible economy, which is highly self-reflective and data-sensitive.

In the new conceptual framework, the notion of data needs to be fundamentally ~~They also should fundamentally~~ rethought~~ink~~ ~~the notion of data~~. In the intangible economy, traditional distinctions (data, facts, interpretation, information) are no longer pertinent. In a provocative article, Phil Agre, Professor of Communications at the University of California at San Diego, argues that data as currently conceived miss at least five key ingredients: ownership, error bars, sensitivity, dependency, semantics. For him, in order to bring data back to life, they need to be more self-reflective and relational [Agre, 1994]. There is also a need to better understand the theoretical and operational implications of the growing heterogeneity of data, which are no longer exclusively quantitative, monetary and numeral but can also be qualitative, physical and graphical.

It could be argued that those tasks go well beyond the brief of statisticians and would be better carried out by more basic research oriented institutions such as universities. ~~After all, putting intangibles at the core of the economy~~ ~~would be~~ is ~~comparable to a transition from mechanistic to quantum physics.~~ This argument would however miss a key point: the need to link theory to action. Efforts to articulate a new vision of economics have already begun and some of them show great promise. Many of them are carried out outside the traditional research establishments, drawing on the experience of various previously separated disciplines. Some of the more exciting projects are inspired by the Complexity approach, which builds upon contributions from mathematics, physics and biology to develop a conceptual framework dealing with complex and non linear systems [Anderson, Arrow and Pines, 1988].

However, pPioneers of the intangible economy and other innovative approaches remain dispersed and suffer from the lack of critical mass and credibility, which comes from the operational exposure. A greater involvement of measurement professionals in the conceptualisation of the intangible economy would raise its visibility, help to federate various initiatives and to ensure their practical relevance. Such involvement It should be structured in a way that capitalises on the expertise of pioneers and stimulates continuing interchange of ideas, theories and experiences across disciplinary, institutional and geographical boundaries.

Changing modus operandi: Ddiversity and openness

In the intangible economy, measurement systems are fundamentally pluralistic. Ultimately, the multiplicity of systems reflects the underlying multidimensionality of economic phenomena: to understand them, more than one measure or viewpoints is~~are~~ required - a single point needs to be replaced by an array.

Official agencies need to go beyond a mere acknowledgement of the existence of the measurement industry and alternative suppliers, they should accept them fully. They should establish or reinforce working relationships, exchange data and, develop joint projects. This would enable the official agencies to leverage their resources and improve the quality and the timeliness of their offerings.

The loss of monopoly raises however a difficult and delicate question: what should be the role of official statistical agencies ? Should they be less of a player and more of a referee ? Should they retain their basic data function of producer function or should they gradually abandon it, totally or partially (through outsourcing), to the other suppliers ? Maybe the emerging role of the One function that official agencies is to act as acould usefully fulfil would be that of the clearinghouse service for data from variousdifferent sources. Their involvement would contribute to alleviate the serious concerns about issue of the reliability and heterogeneity of data, and the robustness of methodologies of private suppliers. here would be the quality insurance concerning the quality of data and the robustness of methodologies. Official agencies are ideally placed to provide quality insurance, to ensure comparability of data and to adjudicate conflicts.

Changes of modus operandi should also affect ~~the~~ relationships with the users of information, be they official, commercial or individual. Official agencies should fully embrace the Information Age and offer extensive, user-friendly and cost effective electronic access to their data through Internet. Setting up Web sites, offering not only promotional material but also useful and downloadable data should be a clear priority for Eurostat and for all EU statistical offices. These sites would not only make them and their output better known to their existing and potential users. They would also support and facilitate substantive work and progress on the issues and tasks discussed above.

Changing temporal outlook: from past to future

Traditionally, ~~the~~ economic performance measurement systems provided information about the past. Statisticians put a premium on continuity and the comparability of data. Today, ~~the~~ comparability becomes more laborious to achieve as goalposts are being continuously moved. More importantly, users want data that signal future trends and performance and help them to cope with ~~the~~ rapid and unexpected change.

Statistics need to become more and more like the meteorology: Their main value should reside in the ability to provide early warning signals and inflection points indicating shifts in major trends.

One of the ways to improve signalling capacity is to rely more on financial markets and its theoretical underpinnings. In particular, option theory offers a promising conceptual approach to the measurement of the economic value of the future [Dixit & Pindyck, 1995]. In his Con~~gress~~ testimony to the Congress in August 1994, Alan Greenspan [Greenspan, 1995] suggested a greater use of financial derivatives to measure expectations

“ Information on firm behaviour and signals from financial ~~and financial~~ markets may warn about the development or easing of bottlenecks sooner than highly aggregate readings on unemployment, national income, prices or the traditional monetary aggregates.”

We are living through a period of a sweeping transition, from one economic framework to another. A transition is always marked by confusion and apprehension. These are exacerbated by the lack of visibility as to where we are going and what~~how~~ the new destination will look like. The traditional role of statistics was to create a map of the present. They now have to provide markers for the trajectoriesy to the future.

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