Digital Tech and the Productivity Pparadox

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Digital Technology and the Productivity Paradox:

After Ten Years, What Has Been Learned?

by

Paul A. DavidStanford University & All Souls College, Oxford

Draft: 20 May, 1999

This paper has been prepared for presentation to the Conference

Understanding the Digital Economy: Data, Tools and Research, held at the

U.S. Department of Commerce, Washington, D.C., 25-26 May 1999.

Please do not reproduce without authors permission.

Contact Author: Professor Paul A. David, All Souls College, Oxford OX1 4AL, UKTele: 44+(0)1865+279313 (direct); +279281 (secy: M. Holme);

Fax:44+(0)1865+279299; E-mail:


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Digital Technology and the Productivity Paradox:

After Ten Years, What Has Been Learned?

1. The Computer Revolution and the Economy

Over the past forty years, computers have evolved from a specialised and limited role inthe information processing and communication processes of modern organisations to become a

general purpose tool that can be found in use virtually everywhere, although not everywhere to

the same extent. Whereas once "electronic computers" were large machines surrounded by

peripheral equipment and tended by specialised technical staff working in specially constructedand air conditioned centres, today computing equipment is to be found on the desktops and

work areas of secretaries, factory workers and shipping clerks, often side by side with thetelecommunication equipment linking organisations to their suppliers and customers. In theprocess, computers and networks of computers have become an integral part of the research and

design operations of most enterprises and, increasingly, an essential tool supporting control and

decision-making at both middle and top management levels. In the latter half of this forty year

revolution, microprocessors allowed computers to escape from their 'boxes', embeddinginformation processing in a growing array of artefacts as diverse as greeting cards and

automobiles and thus extending the 'reach' of this technology well beyond its traditional

boundaries.

Changes attributed to this technology include new patterns of work organisation and

worker productivity, job creation and loss, profit and loss of companies, and, ultimately,prospects for economic growth, national security and the quality of life. (Genetic engineeringmay one day inherit this mantle.) Not since the opening of the atomic age, with its promises

of power too cheap to meter and threats of nuclear incineration, has a technology so deeply

captured the imagination of the public. It is not surprising, therefore, that perceptions aboutthis technology are shaping public policies in areas as diverse as education and macroeconomic

management.

One indication of the wider importance of the issues motivating the research presented

in this volume can be read in their connection with the rhetoric, and, arguably, the substance of

U.S. monetary policy responses to the remarkable economic expansion that has marked the

1990's. For a number of years in mid-decade the Federal Reserve Board Chairman, AlanGreenspan, subscribed publicly to a strongly optimistic reading of the American economy's

prospects for sustaining rapid expansion and rising real incomes without generating unhealthy

inflationary pressures. His conviction that monetary tightening was not called for by the signs

of accelerating output growth and new lows in the unemployment rate appears to have beenbased in large part upon the anticipation of big productivity payoffs from the investments that

have been made in information technology.

Like many other observers, the Chairman of the Fed viewed the rising volume of


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expenditures by corporations for electronic office and telecommunications equipment since thelate 1980s as part of a far-reaching technological and economic transformation in which the

U.S. economy is taking the lead:1

We are living through one of those rare, perhaps once-in-a-century

events....The advent of the transistor and the integrated circuit and, as a

consequence, the emergence of modern computer, telecommunication andsatellite technologies have fundamentally changed the structure of the

American economy.

During 1996, when he was resisting calls within the Fed to raise interest rates in order to check

the pace of expansion and damp down incipient incipient, Chairman Greenspan stressed just

those structural reasons for believing that the relationship between the rate of real output

expansion, unemployment rate and the underlying rate of price inflation had been altered, andthe persisting buoyancy of the economy did not call for the imposition of monetary restraints:

2

The rapid acceleration of computer and telecommunication technologies can

reasonably be expected to appreciably raise our productivity and standards ofliving in the 21st century, and quite possibly in some of the remaining years

of this century.

1 Testimony of Alan Greenspan before the U.S. House of Representatives Committee on Banking and

Financial Services, July 23, 1996.2 Alan Greenspan, Remarks before the National Governors Association, Feb. 5, 1996, p. 1, quoted by B.

Davis and D. Wessel,Prosperity: The Coming 20-Year Boom and What It Means to You, (forthcoming in 1998), Ch.

10.


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Yet, there were other members of the Feds Board of Governors who demurred -- albeitineffectually -- from the Chairmans relaxed monetary policy prescriptions, and there has been

no lack of dissent from the forecast of an imminent productivity bonanza. Soon after Professor

Alan Blinder of Princeton ended his term as Vice Chairman of the Fed, he and his colleagueRichard Quandt co-authored a paper3debunking the notion that the IT revolution already had

greatly boosted productivity. According to Blinder and Quandt (1997: pp. 14-15), even if the

information technology revolution has the potential to significantly raise the rate of growth ofproductivity in the long-run, the long-run is uncomfortably vague as a time-scale in matters of

macroeconomic managment. Going further, they put forward a thoroughly skeptical appraisal

of the prospects for a coming IT-based productivity surge -- likening the optimists on thatquestion to the characters in Becketts play Waiting for Godot.

4 In their view we may be

condemned to an extended period of transition which the growing pains change in nature, but

dont go away.

Some diminution of skepticism of this variety has accompanied the quickening of laborproductivity growth since 1997, and especially the very recent return of the rate of increase in

real GDP per manhour to the neighborhood of 2 percent per annum. But it remains premature

to try reading structural causes in what may well be transient, or cyclical movements which, in

any case, have yet to materially alter the U.S. economys productivity trend over the course ofthe 1990's.

2. The Making and Unmaking of a Paradox -- And the Persisting Puzzle

Disagreements among economists about the underlying empirical question hardly are a

new thing. More than a decade has now passed since concerns about the relationship betweenthe progress in the field of information technology and the improvement of productivity

performance in the economy at large crystallized around the perception that the U.S., along with

other advanced industrial economies, were confronted by a disturbing productivity paradox.The precipitating event in the formation of this view was the rather offhand observation made in

the summer of 1987 by Robert Solow, Institute Professor at M.I.T., and Economics Nobel

Laureate. In the course of a book review Solow remarked: You can see the computer ageeverywhere but in the productivity statistics.

5 This characteristically pithy comment soon

was being quoted by the business press, repeated in government policy memos, and quickly

became the touchstone for proposals to convene academic conferences to assess the state of

knowledge on the subject of technology and productivity. In no time at all the question of whythe information technology revolution had not sparked a surge in productivity improvements

and a consequent supply-drive wave of economic growth was universally referred to as "the

Productivity Paradox." Almost overnight it reached the status of being treated as the leadingeconomic puzzle of the late twentieth century.

3 Alan S. Blinder and Richard E. Quandt, Waiting for Godot: Information Technology and the the

Productivity Miracle?, Princeton University Department of Economics Working Paper, May 1997. 4 Samuel Beckett, Waiting for Godot, A Tragicomedy in Two Acts, 2nd ed., London: Faber and Faber, 1965.

5 Robert M. Solow, Wed Better Watch Out, New York Review of Books, July 12, 1987, p. 36.


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All this commotion was not undeserved. Professor Solows remark had served todirect public attention to what he and some other observers took to be a perplexing, and rather

ironic conjunction of two conflicting impressions about the rate of technological advance in the

industrialised West. On the one hand, excitement in the business press had persisted sinceTime Magazinedeclared the computer as the 'person of the year' in 1982. With the continuing

rapid pace of innovation and rapid growth of investment in computer technologies, industry and

academic economists were preoccupied not only with the immediate effects of the computer butwith the potentially even larger implications of the accelerating convergence of

telecommunication and computer technologies.

On the other hand, in the U.S. Private Domestic Economy the average annual pace of

increase of labor productivity had been cut by well more than half between the periods

1948-1966 and 1966-1989, tumbling from 3.11 to 1.23 per cent per annum.6 This was

sufficient to pull the secular trend rate for the entire post-WW II era (1948-1989) back down to2.05 per cent per annum, which was about the same pace that had been maintained thoughout

the preceeding half-century. In other words, during 1966-1989 labor productivity grew at an

anomalously sluggish pace, only a bit more than half the 2 percentage points per annum rate

that has been characteristic of the epoch of modern economic growth, and barely half the (2.52percent per annum) average rate that was achieved in the U.S. private economy over the

1929-1966 interval.

But, even more disturbing was the evidence that the slowed rise in labor productivity

reflected a collapse in the growth rate of total factor productivity (TFP): a measure of the crude

TFP residual, that is the portion of the output per manhours growth rate that is not attributable to

contribution of increasing capital per manhour, fell to 0.66 percentage points per annum during1966-89. That slow a total productivity growth rate had not been experienced in the US

Private Domestic Economy for a comparably extended period since the middle of the

nineteenth century. Recent calculations by Abramovitz and David (1998) show that during1966-1989 the refined TFP growth rate (adjusting for composition-related quality changes in

labor and capital inputs) plummeted to 0.04 percent per year. Contrast that with the average

annual rate of 1.4 percent that had been maintained over the whole of the 1890-1966 period.The slowdown was so pronounced that it brought the TFP growth rate all the way back down to

the low historical levels that statistical reonstructions of the mid-nineteenth century economys

record reveals.

Superior estimates of real gross output for the private non-farm businesseconomy have

become available from the BLS (May 6, 1998:USDL News Release 98-187). These provide a

more accurate picture, by deflating the current value of output using price indexes thatre-weight the prices of the component goods and services in accord with the changingcomposition of the aggregate. These chain-weighted measures lead to productivity growth

measures which reveal two further points about the slowdown. The first is that rather than

6 The figures cited are based on estimates of real gross product per manhour, assembled by M. Abramovitz

and P. A. David in American Macroeconomic Growth in the Era of Knowledge -Driven Progress: A Long-Run

Interpretation, Unpublished memorandum. December 1998 .


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becoming less marked as the oil shock and inflationary disturbances of the 1970's and therecession of the early 1980's passed into history, the productivity growth rates deviation below

the trend that had prevailed during 1950-1972 interval had grown even more pronounced during

the late 1980s and early 1990's. Labor productivity increased during 1988-1996 at 0.83 percentper annum, fully 0.5 percentage points less quickly than the average rate during 1972-1988.

Correspondingly, the refined TFP growth rate estimate (without allowance for vintage

effects) sank to 0.11 percent per annum, which represented a further drop of 0.24 percentagepoints from the 1972-88 pace.

Perceptions of the productivity paradox as a failure of new technology to accelerate the growth

of the task efficiency of resource use emerged as much from "the bottom up" view of theeconomy as from a "top down" view of highly aggregated categories provided by national

product accountants. Indeed, the notion that there is something anomalous about the prevailing

state of affairs drew much of its initial appeal from the apparent failure of the wave of

innovations based on the microprocessor and the memory chip to elicit surges of growth inlabour productivity and multifactor productivity from those very branches of of the U.S. service

sector that were investing so heavily in computers and office equipment. Worse still, despite

the hopes that many continued to hold that the "information technology revolution" would soon

spark a revival, little support for such optimism could be found in the first wave of empiricalstudies that looked into this question systematically. Some saw no association between greater

use of computers and higher productivity, whereas others reported that heavy outlays on

equipment embodying new information technologies appeared to be associated withdecreasesin productivity or subnormal rates of return on investment (see, e.g., Roach (1987,

1988, 1991), Loveman (1988), Morrison and Berndt (1990).

The economics profession's reactions to these anomalous and perplexing developments havetended to be expressed in one of three characteristic positions: either the Solow paradox is an

artefact of inadequate statistical measure of the economys true peformance, or there has been a

vast over-selling of the productivity enhancing potential of IT, or the promise of a profoundimpact upon productivity has not been mere hype, but the transition to the techno-economic

system in which this will be fulfilled should be understood to be a more arduous, costly, and

drawn out affair than was initially supposed. We shall first consider these positions morefully, before turning in the Part II to assess the light that each has been able to shed on recent

experience, and therefore on future prospects.

2.1 Doubts About the Data -- Distortions in the Mirror of Economic Reality

First to be considered are the numbers skeptics who see the problem to reside mainlyin the productivity statisticsthemselves. The suggest that Professor Solow's formulation of thesupposed paradox contains its own resolution. The economy could well be experiencing

substantial real gains in "productivity" from succeeding waves of ICT innovations, but their

impact are masked by defects and deficiencies in the available measures of economicperformance. By this account, faulty measures have seriously understated the growth of real

output, thereby creating the appearance of spuriously low rates of growth in both labour

productivity and total factor productivity.


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Within the camp of economists who pointed to "measurement errors" as the resolution

of the productivity paradox there was no clear consensus as to when these errors became

dominant. For example, should the same explanation be applied to account for the slowdownobserved in the pace of productivity since the mid-1970's? By the same token, comparatively

little attention has been given to drawing a tighter connection between the suspected severity of

the measurement error problem in recent years, and the nature of developments characterisingthe information revolution itself which would support the proposed direction of causation.

The productivity slowdown emerged by the early 1980s, and thus before the personal

computer's contribution to the rapid advance of the information revolution during the 1980s.This raises the possibility that mechanisms responsible for the slowdown also could have a

major role in the creation of a computer productivity paradox, inasmuch as it was the

proliferation of personal computers to which Professor Solow was referring in 1987. During

the past twenty years, several significant structural changes have occurred in the U.S. economyincluding the continued growth of service activities share of national output, the proliferation of

new products and the enlargement of the role of knowledge-based industries in the economy.

Each of these structural changes as well as accompanying organisational changes are also

linked to information and communication technologies. It is therefore possible that theproductivity slowdown and the computer productivity paradox are different and mutually

reinforcing features of the same set of phenomenon.

2.2 Delusionment with IT -- Maybe Godot Doesnt Exist and Wont Be Coming

In a second explanatory category, as our previous reference to the views of Professor

Blinder indicates, there are "computer revolution sceptics" who maintain that there really isnothing paradoxical about the flagging post- 1973 pace of productivity advance because notion

of a "computer revolution" has been based more upon "hype" than concrete evidence promising

enormous efficiency gains in the branches of the economy where most productive resources areemployed. Quite the contrary, they catalogue the many perverse consequences that have

followed the introduction of computers into the workplace, especially in the service sector.

Those who, like Robert Gordon (1997, 1998) have swung round to a scepticism about

actual impact, certainly can justly point to the existence of essentially transient factors which

had contributed to the high measured rates of total factor productivity growth that characterised

the performance of the post-WWII U.S. economy (and other industrial economies to an evenmore marked degree). Therefore, they maintain, a slowdown was not only inevitable, but an

economy-wide resurgence in the size of "the residual" due to the information technology

revolution remains highly implausible for the foreseeable future. This is the case, they contend,because the old technologies have been exhausted as a source of further efficiencyimprovement in many lines of tangible commodity production industry, whereas the

application of ICT in other, "service" industries has fallen far short of expectations.

Furthermore, other highly promoted sources of commercial innovation, such as advances inbiotechnology, high temperature superconductivity and new materials remain at best rather far

off in the future as major generators of conventional productivity improvement.


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2.3 From the Regime Transition Hypothesis to Cautious Optimism:

Third, there are those who approach the problem of accounting for what has beenhappening with what might be labelled a spirit of cautious optimism. Explanations of this

kind have seized upon the idea that we are involved in the extended and complex process of

transition to a new, information intensive techno-economic regime based, a transition thatinvolves the abandonment of the extensive transformation of some, and renewal of other,

aspects of the former, mature "Fordist" technological regime. This technological regime,

based upon techniques of mass production and mass-marketing of standardised goods andservices produced by capital-intensive methods requiring dedicated facilities, high rates of

through-put, and hierarchical management organisations, had assumed its full-blown form first

in the U.S. during the second quarter of the present century. In its mature stage it underlay the

prosperity and rapid growth of the post-WWII era, not only in the U.S. but in other industrialcountries of western Europe, and Japan, where its full elaboration had been delayed by the

economic and political dislocations of the 1920's and 1930's, as well as by WWII itself.

Regime transitions of this kind, it is argued, involve profound changes, whoserevolutionary nature is better revealed by their eventual breadth and depth than by the pace at

which they achieve their influence. Exactly because of their breadth and depth, they require

the development and coordination of a vast array of complementary tangible and intangibleelements: new physical plant and equipment, new kinds of workforce skills, new organisational

forms, new forms of legal property, new regulatory frameworks, new habits of mind and

patterns of taste. For these changes to be set in place requires decades, rather than years, and

while they are underway there is no guarantee that their dominant effects upon macroeconomicperformance will be positive ones. The emergence of positive effects is neither assured nor

free from the exploration of blind alleys (trajectories that proved economically nonviable and

were abandoned). Moreover, the rise of a new techno-economic paradigm can havedislocating, backwash effects upon the performance of surviving elements of the previous

economic order. In short the "productivity paradox" may be a real phenomenon, paradoxical

only to those who suppose that the progress of technology is autonomous, continuous and,being "hitchless and glitchless" translates immediately into cost-savings and economic welfare

improvements.

Those in the cautious optimist camp suggest that the persistence of slow rates ofproductivity growth should be viewed as a slip between cup and lip which might well be

corrected with the appropriate attention and co-ordination. If so, the future may well bring a

resurgence in the measured total factor productivity residual that could be clearly attributed toadvances in ICT. They are therefore intent to divine the early harbingers of a more widespreadrecovery in productivity growth. But they acknowledge that such a renaissance is not

guaranteed by any automatic market mechanism and argue that it is foolish simply to wait for its

arrival. They point, instead, to the need to concurrently address many of the technologicaldrawbacks that already have been exposed, as well as the difficult non-technological,

organisational and institutional problems that must be overcome in both the economy's public

and private spheres in order to realise the full potential of the "information revolution".


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The foregoing caricatures of the three main explanatory camps into which the

economists seem to have organized themselves are sufficiently overdrawn that it would be

inappropriate to firmly attach names to the various positions. Yet, together they do convey thespirit of much of the recent discussion in the scholarly journals, government studies, and the

business press. Rather than approaching the task of interpreting the evidence as one of

evaluating these as alternative and conflicting hypotheses among which it is necessary tochoose a prime resolution for the productivity paradox, an effort at synthesis appears far more

appropriate. From the evidence that has been accumulating during the past decade it seems

increasingly clear, first, that there is less that is really paradoxical in the economic record, butconsiderable basis remains for puzzlement regarding the sources of the total factor productivity

slowdown. Secondly, while each of the proposed lines of explanation has something to

contribute towards explaining the latter development, greater weight can be placed upon a

combination of adverse productivity concommittants of the regime transition, and severalmeasurement problems that have been exacerbated by the digital technology revolution itself.

3. Unmaking the Paradox -- and leaving a Persisting Puzzle

That there is a quite simple and positive linkage between new technological artefacts

and economic growth remains a view widely held among economists today. Improvedtechnological artefacts are likened to better tools and better tools are supposed make workers

more productive. Moreover, the prospect of higher productivity for the users of tools

embodying the new technologies ought to encourage investment in those assets, and thereby

stimulate demand. If the relative price of these tools are falling, should we not be observinggrowth in both the volume of sales of the tools and the productivity achieved by using them?

There is nothing particularly complicated about such a process. New organizations of

production techniques may simply permit adaptation to changing relative input prices; theycould allow the substitution of inputs whose relative prices are declining for those whose

relative prices are rising, thereby averting upward pressure on real costs per unit of output --

without necessarily increasing multifactor productivity. If relatively rapid technologicalprogress is taking place in the sector that is providing these better tools, the consequent fall in

their price vis-a-vis other inputs will drive the process of substituting them for those factors of

production in a variety of applications, and their contribution to the growth of output will come

in the form of the yields on the necessary investments required put them in place.

It is plain that the first part of this causal chain is strikingly substantiated by the data for

the case electronic computers, and by the larger category of equipment to which they belong:office, accounting and computing machinery, abbreviated as OCAM.

7 According the the

7 The historical continuity of the U.S. NIPA (National Income and Product Accounts) has been preserved

during the computer and telecommunication revolution by the assignment of computers to the increasingly

heterogeneous standard industrial classification computer and office equipment. At this 3-digit level of

aggregation, general purpose digital computers are counted along with paper punches and pencil sharpeners.

Telecommunication equipment at the three-digit level is no less discriminating as a category, mingling cellular


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estimates developed by Dale Jorgenson and Kevin Stiroh (1995: Table1), over the period1958-1992 the volume of OCAM investment in the U.S. was increasing at an average yearly

rate of 20.2 percent, while the associated (constant quality) index of prices was falling at an

average rate of 10.1 percent per annum; the corresponding rates for computers alone were stillmore spectacular, with investment quantities sky-rocketing at an average rate of 44.3 percent

per annum while prices were plunging 19.1 percent per year on average.8

Nothing

fore-ordained that that once the expansion of computer power had begun it should proceed atsuch an explosive pace, but, the still-small size of the computerized sector in the economy

during this phase in a sense limited the scope for its breath-taking growth to set up

complicating, "back-wash" effects at the microeconomic and macroeconomic level, therebyjeopardizing its rapid continuation.

But, by the same token, rather than supposing that the resulting 20 and 47 percentage

point per annum trend rates of growth found for the real OCAM stock and the computerequipment stock, respectively,

9 would translated into commensurately rapid productivity

increases, it is necessary in that connection also to take into account the comparatively small

weight that these forms of capital carry the total flow of capital services. Furthermore, the

productive contribution made by the growth of capital services to the rate of output growthdepends upon magnitude of the "elasticity" of the latter with respect to the former, and that too

lies well below unity. Both considerations should lead one to expect that the contribution made

by the rise of computer capital services to the growth of output would be tightly circumscribed.

Following this familiar line of growth accounting analysis, two path-breaking empirical

assessments have been made of the contribution to the growth of aggreate output in the U.S. by

investments embodying computer technology. Oliner and Sichel (1994), and Sichel (1997:Ch.4) have produced one such set of measurements for he private non-farm business sector from

"computer hardware services"over the long interval 1970-1992, adding estimates for

"computer software services" in the years 1987-1993. Jorgenson and Stiroh (1995: sect. 4,especially) have implemented essentially the same conceptual approach to gauge the

contribution of computer capital services (hardware only) within the framework of a more

elaborate set of growth accounting estimates for the domestic economy as a whole in the yearsbetween 1958 and 1992.

radio telephones with radio and television broadcasting equipment, grouping private branch exchange equipment

with telephone answering machines, and throwing in police sirens for completeness. The seeming anachronism of

these product classifications may yet be reversed by penetration of digital technology into simple artefacts: answering

machines have already acquired intelligence; perhaps, with the insertion of microprocessor chips, we will soon see

paper punches, pencil sharpeners and police sirens smarten up as well.8 These movements reflect the corrections made by the substitution of hedonic price indexes which ineffect measure the change in the nominal price-performance ratio of computer equipment. Given the fact that

the estimates available for the other components of producers durable equipment do not reflect such quality

corrections, comparisons of the relative growth of the constant dollar value of computers and OCAM within that larger

investment category are distorted, as are the resulting figures tracing the relative growth of the comput er capital

stock vis-a-vis the rest of the capital stock. Further discussion of the introduction of hedonic prices for computer

equipment, and its consequences for statistical comparisons, one should consult Wykoff (1995) as well as Jorgenson

and Stiroh (1995).9 See, the estimates presented by Jorgenson and Stiroh (1995:Table 2).


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Not surprisingly, the results of these studies concurr in showing a secularly rising

contribution being made to the output growth rate from this source. Starting from negligibly

low initial levels, these rise to reach approximately similar significant dimensions by the late1980's and early 1990's. But, "significant" in this context can still means a contribution of

amounting to only a fraction of a percentage point in the annual output growth rate: Sichel

(1997: Table 4-2) gives a computer equipment service contribution for 1987-93 of 0.15percentage points, and a combined hardware plus software contribution of 0.26 percentage

points, whereas Jorgenson and Stiroh's calculations put the hardware capital contribution

during 1985-92 at the considerably higher level of 0.38 percentage points per years annum.The relative "contributions" estimated for hardware alone thus lie in the modestly low range

representing 7.5 to 15 percent of the corresponding output growth rates. But, the implied

range for the relative contributions of hardware and software capital services combined is more

substantial, representing between 13 and 24 percent of the output growth rate.10

The circumscribed focus of these studies upon investment in computers does risk

leaving out the broader significance of the micro-processors advent. In recognition of this

Kenneth Flamm (1997) presents a variant story, one that undertakes to quantify thesemi-conductor revolution rather than the computer revolation. Considering the rapid rate

of fall in the price-performance ratio of micro-processors, and their rapid and extensive

penetration of many areas of application in the economy, Flamms calculations neverthelesspoint to consumer surpluses on this account that represents only 8 percent of annual GDP

growth. In other words the measured direct contribution to GDP growth, aside from what the

vendors of micro-processors appropriate through revenues, is found to be about 0.2 percentage

point per annum.

10 Jorgenson and Stiroh's higher estimate for computer hardware capital services implies a considerably

more generous proportional contribution to output growth would have been made by hardware and software services

combined. Using the relationship between the two components reported by Sichel (1997: Table 4.2) for

approximately the same years, the implied contribution from software services could be put at 0.28 percentage points.

The latter must be added to the 2.49 percentage point rate of output given by Jorgenson and Stiroh (1995 : Table 4) for

1985-92, as service flows from software capital are were not included on either the output or input sides of their

growth accounting. The combined relative contribution from hardware and software on this basis leads to the figure

reported as 24 percent in the text: (.38 + .28)/(2.77) x100 = 23.8 percent.


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There are several ways in which these results may be read. The fact that by the early1990's the growth of computer capital services was contributing possibly as much as fifth of

the U.S. economys yearly output growth certainly could be taken as a strong, quantative

refutation of the argument that the investments poured into this sort of capital formation hadbeen squandered, that no comensurate payoff in terms of output and labor productivity, were

forthcoming.11

At the same time, these results can be welcomed as dispelling the widely

optimistic belief that the spectacular pace at which computer power has been growing musthave induced a productivity bonanza. The latter confusion stems from over-looking the fact

that no matter how rapidly a productive asset may be accumulating, what also enters into the

determination of its impact upon output is the size of the flow of productivity services ityields, in relation to the other inputs required for production. In the case of computer services

this share has been found still to be rather small; even in relationship to just the total flow of

capital services (gross of depreciation) in the economy, the computer stock's share had only

reached the 1.0 percent mark by 1985, before the personal computer investment boomenlarged it to 4.5 percent in 1992.

12

It is worth noting that the modern conjuncture of high rates of innovation and slow

measured growth of total factor productivity is not a new, anomalous development in thehistory US economy. Indeed, most of the labor productivity growth rate during the interval

extending from the 1830's through the 1880's was accounted for by the increasing capital-labor

input ratio, leaving residual rates of total factor productivity growth that were quite small by thestandards of the early twentieth century, and a fortiori, by those of the post-WW II era. During

the nineteenth century the emegence of technological changes that were biased strongly in the

direction of tangible-capital using, involving the substitution of new forms of productive plant

and equipment involving heavy fixed costs and commensurately expanded scales ofproduction, induced a high rate of capital accumulation. The capital-output ratio rose without

forcing down the rate of return very markedly, and the substitution of increasing volumes of the

services of reproducible tangible capital for those of other inputs, dispensing increasingly withthe sweat and the old craft skills of workers in the fields and workshops, along with the brute

force of horses and mules, worked to increase real output per manhour.13

11 The counter-argument by technological pessimists would point out that the growth accounting

calculations of Oliner and Sichel (1994), and Jorgenson and Stiroh (1995) merely assumethat the computer equipment

investments have been earning the same net rate of return as the other elements of the capital stock (on an after-tax

basis, in the case of the capital accounting framework developed by Jorgenson (1990) and implemented in his work

with Stiroh). In view of the continuing investments, that does seem a plausible minimum assumption, but, it is

nonetheless a supposition, rather than a point that the growth accounting has proved. As will be seen (from the

contributions by Brynolfsson and Hitt (1995) below, efforts to estimate the rates of return earning on computer capitaleconometrically from data at levels of aggregation below that of the economy, do refute the suggestion that the private

rates of return have been sub-normal. [This is reinforced by subsequent findings reported by Bynolfsson and Hitt

(1997, 1998).]12

These "shares" are calcuated from the estimates in Jorgenson and Stiroh (1995 [Chapter 10]: Table 3).

The corresponding shares of computer equipment services in the flow of services from non-residential producer

durable capital are, of course, considerably larger, reaching 18 percent by 1992.13

See Abramovitz and David 1973, David 1977, Abramovitz 1989. Thus, most of the labor productivity

growth rate was accounted for by the increasing capital-labor input ratio, leaving residual rates of total factor

productivity growth that were quite small by the standards of the early twentieth century, and a fortiori, by those of the


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But, viewed from another angle, the spirit of the Solow computer paradox lingers on,like the Chesire Cats smile; if not a real paradox, there remains a puzzle occasioned by the

surprisingly small a TFP residual. It should be noted that the explanations which stress the

small the contribution made by the rise of computer capital do so under the dual assumptionthat the investments embodying the new information technologies have been earning only a

normal 12 percent net rate of return, like the other forms of capital, and that those private

returns to the investing firms fully capture their contributions to production throughout theeconomy. A different set of calculations made for the period 1987-1993, however, which

allow for the possibility that computer assets might be generating net rates of return very much

above the normal (economy wide) average, finds that the biggest plausible effect would addanother 0.3-0.4 percentage points per annum to the growth rate of labor productivity.

15

15 Sichel (1997: p.81) makes an allowance that increases the net rate of return about four-fold, and raising

the gross share of computer (hardware and software) earnings to .034 from .016. This raises the contribution to

output growth from 0.26 to .56 percentage points per annum. This 0.3 percent per annum increment would be the

magnitude of the rise in labor productivity growth resulting from allowance for the gap between privately appropriated

normal earnings and the hypothesized above normal rate of return. An alternative calculation would consider the

contribution from computer capital-deepening, defined as the growth of computer capital (hardware and software)

in relation to the growth of real output in the economy. For 1987-1993 the figures presented by Sichel (1997, Table4.2) indicate that the real ratio of computer capital inputs to real GDP was rising at about 14 percentage points per

annum. The contribution to the aggregate labor productivity growth rate is found by multiplying that rate by the

ratio of the computer inputs share to the total labor input share in GDP. Calculated under the normal rate of returns

assumption, that ratio is 0.025 whereas under the Sichel super-normal returns assumption it is 0.052. This implies

that the effect of increasing computer input intensity in the economy could be said to be raising labor productivity by

0.34 percentage points per annum under the assumption of normal rates of return, whereas the contribution to the

labor productivity growth rate on the higher rate of return assumption might be as much as 0.73 percentage points, or

almost 0.4 percentage points higher. Thus, the text gives 0.3 to 0.4 as the range if a generous allowance is made for

computer yields above the normal rate of return..


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Yet, might one not have supposed that there were spillovers in the form of inducedlearning effects, benefitting the employers of workers trained on the equipment installed at the

expense of other firms? Similarly, the use of computer equipment in generating new

knowledge that found its way into the productive capabilities of those who did not purchase orrent those R&D investment goods, would constitute another plausible form of externality.

These spill-overs, representing economic value that for one reason or another could not be

appropriated by (internalized within) the entities that bought and operated the IT capital, implythat a gap would exist between the social and the private rates of return on information capital.

Nevertheless, to the extent that they contributed to the productive capabilities of the firms to

whom they accrued, these benefits would have to turn up on the real output side the growthaccountants ledgers for the economy as a whole. Where, then, are the externalities that one

might have expected from the accumulation of this new class of productive assets? Is the story

of the computer revolution simply that every individual private investor has received, and can

only hope to go on receiving exactly what they payed for, and nothing more from the collectiveaccumulation effort?

These are intriguing questions, indeed, particularly when set against the expectations

that have been stirred by discussions of the emergence of the distributed intelligence, thenetworked economy and the national and global information infrastructure. Understandably,

the puzzle continues to compel the attention of economists interested in the long term prospects

of growth at the macrolevel, and those who seek to understand the microeconomics of thephases of information technology revolution through which we have been passing, and their

relationship to those that may lie ahead.

4. Measurement Problems

Those who would contend that the slowdown puzzle and computer productivity paradoxare consequences of a mis-measurement problem must produce a consistent account of the

timing and extent of the suspected errors in measurement. The estimation of productivity

gorwth requires a consistent method for estimating growth rates in the quantities of inputs andoutputs. With a few notable exceptions (e.g. electricity generation), the lack of homogeneity

in industry output frustrates direct measures of physical output and makes it necessary to

estimate physical output using a price deflator. Similar challenges arise, of course, in

measuring the heterogeneous bundles of labor and capital services, but, for the momentattention is being directed to the problems that are suspected to persist in the measures of real

product growth. Systematic overstatement of prices will introduce a persistent downward

bias estimated output growth and, therefore, an understatement of both partial and total factorproductivity improvements.

Such overstatement may arise in several distinct ways. There are some industries,

especially services, for which the concept of a unit of output itself is not well defined, and,consequently, where it is difficult if not impossible to obtain meaningful price indices. In

other cases, such as the construction industry, the output is so heterogeneous that it requires

special efforts to obtain price quotations for comparable products both at an one point in time


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and over time. The introduction of new commodities again raises the problem ofcomparability in forming the price deflators for an industry whose output mix is changing

radically, and the techniques that statistical agencies have adopted to cope with the temporal

replacement of old staples with new items in the consumers shopping basket have been foundto introduce systematic biases. These are only the simpler and more straightfoward potential

worries about mismeasurement, but we shall begin with a consideration of there bearing upon

the puzzle of the slowdown and the computer productivity paradox, before proceeding to someless tractable conceptual questions.

4.1 Over-Deflation of Output: Can this explain the Slowdown puzzle?

The simplest formulation of a mis-mismeasurement explanation for the slowdown falls

quantitatively short of the mark. This does not mean that there is no underestimation of thelabor productivity or the total factor productivity growth rate. Perhaps the paradox of the

conjuction of unpredecentedly sluggish productivity growth with an explosive pace of

technological innovation can be resolved in those terms. There is indeed something to be said

for taking that more limited approach a step further.

The Boskin Commission Report (1997) on the accuracy of the official Consumer Price

Index (CPI) prepared by the U.S. Bureau of Labor Statistics concluded that the statisticalprocedures in use were leading to an anverage overstatement of the annual rate of increase in

"the real cost of living" by consumer prices by 1.1 percentage points. This might well be

twice the magnitude of the error introduced by mismeasurement of the price deflators applied

in estimating the real gross output of the private domestic economy over the period 1966-89.16

Were we to allow for this, by making an upward correction of the real output growth rate by as

much as 0.6 to 1.1 percentage points, would lift the level of the Abramovitz-David (1998)

estimate for the "super-refined" multifactor productivity growth rate back up to the positiverange, putting it at 0.35 - 0.85 percentage points per annum for the 1966-89 period. Even so,

that correction -- which entertains the extremely dubious assumption that the conjectured

measurement biases in the output price deflators existed only after 1966 and not before --would still have us believe that between 1929-66 and 1966-89 there had been a very appreciable

16 The Boskin Commission (1997) was charged with examining the CPI, rather than the GNP and GDP

deflators prepared by the U.S. Commerce Department Bureau of Economic Analysis, and some substantial part

(perhaps 0.7 percentage points) of the estimated upward bias of the former is ascribed to the use of a fixed-weight

scheme for aggregating the constituent price series to create the overall ( so-called Laspeyres type of ) price index.

This criticism does not apply in the case of the national product deflators, and consequently the 1.1 percent per annumfigurecould be regarded a generous allowance for the biase due to other, technical problems affecting those deflators.

On the other hand, the Boskim Commission's findings have met with some critiicism from BLS staff, who have

pointed out that the published CPI reflects corrections that already are regularly made to counteract some of the

most prominent among the suspected procedural sources of overstatement --the methods of "splicing in" price series

for new goods and services. See Maddrick (1997) ; it is claimed that , on this account, the magnitude of the

continuing upward bias projected by the Boskin Commission may be too large. The latter controversey does not

affect our present illustrative use of the the 1.1 percentage point per annum estimate, because we are applying it as a

correction of the past trend in measured real output, and, in the nature of the argument, an upper-bound figure for the

measurement bias is what is wanted.


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slowdown in multifactor productivity growth -- a fall-off in the average annual pace of some0.3 - 0. 8 percentage points. Moreover, there is nothing in the findings of the Boskin

Commission (1997) to indicate that the causes of the putative current upward bias the price

changes registered by the CPI have been operating only since the end of the 1960's.

Plainly, what is needed to give the mismeasurement thesis greater bearing on the puzzle

of the productivity slowdown, and thereby help us to resolve the information technologyparadox, would be some quantitative indication that the suspected upward bias in the aggregate

output deflators has been getting proportionally larger over time. Martin Bailey and Robert

Gordon (1988) initially looked into this and came away without any conclusive answer, andGordon (1996, 1998) moved towards a somewhat less skeptically dismissive position on the

slowdown being attributable to the worsening of price index mismeasurement errors, some

further efforts at quantification are required before the possibility can be dismissed.

4.2 Has the Growth of Hard-to-Measure Activities Led to a Growing Bias?

It is reasonable to consider whether the nature of the on-going structural changes in the

U.S. economy, and elsewhere, are such as would exaccerbate the problem of outputunderestimation, and thereby contribute to the appearance of a productivity slowdown. In this

regard, Zvi Griliches' (1994) observation that there has been relative growth of output and

employment in the "hard-to-measure" sectors of the economy is undisputable. The bloc of theU.S. private domestic economy comprising Construction, Trade, Finance, Insurance and Real

Estate (FIRE), and miscellaneous other Services has indeed been growing in relative

importance, and this trend in recent decades has been especially pronounced. Gross product

originating in Griliches hard-to-measure bloc average 49.6 percent of the total over the years1947-1969, but its average share was 59.7 percent in the years 1969-1990.

17

Nevertheless, is the impact of the economys structural drift towards unmeasurabilitybig enough to account for the appearance of a productivity slowdown between the pre- and

post-1969 periods? Given the observed trend difference (over the whole period 1947-1990)

between the labor productivity growth rates of the "hard-to-measure" and the "measureable"sectors that are identified by Griliches (1994, and 1995 ), the hypothetical effect on the

weighted average rate of labor productivity of shifting the output shares in the way that they

actually moved can be calculated readily. There is certainly a gap in the manhours productivity

growth rates favoring the better-measured, commodity producing sections, but the shrinkage inthat sectors relative size was too small to exert substantial downward leverage on the aggregate

productivity growth rate. The simple re-weghting of the trend growth rates lowers the

aggregate labor productivity growth rate by 0.13 percentage points between 1947-1969 and1969-1990, but that represents less than 12 percent of the actual slowdown that Griliches wasseeking to explain.

18

17 See Griliches (1995 [Chapter 10]:Table 2), for the underlying NIPA figures from which the shares in the

total private (non-government) product were obtained. The averages in the text were calculated as geometric means of

the terminal year values in each of the two intervals.18

The gap betwen the measured and the hard-to-measure sectors long term average rates of real output per


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manhour amounted to about 1.40 percentage points per annum, but it was smaller than that during 1947-1969 period

and widened thereafter. The more pronounced post-1969 retardation of the average labor productivity growth rate

found for the hard-to-measure sector as a whole was thus is responsible in a statistical sense for a large part of the

retarded growth of the aggregate labor productivity. But, as will be noted below, it would be quite misleading to

suggest that every branch of activity within the major sectors labelled hard to measure by Griliches participated in

the slowdown, and that the industries comprising the measured sectors did not.


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A somewhat different illustrative calculation supporting the same conclusion has beencarried out by Abramovitz and David (1998). For that purpose they begin by accepting the

finding of the recent report of the Advisory Commission to Study the Consumer Price Index,

the so-called Boskin Commission (1997), that the measurement biases affecting that index nowtends to overstate current and prospective annual rates of price increase by 1.1 percent points on

average, and that a plausible range around this upward bias extends from 0.8 to 1.6 percentage

points. For the sake of argument, it can then be supposed that in the past the overall bias stoodat the high end of this range, at 1.6 points a year, that an equal overstatement was present in the

price deflator for the U.S. gross private domestic product. Abramovitz and David then

suppose, further, that the upward bias arose entirely from deficiencies in the price deflators usedto derived real gross productivy originating within the the group of hard-to-measure sectors

identified by Griliches, which would imply that the over-statement of the growth of prices was

much higher 1.1 percentage points a year in that sector. They then add a further assumption,

namely that this large over-statement existed since the early post-WW II era in the case of thehard-to-measure sector, whereas prices and real output growth were properly measured for the

rest of the economy. What is the upshot?

Under the pre-suppositions just described, a simple calculation of the weighted bias --taking account of the increasing relative weight of the hard-to-measure sector in the value of

current gross product for the private domestic economy, as before -- must find that the

measurement bias for the whole economy grew more pronounced between the rapid-growthperiod, 1948-66 and the Slowdown period, 1966-89. But, once again, it is possible to put a

measure to the extent of the hypthesized mismeasurement, and the answer found by

Abramovitz and David (1998) is that is that only 12 percent of the slowdown in the labor

productivity growth rate that actually was observed would be accounted for in this way.Although quite consistent with the preceding alternative quantitative assessment of the

mismeasurement hypothesis based upon the structural shift away from commodity production,

the assumptions underlying this version are extreme; this implies that the comparative minorimpact found on this score represents an upper-bound estimate.

Were the foregoing not enough to warrant turning to examine other formulations of theapproach to understanding the productivity slowdown as an artefact of mismeasurement,

Robert J. Gordon (1998a) recently has weighed in on the same point with the findings of some

new calculations that use far more finely disaggregated data from the BLS. His findings

establish that the slowdown in average real output per manhours has been a quite pervasivephenomenon, affecting many industries within the commodity producing groups as well as the

services. Moreover, comparing pre-1973 with post-1973 rates of growth in output per at this

more detailed industry level shows that the experience of a slowdown was not statisticallysignificantly more frequent among the industries that fall into the hard-to-measure categorythat it was among those classified as being well-measured.

4.3 The Role of New Goods in Unmeasured Quality Change

A rather different mechanism affecting the accuracy measured productivity is more


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ubiquitous across industries, and may well have become more pronounced in its effect duringthe past two decades: the turnover of the product line arising from the introduction of new

goods and services, and the discontinuation of old staples, that has been experienced widely

among the advanced industrial economies. This is different from the shift of the product mixbetween sectors whose outputs are intrinsically easier or harder to measure. It is a measurement

difficulty arising from the underestimation of the growth in new products of improved quality,

vis-a-vis the older part of the product line, and consequently an understatement of the rate ofgrowth of the aggregate output of each branch of production in which this is taking place. A

change in product mix of this sort not only would heighten the problem of unmeasured quality

improvement, but might be in some part traceable to the effects of the emerging ICT regime.In that way it would be seen that the information revolution itself could be contributing to the

appearance of a productivity slowdown, and hence to the creation of its own paradoxically

weak impact upon macroeconomic growth. This is an intriguing line of argument that bears

closer consideration.

New information technologies, and improved access to marketing data are enabling

faster, less costly product innovation, manufacturing process redesign, and shorter product life

cycles. Diewert and Fox (1997) present some evidence from Nakamura (1997) on thefour-fold acceleration of the rate of introduction of new products in U.S. supermarkets during

1975-92 compared with 1964-75. By combining this with data from Bailey and Gordon (1988)

on the rising number of products stocked by the average U.S. grocery supermarket, it is possibleroughly to gauge the movement in the ratio between these flow and stock measures, thereby

getting a better idea of the movement in the new product turnover rate. This indicates that in

contrast with the essential stability prevailing between the mid 1960s and the mid 1970s, there

was a marked rise in the new product fraction of the stock between 1975 and 1992: if only halfof new products were stocked by the average supermarket, the share they represented in the

stock would have increased from about .09 to .46. With such an elevation of the relative entry

rate of new products, the potential is raised for underestimation of average output growth dueto the delayed linkage of new to old price series.

There is a further implication. The broadening of the product line by competitors may be

likened to a common-pool/over-fishing problem, causing crowding of the product space,

withthe result that even the reduced fixed costs of research and product development must be

spread over fewer units of sales. Moreover, to the extent that congestion in the product space

raises the expected failure rate in new product launches, this reinforces the implication that

initial margins are likely to be high when these products first appear and will be found to havefallen rapidly in the cases of the fortunate few that succeed in becoming a standard item.

During the 1970s, the Federal Trade Commission was actively interested in whether such product

proliferation was a new form of anti-competitive behaviour and investigated the ready to eat breakfast cereal

industry, see Schmalensee (1978).

_


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The mechanism of product proliferation involves innovations in both marketing and theutilisation of the distribution networks. Traditionally, the new product introduction involved

the high fixed costs of major marketing campaigns and thereby high unit sales. These costs

have been reduced by marketing strategies in which the existing mass market distributionsystem is being configured under umbrellas of 'brand name' recognition for particular classes of

products (e.g. designer labels, 'lifestyle' brands, and products related to films or other cultural

icons) or the reputation of particular retailers or service providers (e.g. prominent departmentstore brands or financial services provided by large retail banks). Although, in the U.S., the

mass market distribution system was well-established early in this century, utilising it for

product and brand proliferation was frustrated by the high costs of tracking and appropriatelydistributing (and re-distributing) inventory. These costs that have fallen due to the use of

information and communication technologies. It is not surprising that a statistical system

designed to record productivity in mass production and distribution should be challenged when

the 'business models' of this system change as the result of marketing innovation and the use ofinformation and communication technologies.

Of course, some progress has been made in resolving the computer productivity paradox

by virtue of the introduction of so-called hedonic price indexes for the output of the computerand electronic business equipment industries themselves. These indexes reflect the

spectacularly rapid decline in the price-performance ratios of such forms of capital, but, by the

same token, they increased the measured growth of the computer capital services, which areintensively used as inputs in a number of sectors, including the services sectors. The implied

rise in computer-capital intensity contributes the support the growth rate of labor productivity in

those sectors, but in itself the substitution of this input for others does nothing for the

multifactor productivity growth rate.

Thus, correcting the excessiely deflationary bias of information technology price

deflators, has done wonders for the growth rate of multifactor productivity in the computerequipment industy, and its effect has contributed to the revival of the manufacturing sectors

productivity simply due to the growing weight carried by that industry, but the persitingly

sluggish multifactor productivity growth rates elsewhere in the economy, wh including withinother branches of manufacturing where computer equipment has been diffusing, continues to

belie the expectations and frustrate the hopes that the information revolution would profoundly

enhance the productive capacity of the U.S. economy.

5. Conceptual Challenges: What Are We Really Supposed to be Measuring?

Beyond the technical problems of the way that the national income accountants are

coping with accelerating product innovation and quality change lies several deeper conceptual

issues. These have been always with us, in a sense, but the nature of the changes in theorganization and conduce of production activities, and particularly the heighten role of

information -- and changes in the information state -- in modern economic life, may be bringing

these problematical questions to the surface in a way that forces reconsideration of what are


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measures are intended to measure, and how they actually relate to those goals.

In this section we look at three issues of this sort. First some surprises appeared when

economists sought to illuminate the macrolevel puzzle through statistic studies of the impact ofIT at the microeconomic level, using observations on individual enterprises peformance. This

highlights the conceptual gap between task productivity measures, on the one hand, and

profitabilityand revenue productivitymeasurements on the other. It will be seen that not only isthere an important difference, but the relationship between the two conceptual measures may

itself be undergoing a transformation, as a result of the impact of the way IT is being applied in

businesses. Next, we must consider the way we wish to treat investments in learning to utilizea new technology, and the implications this has for national income accounting. A major

technological discontinuity, which is what the advent of a new general purpose engine often has

been seen to be, may induce more than the usual increment learning processes which are not

counted as production of intangible assets, and not recorded in the national income and productaccounts. If so, this has a potential to occasion a more serious distortion of our

macroeconomic picture of the way resources are being used, and what is being produced.

5.1 The Microeconomic evidence about productivity impacts of IT--excess or subnormal?

Further light on the puzzle has been gained through the path-breaking research into the

productivity impacts of IT that have been conducted at levels below that of the macroeconomyhas been pursued by Brynolfsson and Hitt ( see Ch. ?8, here, based on 1995, 1996; followed by

Brynolfsson 1997) and Lichtenberg (see Ch: ?7 based on 1995, 1997). These studies make use

of company level cross-section data. An initially puzzling feature of their findings was that

the elasticity of product with respect to the use of IT capital by the company was so high that itimplied supernormally high, or "excess returns" to computer investments by the large firms

represented in the cross section samples.

This was a surprise, as it flew in the face of those who suggested that corporate America

was wastefully pouring too much investment into the purchase of electronic office equipment,

and implied that still more intensive use of suc equipment would be warranted. But it also wasanomalous when viewed against the apparent sluggish growth of productivity in some of the

very same industries and sectors that were represented in these cross-sections. These puzzles

were soon resolved by the recognition that what the cross-section production function analyses

were measuring was the impact of computers not on task productivity, but, instead on revenueproductivity. The only way to render the outputs of the firms drawn from different industries

comparable for purposes of statistical analysis of that kind was to measure they all in monetary

units. The gap between big (cross-section) impacts gauged in revenue productivity terms, andweak (time series) effects gauged in terms of task productivity means that there could be goodprivate profit-making reasons for this investment that do not translate into the equivalently

powerful social rate of returns, the latter being what is called for in assessing the contribution of

computer capital to national product growth.

In other words, the standard for gauging what represents "excess returns" on computer

and office equipment investments must be adjusted for the rapid rate of anticipated depreciation


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of capital value due to the falling price performance ratio. At the equilibrium point where therewill be indifference between installing new equipment and waiting to do so, the firm's expected

net operating benefits per dollar of reproduction costs for these durable assets must equal the

opportunity cost rate of return on the firm's outlay, plus the expected annual rate of assetdepreciation. If prices of equivalent performance computer equipment are declining at rates

approaching 20 per cent per annum, then we should be thinking of excess pre-tax returns as

starting somewhere above 30 percentage points.

It also is the case that subsequent investigations along the same lines have found that

there were additional correlative of IT intensity among firms, such as higher quality workers,and company reorganization programs. Taking those into account statistically led to a

substantial elimination of the apparent excess of the estimated returns on IT capital vis-a-vis

the returns on capital of other kinds. The significance of the latter findings will be considered

more fully below.

5.2 Leaving Out Learning Investment: Is the Scope of the NIPA Overly Narrow?The computer revolution involves a transformation of the tools used in productive work

and thereby a dramatic change in the skills needed within the workforce. A very important

component of the adjustments made to inputs in accounting for the total factor productivity

residual was a more adequate account of the changing quality of the workforce. In particular,educational attainment has been taken as the main indicator of the increasing quality of the

workforce. While it is undeniable that educational attainment has improved, it is also possible

that this variable overstates the change in worker skills relevant to employment. Skills that

must be acquired 'on the job' represent an investment in intangible capital to organisations.These investments are not capitalised and therefore appear as current labour costs in the

national income accounts.

For these investments in intangible capital to be relevant to the productivity slowdown

and the computer productivity paradox, it would be necessary to demonstrate that the 'match'

between educational attainment and relevant employment skills was falling over time. If it istrue that the real costs of these workers are higher to companies due to the extent of 'on the job'

training necessary for their effective performance in increasingly information technology

intensive work environments, the skills attributed to educational attainment, may be

discontinuous, overstating the 'quality' of labour. To the extent that the relevant skills arenon-cumulative (e.g., 'specific' to a given generation of information systems), the intangible

investments of companies will remain high and will also be difficult to address through reforms

in the educational system.

By comparison, for earlier eras, there is evidence that the match between education and

skills was better. During the 1890-1919 period, secondary school expansion was able to keep

ahead of the rising requirements for more educated workers and the skills conveyed insecondary school may have been more relevant to those needed in the workplace.

Correspondingly, evidence recently developed by Goldin and Katz (1996) suggests that

changes in the educational system during the 1920s supported the growth of the new high-skill


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industries on the eve of the Great Depression. The rapid expansion of higher educationfollowing World War II has been identified by Nelson (1990) as a source of U.S. leadership in

technology and productivity during the 1950s and 60s.

If the link between educational attainment and labour skills deteriorated during the

1970s and 1980s, this deterioration could be linked to both the productivity slowdown and the

computer productivity paradox. The significance of this deterioration for 'mismeasurement'would, however, depend very much on the potential for its alleviation. If the mismatch is a

persistent result stemming from rapid technological change and the need to 're-create' the

complementary skills needed for employment in an information technology-intensiveworkplace, shortcomings in productivity growth are likely to persist indefinitely. This is, of

course, consistent with the computer revolution sceptic point of view. On the other hand, if the

investments that companies are making in information technology related skills are cumulative

and complemented by the growing extent to which computer literacy is being incorporated insecondary and post-secondary education, the size of intangible investments made by companies

should begin to decline with the surplus recorded as productivity improvement and, eventually,

wages. If this interpretation is accurate, the 'cautious optimist' viewpoint would be vindicated.

5.3 Can Conventional Measurement Scales Be Trusted in a "Weightless Economy"?

Biases in measurement of output growth within the conventional NIPA framework mayhave been contributing to both the puzzling slowdown and generating the appearance of

paradoxically weak impacts from computerization, but, the case remains to be made that this is

the form of 'magic bullet' that would conclusively dispatch both puzzles. Existing

candidates proposed for this role are deficient, in either on grounds of timing or magnitude.While it is possible to expand the list of measurement problems in a way that would conjoin the

two sides of the puzzle, and thus contribute further to their resolution, the most promising

approach along those lines involves a head-on challenge to the existing productivitymeasurement framework; it argues that the scope of what is considered by the official accounts

to be the economy's "gross output" is overly narrow, and the a properly consistent realignment

of the definitions of outputs and inputs would raise the growth rate of the former in relationshipto the latter. Moreover, it suggests that such a realignment is needed especially in view of the

way that the information revolution has been affecting economic activity.

This this challenge to the official statistics is worth examining more closely for if theirusefulness in tracking macroeconomic performance is deteriorating, they will become

increasingly misleading as a guide in fiscal and monetary management; increased scope for

variant readings of signals whose accuracy has been impeached by experience is bound tointroduce a greater degree of subjectivity in policy formation -- so that the public trust in thepersonal judgements of those in positions of responsibility for policy-making, rather than in

the economic logic and empirical reproducibility of the bases for their judgements, must come

increasing to the fore. At present, those, like Chairman Greenspan, who are 'cautiousoptimists' about the future returns on information technology investment may be hostages to

fortune. A resurgence of inflation, perhaps induced by mechanisms unrelated to those

discussed so far, would support the advice, if not necessarily the reasoning, of the computer


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revolution sceptics.

What does this line of approach have to add concerning the relation between

productivity measurement and economic performance? Economists generally agree that afundamental standard for assessing economic performance is the improvement of social

welfare. Conventional measures of productivity growth have the virtue of being

unambiguously linked to welfare improvement, at least if one is prepared to ignore or otherwiseaccount for issues such as environmental externalities. This link may be summarised by the

maxim that social welfare is increased by expanding output and that this welfare will be further

increased if more "utility" can be obtained from the goods and services created by"transforming" inputs that represent the same or a smaller sacrifice of "utility." That

formation parallels the traditional notion of productivity, or efficiency being gauged by the ratio

of some physical measures of outputs to inputs. The shift to a "utility" metric, however,

implicitly opens the door to a far wider scope for what should be counted as output, andcorrespondingly as inputs.

Indeed, it might be thought begging the question to presuppose that the use of

information technology necessarily carries very substantial conventional productivity gains atall, inasmuch as some of the central issues in the productivity paradox are acknowledged to

revolve around the conceptual ambiguities and measureability of the economic impacts of the

new computer and telecommunications technologies. The latter are historicallyunprecedented in the readiness with which they are finding applications in the

information-intensive service sectors of the economy, where the notion of ept of "output of

constant quality" itself is a slippery construct that continues to resist direct translation into

simple, scalar measures of the task efficiency achieved in firms and industries. As has beenpointed out already, a substantial degree of uniqueness and context-dependence inheres in the

very nature of information products. The intuitive and conventionalized association of the

notion of "productivity" with the engineering concept of standardized-task-efficiency thus isbeing seriously challenged by the increasing intangibility and mutability of "outputs" and

"inputs." Rather than being easily "pinned down" for quantification, the new so-called

"weightless economy" should be seen to be floating loose in statistical space.

A range of concrete examples may help convey a better appreciation of the connection

between the expansion and increasing sophistication of "the information economy" and the

suspicion that outmoded national accounting concepts may be more and more seriouslydistorting our perception of the economy's productive performance. Were two lawyers each to

have drafted identical legal codicils, each to be attached to the will of two different clients, the

task efficiency concept of productivity would have us ask whether the effort involved -- interms of the lawyers' time and office capital used -- was the same in the two instances. Werethat found to be the case, the levels of productivity in the two situations would be judged

identical. On the other hand, the circumstances of the two clients might have been different, and

the value of having an expert draft the codicil might correspondingly differ between them,which could reflect itself in a difference in the fees the clients were willing to pay. Ought this

to be taken into account, thereby measuring the amount of "constant quality legal services" as

being different in the two instances? Other things being the same, the latter procedure would


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register a difference in the associated productivity measures?

The source of the conundrum just posed is not simply that the "meaning" or, the

economic utility of the product in question is dependent on characteristics of the consumers(which include their circumstances and subjective states); in some degree that is true in

general. The national income accountant's troubles stem from the possibility that each such

transaction in what, from the service-provider's viewpoint might be the same commodity item,can be separately provided and differently priced according to the legal needs of the client.

If this is a complication at one point in time when consumers are heterogeneous, it is equally a

problem when the circumstances of consumers change accross time. New forms of insurance,and new financial derivatives that facilitate portfolio hedging may reduce the financial risks to

which people are exposed. The increased security is worth something , and its value is

reflected in the customers' willingness to pay the commisions and premiums charged by the

vendors of these assets. With changes in external circumstances, willingness of a givencustomer may be subject to change. Should we say that the providers of such insurance

instruments have become "less productive" when the premium rates paid by the purchaser(s) is

lowered -- say, because the volatility of financial markets has been reduced by closer

integration and lower arbitrage costs, or because people with greater wealth have become morepsychologically tolerant of a given degree downside risk?

In the same vein one might view the "quantity" of medical malpractice insurance"service" received by doctors (and hospital administrators) to be well-defined in economic

welfare terms, measureable in principle by asking what real income increment that would

compensate an individual practitioner for the withdrawal of a specified incremental amount of

"cover." Do we then want to say that the volume of service represented by a given policy --and hence the "productivity" of the agent providing it -- has increased, or view it as remaining

the same, when the insurer boosts the premium rate in response to an upward trend in

jury-awarded damages to the plaintiff in suits alledging malpractice? Or should that changebe disregarded by being treated as a pure price increase rather than a "service-quality"

increase?20

20 Note that if the change in viewed as a price increase that exactly corresponded to the value of the

increased actuarial risk assumed by the insurer, one might say that more "insurance service" had been provided by

the policy in question. In making a productivity calculation, if at the margin the increased value to the customer of

being relieved of incremental risk was matched by the increased cost to the insurer of assuming that risk (i.e., no profit

occurring at the margin) then inclusion of the costs of riskbearing among the inputs should just offset the incresed

output and there would be no recored gain in measured total input efficiency (multifactor productivity).


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Like the preceding examples, this exhibits the conceptual distance between theengineer's and the economists intuitive notions of what an economys productivity is

measuring. The engineering conceptualization of productivity is that it measures the

efficiency with which the provision of a standardized, producer-defined good or service iscarried out. By contrast, the economist is more disposed to think that an economy's

"productivity" should be gauged by the ratio between the economic welfare ("utility", or "final

user satisfaction") that is yielded by the goods and services produced, and a correspondingvaluation of the inputs used up by the production process. Although latter conceptual

framework is flexible enough to permit its implementation for measurement purposes despite

the presence of heterogeneous, and increasingly intangible outputs and input, the problemposed by the growth in the importance of "information-goods" on both the input and output

sides of the production process is that the "transformations" that the latter involves are more and

more of the (immaterial) sort that go on in people's heads. Hence, they are becoming less

subject to the familiar class of constraints that material transformations are expected to obey.

At least two implications may be drawn from the latter perception of the nature of the

digital technology revolution. First, the proliferation of products that we have considered in

Section 4.2 would seem to be at odds with a traditional understanding of the link betweenproductivity and welfare. More is being produced, but the 'more' in the case is not necessarily

the same 'more' that would be measured by conventional productivity measures. What is being

produced is greater diversity in the available array of goods and services, i.e., increased varietyof choice for the consumer. Now it has long been recognised that the social welfare value of

variety is ambiguous. Product differentiation may either increase or reduce social welfare,

depending upon how consumers value the choices it provides, and the extent to which

producers use the market power it provides to raise prices (incurring deadweight losses inconsumer surplus in addition to transfers from consumer to producer surplus). Thus, even if

the hypothesised effects of marketing innovation and information technology-related

efficiencies in distribution are established, their influence on social welfare cannot beestablished without further assumptions and evidence.

Secondly, another, similarly ambiguous conclusion results from the discussion ofwhether we should expand measured output to include investments in "learning." In the

situation at hand, such sacrifices of current conventional goods and services production are

made in the course of upgrading organizational and individual labor skills, so that in the future

it will be possible to exploit the full potential of the latest vintages of computer hardware andsoftware. If the information technology skills acquired by those who entered the labor force

after 1970 are cumulative, social welfare is likely to improve as the average competence of

employees is enhanced. This would be so, even if private enterprises might not be ableindividually to capture all the benefits of the upgrading the skills of their workers andmanagers. On the other hand, if the decision to introduce new equipment, and new computer

programs is seen as having de-skilled individuals and organizations, by rendering their

technology-specific competence obsolete, the matter become more problematic. If humancapital and and organizational competence were to go on being rendered obsolete at

something close to the same pace at which information technology relevant capabilities are

being acquired, it would be fair to conclude that both the productivity and welfare promises of

8/13/2019 Digital T

Digital Tech and the Productivity Pparadox

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