Statement of Hal R. Varian

Dean, School of Information Management and Systems
UC Berkeley,
before the Subcommittee on Basic Research
of the Committee on Science
United States House of Representatives

March 16, 1999

Statement

Mr. Chairman and distinguished committee members, my name is Hal R. Varian. I am Dean of the School of Information Management and Systems at the University of California at Berkeley. I was the chair of the National Research Council committee that authored Fostering Research on the Economic and Social Impacts of Information Technology. I am also co-author, with Carl Shapiro, of the book Information Rules: A Strategic Guide to the Network Economy, published by Harvard Business School Press.

I am here to talk today about research in the economic and social aspects of computing and communications.

It is widely recognized that there has been a revolution in computer and communications technology in the last two decades. This revolution is due, in large part, to Federal funding of basic research more than twenty years ago, and I join with my colleagues in urging that funding for basic research in this area be increased.

This basic research in computer science has had, and will continue to have, a major impact on our economy and society. Information technology has accounted for 1/3 of the productivity growth since 1992 and has created millions of jobs. The World Wide Web has exploded from virtually nothing in 1994 to a vast information network in just a few short years, and it has become clear that it will have a profound impact on the way we work, play and educate.

Information technology will also have a significant impact on law, education, commerce, organizations, and communities. Policy choices made now, such as definition of technological and legal standards, will be with us for a long time, and attention must be paid not only to their technological merit, but also their social and economic impact.

There have been several research studies that have contributed to our understanding of the social impact of computing and communications. For example, economic studies of auctions contributed to the design of the FCC airwave auctions; sociological studies of technical support communities contributed to better practices in documentation and usability; and historical studies of intellectual property issues have shed light on current policy debates.

But there is much more to be done. The Telecommunications Act of 1996 mandates subsidized access to schools and libraries, yet we have almost no understanding of how the Internet is being used in these environments. Electronic commerce has grown dramatically in just the last two years, but we have little understanding of how these industries will evolve, and what policies are appropriate for taxation, privacy, content management, and liability in these industries. Users of the World Wide Web are fascinated by the wealth of content, but are also frustrated by the difficulty of finding reliable, accurate, and relevant information. We need better tools to manage information at the individual, organizational, and societal level.

Federal funding for research in Social, Behavioral and Economic Sciences is small: it occupies less than 4% of the National Science Foundation's budget. And of this amount, only a small fraction is devoted explicitly to social impact of computing and communications.

Research in this area is desperately needed. Due to the success of the basic research funded in the seventies and eighties, the major engineering question facing those deploying technology is not so much ``how to build'' but rather ``what to build.'' But ``what to build'' is, ultimately, a social and economic question. We all hope that information technology can help us build a more prosperous, fulfilling, and democratic future. We will have a much greater chance of accomplishing this goal if we understand the social and economic consequences of our technological choices.

Examples of Social Science Research

These examples, some of which are taken from the National Research Council Report Fostering Research on the Economic and Social Impacts of Information Technology, illustrate the breadth of topics amenable to social science research.1

Residential Broadband

Much of the discussion about the desirability of residential broadband has taken place in a vacuum, since no one really knows how much people are willing to pay for bandwidth. Berkeley's INDEX project, managed by Pravin Varaiya and myself, and supported by the National Science Foundation, is investigating the willingness to pay for bandwidth. We have done this by providing metered ISDN service to a sample of users, and varying the prices that they face each week. This has allowed us to see how usage responds to changes in prices. We have experimented with a variety of pricing schemes, including bandwidth price, per bit pricing, flat rate pricing, and so on. We have found, among other things, that users are very sensitive to bandwidth pricing, while relatively insensitive to per-bit pricing.

If network access becomes widely available, how will people use it in the home? Carnegie Mellon University's HomeNet Project attempts to answer this question by giving 100 Pittsburgh area residents computer equipment, subsidized access to the Internet, and training in using both their computers and the Internet. Through detailed, ongoing questionnaires and electronic data collection, Internet usage and its effects on participants' lives can be studied and analyzed in unprecedented detail.

The 1996 Telecommunications Act has mandated subsidized Internet access by schools and libraries. How do children use computers and the Internet, and how is their use evolving? The University of Michigan's Child Development Study is examining how children from 2,500 families use their time, including detailed reports on computer usage. The study records time reports from parents, teachers, and the children themselves.

These studies are not cheap--they require recruiting human subjects, providing them with equipment, and monitoring their behavior over extended periods of time. Yet this sort of careful study is the only way that we can learn about how computers are affecting people in their homes and schools.

Electronic Commerce

In Information Rules: A Strategic Guide to the Network Economy, Carl Shapiro and I examine five aspects of competitive strategy in information industries. Although the intent of our book is to offer practical advice for businesses operating in technology-realated industries, each of the topics we examine raises policy questions.

Differentiation of products and prices.
The high first-copy costs of information inevitably lead to price and product differentiation. Mass customization, differential pricing, personalized content, and versioning are ubiquitous strategies in information industries. When do these strategies operate in the social interest, and when do they confer unfair advantages to dominant firms?
Rights management.
Firms should manage their intellectual property to maximize its value, not to maximize its protection. How should intellectual property policy be designed to facilitate production and dissemination of information?
Lock-in.
Since information technology products work in systems, switching any single product can cost users dearly. The lock-in that results from such switching costs confers a huge competitive advantage to firms that manage their installed base of customers effectively. What forms of competition policy are appropriate to deal with technological lock-in?
Positive feedback.
Network externalities are ubiquitous in information industries, which leads to intense competition and winner-take-all markets. Will market forces alone lead to desirable outcomes in such industries?
Standards and alliances.
Information technology strategy often requires you to build alliances around common standards. What is the government's role in facilitating and coordinating such standards creation?

Productivity Paradox

The rapid pace of technological change in computing and telecommunications has been astounding. However, it has been hard (at least until very recently) to find evidence for improvements in productivity as a result of these dazzling technological innovations. This ``productivity paradox'' was waggishly summarized in a comment attributed to Solow: ``Computers are showing up everywhere except in the productivity statistics.'' (See Brynjolfsson (1993), Attewelll (1994), and Sichel (1997) for empirical studies of the productivity paradox.)

While the various scientific and engineering disciplines excel at producing technological developments, understanding how these developments lead to greater productivity is a quite different matter. Replacing old information technology for new while retaining the same work practices and organizational structure may have little impact on productivity. The true measure of the technology's worth can only be evaluated when work practices and organizational structures are revamped to best take advantage of the flexibility and power of today's computing and communication technologies.

The subtle process of extracting productivity gains out of technological advancements has been the subject of much scrutiny by social scientists. One particularly relevant and illuminating study is by David (1990); it discusses the Electric Dynamo and its role in an earlier ``productivity paradox.'' At the turn of the century, electrification was seen, much as computers are today, as a transformational technological advance whose impact would soon be widely felt. However, factory electrification did not have much impact on productivity growth in manufacturing before the 1920s.

``The proximate source of the delay in the exploitation of the productivity improvements potential incipient in the dynamo revolution was, in large part, the slow pace of factory electrification. The latter, in turn, was attributable to the unprofitability of replacing still serviceable manufacturing plants embodying production technologies adapted to the old regime of mechanical power derived from water and steam.'' (David (1990))

The first phase of electrification (from the mid 1890's to 1920), mainly utilized the ``group drive'' system of power transmission. This entailed minimal changes to the basic factory design, and essentially replaced the old mechanical power system with an electric one. However, in the 1920, the ``unit drive'' approach (where individual motors powered each piece of equipment) was widely adopted. The benefits of this approach were not limited to the immediate savings due to greater energy efficiency. In fact, the greatest benefits derived from the ability to build lighter, and more modular, single story factories using this new technology. Learning how to do best utilize this flexibility was not immediate:

``Although all this was clear enough in principle, the relevant point is that its implementation on a wide scale required working out the details in the context of many kinds of new industrial facilities, in many different locales, thereby building up a cadre of experienced factory architects and electrical engineers familiar with the new approach to manufacturing.'' (David (1990))

The analog of this story for the computer has yet to be written. While there are encouraging reports (see Brynjolfsson and Hitt (1996,1997)) that perhaps the productivity paradox is no more, there yet remains substantial work to be done in understanding what work practices and organizational structures are optimal in this new computer age. How will we develop modern counterpart to David's ``cadre of factory architects''? That is the challenge facing the social scientists studying the new industrial frontier.

Inequality

One of the most striking changes in the economic landscape of the United States over the past 20 to 30 years has been a dramatic increase in inequality of earnings. A growing number of researchers suspects that technological change in general, and computerization in particular, may be part of the explanation. While there was relatively little change in the dispersion of wages in the 1950s and 1960s, starting in the 1970s wage inequality increased rapidly. Per capita income and family income show similar patterns. Interestingly, the changes in inequality are evident across virtually every income subgroup: the wages for those at the 95th percentile increased relative to those at the 90th percentile, which in turn outpaced those at the 85th percentile and so on down to the poorest people in the country.

While the rise in inequality has been well-documented in the academic literature (see Levy and Murnane (1992) and Gottschalk (1997) for reviews), there is not yet a consensus as to its causes. However, much of the increase in inequality seems to be related to a growing premium for skilled workers throughout the economy. For instance, the premium paid to college-educated worker and those with more experience has grown significantly. Since skilled workers were already at the top of the wage distribution, any increase in their relative wages will tend to increase overall inequality. Furthermore, because the supply of college educated workers has grown over the past several decades, the fact that their relative wages have increases indicates that the demand for such workers has grown even faster.

The increased demand for these workers cannot easily be explained by changes in the composition of industry output or other observable factors so ``technical change,'' typically a residual in wage equations, has been left as the best explanation. More direct evidence that technical change is behind the growth in inequality was provided by Berman et al. (1994). They found that the rate of investment in computers was positively correlated with higher demand for skilled workers relative to less skilled workers. This finding clearly runs counter to the claim that computers ``deskill'' work, as some have claimed. While this is clearly the case in certain applications, the findings of Berman, Bound and Griliches suggest that it is not true on average.

The mechanism by which computers increase the relative demand for skilled work is still not well understood. There are at least 5 distinct possibilities.

Existing measures of income inequality do not consider the non-market goods and services that people consume. However, a significant share of many peoples well-being is derived from factors that are not counted in traditional income. For instance, if people find that working with computers is more (or less) enjoyable than it was before the work was computerized, then this my exacerbate (or mitigate) the increase in inequality. Unfortunately, there is relatively little data on the extent to which people value non-market services and virtually none on how computerization might affect such services.

Technical Support Communities

In the mid-1980s, anthropologist Julian Orr conducted extensive field work among Xerox service repair technicians (Orr (1990)). One of his findings was that technicians never relied exclusively, or sometimes even at all, on the company-provided service manuals when trouble-shooting machine problems. Often the manuals were out of date or did not address local, idiosyncratic problems. Instead, or in addition, they used war stories passed from technician to technician in an oral story-telling culture. Orr pointed out the value of these stories to corporate management, noting that they represented an important intellectual resource that the company should capitalize upon. Partly inspired by Orr's work, a development team spent a long time in the field, learning what would be useful to technicians from their point of view. Based on their fieldwork they built a system to leverage technicians' local knowledge through a community-validated tips database. A ``tip'' is a problem-cause-solution case that is written and submitted by anyone in the field service organization and validated by technical specialists. When the tip is released to the field, it carries the name of both the submitting technician and the validator on it. In one field trial with 1300 field support people, about 15% of the employees submitted tips and the tips data base was accessed over 1,000 times a day. (Bell et al. (1997))

Federal Funding for Research and Development

The following table is based on data from National Science Foundation, Federal Funds for Research and Development: Fiscal Years 1994, 1995, and 1996, Vol. 44, Detailed Statistical Tables, NSF 97-302. It shows the fraction of the total budget of the Social, Behaviorial and Economic (SBE) division of the NSF, along with the total spending by the Federal government on social science research. Note that this is all social science; spending on social science relating to information technology research is only a small fraction of these numbers.


 
Table 1: Federal spending on Social, Behavioral, Economic (SBE) Research. Figures in millions of dollars.
Year SBE NSF Percent Federal NSF Table
  division total SBE social percent number
1994 65.714 2040.358 3.2 655.037 10.0 C19
1995 75.947 2145.369 3.5 740.768 10.3 C20
1996 80.712 2303.056 3.5 740.703 10.9 C21

Biography

Hal R. Varian is the Dean of the School of Information Management and Systems at UC Berkeley. He is also a professor in the Haas School of Business, a professor in the economics department, and holds the Class of 1944 Chair at Berkeley. He received his S.B. degree from MIT in 1969 and his MA (mathematics) and Ph.D. (economics) from UC Berkeley in 1973. He has taught at MIT, Stanford, Oxford, Michigan and several other universities around the world.

Dean Varian is fellow of the Guggenheim Foundation, the Econometric Society, and the American Academy of Arts and Sciences. He has served as Co-Editor of the American Economic Review, and as an Associate Editor of the Journal of Economic Perspectives and the Journal of Economic Literature.

Professor Varian has published numerous papers in economic theory, industrial organization, public finance, econometrics and information economics. He is the author of two major economics textbooks which have been translated into 10 languages. His current research involves the economics of information technology. In particular, he is investigating investigating strategic issues in technology management, the economics of intellectual property, and public policy surrounding information technology.

His homepage is at http://www.sims.berkeley.edu/~hal.

Disclosure

I am currently co-PI on an NSF Grant, ``Demand for quality-differentiated network services,'' which was awarded $598,081 for the period 08/15/97 - 08/14/00.

Bibliography

Paul Attewelll.
Information technology and the productivity paradox.
In Douglas Harris, editor, Organizational Linkages: Understanding the Productivity Paradox. National Academy Press, Washington, DC, 1994.

David G. Bell, Daniel G. Bobrow, Olivier Raiman, and Mark H. Shirley.
Dynamic documents and situated processes: Building on local knowledge in field service.
In Toshiro Wakayama, Srikanth Kannapan, Chan Meng Khoong, Sham Navathe, and JoAnne Yates, editors, Information and Process Integration in Enterprises: Rethinking Documents. Kluwer Academic Publishers, Norwell, MA, 1997.

Eli Berman, John Bound, and Zvi Griliches.
Changes in the demand for skilled labor within U.S. manufacturing: Evidence from the annual survey of manfacturers.
The Quarterly Journal of Economics, pages 367-398, May 1994.

Erik Brynjolfsson.
The productivity paradox of information technology.
Communications of the ACM, 26(12), 1993.
http: //ccs. mit.edu/erik.html.

Erik Brynjolfsson and L. Hitt.
Paradox lost? firm-level evidence on the returns to information systems spending.
Management Science, 1996.

Erik Brynjolfsson and L. Hitt.
Computers and productivity growth: Firm-level evidence.
Technical report, MIT Sloan School, 1997.

Paul A. David.
The dynamo and the computer: An historical perspective on the modern productivity paradox.
American Economic Review, 80(2):-61, 1990.

Martha Feldman and James March.
Information in organizations as signal and symbol.
Administrative Science Quarterly, 26:-186, 1981.

Peter Gottschalk.
Inequality, income growth and mobility: The basic facts.
Journal of Economic Perspectives, 11(2):-40, 1997.

Alan Kreuger.
How computers have changes the wage structure: Evidence from microdata, 1984-1989.
Quarterly Journal of Economics, 108:-60, February 1993.

Frank Levy and Richard J. Murnane.
U.S. earnings levels and earnings inequality: A review of recent trends and proposed explanations.
Journal of Economic Literature, 30:-81, September 1992.

Jerome S. Mark.
Technological change and employment: Some results from BLS research.
Monthly Labor Review, April 1987.

Julian E. Orr.
Talking about Machines: An Ethnography of a Modern Job.
PhD thesis, Cornell University, 1990.

Andrew Sichel.
The Computer Revolution: An Economic Perspective.
Brookings Institution Press, Washington, DC, 1997.



Footnotes

... research.1
The authors of the report were Hal R. Varian (chair), Frances Allen, Erik Brynfolfsson, Jorge Schement, Scott Shenker, Lee Sproull, and Richard Sutch.


Hal Varian
1999-03-11