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Unbalanced Data Leads to Obsolete Economic Advice

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Unbalanced Data Leads to Obsolete Economic Advice, illustration

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The high technology industry is recognized as being a major driver of the current economy. I am concerned about how poorly its role is understood in governmental decision making. Computer scientists do express concerns about disturbing trends.9 An early study sponsored by ACM was based on opinions, rather than data.1 Similar discussions address other high-technology engineering disciplines.2 Analyses of relevant data should be the basis for decision making. Having "big data" raises high expectations.7 But there are two related lacunae:

  • Most analysts ignore the mechanisms that drive high technology and the intellectual origin of contents in the products being marketed.
  • The data needed to measure the business interactions involving intellectual products within and among high technology enterprises is unavailable to economists.

In this Viewpoint, I expand on these two factors, which lead to misleading advice and imbalanced decision making.

Our leading economists have grown up and been educated in a time when financial capital and cheap labor were the crucial contributors to growth.8 Building aircraft, automobiles, as well as the steel mills and machine shops that supplied them, all depended on much labor and substantial financial capital. These industries were associated with known locations, and their products were costly to ship. Geography was an important factor.

The world has changed. The post-industrial economy is based on intellectual capital, the experts, and the intellectual property (IP) they generate. The Apples, Microsofts, Googles, and the many smaller, hipper players that create an ever-larger fraction of the goods people purchase are not strapped for financial capital. The GEs, Intels, and similar enterprises that do require costly factories have moved much of the labor-intensive production of their tangible products overseas. The critical intangibles embedded in chips, phones, and computers are transmitted from their origin to far-away factories. Much research, development, testing, and prototyping, and the equally important market research and promotion activities remain in the U.S., complemented with laboratories in the EU and Asia.

Intangible products can be copied at negligible costs and shipped freely worldwide over the Internet. Containerized shipping has similarly reduced the costs of distributing the high-technology tangible products. It costs only approximately $0.50 per product to send a pallet stacked with iPads anywhere in the world. Computerized logistics minimizes inventory investments. Online payment systems allow revenues from worldwide sales to be collected anywhere, preferably in locations that do not insist on excessive reporting to their government agencies.

All these inputs to the modern economy need intellectual capital. But the prominent economists, those that have risen to the level of providing advice to governments, continue to focus on financial capital for their metrics and tools. For instance, keeping interest rates low helps primarily the traditional segments of industry, but does very little for high-technology enterprises.

However, one should not blame the economists. They depend on production and cost data derived from corporate financial results. They may also use income data from tax revenues. For tangibles and money such data is reported down to the pennies by accountants and presented in annual reports and aggregated for economists' think tanks. However, for high-tech enterprises operating globally, these "booked" values tend to be a fraction, about 20% on the average, of the market value investors assign to the corporations. Reported book values include the financial assets held outside the U.S. in tax havens as tangibles, held there for potential offshore investment by blocker statements, as being "subject to management's decision to indefinitely reinvest those earnings."5 Keeping U.S. capital costs low discourages repatriation of those funds for investment in the U.S.3

Computer professionals are at the center of the storm that surrounds the industry.

However, investors in high-technology businesses value an enterprise according to future expectations, not by past and current costs. They count on future income due to the smart people and the IP they generate and exploit to make attractive products.10 Predicting the future success of their results is always risky, but critical to understand high-technology enterprises. Avoiding the collection of suitable data because of risks and imprecision is not acceptable.

What data can be collected to drive future analyses? Amounts spent on research, development, maintenance, and marketing are available within businesses. Reporting it consistently can provide useful aggregations by industry. The maturity of an enterprise should be taken into account, since a Twitter is bound to present a different profile than a Microsoft. Venture capitalists do estimate the overall leverage of their investments and develop useful insights, but rarely share them beyond their peers. Prices of startup exits and merger prices reflect rational expert opinions. Stock market prices represent the wisdom of the investing crowd. While such data is not based on verifiable accounting data, in the aggregate it is as realistic as values for the tangibles listed on corporate books.

Economic analyses now cannot measure the value of the intellectual capital—the technological and marketing experts, the management, and IP—the factors that drive modern industry. Ignoring its contribution in decision making means the needed infrastructure—education, training, communication, as well as protection against external threats—is short-changed, since there is no documentable path of such investments to the outputs of modern industry. There are many anecdotes, and calls to allow more or less immigration of knowledge workers. But these are not placed into a broad coherent economic model.

Still, few computer scientists and technological workers worry about their role in the economies of their industries and their countries. They are willing to advocate for more education, ubiquitous Internet access, and job security. A complicating issue is that some experts advocate software should be free. That implies they expect to be supported by public funds or maybe by tax-deductible donations. Without support from professional experts little change can be expected.6 Computer professionals are at the center of the storm that surrounds the industry. They should not just observe the effects, but try to provide data, analyses, and mechanisms so they will affect the world around them. Some modern economists will be pleased if more data becomes available.4

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1. Aspray, W., Mayadas, F., and Vardi, M.Y., Eds. Globalization and Offshoring of Software; A Report of the ACM Job Migration Task Force, ACM, 2006.

2. Charette, R.N. The STEM crisis is a myth. IEEE Spectrum, (Aug. 30, 2013).

3. Damodaran, A. Unlike the U.S. tax code, Apple is perfectly rational. Financial Times (May 7, 2013).

4. Damodaran, A. The Aging of the Tech Sector: The Pricing Divergence of Young and Old Tech Companies. Musings on Markets,

5. Fleischer, V. Overseas cash and the tax games multinationals play. New York Times (Oct. 3, 2012).

6. Gibbs, R. Leveling the Playing Field: Curbing Tax Havens and Removing Tax Incentives For Shifting Jobs Overseas. The White House (May 4, 2009).

7. Jagadish, H.V. et al. Big data and its technical challenges. Commun. ACM 57, 7 (July 2014), 86–94.

8. Nasar, S. Grand Pursuit: The Story of Economic Genius. Simon & Schuster, 2011.

9. Vardi, M. Is information technology destroying the middle class? Commun. ACM 58, 2 (Feb. 2015), 5.

10. Wiederhold, G. Valuing Intellectual Capital, Multinationals and Taxhavens. Management for Professionals, Springer Verlag, New York, Aug. 2013.

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Gio Wiederhold ( is Professor (Emeritus) of Computer Science, Medicine, and Electrical Engineering at Stanford University, Stanford, CA.

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The Digital Library is published by the Association for Computing Machinery. Copyright © 2016 ACM, Inc.


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