A Greater Appreciation for the Contribution and Value of Some Intangibles (particularly "free" intangibles)?

In a recent speech titled, “Trucks and Terabytes: Integrating the 'Old' and 'New' Economies,” at the 61st Annual Meeting of the National Association for Business Economics, Federal Reserve Chairman Jerome H. Powell challenged the underlying data concerning measurements of economic growth.  He asks: “with terabytes of data increasingly competing with truckloads of goods in economic importance, what are the best ways to measure output and productivity? Put more provocatively, might the recent productivity slowdown be an artifact of antiquated measurement?”  In considering the question, here are his comments: 

How Should We Measure Output and Productivity?
Let's now turn to the second question of how to best measure output and productivity. While there are some subtleties in measuring oil output, we know how to count barrels of oil. Measuring the overall level of goods and services produced in the economy is fundamentally messier, because it requires adding apples and oranges—and automobiles and myriad other goods and services. The hard-working statisticians creating the official statistics regularly adapt the data sources and methods so that, insofar as possible, the measured data provide accurate indicators of the state of the economy. Periods of rapid change present particular challenges, and it can take time for the measurement system to adapt to fully and accurately reflect the changes in the economy.

The advance of technology has long presented measurement challenges. In 1987, Nobel Prize–winning economist Robert Solow quipped that "you can see the computer age everywhere but in the productivity statistics."⁶ In the second half of the 1990s, this measurement puzzle was at the heart of monetary policymaking.⁷ Chairman Alan Greenspan famously argued that the United States was experiencing the dawn of a new economy, and that potential and actual output were likely understated in official statistics. Where others saw capacity constraints and incipient inflation, Greenspan saw a productivity boom that would leave room for very low unemployment without inflation pressures. In light of the uncertainty it faced, the Federal Open Market Committee (FOMC) judged that the appropriate risk‑management approach called for refraining from interest rate increases unless and until there were clearer signs of rising inflation. Under this policy, unemployment fell near record lows without rising inflation, and later revisions to GDP measurement showed appreciably faster productivity growth.⁸

This episode illustrates a key challenge to making data-dependent policy in real time: Good decisions require good data, but the data in hand are seldom as good as we would like. Sound decisionmaking therefore requires the application of good judgment and a healthy dose of risk management.

Productivity is again presenting a puzzle. Official statistics currently show productivity growth slowing significantly in recent years, with the growth in output per hour worked falling from more than 3 percent a year from 1995 to 2003 to less than half that pace since then.⁹ Analysts are actively debating three alternative explanations for this apparent slowdown: First, the slowdown may be real and may persist indefinitely as productivity growth returns to more‑normal levels after a brief golden age.¹⁰ Second, the slowdown may instead be a pause of the sort that often accompanies fundamental technological change, so that productivity gains from recent technology advances will appear over time as society adjusts.¹¹ Third, the slowdown may be overstated, perhaps greatly, because of measurement issues akin to those at work in the 1990s.¹² At this point, we cannot know which of these views may gain widespread acceptance, and monetary policy will play no significant role in how this puzzle is resolved. As in the late 1990s, however, we are carefully assessing the implications of possibly mismeasured productivity gains. Moreover, productivity growth seems to have moved up over the past year after a long period at very low levels; we do not know whether that welcome trend will be sustained.

Recent research suggests that current official statistics may understate productivity growth by missing a significant part of the growing value we derive from fast internet connections and smartphones. These technologies, which were just emerging 15 years ago, are now ubiquitous (figure 3). We can now be constantly connected to the accumulated knowledge of humankind and receive near instantaneous updates on the lives of friends far and wide. And, adding to the measurement challenge, many of these services are free, which is to say, not explicitly priced. How should we value the luxury of never needing to ask for directions? Or the peace and tranquility afforded by speedy resolution of those contentious arguments over the trivia of the moment?

Researchers have tried to answer these questions in various ways.¹³ For example, Fed researchers have recently proposed a novel approach to measuring the value of services consumers derive from cellphones and other devices based on the volume of data flowing over those connections.¹⁴ Taking their accounting at face value, GDP growth would have been about 1/2 percentage point higher since 2007, which is an appreciable change and would be very good news. Growth over the previous couple of decades would also have been about 1/4 percentage point higher as well, implying that measurement issues of this sort likely account for only part of the productivity slowdown in current statistics. Research in this area is at an early stage, but this example illustrates the depth of analysis supporting our data-dependent decisionmaking.

The full speech is available, here.  The paper concerning measuring value using volume of data, titled, "Accounting for Innovations in Consumer Digital Services: IT Still Matters," is available, here.  

"The winner takes it all" (or at least most), productivity and frontier companies: how does IP fit in?

The Economist magazine recently discussed (“The great divergence’, November 12th) an (unnamed) research report carried out by three researchers at OECD (Dan Andrews, Chiara Criscuolo and Peter Gal), which suggests that the Schumpeterian notion of “creative destruction” may be stuck in neutral. Leading companies seem more and more to be enjoying a continuing lead in their industries, with less and less challenges from scrappy newcomers.

In particular, the report found a major distinction in productivity between the top 5% companies surveyed. These so-called “frontier” companies show productivity gains of 2.6% per year, while the remaining 95% have managed only 0.6% productivity gains. The difference in productivity is even more stark when comes to services: 3.6% for the frontier companies as compared to only 0.4% for the stragglers. Two major themes relating to IP emerge from The Economist article: (i) the role of patents and know-how; and (ii) the transmission mechanism for innovation.

The role of patents and know-how—Regarding patents, the report states that frontier companies “[u]nsurprisingly …are ahead of the pack in technological terms, and they make much intensive use of patents.” No more explanation is provided, which is a shame, because the statement as provided is not entirely clear. How does one measure “intensive use of patents”; is it a quantitative or qualitative analysis? Is it really the case that a major indicium that distinguishes between the frontier companies and the laggards is patent activity? One need only think of the large patent portfolios that were sold several years ago by failing companies such as Kodak and Nortel. It is a pity that the article does not elaborate.

Of equal interest is the role of know-how. The article writes that “…frontier firms (the 5%) have each discovered their own secret sauce”, going on to describe the know-how that has enabled companies such as 3G Capital (a successful, Brazilian-based private equity firm), Amazon, and BMW to dominate. The linkages between the patent position and the development of special know-how tailored to each of these companies’ activities suggest that the two work in tandem.

If so, even the most sophisticated patent analytics may be missing a crucial component in seeking to explain the success of technology-based companies. What may be needed is a metric measuring the contribution of know-how, which can then be applied together with patent analytics to provide a more robust picture of the IP position of these companies, and whether any generalizable insights can be obtained.

The transmission mechanism for innovation-- Here, the article focuses on how technology spreads horizontally between companies that are members of the top 5% as well as vertically within a given economy. The suggestion is made that with respect to frontier companies—

“…technological innovations from the frontier are spreading more rapidly across countries than they are within them. The gap between an elite British firm and an elite Chinese firm is narrowing even as the gap between an elite British firm and its laggardly compatriots is expanding.”

The upshot is that—

“…technological diffusion has stalled: cutting-edge ideas are not spreading through the economy in the way that they used to, leaving productivity-improving ideas stuck at the frontier.”

The result is what has been termed a “winner takes all (or at least most)” position in the relevant market. Schumpeterian notions of “creative destruction” are less likely to apply because not only do the frontier companies better exploit their patent/know-how mix, but they are able to attract the most talented persons in their industry. In such a scenario, continuing incumbency as an industry leader becomes more of the norm.

The causal direction of this relationship is not entirely clear, i.e., do more talented people lead to a continued stream of better patents and know-how, or is it the reverse, or are they merely coincident factors in connection with productivity and market dominance? Of perhaps greater concern is the suggestion that useful IP, particularly patents, will be increasingly the purview of only the top layer of companies, with less and less vertical transmission within the relevant industry. When leavened together with unique know-how, this combination gives rise to the increasingly expressed concern that IP, particularly patents, are more an instrument for maintaining market power than a facilitator of broad-based innovation.