By quantifying the unmeasured, Fed economists shed light on the stock market, productivity and the development of dynamic economic theory.
Published December 1, 2005 | December 2005 issue
Not to belittle Adam Smith’s powers of observation—he did notice that hand, after all—but when he hoped to understand productivity in the 18th century, he had only to visit a pin factory.
One man draws out the wire, another straightens it, a third cuts it, … and the important business of making a pin is, in this manner, divided into about eighteen distinct operations.
In recent decades, it seems, the sources of productivity have been more difficult to observe and (forgive me) pinpoint. In the 1980s, for example, many assumed that information technology would improve productivity, but the data showed nothing of the sort. “[W]hat everyone feels to have been a technological revolution,” wrote economist Robert Solow in 1987, “has been accompanied everywhere … by a slowing-down of productivity growth, not by a step up. You can see the computer age everywhere but in the productivity statistics.”
And in the 1990s, Fed Chairman Alan Greenspan based monetary policy in part on his sense that productivity growth was allowing expansion without inflation. But the data, again, showed nothing. Asked later about this intuition, Greenspan made an analogy to the discovery of Pluto: Astronomers looked for a new planet because the movement of other planets could only be explained by an unobserved celestial body.
If productivity is confusing, the stock market has been inscrutable. Just before it fell in 2000, some economists claimed the market would rise to “Dow 36,000” while others were certain it would plummet. No one seemed to have a handle on what equities were truly worth. Nor could anyone explain why stocks had nearly doubled in value since the 1960s.
But over the past five years, Minneapolis Fed economists Ellen McGrattan and Ed Prescott have generated a body of work that has dramatically advanced understanding in both areas. Their research—based on theory driven by data, rather than intuition or astronomy—explains why most economists and statisticians have been unsuccessful in tracking productivity and understanding stock market value. More importantly, it presents a picture of U.S. macroeconomic performance that is, in many respects, at odds with the conventional wisdom—precisely because that “wisdom” relies on incomplete measurement.
In specific, McGrattan and Prescott have found that—contrary to official statistics—productivity surged dramatically in the late 1990s, as did corporate profits and investment. Their research also confirms that the stock market was fairly valued early in 2000, prior to its dramatic decline, and slightly undervalued right before the October 1929 stock market crash. Moreover, they provide a cogent explanation of why equity values nearly doubled between the 1960s and the 1990s in both the United States and the United Kingdom. In a word: taxes.
These McGrattan-Prescott papers are important for what they reveal about productivity, markets and the macroeconomy, certainly, but also because they provide a lucid demonstration of how economic thought develops, from initial inspiration and modeling to refinement, critique and further modification. And then new inspiration—never quite final, always evolving.
At the core of this work lies intangible capital—a reality as amorphous, yet real, as Smith’s invisible hand. The term includes corporate assets that can’t readily be touched, things like research and development, patents, trademarks, skills training, advertising and investments in organization-building.
“Virtually all of the value of Microsoft is intangible capital,” observes Prescott, in a recent interview. Prescott, a 2004 Nobel laureate in economics for his work on business cycles and monetary policy, is a senior monetary adviser at the Minneapolis Fed and professor of economics at Arizona State University. “The same is true of Cisco. Or Coca-Cola with its brand name or drug companies with their patents.” As McGrattan puts it, “If you went into Microsoft and counted up the value of the desks, there wouldn’t be much.”
But while these examples of intangibility give a sense of the economists’ thinking, their true working definition is more specific. “Intangible investments,” says McGrattan, also a Fed monetary adviser and an adjunct professor at the University of Minnesota, “are those that are treated in government statistics as operating expenses; most of these, it turns out, are not touchable.”
In the national income and product accounts (NIPA), the federal government’s official statistics on economic activity, intangible capital is dealt with differently than tangible capital, in part because accountants find it very difficult to measure. Expenditures on intangible goods are often made within business enterprises, so an objective “arm’s-length” market value is hard to establish. Also, the physical boundaries of intangibles are a bit nebulous, so intangibles are easily shared, or “appropriated” by others, making ownership difficult to attribute.
Due to these measurement problems, accountants generally treat spending on intangibles not as an investment that will result in future profit but as a current expense. And as such, intangible capital is largely neglected when accountants establish their estimates of corporate value. (Not all intangible capital is left off the accounts; software, for instance, is included.)
What are you buying?
The larger implications of this seemingly arcane statistical detail become clear when McGrattan and Prescott examined the stock market in their Fall 2000 Quarterly Review article, “Is the Stock Market Overvalued?” In this research, the economists carefully demonstrated that in the first half of 2000, the value of the U.S. stock market was equal to the combined value of the underlying corporations’ assets. Thus, they concluded at the time, the market was fairly valued. (In later work, they refined this conclusion—bear with me.)
Most economists who look at this problem examine only tangible assets. For them, the fair market price for a hardware store—or a hardware company, for that matter—would equal the cost of replacing its inventory of tools and material, plus the building itself and the land it stands on—all very tangible stuff.
For the entire stock market, then, the conventional economist’s comparison would be between the market value of all corporate equities and the cost of replacing all tangible assets owned by those corporations. Looking at the issue in 1969, Yale economist James Tobin concluded that “the value of capital relative to its replacement cost”—a ratio since called “Tobin’s q”—should be 1 in equilibrium; otherwise, either the market is overvaluing capital or companies should buy more assets.
But McGrattan and Prescott point out that this perspective neglects two important factors: intangible investment and taxes. The first—intangibles—is a reality that official statistics simply don’t measure. In the hardware store analogy, it would mean coming up with the cost of replacing, for instance, the previous owner’s reputation or his staff’s know-how. The figures are hard to establish. But if they’re overlooked, the level of investment is dramatically underestimated.
And the second—taxes—affects the value of capital. Because of taxes, show McGrattan and Prescott, the value of capital isn’t equal to the cost of replacing it, as in Tobin’s equilibrium formula. Rather, taxes create a gap between the cost of investing and the actual value of that investment.
The relevant tax in this situation is the corporate income tax, and it affects the price of intangibles, not the price of tangibles. Because outlays on intangible investment are a business expense rather than a capital expenditure, they reduce taxable corporate income. So if a pharmaceutical company spends $50 million on drug research (an intangible investment), its taxable income declines—meaning that tax rates will have implications for corporate decisions regarding such outlays, and moreover, that the value of such investing will be lower than the cost.
In their model, therefore, McGrattan and Prescott take pains to estimate and include a figure for the U.S. tax rate on corporate income. It seems obvious in retrospect, but it’s a factor that financial economists have largely ignored.
Here’s how they do the math. First they establish the value (the “market capitalization”) of the entire U.S. stock market in the first half of 2000: 1.84 times gross national product. Then they total up the other half of the equation: the cost of replacing the assets of the underlying corporations. Measured tangible capital as reported by the Bureau of Economic Analysis (BEA) is 0.821 times GNP. Including inventories and land brings the figure up to 1.042 GNP. Adding in the value of U.S. foreign subsidiaries (0.382) brings the sum to 1.424 GNP.
Without intangible capital, then, the stock market would have been substantially overvalued: 1.84 GNP market value vs. 1.424 GNP worth of corporate assets. Tobin’s q would be far greater than 1. But here are the McGrattan and Prescott innovations. They estimate the stock of intangible capital by calculating the rate of return on tangible capital, assuming an equal return on intangibles and backing out a figure for intangible capital stock: 0.645 times GNP. And then, because the government taxes corporate income, and investment in intangibles is counted as a business expense, which reduces income, the value of intangible capital is reduced by the corporate tax rate, which they estimate at 35.6 percent. That leaves a value for intangible capital of 0.415 times GNP (= 0.645 GNP – (0.645 GNP x 35.6%)).
Adding that to the figures for tangible and foreign capital (1.424 GNP), they arrive at a total of 1.839 GNP, virtual equality with the value of the U.S. stock market. “According to standard economic theory,” they write, “the stock market today is correctly valued.” (But remember, as their work evolved, this conclusion had to be revised.)
Before the fall
The economists use essentially the same technique to estimate the value of the stock market in August 1929, shortly before the October 1929 crash. At the time, famed Yale economist Irving Fisher stated that the market was slightly undervalued, a judgment that seemed ill-founded after the crash. Fisher had made a fortune with his invention of what would later be known as the Rolodex; in the crash he lost both wealth and reputation. But McGrattan and Prescott find that Fisher was on the money, so to speak, and they state it unequivocally in the title of their December 2003 staff report 294, “The 1929 Stock Market: Irving Fisher Was Right.”
First, the Fed economists come up with a figure for stock market value in 1929. Based on several sources, they suggest that the best estimate is 1.54 times GNP, but because they want to be conservative in evaluating Fisher, they choose a somewhat higher estimate of 1.67 GNP, based on the Standard & Poor’s composite price index of 90 companies.
Again, the question is whether the market was too high, as it seemed after the crash, or too low, as Fisher suggested. To answer it, McGrattan and Prescott must derive an estimate of what they call the “fundamental value” of U.S. corporations at the time: “the value of the underlying productive assets—both tangible and intangible—of the corporate sector.” The economists consult historical records from the BEA and the Internal Revenue Service and find that the cost of tangible capital—structures, equipment, inventories and land—is 1.4 times GNP.
At this point, the economists introduce another innovation: accounting for taxes on corporate distributions. Just as the value of intangible capital is less than its cost because of the government’s tax on corporate income, the value of tangible capital differs from its cost because it’s subject to a government tax—namely, the tax on shareholder dividends or stock buybacks: corporate distributions. So in their calculations of fundamental value, the economists reduce the cost by the prevailing dividend tax rate of 10.3 percent to arrive at a value for tangible capital of 1.26 GNP (= 1.4 GNP – (1.4 GNP x 10.3%)).
The determining factor
If they’d stopped there, McGrattan and Prescott would have concluded that Fisher was indeed wrong. The stock market was at 1.67 GNP in 1929, a full third higher than the value of underlying tangible capital assets, at only 1.26 GNP.
But intangible capital is the “determining factor,” write the economists, both for their estimates and Fisher’s. Fisher recognized that investments in scientific research and invention, patents and organizational capital provided substantial value to corporations. AT&T, for instance, employed 4,000 scientists, he noted, “more than any university could equal.” He also referred to “management engineering” as a type of investment that enhanced corporate value.
McGrattan and Prescott derive estimates for such intangible capital by again assuming equal rates of return for tangible and intangible capital and backing out a figure for intangibles. And once more, they find that “inclusion of intangible capital is crucial in the analysis.”
In their model, McGrattan and Prescott include two taxes that affect the value of intangible investment—the corporate income tax (as in their 2000 stock market paper) and the tax on corporate distributions (as for tangible investments). This complicates the calculation, but doesn’t prevent it.
In the end, they estimate a value of intangible capital at least 61 percent that of tangible capital. Combining intangible and tangible capital and using reasonable figures for tax rates on corporate profits and distributions results in a “conservative estimate for the fundamental value of U.S. corporations in 1929 [of] 1.9 times 1929 GNP,” write McGrattan and Prescott. Compared to a stock market then valued at 1.67 GNP, this indicates that Fisher was indeed right. According to modern economic theory and the best historical data available, the stock market was undervalued just before its crash on Black Thursday.
What goes down …
McGrattan and Prescott don’t try to guess why the market crashed in 1929, nor why it collapsed in 2000. “[T]hat question is not addressed here,” they write in the introduction to their Irving Fisher paper. But they hint at an explanation for the 1929 crash. “Before the crash, the Federal Reserve severely tightened credit to stock investors. … Not long after the crash, the Fed eased credit, and stock prices recovered. This correlation is worthy of its own detailed investigation.”
As for the 2000 market collapse, the authors don’t yet have an explanation. Their work concludes that the market was fairly valued early in 2000, not irrationally exuberant, but it doesn’t try to explain sudden crashes. “As far as theory goes, the puzzle is not the rise in the market during the ’80s and ’90s, it’s the fall after 2001,” observes McGrattan in an interview. “We use theory to predict roughly where the market should be hovering. Our work doesn’t try to explain short-term climbs or crashes.”
Adds Prescott, “It got above fair value in March 2000. Now it seems to be below fair value. Over the long run, I’m pretty confident about what the value of the stock market will be relative to GDP, given the tax system.”
And that’s a big given. Staff report 309 by McGrattan and Prescott, “Taxes, Regulations and the Value of U.S. and U.K. Corporations,” uses the techniques described above to explain movements in stock market value relative to gross domestic product between 1960 and 2001. In this paper, published in the Review of Economic Studies in July 2005, the economists refine their earlier work on U.S. stock market value and extend it to the United Kingdom, which also underwent a dramatic rise in equity values over that 41-year period (see chart).
Source: McGrattan and Prescott, 2005,"Taxes, Regulation, and the Value of U.S. and U.K. Corporations," Research Department Staff Report 309, Federal Reserve Bank of Minneapolis
Intangible capital again plays a central role in determining the level of stock market value; without its inclusion, calculations of U.S. corporate value in the 1998–2001 period, for example, would be underestimated by a fifth. But in this paper, McGrattan and Prescott’s primary goal is explaining the rise in equity values, and for this they focus on the impact of corporate distribution taxes.
In the United States, these distribution tax rates declined substantially over this period. Part of the decline was due to a fall in income tax rates, with three cuts between 1964 and 1986. But more importantly, the Employee Retirement Income Security Act (ERISA) of 1974 encouraged pension funds to hold equities, and other tax law changes in subsequent years promoted the development of individual retirement accounts and defined contribution plans. Corporate distributions and capital gains to these retirement entities were tax-free, and as the share of equity held by them increased—from 4 percent in 1960 to 51 percent in 2000—the effective marginal tax rate dropped dramatically, from 41 percent in the 1960s to 17 percent in the 1990s.
With dramatically lower marginal tax rates, tangible and intangible capital—the underlying assets of the corporations—increased in value. “The principal reason that the total value of corporations nearly doubled relative to GDP between 1960 and 2000 was not that the cost of … capital relative to GDP increased, as the ratio changed hardly at all,” write McGrattan and Prescott. “Rather it was that the effective marginal tax rate on corporate distributions fell by more than a factor of two.”
To see whether this drop in distribution taxes can indeed explain the rise in equity values, the economists create a mathematical model of the U.S. economy, with utility-maximizing households and profit-maximizing corporate and noncorporate sectors. And in this model, the economists again account for the critical tax difference between tangible and intangible capital—subject to different tax treatments because the former are capitalized and the latter are expensed. (They also account for changes in capital subsidies offered by the U.S. and U.K. governments over the 40-year period, since a subsidy is basically the inverse of a tax.)
Model built and values inserted, the economists find their theory borne out. Their model predicts fundamental values of corporate capital (tangible, intangible and foreign) of 0.877 GDP in the 1960s, rising to 1.567 GDP in the 1998–2001 period. This compares with actual market values of 0.940 GDP in the early period and 1.604 GDP in the later. “[T]heory predicts the data well,” they conclude.
And in fact, these results revise the answer to their 2000 paper, “Is the Stock Market Overvalued?” In that paper they concluded that the market was fairly valued in the first half of 2000. But when they improved their model by accounting for the impact of distribution taxes, their estimate of market value came in at about 1.6 GDP, rather than 1.8 GDP. Thus, they conclude in retrospect, the market was overvalued. “If improved theory contradicts earlier findings, you’ve just got to face it,” observes Prescott. “This is how we improve our models. This is how economics progresses.”
When they extend the model to the United Kingdom, they again find that tax reform and regulations governing pension funds led to a large decline in effective tax rates on corporate distributions, from about 49 percent in the 1960s to minus 5.3 percent in the 1990s. The result also is similar. According to their model, the fundamental value of U.K. corporate assets (tangible, intangible and foreign capital) soared from 0.8 GDP in the 1960s to 2.148 GDP in the 1998–2001 period. And actual market values similarly rose from 0.792 GDP to 2.22 GDP. The model, incorporating intangible capital and declining marginal tax rates, accurately predicted the levels and the rise of equity value.
“Here we have derived the prediction of growth theory—the standard tool of macroeconomics and public finance—for the value of U.S. and U.K. corporations in the period 1960–2001,” write McGrattan and Prescott. “We… find that predicted and actual valuations are close in magnitude, indicating that the tax system is a quantitatively important factor for the large, secular movements we observed.”
Gross domestic productivity
By highlighting the importance of intangible capital, this work on stock market value uncovered the inadequacy of NIPA statistics. Essentially, NIPA ignores a vast chunk of economic investment—intangible capital—by treating outlays on research and development, for instance, as an expense item rather than an investment. And thus, many indicators derived from NIPA, such as GDP, present a distorted picture of reality.
Recall that McGrattan and Prescott’s definition of tangible and intangible capital abstracts a bit from the no-touch rule.
“Let me try this,” says Prescott, who as 2004 Nobel laureate has now had a year’s practice in translating impenetrable economics for laypeople.“Tangible: touch. Intangible: no touch. In NIPA accounts, it turns out that tangible investment and ‘capitalized’ line up almost perfectly with each other. And intangible and ‘expensed’ line up almost perfectly. In our theory, the key distinction is ‘expensed’ versus ‘non-expensed,’ and ‘expensed’ and intangible are de facto—”
“Or close to,” clarifies McGrattan.
“For all practical purposes,” modifies Prescott, “—the same.”
“So in our models,” McGrattan continues, “when we distinguish between tangible and intangible capital, we are talking about capital that is measured in the national accounts and capital that doesn’t really appear; it’s unmeasured.”
“Measured and unmeasured are the same as capitalized and expensed,” explains Prescott, referring to how their theoretical constructs line up with NIPA’s detailed figures. “There they match up perfectly.”
Our official national accounts, then, simply don’t measure investment in intangible capital, meaning that figures on economic output dramatically understate actual output. “The problem with not including intangibles,” explains McGrattan, “is that GDP is not measuring true output. And since a measure of productivity is output per hour, if you’re miscounting output but counting hours correctly, you’ll get wrong estimates for productivity.”
The missing piece
And this is the crux of McGrattan’s and Prescott recent article, “Productivity and the Post-1990s U.S. Economy,” published in the July/August 2005 issue of the Federal Reserve Bank of St. Louis Review. In it, the economists compare official figures for productivity to their estimates, which include the crucial missing piece: intangible capital. During the 1990s, the economists discover, the two trends were very different.
In this paper, McGrattan and Prescott use the terms “accounting productivity” and “economic productivity” to distinguish between the standard calculation and their own. Accounting productivity is GDP per hour worked. Economic productivity, they write, includes intangible investment: “expenditures that increase future profits but, by national accounting rules, are treated as an operating expense rather than as a capital expenditure.”
They derive estimates for these expenditures and find wide swings, relative to GDP, throughout the decade, with a “sixfold increase in the level of intangible investments between 1997 and 2000,” they write. “This change in investment has consequences for output, profits and total investment.”
Specifically, rather than declining slightly (relative to a historical growth trend of about 2 percent per year) economic productivity dropped sharply between 1990 and 1997 and then climbed much faster over the next three years, compared to accounting productivity, which ignores intangible investment. Similarly, trends in corporate profits and total investment look much different if intangible investment is taken into account.
In brief, then, when statistics on national economic output are corrected to reflect investment in intangible capital, trends in productivity, profits and overall investment tell a very different story from that depicted by standard government reports. Given that monetary and fiscal policy, not to mention corporate decisions, are contingent to some degree on an accurate sense of such economic trends, these findings have great significance.
Sultans of sweat
So the official story isn’t the right one. Output, profits and investment soared in the late 1990s, well beyond government estimates. And in fact, this corrected version of events may even prove to be an understatement if exploratory work by the economists bears fruit.
In working paper 636, issued in September 2005, McGrattan and Prescott expand their focus. In addition to “expensed investment”—the outlays on intangibles looked at earlier—they introduce a new concept, a very particular form of intangible investment: when business owners invest hours of work without drawing full compensation. McGrattan and Prescott call it “sweat investment,” and the capital stock built by such intangible investing is, as many homeowners know, “sweat equity.” McGrattan and Prescott emphasize that the work is tentative. “If you write about this,” says McGrattan, “can you stress that it’s preliminary? The figures will change; the math will change.” In fact, the September working paper is a 43-page revision of a 25-page version issued in June. The current version is expanded, reworked, fine-tuned, yet still tentative. But the caution is all about the details, not the concepts.
“Sweat investment is financed by worker-owners who allocate time to their business and receive compensation at less than their market rate,” they write in working paper 636. Why would anyone do such a thing? Think back to the late 1990s when MBAs were dropping out of business school to start dot-coms, with dreams of massive capital gains upon going public or being bought out. Some of the dreams came true—does “Google” ring a bell? Others evaporated.
These capital gains aren’t included on the income side of official national accounts, note the economists, and the sweat equity investment doesn’t show on the product side any more than other forms of intangible investment. But hours worked by sweat equity investors are counted by the Bureau of Labor Statistics. “Taking into account hours spent building equity while ignoring the output,” write the economists,“introduces an error in measured productivity and distorts the picture of what is happening in the economy.”
If an MBA quits her $100,000 a year job to start a company, paying herself just $15,000 the first year, her sweat investment is $85,000. But economywide data on this “sacrifice” aren’t easily found. “How do you get a measure of that forgone wage, the forgone explicit payments, relative to what their shadow price in the market is?” asks Prescott.“The sum over all these people is what you’d love to have.”
The data aren’t readily available, so McGrattan and Prescott use the economic model they developed for stock market analysis to explore the world of sweat investment. The results, though preliminary, are provocative. Standard measurements of productivity “show a significant fall relative to trend until 1997, and then the economy is roughly on trend,” they write. “But actual productivity [which includes intangible investment, both expensed and sweat] shows that the economy is roughly on trend starting in 1993, and then in 1995 the economy is above trend. These are very different predictions.” (See chart.)
Labor Productivity, for the Model, With and Without Intangible Investment (Real, Detrended) 1990-2003
Source: McGrattan and Prescott, 2005, "Expensed and Sweat Equity," Research Department Working Paper 636, Federal Reserve Bank of Minneapolis
Similarly, they show, investment trends during the 1990s look much different when intangible investment is included. Between 1991 and 1999, tangible investment rose by almost 20 percent, but total investment (including intangible) rose by more than 30 percent. “Again, the predictions—with and without intangible investment—are very different.”
Moreover, the economists point out, intangible investment varies over time. From 1992 to early 2000 it rose from a 0.02 share of GDP to just over a 0.08 share before falling again to 0.02 GDP by 2003 (see chart). “The bottom line of our study is that it is large and increased significantly in the late 1990s,” they write. “Hence, standard accounting measures do not highlight what was actually going on in the U.S. economy during this period.”
Source: McGrattan and Prescott, 2005, "Expensed and Sweat Equity," Research Department Working Paper 636, Federal Reserve Bank of Minneapolis
Not surprisingly, some analysts disagree with McGrattan and Prescott, who say they welcome the critiques. Learning the weaknesses of their models through a process of peer review is an important part of building better theory. When Massachusetts Institute of Technology economist Richard Caballero commented last year on their 1990s productivity paper at a St. Louis Fed conference, he congratulated them for their bold statements and careful steps in amending conventional national accounts. But he also criticized their methodology and depiction of the 1990s.
“The late 1990s are perceived as a time of massive investment, fast productivity growth, and corporate bonanza,” he writes in his commentary, in contrast to the “gloomy characterization” given by McGrattan and Prescott of modest productivity growth, low profits and moderate investment.
McGrattan and Prescott respond that their characterization is a better reflection of reality than the standard media cheerleading regarding the 1990s. By historic standards, they point out, productivity in the 1990s was not especially high—it only seemed so compared to the doldrums of the 1970s and 1980s.
Caballero also suggests that McGrattan and Prescott’s economic model would have shown very different results if they had allowed for “frictions.” “On the investment side, the authors assume no adjustment costs. … Short-run frictions are of the essence in investment theories,” he writes. “On the labor side, there are assumptions of perfect labor mobility.”
McGrattan and Prescott agree that they’ve abstracted from these frictions, but not without good reason. “One justification for abstracting from these frictions is that there is, in fact, a huge amount of mobility of labor,” notes Prescott. Perfect mobility? No, but enough to justify that assumption in an economic model. “We’re assuming perfect mobility,” says McGrattan. “He’s assuming all sorts of stickiness. The evidence is more to us. When put into a model, the quantitative impact of these frictions is small.”
Again, these charts are tentative; the numbers will change, just as further refinements on their stock market analysis changed their estimate of total corporate value in 2000. But the question is one of magnitude: How large was the sweat investment? The issue of undercompensation is critical in this analysis. “This factor is clearly there,” argues Prescott. “The question is, How big is it? How do we measure it and get a decent estimate?”
In addition, the work will be judged by other economists at seminars around the world and reviewed closely by journal editors and anonymous referees before publication. “It needs to be presented broadly and held up to more scrutiny,” observes McGrattan, who first presented the paper in early October to a collegial but critical audience at the Minneapolis Fed. At this point the model and results are still being revised. “But,” McGrattan declares, “it won’t be exploratory forever.”
Their comments about sweat equity are applicable as well to the broader topic of intangible investment. It isn’t a new idea. Indeed, Smith’s observations about division of labor at the pin factory were, to a degree, a precursor to Prescott’s work on “organization capital.” (“Information about employee and task characteristics that influence productivity is part of the firm’s capital stock,” write Prescott and Michael Visscher in a 1980 Journal of Political Economy article.)
But only recently have economists tried to measure intangible capital, and even less effort has been devoted to its incorporation into economic models. The accurate measure of intangibles and their economic impact remains work in progress. But McGrattan and Prescott’s research has given both shape and direction to the intangible, a reality that until now economists have considered beyond their grasp.