Archive for May, 2016
Counterfactual Failure Alert!
We’ve been focusing on productivity in recent issues and had some questions concerning possible measurement of high-tech productivity from some readers in the last weeks. Wouldn’t that be nice, but, alas, two new studies dim such hopes.
The two papers make many of the same points. All agree that there is a measurement problem, but that it was likely larger during the high growth period of 1995 to 2004 than it is today. In “Does the United States have a productivity slowdown or a measurement problem?” authors David M. Byrne, John G Fernald, and Marshall B. Reinsdorf suggest some adjustments to IT-related sectors, which make recent growth in investment and GDP look a bit better, and adjustments to durable goods manufacturing, which make labor productivity look even worse.
In his “challenge to mismeasurement explanations,” University of Chicago professor Chad Syverson argues that the highest estimate of the surplus generated by internet-linked technologies is only one-third of the “purportedly mismeasured GDP,” even using his “very expansive assumptions about the value of leisure time.” Equally bad, to account for even a modest piece of the $2.7 trillion hole left by the productivity slow-down, output and productivity in information and communications technologies (ICT) would have to be multiples of what is currently reported. For example, combined employment in computer/electronic manufacturing, information, and computer systems design rose 3.6%, from 5.58 million to 5.78 million, between 2004 and 2015. If those workers actually did produce the output lost to the productivity slowdown, real value added per worker would have risen an “astounding” 363% over those years, far outpacing the 83% growth in durable goods manufacturing between 1995 and 2004.
Syverson throws cold water on the argument that Gross Domestic Income being slightly higher than Gross Domestic Product since 2004 suggests that people are being paid to make things that are sold at heavy discounts: that disparity is based on “unusually high” capital income [read profits], not labor income. He points out that if the annualized 1.5% drop in labor productivity were to persist over the next 25 years it would compound to a 45% decrease in per capita income.
Byrne et al. argue that since domestic production of IT hardware has decreased, the effect of mismeasurement was likely larger before the as-measured slowdown after 2004. They also make the point that consumer benefits from Google searches and fun on Facebook are non-market (akin to playing soccer with one’s children), and anyway are too small to compensate for the loss in “overall wellbeing” driven by slower market-sector productivity growth. They see real improvement in matching products and services with consumers, but nest these in a continuum of changes that once included the shift in responsibility for doing the laundry from a domestic washer-person, to a family-member, and finally to a washing machine.
They point the finger at the decline in economic dynamism including the dearth of start-ups and slower reallocation of resources following productivity shocks, and note the possibility that the fast-growth period between 1995 and 2004 might be the anomaly. And they admit they don’t know what gains will come from cloud computing, and that more IT-driven increases may be in the offing.
The productivity showdown is widespread, and Syverson matches OECD labor productivity data with ICT intensity, which he measure as access to broadband, for close to 30 countries. He regresses labor productivity with broadband penetration for a -0.001 co-efficient, a point estimate that implies that one standard deviation (SD) in broadband penetration comes with one-fiftieth of a SD in the magnitude of the slowdown. This coincides with work showing that differences in the slowdown in total factor productivity in U.S. states are not correlated with each state’s ICT intensity.
Syverson writes that the “intuitive and plausible empirical case for the mismeasurement hypothesis faces a higher bar in the data,” and that the slowdown is real. In closing he notes that whether the slowdown will end “anytime soon is an open question.” We’re not seeing it yet, so that’s a question we have to address.
Oil and the Economy
In our reports, we have often made the point that the belief that shoppers spend their fuel savings on other sending is largely a myth—overall spending and spending on gas generally move together, and we tend to drive more when gas is cheaper. But just what is the relationship between oil prices and economic growth? Are high prices signs of economic strength or do they portend decline? Conversely, are low prices stimulative, or are they a sign of weakness? How do we separate cause and effect?
New York Fed economists Jan Groen and Patrick Russo have been on the case. The answer is basically—and unsurprisingly—“it’s complicated.” Groen and Russo develop a model, using what they describe as “a large number of financial variables,” to isolate supply and demand influences on the price of Brent crude since 1986. In a June 2015 post, they report that the price declines of the late 1980s and late 1990s were driven by supply-side shocks, namely aggressive expansion of production by OPEC members, notably Saudi Arabia. More recently, they find that the 2001–2001 and 2007–2009 declines were driven by demand shocks resulting from U.S. recessions. But outside these recessions, tighter supplies put upward pressure on prices through 2010. Between 2010 and 2012, prices were driven higher by a combination of rising demand and supply constraints. But since then, expanding supply has driven prices lower—a tendency that was partly counterbalanced at first by rising demand through mid-2014. Since then, demand has weakened while supply has remained plentiful.
And what are the effects of changes in oil prices? They find that price declines resulting from supply shocks have only modestly stimulative effects on GDP and consumption—roughly a +0.10–0.15% kick to both from a one-standard-deviation supply shock in the first quarter or two afterwards that decays in about four quarters. Real nonresidential fixed investment responds more strongly but more slowly, maxing out at about 0.30% three quarters after the shock. Investment takes a little longer to decay, but the effect is all gone in seven or eight quarters. Their model projected that the decline in oil prices of late 2014 and early 2015 would have only a modest stimulative effect during the second half of 2015, and would be mostly dissipated by early 2016. Given recent growth rates, that looks like not a bad forecast.
In a recent post, Groen and Russo updated their work. Their model suggests that the price declines in late 2015 and early 2016 have had and will have little effect this year. Perhaps, then, we all pay too much attention to oil prices.
Telling it like it is in the Great Plains
We thought you all might like this comment on gas prices and overall spending from one of our tax contacts in the Great Plains:
I think of savings on gas as pre-spent money. Spending on gas is inelastic, and the average consumer saves about $1,500 a year [for every dollar drop in price]. For the working-class person that $1,500 may have already been spent. Now, instead of being $150 in the hole each month, they are only in for $25. That would explain why the $500 payment back in 2001 didn’t provide substantial gains, and why we didn’t see an increase in spending when gas prices halved.
A Missed Opportunity
We’ve often lamented the low level of capital spending—bad news for productivity and income growth—despite high rates of corporate profitability. Here’s another perspective on that: real rates of return are higher than returns on financial assets, but that hasn’t led to a rush of capital into real investment.
Graphed below are two financial rates of return—the earnings yield on stocks (the inverse of the P/E ratio) and the ten-year Treasury yield—against our measure of nonfinancial corporate profitability (pretax profits from the national income accounts divided by the value of the tangible capital stock from the Fed’s financial accounts). Note that in recent years, returns on real capital have been comfortably higher than financial returns. Since 2012, the earnings yield on stocks has lagged real returns by an average of 1.1 percentage points—not as big as the 1.9-point gap of the late 1990s, when there was a gusher of real investment that produced a serious acceleration in productivity growth, but still wide compared to the -0.3 point average of the full 1952–2015 scope of the graph.
The gap with Treasury yields is even more striking—4.4 points since 2012, compared to an 0.3 point average in the late 1990s and 0.4 for the full 63-year history presented here.
Profitability is now weakening, so the relative lure (at least on paper, or its silicon equivalent) of real investment is losing some of its charm. But this period of high real returns and low investment is looking like a missed opportunity. That so much corporate cash has been either hoarded, or devoted to buybacks and M&A, is not what long-term prosperity is made from. (Along with mildly tightening standards on C&I loans, the Fed’s recent loan officer survey found weakening demand for them, with “decreased investment in plant or equipment [as] the most commonly cited reason.”) Thirty years ago, as the buyout and buyback booms were just getting going, Peter Drucker wrote: “Everyone who has worked with American management can testify that the need to satisfy the pension fund manager’s quest for higher earnings next quarter, together with the panicky fear of the raider, constantly pushes top managements toward decisions they know to be costly, if not suicidal, mistakes.” It’s amazing how little has changed since the mid-1980s.