Last week, the Labor Department reported US labor force productivity slipped -0.3% y/y in Q3, its first contraction in almost four years. The dip returned a long-running worry to the spotlight: Weak productivity holding back the economy and stocks. In our view, however, measured productivity is overrated as an economic driver and basically irrelevant as a near-term market driver.
Now, we aren’t talking about productivity in the general sense of the term. We are referring to the economic metric, as tabulated by government stat wonks. To calculate productivity, they divide total output by total hours worked. Since hours worked grew more than output in Q3, productivity fell. To many, this is ominous. Conventional wisdom argues economic growth requires more workers, more efficiency from existing workers or a combination of the two. As Baby Boomers age out of the workforce, many worry the US will stay stuck in a slow-growth rut absent productivity gains. But in our view, this narrative paints an incomplete and inaccurate picture.
For starters, a demographic decline isn’t a foregone conclusion. Not only are life expectancies rising, but people are much healthier in their 60s, 70s and even 80s than prior generations were a few decades ago. Older folks’ increased activity, plus the prevalence of less physically demanding jobs, undercuts the notion of a retirement tidal wave. According to the Pew Research Center, the majority of Boomers (those born from 1946 – 1964) were still in the labor force last year.[i] Further, the oldest contingent (ages 65 – 72) were working at higher rates than the preceding two generations did in the same age range.[ii] Not that this is an economic boon—just as a flat or falling population doesn’t spell doom. Demographics aren’t destiny.
Second, we think focusing on population size and productivity discounts technology and capital’s pivotal roles in fueling economic growth. Technological advances that boost product or service quality while lowering costs are tough to capture in broad output data like productivity and GDP. These metrics are designed for an economy built around producing physical stuff—a far cry from today’s services-heavy US economy. For example, if Ted’s Widget Factory churns out 1,000 more widgets this month without adding assembly line workers or shifts, the productivity increase is obvious. Enhancements to, say, an already free app or other software component aren’t nearly so tangible or measurable. For this reason—and GDP’s odd treatment of imports, inventories and government spending—the measures don’t perfectly reflect the economy. Therefore, we think “productivity” gauges hinging on GDP have holes.
Capital, the other crucial missing ingredient, can take the form of physical structures used to produce things (think: factories or equipment) or money (think: lending, which drives money supply growth). Consider the latter: When credit is flowing, businesses can borrow to make long-term investments, boost output and/or hire more. This wouldn’t necessarily speed up measured productivity growth—investments might not pay off for a while, and growth in hours worked could surpass output growth. But it is still economic fuel.
In our view, decreased capital availability tied to poor monetary policy better explains slow US GDP growth in this cycle. The combination of near-zero short-term interest rates and the Fed’s long-term bond buying under its quantitative easing program meant a tiny spread between short and long rates. Banks borrow short term to fund longer-term loans—the gap is their profit. While the Fed thought lowering long rates would encourage borrowers and spur the economy, it ignored loan supply. The upshot: US lending growth has lagged all expansions since records begin in 1975, averaging 3.6% y/y through October.[iii] For comparison, it grew 6.0% on average during the 1990s expansion and 8.4% from 2002 – 2007.[iv] Unsurprisingly, money supply growth has also been the slowest of any expansion on record. When credit is tight and money supply is stagnant, growth seldom surges.
Extrapolating productivity dips forward is also an error, in our view. The Labor Department’s gauge contracted frequently between 2011 and 2015 before rising for 14 quarters.[v] Sharp falls early in the 1990s’ expansion didn’t preclude many subsequent years of mostly unbroken productivity growth.[vi] Decelerating capital expenditure growth isn’t self-fulfilling, either—nor does it mean businesses are innovating less. There isn’t a linear relationship between business investment and productivity-boosting innovation. In an economy where software and digital goods loom large, breakthroughs don’t necessarily require armies of researchers or huge up-front costs.
Most importantly for investors, productivity figures don’t predict economic or market direction. Both the measure’s inputs are backward-looking, and one (hours worked) is late-lagging—it reflects hiring decisions made in response to economic conditions months ago. Combining them doesn’t make the resulting figure predictive, in our view. Stocks, meanwhile, assess corporate profits’ likely path over the next 3 – 30 months. Over that span, how expectations square with reality matters most. To us, this entire expansion highlights the fact stocks don’t need rapid productivity or GDP growth to rise. A middling but better-than-expected reality is typically sufficient.
[i] “Baby Boomers are staying in the labor force at rates not seen in generations for people their age,” Richard Fry, The Pew Research Center, 7/24/2019. https://www.pewresearch.org/fact-tank/2019/07/24/baby-boomers-us-labor-force/
[ii] Ibid. In 2018, the Baby Boomer labor force participation rate was 29%, compared to 21% for the Silent Generation in 2000 and 19% for the Greatest Generation in 1979.
[iii] Source: Federal Reserve Bank of St. Louis, as of 11/11/2019. Year-over-year change in loans and leases in bank credit, all commercial banks, monthly, April 1975 – October 2019.
[iv] Ibid. Year-over-year change in loans and leases in bank credit, all commercial banks, monthly, April 1991 – February 2001and December 2001 – November 2007.
[v] Ibid. Statement based on the year-over-year change in real output per hour of all persons, monthly, Q1 2011 – Q4 2015.
[vi] Ibid. Statement based on the year-over-year change in real output per hour of all persons, monthly, Q1 1993 – Q3 1994.
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