Why Can’t We Find Productivity Gains?

Soaring Productivity Is Missing From the Numbers
We produce more with less because of technology. But data measurement hasn’t kept up.
Bloomberg, April 1, 2016




You can see the computer age everywhere but in the productivity statistics.  –Robert Solow


Government data [Friday] showed that the U.S. gained 215,000 new jobs last month. Unemployment ticked up to 5 percent from 4.9 percent, as more people returned to the labor force. Wages increased 0.3 percent month to month, and are up 2.3 percent year over year. Payrolls expanded for the 70th consecutive month, averaging 198,000 a month during that stretch. Since the Great Recession ended, 14.5 million new private-sector jobs have been added to the economy.

Those big three data points — the unemployment rate, number of new hires and wage gains — are what everyone focuses on. The one data point you don’t hear much about is productivity. Looking only at the Bureau of Labor Statistics data, you might imagine that the level of productivity hasn’t improved much. This is crucial, because productivity is a big part of the economic-growth equation.

However, based on nothing more than my own personal experience, and nearly everyone else I have asked about this, something quite different is happening — productivity is soaring. Yet, there’s nothing to be found in the official numbers. To paraphrase Solow, productivity gains are everywhere except in the productivity statistics.

Think for a moment about the technology you use in your personal and professional life; consider how much more you can do in a given span of time thanks to technology; the integration of mobile wireless and information services, the Internet, software and apps and what it all allows you to accomplish each day compared with the recent past.

I wager that your personal experience overwhelmingly suggests productivity gains are everywhere despite the lack of hard data.

Analysts at the BLS looked at this in 2014. They noted in a report some rather intriguing data: employees “in the U.S. business sector worked virtually the same number of hours in 2013 as they had in 1998—approximately 194 billion labor hours . . . there was no growth at all in the number of hours worked over this 15-year period, despite the fact that the U.S population gained over 40 million people during that time, and despite the fact that there were thousands of new businesses established during that time.”

That 15-year period also saw a 42 percent increase in real output; American businesses produced $3.5 trillion more in goods and services (in real terms) in 2013 than in 1998.

As a nation, how can we have such a massive increase in output without an large increase in productivity? Technology must be part of the answer; the other part probably is a measurement issue.

Rick Rieder, chief investment officer of global fixed income at BlackRock, calls today’s slow productivity growth “a statistical mirage.” He further observes that “traditional economic metrics simply haven’t kept pace with fast-changing technologies geared toward greater efficiency at lower cost.”

Others at BlackRock have looked at the productivity slowdown, exploring cyclical and structural reasons for the “missing” gains.Measurement error continues to be the leading culprit.

The way we capture formal productivity data hasn’t kept up with modern ways of doing business. As a result, I believe economists underestimate productivity increases. Think about it: Most of us walk around with more computing power in our pockets and hand bags than the Apollo astronauts had at their disposal on the lunar voyages. Smartphones and related technology make everyone more productive.

As U.S. businesses and consumers continue to adopt new technologies at the fastest rate since the advent of the television, the result is ever-increasing productivity. In the app-economy, productivity gains are everywhere — except in the official data. Let’s hope that changes soon.




I originally published this at Bloomberg, April 1, 2016. All of my Bloomberg columns can be found here and here



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