Nineteen Ninety-Six: The Robot/Productivity Paradox
From 1996 to 2015, GDP grew at a compound annual rate of 2.3% while Net Worth increased at the rate of 3.6%.
Responding to an editorial in the New York Times, Jared Bernstein reprised a theme that Dean Baker has been stressing for a while — that productivity and investment measures don’t support the “robots are stealing jobs” story. I agree with Jared and Dean that it is policy, not robots that are stealing the jobs. But I am skeptical about using productivity numbers as evidence against the role of labor-saving technology in displacing people from employment.
The reason for my skepticism is that labor productivity is a ratio between two very broad aggregates — GDP and hours worked — that lump together a myriad of disparate economic factors. Here is the argument I made to Dean back in December. He was not persuaded:
The difficulty I have with the evidence you [Dean] use for your argument has to do with the changing composition of the aggregate measures that make up the productivity calculation and the possibility that confounding variables in each of those aggregates may be “compounding the confounding” when used for year-to-year comparison.
As Block and Burns pointed out, the National Research Project that developed the original productivity estimates argued that “no such thing exists in reality” as the productivity of a group of diverse products. Instead they presented two calculations of productivity, using different weighting, to show that the “measurement” depended in part on the weighting of the variables.
The shift from physical output to GDP measures obscured the fact that there is “no such thing” as the productivity of a diverse collection of products. Monetary value converts those diverse products into so much “leets” — to use Joan Robinson’s sarcastic term. Obviously the mix of goods and services that make up the GDP differs from year to year. The GDP deflator is intended to adjust for price changes and quality improvements but doesn’t deal with distributional changes and product substitution.
The government services component of national income has been a particular issue, the critique of which goes back to Kuznets’s 1947 criticism of the Commerce Department’s GNP and Kaldor’s statistical appendix to Wm. Beveridge’s Full Employment in a Free Society. Kuznets argued that much of government services should be treated as intermediate goods rather than final consumption goods. Kaldor considered the inflationary affects of government deficit spending, arguing that some of that “inflation” simply reflected the increased share of collective consumption. Warsh and Minard offered a critique of “inflation” in the 1970s that could easily have referenced Kuznets’sand Kaldor’s arguments. Their idea was basically that as government expenditure increases as a percentage of GDP, much of the taxation to pay for it is passed on to the consumer in the form of higher prices. It is an argument about the incidence of taxation.
Finally, there is the question of the “productivity” of hours of work themselves. Presumably there is an optimal length (or innumerable optimal lengths) of the working day, workweek or year and variation above or below that optimum will result in lower output per hour. Aggregate hours of work and average annual or weekly hours do not reflect changes in the dispersion of hours of work that may in turn be affecting the productivity of hours. Computationally, this injects a circular reference into the measurement of productivity. If you tried to do this on an Excel spreadsheet you would get an error message. It is only by ignoring the feedback effect of changes in hours and changes in dispersal of hours that productivity can be calculated as GDP/Hours.
By definition, new technology introduces changes in product mix and changes in work arrangements. But also, by definition, the two components of the productivity calculation assume “no change” in product mix or work arrangements. So I’m having trouble seeing how a ratio that relies on an assumption of no change could be adequate to measure the effects of change.
When Jared posted his commentary, I wanted a quantitative illustration of the point I was trying to make. I had already been wondering about the question raised by Bill Gates about taxing robots and the idea that wealth creation might be “bypassing” income, so I looked up the net worth statistics.
After a bit of number crunching, I am astonished at what I see in the numbers. It is not just the discrepancy between GDP and net worth that impresses me but also the long period prior to 1996 during which the two numbers grew at a very similar rate. In the chart below, I have indexed both series to 100, with 1996 as the reference date. The smooth curve is actually two trend lines based on the 1947 to 1996 trend for each series:
Logically speaking, and using the plain language meaning of the terms, wealth is something that is produced. So increases in wealth presumably are predicated on increases in production. It makes intuitive sense that over the long run there would some sort of stable relationship between the growth rates of GDP and of wealth. I was not anticipating, however, such a close fit between the two series from 1947 to 1996. It only accentuates the disjuncture between GDP growth and growth of Net Worth after 1996.
The above chart only goes to the end of 2015, so it doesn’t include the recent stock market boom. Nevertheless, it presents an unsettling picture.
Returning to the puzzle of productivity, the point that I was trying to illustrate is that the comparability of the productivity measure requires a good deal of faith in the proportional stability of the economic relationships over time. If there are significant shifts in employment by sector, technology, resource availability, trade arrangements and/or consumption tastes, then comparing productivity between periods is futile. There is too much noise in the component aggregates to begin with — but using a ratio between them amplifies the noise.
Sandwichman:
” that productivity and investment measures don’t support the “robots are stealing jobs” story. ”
Perhaps defining robotics might be better example of disappearing Labor? One 5-Axis CNC cell manned by one person doing the work of 5 other machines manned by 5 people. If this is not an increase in productivity and throughput by one robot eliminating Labor, all of my work over the last 40 years was for naught.
The one issue I have with economics is the broad based statements which come out of it by its leaders whom I happen to like. What am I missing here that is so obvious to me and ignored by them?
A couple of points. First, I’m sure you know but the way you wrote about it raised doubts. But productivity does not include government. It measures business output so I’m not sure what your real point was. Yes, there are issues with measurement of government in GDP but it does not distort the productivity data.
Second, I’ve been looking at the work Tim Taylor did last week on the weakness in net, not gross capitl spending in the modern economy where high teck equipment has a much shorter life span than more traditional equipment. So more and more of current capital spending is just to replace old equipment. When i look at the real capital stock per employee I find a very strong relationship to productivity and see that both have been growing much less in recent years. So much of the problem is a lack of investment.
Thanks. That was sloppiness on my part. What I was trying to get at is that the changing composition of GDP gets obscured in the aggregate number and the “deflation” of nominal GDP to get “real” GDP amplifies the noise rather than damping it. “Inflation” (which is a misleading term) leaks into and out of the business sector from government through tax increases or cuts regardless of whether people are getting more F-35s, more toxic waste clean up or less public swimming pools.
Samich
i suspect you are right, at least as a beginning to correct over simplified “economic analysis.”
but meanwhile we need to see the elephant for the trees: “wealth” has increased (due no doubt to machine productivity). There is no reason that that wealth should go entirely to the owners of “capital.” Simply raising the wages of workers to reflect the increase in their,machine aided, productivity would go a long way to solving the problem of “low wages” as well as “inequality.” this is a political problem, not an economic problem.
Things get more speculative.
First, I think wealth accumulation is increasingly bypassing income. Income is taxable but wealth is not. Second, I suspect that the escalation of wealth accumulation generates a positive feedback in the form of asset inflation.
Does the figure of $24 trillion sound reasonable? That’s my calculation of how much current net worth exceeds the historical average ratio (1947-1996) between US GDP and net worth. By the end of 2008, net worth fell $10 trillion from what it had been at the end of 2007. The 2007 excess over the historical average was a little under $14 trillion.
You have a point on wealth. I know people who are investing in art so they hope they can avoid wealth taxes down the road.
One assumes that wealth is an integral of some fraction of GDP. Income is also a fraction of GDP, so wealth rising faster than GDP indicates that more GDP is being saved rather than spent which makes sense as GDP is increasingly diverted to those least likely to spend it.
Possibly. But if it was JUST an increased propensity to save, what would explain the increased volatility of the rate of increase (or decrease) in wealth from year to year? No doubt more GDP is being diverted to those who are least likely to spend it but simultaneously more wealth is being “created” from thin air. If rich people suddendly abstained from spending half of total GDP in a year or “didn’t spend” an amount equal to more than a third of GDP for three years running, the entire economy would collapse.