According to preliminary data recently released by the Bureau of Labor Statistics, nonfarm business sector labor productivity increased 3.6 percent in the first quarter of 2019.
That was the largest year-over-year increase in more than eight years.
This increase surprised most analysts, and while practitioners of the dismal science rarely get excited, this certainly caught our attention. It is not an exaggeration to say that the rate of change in productivity levels is the most important statistic in macroeconomics.
Just think about it: If you want to expand the size of the overall economic pie in the long run, all you have to do is add more people. This tends to happen naturally as a result of a positive birthrate and immigration, so we don't really need economists to understand this.
But if you want to give everybody a bigger piece of pie and raise their standard of living, you must increase productivity. In the long term, growth in real GDP is population growth added to productivity growth.
Here is where things get tricky — and yes, the tricky times are when economists come in handy. The rate of productivity is an easy concept to understand, but in practice it is almost impossible to measure.
The Bureau of Labor Statistics (BLS) calculates labor productivity by measuring total real output of goods and services in one calendar quarter and then dividing it by the total number of hours worked that quarter.
Plastics companies can do something similar, and I think it is worthwhile. For example, an injection molder can take the total number of parts it makes in a month, divide it by the number of hours all the employees worked, and it would get a productivity rate expressed as parts per hour. If that rate increases over time, then the molder is more productive.
The problem for BLS is that the U.S. economy is incredibly large, diverse and mostly service oriented. Compounding these problems is the fact that technology is rapidly changing the types of goods and services produced and the speed it takes to produce them. So even if BLS could get a pretty good estimate of hours worked, it is very difficult to consistently measure the real output levels for all the various types of goods and services that are produced.
As a result, the most important macroeconomic indicator for measuring changes in U.S. competitiveness and prosperity has a very large margin for error. Nevertheless, I still think it is instructive to monitor the longer-term trends in these data.
It stands to reason that the trend in productivity levels for the U.S. manufacturing sector would be a bit easier to calculate because manufacturers, like injection molding companies, tend to make things that can be more easily measured. To be sure, U.S. manufacturing is large, diverse, and rapidly changing. But I tend to think it is less difficult for manufacturers to get their heads around the idea of productivity.
But while BLS manufacturing data might be more reliable, the recent trend in this data is not as strong as the trend in the overall data. Manufacturing sector labor productivity increased 1.7 percent in the first quarter of 2019 when compared with the fourth quarter of 2018. The year-over-year comparison indicates that manufacturing productivity in the first quarter increased by 1.2 percent when compared with the same quarter a year ago.
The chart of this data shows that trends for the manufacturing sector and the overall economy started to diverge about four years ago and that the gap has widened every year since. Gains in productivity for manufacturers have accelerated in the past couple of years — indicated by the steeper slope of the line — but these increases are not keeping pace with gains in many other sectors of the economy.
This is a stark contrast to the situation that many of us remember when we first started our working lives. For many years, the U.S. manufacturing sector was the very definition of increasing productivity. Whole communities were built around factories, and manufacturing workers were the backbone of America's middle class. U.S. manufacturers were increasingly productive, so everybody's piece of economic pie steadily grew larger.
Nowadays, the average wages paid to U.S. manufacturing workers are below the overall national average, and the rate of increase in wages in recent years is also slower. Clearly, we need to increase the slope of the manufacturing line on my chart. But while it is easier to measure productivity levels for manufacturing, accelerating the gains in these levels will prove incredibly difficult.
At the risk of oversimplifying the problem, I offer the following ideas as a starting point for pushing the manufacturing curve ever higher:
• We must innovate. This means developing new products and new processes for producing them. This is already happening at a rapid rate, but we must maintain the momentum.
• We must invest. We must invest in capital equipment and invest in employee skills. The trends in both these areas have improved recently, but they are coming after a long period of chronic underinvestment, and the overall levels are still below where they should be.
• We must inspire. We must inspire our business leaders to invest more and our workers to learn more. This is a symbiotic relationship in which both sides help each other get to where they need to be.
Once this occurs, it will inspire the global marketplace to demand more of the world's most innovative products manufactured by skilled, inspired, highly paid workers.