Is Okun's Law Broken? SF Fed Discusses Why Record Worker Productivity Is Painting An Overly Optimistic Jobs Picture

Tyler Durden's picture

One of the big puzzles over the past several months has been the apparent plateau in the unemployment rate, even despite a double dip in initial claims and an overall sentiment that the economy is ready to take a second, post-stimulus, leg down. Aside from the traditional allegations of data fudging by the BLS, one concept often presented has been the unprecedented surge in labor productivity, which despite overall declines in hours per worker and a deterioration in the labor force, has allowed GDP to not only regain its losses from the recent lows, but to stage a dramatic improvement. Today, in a must read paper, the San Francisco Fed tackles precisely this topic, and comes to the unpleasant conclusion that unemployment rate forecasts may well be too rosy for 2010 and beyond, especially if companies continue to sacrifice workers at the expense of ever increasing "worker productivity" which in itself is about as "credible" as any other data series presented by the government over the past year.

The core of the article revolves around a recently observed record variation from the expected Okun Law distribution of the Output Gap and Unemployment, which as can be seen in the chart below, has never been as dramatic as in Q4, 2009.

Here is a brief observation on what the chart above details:

The figure plots the relationship between deviations from trend of real GDP and the unemployment rate from the first quarter of 1949 through the fourth quarter of 2009. Trends are taken from the Congressional Budget Office’s (2010) most recent estimates. The dotted line plots a statistical relationship between the output and unemployment gap from the first quarter of 1949 through the first quarter of 2007. As the plot shows, the empirical association that Okun noted generally describes the  data well. This is true across different points in the business cycle and across a long span of time.

Indeed, early in the 2007 recession there was little evidence of divergence from Okun’s law. In the second quarter of 2009, however, things went off track and a wedge began to emerge between changes in output and changes in unemployment. As shown by the red squares appearing above the line in Figure 1, the familiar two-for-one pattern broke down and unemployment went up by substantially more than expected. By the fourth quarter of 2009, the deviations in output to unemployment were the largest observed over the span of the data. The divergence of the current data from the typical pattern wreaks havoc with forecasters, but also leaves a puzzle: Why did unemployment rise so rapidly in 2009?

The FRBSF then goes on to detail the key variables that go into determining the output gap and overall unemployment: the labor market participation rate, the hours worked per worker, and, most notably the GDP per nonfarm hour:

The first point to consider is whether changes in worker behavior have boosted the unemployment rate and disrupted the Okun’s law relationship. As the first panel of Figure 2 suggests, labor force participation, or the fraction of the working-age population reporting that it is working or looking for work, has bounced around during this downturn. Typically, labor force participation will fall in a downturn as potential workers realize their prospects are weak and withdraw from the labor force to pursue other goals or because they are discouraged. In the first year of the recession, this normal pattern failed as individuals remained in the labor force despite the weakening economy (Daly, Hobijn, and Kwok 2009). However, by 2009, this pattern had reversed and labor force participation dropped precipitously. Currently, the trend in the labor force participation rate is helping reduce, rather than boost, measured unemployment.

Another factor that might be contributing to the breakdown in Okun’s law is hours worked per employee. In recessions, the number of hours worked generally falls as firms cut back on overtime or regular hours in response to declines in demand. By reducing worker hours instead of reducing the workforce, firms lay off fewer workers. If this recession were different and firms laid off more workers and then worked the remaining ones longer, then we would expect some deviation in the normal GDP/unemployment relationship. However, the second panel of Figure 2 does not support this hypothesis. The hours worked per employee is roughly in line with previous periods and, if anything, is working to reduce, rather than increase, the wedge in Okun’s law.

The final panel of Figure 2 points to the factor that turns out to be the main driver of the recent departure from Okun’s law—average labor productivity, measured as GDP per nonfarm hour worked. The deviation in average labor productivity relative to the GDP gap is far outside the range plotted over time and is consistent with the rapid productivity growth recorded in 2009. The surge in labor productivity allowed employers to keep output steady while shedding workers and reducing hours of work in the economy. As such, it allowed unemployment to rise much more than expected given the change in GDP, breaking the normal pattern between the two measures observed over the past 60 years.

A longitudinal time-course analysis presents these finding in a more digestible way: the only reason why GDP has not collapsed, and why the output gap is not double where it is presented to be, is exclusively due to workers who are currently employed playing far less Solitaire and just happy to have their jobs, even though average wages have continued to be at cycle lows.

The authors' conclusion is a troubling one, not just because it comes from the Federal Reserve itself, which is always conflicted and has a propensity to demonstrate data in the rosiest picture possible, but because they are in fact, very much correct in their interpretation.

The data presented here consistently point to unusually strong productivity growth as the main driver of the departure from Okun’s law in 2009. A key question that remains unanswered by this analysis is whether this pattern will continue in 2010. Most forecasters assume that the economy will return to its historical path this year, following Okun’s two-to-one ratio of changes in GDP and changes in unemployment. Under this scenario, unemployment would begin to edge down this year as the economy recovers and gains momentum. But there are clearly risks to this view. Some of the surge in productivity growth in 2009 was likely due to such cyclical factors as layoffs of least productive workers, greater intensity of work effort, and shifts away from producing intangible capital, which is not measured in output statistics. Anecdotal evidence suggests that efforts to contain costs and remain nimble in the face of uncertainty have become a fixture in business strategy. If productivity keeps on growing at an above-average pace, then unemployment forecasts based on Okun’s law could continue to be overly optimistic.

While it would have been easier to buy the premise that Americans are suddenly far more productive because our civilization suddenly discovered the Internet, this is patently not true. The last secular boost to productivity came ten years ago with the advent of information commoditization courtesy of the interwebs. Since then the only major discovery has been the iPhone and Twitter, which one could argue detract from productivity, not add to it. Indeed, it is very hard to swallow that our economy has not collapsed merely because those who are employed have been cranking out widgets at a record pace.

Michael Pento does an astute, if somewhat perfectly cynical, analysis of this quandary.

I went through the last 20 years of productivity data and couldn't
find anything close to those three consecutive quarterly booms in
output per hour of work. It sort of like saying at the start of Q2 2009
we invented the internet and the wheel on the same day.

What makes the claim of surging productivity even more amazing is
that the U.S. economy is comprised of nearly 90% services. That means
waitresses must be kicking people out of restaurants before they are
finished eating or people have learned to eat much faster. Then again
maybe doctors have learned to truncate their exams of patients or
perhaps they have somehow found away to eliminated the second waiting
room you have to sit it once you get past the reception area.

I guess productivity gains can come by magic just through the
process of firing workers. Somehow we were are able to increase the
output of goods and services as a nation even though 8.4 million people
have lost their jobs and hours worked are down. What a relief it must
be for businesses to shed themselves of all that dead wood. If we are
to believe these productivity numbers we also must believe those
formerly employed individuals were doing nothing at all but standing
around with their thumbs up their bum.
Call me skeptical.

Skeptical indeed. And since there is a direct causal chain in the variables that ultimately lead to GDP, productivity is the one intangible where the conflicting data of rising GDP and declining workforce collide. The question is whether this is a cause or effect: is the Census bureau spinning (and spewing) data that has no bearing in the real world (i.e., GDP), with the weakest link being this unprecedented worker productivity? We leave it up to readers to decide whether they believe the productivity boost thesis is credible, although with even the San Fred Fed questioning it outright, we expect to see some major declines in GDP once productivity recedes to historic levels, if it is not accompanied by an increase in the work force. And based on contemporaneous data, even with massive BLS fudging, this is not going to happen any time soon, once again leaving us with the sad conclusion that all rumors of V- or U-shaped recovery are greatly exaggerated.

Full San Fran Fed paper.