Part of my research involves examining the “flow” of persons among three labor force classifications: employed, unemployed, and not in the labor force (NILF). These flows are calculated by observing the change in a person’s labor force status from one month to the next. For example, a person who was unemployed last month but had a job this month would have made a UE transition. The sum of all persons making such transitions that month is called the UE flow.
We use the term gross flows to distinguish such measures from net flows, which are the change in the stock from one month to the next. It is the net change that gets reported in government statistics. For example, if 250,000 persons found a job this month and 100,000 lost a job, the net change is +150,000 persons. The total gross flow, however, is 350,000 persons.
Gross flows are considerably larger than net flows. Over the last 30 years the U.S. economy has added about 150,000 jobs a month (net) on average. During that same period the average gross flow into and out of employment is over 10 million persons a month! To put that figure in perspective, 5.4 percent of the U.S. working-age population moves into and out of employment every month. Accordingly, the net changes reported in the monthly Employment Situation release do not capture the true dynamism in the U.S. labor market.
Although not directly germane to my research, I recently became interested in the long term trend in gross worker flows. The figure below plots the trend in worker flows for 1976-2007. The series shown is the sum of all flows into and out of employment, expressed as a share of population. Since I am interested in only the trend in the series, I remove the substantial month-to-month variation by seasonally adjusting the data and then smoothing the seasonally-adjusted data using a local weighted least squares regression. Shaded bars indicate recessions as determined by the NBER.
There has been a dramatic decrease in gross flows over the past 30 years. This decrease is consistent with evidence from Bleakley, Ferris, and Fuhrer (1999) and Fallick and Fleischman (2004), who also observe declines in gross flows.
In the late 1970s, flows averaged about 5.8 percent of the population a month. This fell more or less steadily throughout the 1980s and early 1990s until bottoming at 5 percent at the end of 1996. Flows grew to just over 5.3 percent a month in 2001 after which they fell off a cliff, stabilizing briefly in 2004-05. By the end of 2007, the total gross flow was below 5 percent of the population. To put a number to this trend, the decline in gross flows means that about 1.7 million fewer persons a month move into and out of employment today compared to 1977.
Identifying an empirical regularity is only a first step in research. Without understanding the causes of this trend it is impossible to draw any meaningful implications from the data. In fact, it is difficult to say whether the secular decline in total gross flows into and out of employment is “good” or “bad”. On the one hand, if the decline represents decreased employment volatility for U.S. workers — increased job stability — then it may be a positive development. On the other hand, if the observed decline in gross flows results from decreasing allocative efficiency — labor market “sclerosis” — then the trend may be worrisome. Other possible explanations include “job lock,” where employees cannot easily change jobs because of employer-provided health insurance, and increased efficiency in employer-employee job matching, resulting in fewer low-quality matches and thus less job turnover.
The examples above show that both explanations and implications can be conflicting and contradictory. This is why economists write models. Also why Truman wanted a one-armed economist.
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