Where Have All The Workers Gone? By Guest Blogger Buck Klemkosky
Employment. Where is Hercules?
ObamaCare, Jobs, and Global Competitiveness
Payroll Employment Data Releases – Will the fans go Crazy or not?
Look at the data — Employment and Unemployment
The following charts from the St. Louis Fed contain long-term data for several key U.S. labor indicators. See the following links for updates: http://research.stlouisfed.org/publications/net/page10.pdf
Labor force is a measure of the number of persons in the population that either are working or are actively looking for work. The labor force is estimated by surveys done by the U.S. Department of Labor (or its counterpart in other countries)
Labor force participation rate is the percent of the population (16 years old or older) that are employed or seeking work. The second chart shows that the labor force participation rate reached about 67% in the late 1990s. It was up from about 64% in 1979. After 2000 the labor force participation rate shows a downward trend from a high of 67% to about 64% of the population in 2011.
Employment is the number of persons in the labor force who have found work or will soon be reporting to work. Two different government surveys indicate employment. The Household survey includes persons in agriculture and counts each person (who says they are employed) as having one job. The payroll survey does not include agricultural establishments and counts every job. The first chart shows the percentage changes in these two measures. There was much discussion about the different measures following the 2001 recession when the household survey was showing much faster employment growth than the payroll survey. Because of its larger sample size, most economists attribute more reliability to the payroll survey. However, because the household survey covers a wider number of industries and since it covers the many start-ups, small, and self-employed companies, some experts believed it was giving the most accurate reading of employment changes. Notice that while divergences in these two series readily occur, their differences often decrease over time. More recently, employment fell by almost 5% in 2009 and while it was no longer falling in 2011, the growth rate was weak, barely above zero percent.
Unemployment rate is the number of unemployed persons divided by the number of persons in the labor force. The second chart shows a long time period of declining unemployment rates between 1992 and 2000. It also shows what appears to be a downward trend – with the successive peaks and valleys getting smaller and smaller. Cycles revolve around this trend but the overall direction has been towards a lower unemployment rate in the U.S. What might be considered a “normal” unemployment rate in the early 1980s would be higher than a “normal” unemployment rate in 2000. Most recently, the unemployment rate exceeded 9% in the recession and was still near that rate in 2011.
Frictional unemployment refers to the number of unemployed persons who will find jobs quickly. They are not literally between jobs but they will find employment in about four weeks or less. The above chart shows the unemployment rate by duration. Since about 1995, the unemployment rate of those who were unemployed for less than 5 weeks was approximately 2%. That means that close to half of all the unemployed over that time period would fit into this category of frictional unemployment.
Structural unemployment refers to people who will be without jobs for a substantial period of time. According to the above chart, the median time spent unemployed in 2011 was about 22 weeks. That compares to about 10 weeks in the decade before. What we mean by structural unemployment is probably more than 52 weeks – so we know that in that year, the structurally unemployed group was quite small.
Full Employment is a term that is meant to describe an optimal level or rate of unemployment. Because of both frictional and structural unemployment, most countries will never attain a zero unemployment rate. What we mean by full employment can be described several ways.
- First, it means it is about the best we can normally do with employment when times are good.
- Second, we acknowledge that there are times when the actual unemployment rate could be lower than the full employment unemployment rate, but such times would not be frequent or normal.
- Third, being a best-normal unemployment rate we often think of it as a long-term equilibrium rate – one that is like a magnet. Unemployment can be above or below this rate – but it would always be “drawn back to the normal long-run equilibrium or the full employment rate.
- Fourth, this full employment rate may be a long-run rate – but even it can change. We don’t expect the full employment rate to change from month to month or even from year to year. But it might differ in the 1990s from what it was in the 1980s. Below we discuss more why it might change.
The Natural Rate of Unemployment is a synonym used for the full employment rate. The word “natural” is meant to convey the idea of equilibrium – the mean-reverting aspect of unemployment. Economists, therefore, measure the natural rate of unemployment as the average unemployment rate over a given period of time. If the average unemployment rate in the 1980s was higher than the average of the 1990s, then we would infer that the full employment unemployment rate declined.
NAIRU was a famous person from India. No, just kidding.
That was Nehru. NAIRU literally means “non-accelerating inflation rate of unemployment.” NAIRU is another synonym for full employment. In this case the definition of full employment hinges on the behavior of inflation. In practical terms, if NAIRU is 6%, then it means that so long as the actual unemployment rate stays above 6%, then the inflation rate will not rise (and it probably will fall). If NAIRU is 6% and the actual unemployment rate is less than 6%, then inflation will probably rise. In general terms, then, it is the relationship between NAIRU and the actual unemployment rate that is a predictor of the inflation rate. The lower is NAIRU, relative to the actual unemployment rate, the lower will be the rate of inflation.
- UN > NAIRU ………. inflation rate falls
- UN < NAIRU ……….. inflation rate rises
- UN = NAIRU ……….. inflation rate is unchanged
This next link takes you to the Bureau of Labor Statistics of the US Department of Labor. It is the press release for the monthly report on employment and unemployment.
http://www.bls.gov/news.release/pdf/empsit.pdf This is included here just to show how the employment/unemployment data are presented and analyzed. It illustrates many of the concepts discussed in this note.
International Application: Unemployment rates for nine countries
The following table is from the Organization for Economic Cooperation Economic Outlook No. 9:
http://www.oecd.org/document/61/0,2340,en_2649_201185_2483901_1_1_1_1,00.html ⎯ it has comparisons of unemployment rates for OECD countries since 1992. Looking across the row for unemployment rates in the early part of 2004, the highest rates were in Poland, The Slovak Republic, Spain, Greece, France and Germany and the lowest were Japan, the Korea, New Zealand, Ireland, and the Netherlands. Looking at the rates over time creates some interesting perspectives.
Harmonized unemployment rates show that most countries continued to struggle with high unemployment rates in 2011. At 3.1% Korea has the lowest rate amongst the countries listed. Spain in contrast was struggling with rates above 21.2% in 2011.
Some people use this simple NAIRU theory as a basis for inflation forecasting. It sounds pretty straight forward but several things make this challenging.
- First, you have to know the exact value of NAIRU. As it turns out, NAIRU is one of those economic ideas that is hard to nail down. It has the annoying habit of being both complex and changing.
- Second, there is no published data on NAIRU. It is something that economists try to estimate using other figures but there is no direct measure of it.
- Third, inflation forecasts and NAIRU depend very much on the public’s inflation expectations. As we noted above, forecasting measures of inflation expectations is not easy either.