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Posts tagged with: "CE16OV"

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When initial claims, unemployment, and payroll employment clash

Not long ago, the FRED Blog discussed several details about the construction and interpretation of the data for initial weekly claims for unemployment benefits. As of May 30, FRED shows that the four-week moving average was 2.3 million new claims. Yet, the FRED graph above shows that for the entire month of May 2020, there was a decrease in the number of persons unemployed. And there was also a simultaneous increase in the level of payroll employment. How is all this possible?

First of all, data related to the labor market come from different sources: The U.S. Employment and Training Administration reports the number of initial weekly claims for unemployment benefits; and the U.S. Bureau of Labor Statistics, through the Current Employment Statistics (Establishment Survey), reports the payroll employment and unemployment figures.

Also, the data series have similar names but represent different concepts. Even if you file an initial claim for unemployment benefits, for example, it does not necessarily mean that you will be counted as unemployed.

Finally, keep in mind that changes in the number of persons listed on payrolls do not correspond to changes in the number of persons employed or unemployed. The FRED graph below shows that during May, June, July, and October of 2019 there were simultaneous increases in the level of payroll employment and increases in the number of persons unemployed.

How these graphs were created: Search for and select “All Employees, Total Nonfarm” anuse the “Edit Graph” menu to add two more lines: “Unemployment Level” and “Employment Level.” Next, change the units of any of the three series to “Change, Thousands of Persons” and click on “Copy to all.” Lastly, change the graph format to “Bar,” edit the colors to taste, and change the date range to match the time periods of each graph.

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: CE16OV, PAYEMS, UNEMPLOY

The recent evolution of labor force participation

Small movements from a lot of labor market churn

Since the early 2000s, labor force participation has been declining in the U.S. After peaking at 67.3 percent in March of 2000, the labor force participation rate declined consistently to 62.4 percent in September 2015 and has since flattened out. The first graph shows the period of decline in the labor force participation rate, which started in early 2000, flattened out in mid-2005, and then declined again from the onset of the Great Recession to 2015.

Several variables in FRED can illustrate the labor force dynamics at play behind the declining labor force participation rate. The next graph shows the annual change in the labor force (employment plus unemployment). While the labor force has mostly been increasing since 2000, it has not been increasing fast enough to keep up with population growth. Starting in 2014, however, the pace of growth in the labor force picked up, which led to the flattening out of the participation rate.

The last graph shows monthly flows into (red line) and out of (blue line) the labor force. These gross flows are very close to each other, with the net changes (green line) always close to zero. It is the net changes that explain the evolution of aggregate labor force participation. From 2009 to 2016, the positive values are not enough to offset the more negative values and more people flowed out of the labor force. More recently, however, the positive contributions more than offset the negative values, leading to an increase in participation. Despite this recent evolution, the graph does not seem to point to any particular new trend that’s different from the past. This suggests that more research is needed to understand the observed decline in the participation rate.

How these graphs were created:
Graph 1: Search for “Labor Force Participation.” Graph the first result and limit the date range from 2000 to current.
Graph 2: Search for “Unemployment.” Graph the series titled “Unemployment Level.” From the Edit Graph tab, type “Employment Level” in the customize data section search box. Click the series titled “Civilian Employment Level” and then click Add. Finally, type a+b in the formula box and change the units to “Change, Thousands of Persons.”
Graph 3: Search for “Labor Force Flows.” Graph the series titled “Labor Force Flows Employed to Not in Labor Force.” Repeat the process outlined in Graph 2 to modify the line by adding “Labor Force Flows Unemployed to Not in Labor Force” to the graphed series. Now, select the middle menu and search for “Labor Force Flows Not in Labor Force to Unemployed” and add this series as a new line. Repeat the process to modify the line by adding “Labor Force Flows Not in Labor Force to Employed.” Once again, use the middle menu to add “Labor Force Flows Not in Labor Force to Employed” as a new line and then modify the line by adding the remaining three flows as additional series on the new line. Use the letters assigned to each series to calculate the difference of the sum of those flowing into the labor force less those flowing out of the labor force (e.g., consider (a+b)-(c+d)).

Suggested by Maximiliano Dvorkin and Hannah Shell.

View on FRED, series used in this post: CE16OV, CIVPART, LNS17200000, LNS17600000, LNS17800000, LNS17900000, UNEMPLOY

Overcoming the global crisis: USA, Japan, and Italy

Recent GDP data for Italy have rekindled concerns about how well some countries are moving out of the global financial crisis. Professor Justin Wolfers plotted a comparison between real GDP in Italy and the United States that shows the dismal Italian “recovery” and hints at the possibility of a triple-dip recession. (FRED lets you plot this graph pretty quickly.) Several Italian commentators have also made comparisons between Italy and Japan. But these FRED graphs show that the path of Japan’s GDP is more similar to that of U.S. GDP. And, as Professor Wolfers points out, U.S. GDP hasn’t been all that bad in an international context.

Italy’s GDP appears even more dismal if you consider real GDP per capita, which smooths out differences in population growth:

In terms of real GDP per worker (a ratio also used as a measure of labor productivity), Japan’s trend has diverged from the U.S. trend only since the global financial crisis. Because there is a tighter relationship between employment and GDP in the United States than in Japan, real GDP per worker in the United States hardly reveals a recession at all: As GDP was falling in 2008-09, the number of employed workers was also dropping. In Japan, however, workers were not being laid off in such large numbers, so the ratio declined more. Chalk that up to stark differences in the labor markets of these two countries.

Yet, the divergence of Japan from the United States is dwarfed by that of Italian real GDP per worker, showing a dismal protracted reduction since the global financial crisis.

How these graphs were created: The first and second graphs simply use data on real GDP and real GDP per capita, rebasing them to 100 in 2001 using the options under the “EDIT DATA SERIES” tab: Select “Index (Scale value to 100 for chosen period)” and choose the 2001 option. Note that this is a default option for rebasing the series, but one can also choose different dates. Construct the third graph as follows: Create the ratio of the original series (real GDP = a and civilian employees = b; a/b) and then apply the transformation “Index (Scale value to 100 for chosen period)” and again choose 2001. Finally, remove the legend axis on this last graph, which reduces the clutter.

Suggested by Silvio Contessi

View on FRED, series used in this post: CE16OV, GDPC1, ITAEMPTOTQPSMEI, JPNEMPTOTMISMEI, NAEXKP01ITA189S, NAEXKP01ITQ189S, NAEXKP01JPQ189S, NYGDPPCAPKDITA, NYGDPPCAPKDJPN, NYGDPPCAPKDUSA


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