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How healthy is the labor market, really?

Economists, policy wonks, and the public often look at the unemployment rate to quickly assess the U.S. economy. Although the unemployment rate provides some understanding of the cyclical state of the labor market, it doesn’t account for those who have dropped out of the labor force. The labor force participation rate captures that information. Both rates (shown in the top graph) have declined since the end of the Great Recession, which may imply that there’s unmeasured slack in the labor market.

Andreas Hornstein and Marianna Kudlyak from the Federal Reserve Bank of Richmond and Fabian Lange from McGill University constructed a more comprehensive way of examining resource utilization in the U.S. labor market. Their non-employment index (NEI) counts those who are unemployed (as traditionally defined) and those who have dropped out of the labor force. The NEI weights those who have dropped out of the labor force according to their “attachment”—defined by the Bureau of Labor Statistics as the likelihood a person will transition back to employment, which is based on each group’s historical transition rate to employment relative to the highest transition rate among all groups. This weighting allows the authors to count all non-employed individuals without drawing “arbitrary distinctions on who is to be included.”

The BLS classifies the groups in the index as (1) unemployed, (2) out of the labor force but desiring a job, or (3) out of labor force but without the intention to reenter. The BLS further categorizes those who are out of the labor force but want a job as (2a) marginally attached because they’re discouraged by poor job prospects, (2b) marginally attached but haven’t looked for work during the most recent month, or (2c) temporarily out of the labor force for other reasons. Finally, the BLS classifies those who are out of the labor force but do not want a job as (3a) in school, (3b) not in school, (3c) retired, or (3d) disabled.

Hornstein, Kudlyak, and Lange recommend interpreting the NEI in comparison with the standard measure of unemployment. Generally, the two measures move in line with each other, with the exception of the period following the Great Recession, as shown in the bottom graph. This graph also includes a third series—the green line—that incorporates those who work part time in lieu of full time for economic reasons. More information on the NEI can be found here.

How these graphs were created: Top graph: Search for and select the monthly, seasonally adjusted unemployment rate. Use the “Add Data Series”/“Add new series” option to search for and select the monthly, seasonally adjusted labor force participation rate; be sure to set the y-axis position to the right. Bottom graph: Again, search for and select the monthly, seasonally adjusted unemployment rate. Then use the “Add Data Series”/“Add new series” option to add the two other series: Search for “non employment index” and select the base index (not the index that includes people working part-time for economic reasons). Then search for “non employment index” again and select the index that includes people working part-time for economic reasons.

Suggested by Travis May

View on FRED, series used in this post: CIVPART, NEIM156SFRBRIC, NEIPTERM156SFRBRIC, UNRATE

The rise of education and health services

There’s little doubt that the prices of education and health care have risen considerably over the past decades. One reason for this is that more and more people work in these fields. The graph displays the share of workers in the education and health services sector among all employees: The share was about 4 percent in the 1940s and is now above 15 percent. Note also that this sector appears to be quite recession-proof: The share has gone up in all recent recessions, mostly because general employment declined while this sector’s employment did not. Interestingly, the employment share systematically stays up when the recession is over.

How this graph was created: Search for and select “All Employees: Education and Health Services,” and then modify the existing series by adding the “All Employees: Total nonfarm” series and applying the data transformation “a/b.” Choose graph type “Area” in the graph settings.

Suggested by Christian Zimmermann

View on FRED, series used in this post: PAYEMS, USEHS

The range of bank deposits worldwide

Safe and sound banks are key to a healthy US economy and are at the heart of promoting growth and development. Banks’ basic intermediary function of matching savers with investors is predicated on receiving deposits that can be transformed into loans. There is no rule of thumb for how large those deposits need to be for banks to best operate as financial intermediaries, and there are large differences among countries in that regard.

The FRED map shows data from the World Bank about the value of bank deposits by nation divided by the value of that nation’s gross domestic product (GDP). This is reported as a percent. During 2020, that figure had a median value of 64% but widely ranged between 9% (Tajikistan) and 429% (Luxembourg). Why such differences?

As mentioned above, a solid banking system helps promote economic growth and development, so economists argue that good access to finance is both part and parcel of prosperity. However, the specific relationship between financial development and economic growth continues to be the subject of active research. You can learn more about this topic from the World Bank and the International Monetary Fund.

How this map created: Search FRED for “Bank Deposits to GDP for Nigeria” and click the “View Map” option. Next, click on “Edit Map” and select “Data grouped by: User Defined Method.” Change the data interval values and customize the colors for each interval to match those shown in the map.

Suggested by Diego Mendez-Carbajo.



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