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Unemployment rates by occupation

Layoffs are more likely for some jobs

This FRED graph shows the unemployment rates for various occupations. What’s striking is that, over the 18-year sample period, the ordering hardly changes. Of course, the magnitude of unemployment responds to what’s happening in the overall economy. But management occupations and professionals, for example, always have the lowest unemployment rates by quite a margin. Mining, agriculture, construction, and maintenance have the highest unemployment rates, whether the economy is in a boom or a recession, with manufacturing and other production occupations a close second. These two are particularly affected by recessions. Sales, office, and service occupations fall in the middle.

Obviously, what happens in specific labor markets correlates with what happens in the sector at large: For example, construction workers typically work in the construction sector. But this correlation isn’t absolute—a prime example being that managers are sprinkled across all sectors. This data picture shows that choosing which occupation to work in can be more important than which sector to work in. The Current Population Survey has more detailed data that can add to this perspective.

How this graph was created: Start from the Current Population Survey, click on the table with employment and unemployment by occupation (A-13), select the relevant series, and click “Add to Graph.” Change the order of the series legend to match the order in the graph by clicking “Edit Graph,” opening the format tab, and moving the series up or down. (This last step can be slow.)

Suggested by Christian Zimmermann.

View on FRED, series used in this post: LNU04032215, LNU04032218, LNU04032219, LNU04032222, LNU04032226

When economies just don’t grow

Some countries suffer from long-term economic stagnation

In general, economies grow. They do this by accumulating capital (machinery, structures, infrastructure), increasing higher education, and making technological progress. Sometimes they shrink for a time because of recessions, but the general trend is for economies to move upward. Yet, there are a few countries that have stagnated or even shrunk over the longer run.

The graph shows five of these countries. (By the way, we use real GDP per capita so that population growth and inflation don’t muddy our measurement of economic performance.) Two of these are poor countries that just don’t seem to be making any progress. The worst case is Madagascar, which has suffered from endemic mismanagement since its independence. The other is Zimbabwe, which had impressive growth in the late 1960s and early 1970s that was reversed in the past two decades by mismanagement that culminated in extreme hyperinflation.

Two other countries have a very different history. Brunei is a small southeast Asian nation rich in oil and natural gas. It has been wealthy since its independence, but the decline of oil prices as well as lower production have had an adverse impact on the economy. Equatorial Guinea benefited from the discovery of oil in the 1990s, leading to a spectacular boom that allowed it to shoot past its former colonial power, Spain. But here, again, the lower price of oil has shrunk the economy substantially in subsequent years.

The final case is Ukraine, which had a few very rough years after the fall of the Berlin Wall, as did all economies in the former Soviet Union and Eastern Bloc. But unlike its neighbors, it’s still far from returning to the level it started from, at least in part because of chronic corruption and political upheaval at home and with neighboring countries.

How this graph was created: Search for “constant GDP per capita Madagascar” and click on the series. To add the other lines, click on “Edit Graph,” open the “Add Line” panel, and search for the next series. Add the series and repeat until satisfied. Finally, as the range of values for the series is quite wide, open the “Format” panel and put the y-axis to right for some of them (in our case, Brunei and Equatorial Guinea).

Suggested by Christian Zimmermann.

View on FRED, series used in this post: NYGDPPCAPKDBRN, NYGDPPCAPKDGNQ, NYGDPPCAPKDMDG, NYGDPPCAPKDUKR, NYGDPPCAPKDZWE


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