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Wage paradox at the industry level

There’s a well-known disconnect between the fluctuations of average employment and of average wages: Employment is volatile and dips during recessions, while wages tend to be quite stable. This is a problem for economic models, which have difficulty reconciling the fluctuations in productivity that must justify the changes in employment levels despite the smoothness of wages. (There are exceptions, of course, such as Rudanko (2009) and Lamadon (2014).)

Averages, however, don’t tell the whole story, as we’ve pointed out here before. So we look a little deeper at the occupational level. In the past 15 years and through two business cycles, different occupations have clearly been affected differently by both long-term and cyclical changes. Manufacturing is a notable example of a long-term decline, punctuated by more rapid change during recessions; construction has had a stark rise and fall. On the other hand, white collar service work has been more stable over time. In the graph above, we see large changes in employment among “production occupations” but see much less volatility in “installation and repair occupations” (two sets of occupations with similar skills). Construction and extraction occupations have been subject to well-known fluctuations in demand associated with the housing bubble and resource boom, and these factors show up in the employment figures. “Administrative support”—a different set of skills but at a similar level—has been relatively stable over the period and the cycle.

The employment situations look vastly different for these different occupations, but wages are starkly similar, as shown in the graph below: Wages for each occupation, after normalizing out the difference in levels, follow almost exactly the same pattern. This is strange because economists often assume that wage changes will guide the shifts of workers from one occupation to another; but it seems these shifts are occurring without wages leading them. Or, to explain it from the other direction: If demand is low in an occupation, restricting workers’ ability to work there (i.e., reducing the number of available jobs) should depress wages; but, again, wages do not seem to follow the changes in the levels of workers in these occupations. There are potential explanations, of course, but these facts challenge our initial beliefs.

How these graphs were created: Go to “Browse data by release” and on the final page is “Weekly and Hourly Earnings from the Current Population Survey.” Choose “Classified by occupation and sex.” For the top graph, choose “number of workers” and for the bottom graph choose “median usual earnings.” Finally, choose quarterly data and then the four occupations we’ve shown using data for both sexes. Normalize the data to be 100 at the trough of the Great Recession, June 2009.

Suggested by David Wiczer.

View on FRED, series used in this post: LEU0254498800Q, LEU0254505100Q, LEU0254509100Q, LEU0254512900Q, LEU0254552200Q, LEU0254558500Q, LEU0254562500Q, LEU0254566200Q

The composition of federal tax receipts

The government provides public goods that need to be paid for…somehow. Often this is done with tax revenue. In the case of the U.S. federal government, the composition is illustrated above (in honor of Pi Day, we had to show a pie chart). But the composition of tax receipts has changed over time, which is illustrated below. In the graphs, we see there are four main sources of income: 1) Social Security tax, whose share increased over the first half of our sample, as its tax rate was adapted to finance an older population retiring earlier. 2) Personal income tax, whose share has been surprisingly stable in the lower 40% for 70 years. 3) Import and production taxes, whose share has shrunk considerably, especially as many tariffs have been abolished. 4) Corporate income tax, which has a reputation for being very high in international comparisons and yet yields a relatively small and decreasing share of total federal receipts. If you look closely, you will also notice some interesting fluctuations, such as an increase in 2013-14 in income from assets (in red; the sale of the assets accumulated in the previous years to bail out some firms).

How these graphs were created: Start from the Federal Government Current Receipts and Expenditures release, select the series you want to display, and click on “Add to Graph.” For the top graph, change graph type to “Pie.” For the bottom graph, change the graph type to “Area” with stacking set to “Percent.” At the time this post was written, the corporate income tax data weren’t yet available for 2015:Q4, so the last data point was removed.

Suggested by Christian Zimmermann

View on FRED, series used in this post: A074RC1Q027SBEA, B075RC1Q027SBEA, W007RC1Q027SBEA, W008RC1Q027SBEA, W009RC1Q027SBEA, W011RC1Q027SBEA, W780RC1Q027SBEA

Net migration: The people in (and out of) your neighborhood

 

People move. From house to house, region to region, and country to country. This GeoFRED map colors the big picture with 2008-2012 data on how the world’s population has moved.

Specifically, these numbers reflect national net migration. Green represents positive net migration, with more immigrants than emigrants—that is, more people moved into the country to live than left the country to live elsewhere. Orange represents the opposite, negative net migration, with more emigrants than immigrants. These data, which are 5-year estimates, include both citizens and noncitizens.

Some not-so-surprising observations: The U.S. attracted a net inflow of over 5 million. The people of North Korea stayed put, with a net migration of effectively zero. Syria, in part due to the civil unrest since early 2011, had a net outflow of over 4 million people. And we have no migration data at all for Greenland, which has only about 50,000 residents.

How this map was created: After clicking the “Build New Map” button in the top right, use the “Tools” menu in the top left to do the following: (1) Under “Choose Data,” search for “Net migration.” (2) Under “Edit Legend” / “Number of Color Classes,” select 3 classes and insert the following values in the three user-defined intervals below: -0.1, 0, and any value above the U.S. value of 5.01 million, the highest in the world. (3) Under “Choose Colors,” choose the color scheme you prefer, including the one used here, which is second to last under “Divergent.”

Suggested by Chris Russell.



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