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SNAP!

FRED recently added SNAP data. SNAP stands for “Supplemental Nutrition Assistance Program”—more commonly referred to as food stamps. FRED has data at the state and county level on the number of benefit recipients for the past 30 years or so. In the graph here, we chose five states with similar population size. A few points stand out: 1) It’s remarkable how little the state rankings have changed over the years. The rise of Arizona is likely due to a relative population increase. 2) Apparent seasonal fluctuations in some states disappear after a few years. 3) Since 2000, the numbers of recipients has more than doubled; in Massachusetts, it quadrupled. This rise has occurred through both booms and recessions and cannot be explained by population increases.

How this graph was created: Search for SNAP, then restrict the results by selecting the “monthly” and “states” tags in the sidebar. Then choose your states and click “Add to Graph.”

Suggested by Christian Zimmermann

View on FRED, series used in this post: BRAZ04M647NCEN, BRIN18M647NCEN, BRMA25M647NCEN, BRTN47M647NCEN, BRWA53M647NCEN

The demographics of the labor force participation rate

There is much lamenting about the decline in the labor force participation rate. As we recently discussed on this blog, while the rate decreased quickly during the previous recession and its recovery, the overall decline began several years before. This decline indicates there must be more than cyclical or even policy-related forces at work. One likely candidate is demographics. In the graph above, the proportion of the U.S. population 25 to 54 years of age follows a pattern similar to that of the labor force participation rate over the past 10 years. Why look at this 25-54 age range? Because this group has the highest labor force participation rate. So, if the share of this age group is declining, the aggregate labor force participation rate is likely to decline as well.

How this graph was created: For the first line, search for “population 25-54” and select “Civilian noninstitutional population—25-54 years.” To create the ratio, add the “Civilian noninstitutional population” series via the “Add Data Series” option: When you add this series, be sure to select “Modify existing series” for series 1. Then use the “Create your own data transformation” option using the formula a/b*100 so that the result is expressed in percentages. For the second line, simply add the civilian labor force participation rate as series 2.

Suggested by Christian Zimmermann

View on FRED, series used in this post: CIVPART, CNP16OV, LNU00000060

Don’t be deceived by seasonality

In the graph above, the two series have the same label, yet they tell very different stories: The red line bounces between a few values, and the blue line shows a large increase last summer and then a decrease this winter. The difference is that the blue line reflects raw data, while the red line has been adjusted for seasonal regularities. Obviously, we need to take into account that the labor force participation rate increases every summer; only then can we correctly analyze how the economy is faring. Otherwise, one could draw false conclusions, especially by looking at a single year.

Expanding the sample period reveals the obvious seasonal variations in the path of the blue line, and the graph below shows this. (You can also use the slider bar under the graph above to achieve the same view.) Note, however, that these seasonal variations are not as strong as they used to be, presumably because the economy has become less sensitive to weather conditions.

How these graphs were created: Search for “Labor force participation,” select the two series you want, and click on “Add to Graph.” Limit the sample period to one year for the top graph and fully expand the sample period for the bottom graph.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CIVPART, LNU01300000


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