Federal Reserve Economic Data

The FRED® Blog

The pitfalls of mapping poverty

Definitions are important, but difficult to pin down

Where is poverty prevalent in the United States? There’s no simple answer to this question because notions of poverty differ. And defining an objective threshold for poverty is especially difficult. But we can use FRED to put forth a good-faith effort. The Census Bureau uses a specific procedure to categorize poverty and then provides the data: First, they categorize 48 types of American households—which vary by age and composition. Second, they determine what income counts toward the threshold. And third, they determine what that threshold is. They then estimate what proportion of these households live below that threshold.

The results at the county level are shown in the GeoFRED map above. Before interpreting it, though, one needs to keep in mind that there’s no geographical variation for the poverty thresholds. This means that two families with the same income may be considered to be living in poverty regardless of whether they live in a high-cost or low-cost county. This absence of regional adjustment may bias the map. Indeed, according to some (subjective) poverty standards, too many people may be counted as poor in Mississippi (where costs are rather low) and not enough may be counted in the Washington, DC, area (where costs are rather high). So, one should always be cautious when looking at poverty data.

How this map was created: The original post referenced an interactive map from our now discontinued GeoFRED site. The revised post provides a replacement map from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.

Suggested by Christian Zimmermann.

Who holds mortgages?

When you take out a mortgage, someone (usually some financial institution) “holds” that mortgage. That is, they’re the lender and you must pay them back. Nowadays it’s not always obvious who holds your mortgage, as it may have been sold to someone else, much like a Treasury bond can be sold. The Board of Governors, though, has been tracking this information since WWII. The graph above reveals that the composition of mortgage holders has changed over time. Initially, it was mostly banks—but also some individuals and, to a small degree, also the government. Gradually, mortgage pools and trusts have taken over—that is, companies that specialize in the pooling of similar mortgages that can then be sold as securities. Thus, the so-called securitization of mortgages. These are the institutions that some believe were at the center of the troubles that led to the previous recession and financial crisis. Indeed, the graph shows that the government took over a large portion of their portfolios in 2010 in an attempt to stabilize the mortgage and real estate markets.

How this graph was created: Search for mortgage debt outstanding release in FRED, check the series you want,* and click on “Add to Graph.” From the “Edit Graph” menu, open the “Format” panel, choose graph type “Area” with stacking set to “Percent.” Have the graph start in 1952 to avoid those messy first years.

* Pay careful attention to the series you choose; many of them have similar titles, and some are subsets of larger series. Refer to the series IDs noted below if you want to use the specific series shown here.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: MDOTHFRA, MDOTHIOH, MDOTHMFI, MDOTHMPT

A plateau for manufacturing?

After steady growth, manufacturing productivity seems at a standstill

The Bureau of Labor Statistics’ productivity and costs release provides data that can help us better understand the state of U.S. manufacturing. The graph above shows the evolution of manufacturing output since 1987. Notice the slow but steady growth in output since the Great Recession’s big dip.

What’s behind this slow and steady growth? The first suspect we’ll look at is manufacturing employment. The graph above shows there’s been a strong downward trend, which has accelerated during each recession. Yet, since 2010, manufacturing employment has been slowly making its way back up.

Next we’ll look at how much each worker produces in the manufacturing sector. Here, the story’s different: The general trend has been continuous increases in productivity per worker, but something seems to have broken with the Great Recession. First a major drop in productivity, then some progress getting back to trend, and then no progress since about 2010.

What if, since the Great Recession, manufacturing jobs have offered fewer hours of work or more part-time work? Maybe productivity per hour worked is growing. But the graph above, which shows productivity per hour instead of per person, shows no difference. The cause of this productivity standstill is thus either lack of technological progress or (more likely) a change in the composition of the manufacturing workforce toward lower-productivity work.

How these graphs were created: Search for “manufacturing sector” and each of the discussed series should be among the top choices. Simply choose them and click “Add to Graph.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: OPHMFG, OUTMS, PRS30006013, PRS30006163


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