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Where is the U.S. growing?

Population growth in metropolitan statistical areas

If you’ve looked at FRED data, you’ve probably seen the term MSA, which is “metropolitan statistical area,” which the Census defines as “a core area containing a substantial population nucleus, together with adjacent communities having a high degree of economic and social integration with that core.” It’s that high degree of economic integration that can make MSAs more comprehensive and relevant than just the specific governmental boundaries of cities and counties. In fact, MSAs often span several counties and sometimes straddle state borders. Think of it as a commuting basin… Or create your own metaphor!

The GeoFRED map here shows population growth for MSAs: Red is at the strong end of the growth spectrum and dark blue is at the weak end. What’s behind these changes in population? The main drivers are moves between MSAs, moves from rural areas into MSAs, and immigration from abroad. In some years, the boundaries of some MSAs are adjusted and can lead to substantial increases. If you follow the “View on GeoFRED” link below the map, you can select different years and see migration patterns over time, which are affected by local economic conditions. Some MSAs, like New York–Northern New Jersey–Long Island, change pretty drastically from year to year. Other MSAs are steadier: For example, growth in St. Louis is consistently slow and growth in Las Vegas–Paradise is consistently fast.

How this map was created: On FRED, search for the population of any MSA you can think of: Choose one of the larger U.S. cities, and the MSA data should appear near the top of the results. Then click on the link and navigate below the graph to the Related Resources section. Click the link to the GeoFRED map. You may need to change the units to “Percent change from year ago” and zoom out to see more of the nation. You’ll need to zoom out even further to go beyond the continental U.S. (Sorry, Alaska and Hawaii.)

Suggested by Christian Zimmermann.

Living in an uncertain world

More uncertainty data in FRED

We’ve recently looked at different ways to measure uncertainty in the U.S. economy. Today, we look at international data on economic and policy uncertainty. While U.S.-level data were measured by looking at what newspapers report, the international data are based on quarterly reports from the Economist Intelligence Unit in each country. Having a single source for each country means one must be careful in interpreting the data: It contains quite a bit of noise, and there may be some idiosyncrasies for each country that make cross-country comparisons difficult: A report may focus on one particular aspect of a country, or it may be related to uncertainties in other locations that may affect that country.

The GeoFRED map above covers the third quarter of 2019. The countries with the highest uncertainty are Ireland and the United Kingdom, no doubt due to the Brexit situation. But Switzerland also has a very high score, while Iraq and Pakistan enjoy perfect scores. And observations from other quarters change dramatically for some countries. This is where it’s important not to focus on a single data point, but to have a more holistic approach to the data.

The graph below shows a few things: The economic and policy uncertainty in the United Kingdom was not a fluke for that one quarter. The situation in Iraq is clearly not always that rosy, but it still regularly scores low, maybe because no change is expected. In Switzerland, where certainty is the norm, uncertainties are worth playing up.

As we implied earlier, there are some lessons to draw from the data taken as a whole. The authors of the data highlight in their report that this uncertainty index does usually foreshadow growth troubles. Democracies, likely due to their political process, have more uncertainties than authoritarian regimes. (Again: See Switzerland versus Iraq.) More developed economies also have fewer uncertainties to worry about.

How the map and the graph were created: The graph: From the World Uncertainty Index release table, click on the link to the individual country indices, select the relevant country, and click “Add to Graph.” The map: Look below the graph at the related content, click on the GeoFRED link, and zoom out to the desired focus.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: WUICHE, WUIGBR, WUIIRQ

The national growth quilt

GDP growth for each U.S. county

What’s new from the Bureau of Economic Analysis? Real GDP data at the county level, which is now part of FRED’s ever-growing database. The data shown here are for 2015 and are still considered “beta”; but visit FRED in December and the data will be even more definitive.

The map above shows GDP growth for each county across the U.S. It looks like a patchwork quilt. Clearly, high and low and middle-ground growth rates are sprinkled across the nation, with very little uniformity within each state. (Though you could make a case that Nevada and Illinois have much more homogeneous growth across the state.)

The data are even more detailed than just overall county growth: They’re also divided into the government, services, and goods sectors. The second map shows growth of real GDP in the government sector. Here, state borders do seem to matter in many cases, as county- and local-level government finances are in many cases governed at least partially by state-level funding decisions.

The last two maps show the services and goods sectors. The former reveals another patchwork across all states, with more uniformly strong growth in services in the West and Florida. The latter reveals weakness in goods production in the Midwest and the Mississippi Valley and stronger growth in the northern Mountain states, the West, and Florida.

How these maps were created: Search FRED for GDP for your favorite county and select the growth rate. Below the graph, there is a section for related content, including a GeoFRED map. Click on that and expand it to show the entire country. You can adjust the sizing to show Hawaii and Alaska. Once you have the first map, you can find the others by clicking on the cogwheel and selecting another series.

Suggested by Christian Zimmermann.



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