Federal Reserve Economic Data

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Growth and decline in U.S. metropolitan population data

FRED has included a lot of population data over the years, and it now offers data specifically for U.S. metropolitan statistical areas (MSAs).

First, a couple of caveats: It makes sense to study population numbers as a percent change year over year; looking at raw numbers can be misleading because size and density matter on a map. Also keep in mind that MSA definitions change, especially after a decennial census but sometimes midway between censuses; so, values at these dates may reflect changes in population, definition, or both.

The GeoFRED map above shows 2018 U.S. Census Bureau data for the 383 MSAs: 295 of them grew and 88 shrank. The largest (proportional) growth was in Midland, TX, with 4.32% in a single year, followed by 3.78% in Myrtle Beach, SC/NC, and 3.52% in St. George, UT. The largest (proportional) decline was in Charleston, WV, with -1.57%, followed by -1.55% in Pine Bluff, AR, and -1.47% in Farmington, NM. In terms of raw numbers, Dallas-Fort Worth-Arlington, TX, added over 130,000 residents in 2018 while Chicago-Joliet-Naperville, IL-WI-IN, lost about 22,000.

The map makes it easy to see exactly where population is moving in and out: Blue areas are declining, and it’s quite clear they’re almost all in the Northeast and Midwest. Red areas are growing the most, mainly in Florida, the central U.S., and the West.

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.

One rate does not rule them all

Unemployment is uneven across U.S. counties

The graph above shows the annual civilian unemployment rate from 1948 to 2018, and here are some highlights: Ten years ago, after the Great Recession, the U.S. unemployment rate peaked at 9.6%. (The only higher unemployment rate in this series was 9.7%, in 1982.) It gradually came down to 3.9% in 2018, the lowest in fifty years. (The rate in 1969 was 3.5%.)

But these national unemployment numbers mask the variation that exists across different regions in the U.S. Fortunately, we have GeoFRED to paint a clearer picture: The map below shows the unemployment rate for 2018 for 3,133 U.S. counties. The counties are split into two equally sized groups according to their unemployment rates: Those with lower unemployment are in blue, and those with higher unemployment are in red. Specifically, the blue group had a rate lower than 3.87%, and the red group had a rate between 3.87% and the maximum of 18.08%. (By the way, all counties in New Hampshire are blue and all counties in Arizona are red.) 

The map reveals that unemployment rates are unevenly distributed across the nation. Many counties in the Midwest have lower-than-average unemployment rates. In particular, Iowa and Nebraska counties, with only a few exceptions, are blue. In contrast, it’s not surprising to see that the Rust Belt region—e.g., Illinois, Michigan, and Ohio—is home to many counties with high unemployment rates. There are also many red counties in the Sun Belt and on the West Coast, which have rates higher than the national average.

With only the national average unemployment rate and without a county-level view, we wouldn’t know that lower unemployment rates concentrate in the Midwest and higher rates spread out over the rest of the nation.

How these graphs were created: For the first graph, search for and select “Civilian Unemployment Rate (UNRATE).” From the “Edit Graph” panel, select “Percent” for “Units” and modify the frequency to be “Annual.” Choose “Average” for “Aggregation Method.” 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 Sungki Hong.

View on FRED, series used in this post: UNRATE

Fixing the “Textbook Lag” with FRED (Part II)

Monetary policy in a world of ample reserves

Your economics textbook may still say the Federal Reserve uses open market operations to influence the federal funds rate. But in today’s economy, the Fed uses different policy tools.

In simple terms, this is how monetary policy currently works: The FOMC sets a target range for the federal funds rate (FFR) and uses interest on excess reserves (IOER) and the overnight reverse repurchase agreement (ON RRP) facility to keep the FFR rate in the target range. (See our previous post for an introduction to this topic.)

The Fed pays IOER to banks holding reserves at the Fed, which offers those banks a safe, risk-free investment option. Arbitrage ensures that the FFR doesn’t drift too far from the IOER rate. If the FFR drifts much below the IOER rate, banks then have an incentive to borrow in the federal funds market at the lower FFR and deposit those reserves at the Fed to earn the higher IOER rate.

From December 16, 2008, to June 13, 2018, the IOER and ON RRP rates, respectively, served as the upper and lower limits of the FFR target range. The FFR moved between the two rates, but over time it has moved closer to the IOER—that is, the gap between the two has closed, as shown in the FRED graph above.

Again, because the IOER rate was set at the upper limit of the target range, as the FFR moved closer to the IOER rate, by definition it moved closer to the upper limit of the range. To ensure that the FFR remained within the range, the Fed has lowered the IOER rate by 5 basis points at three different times in the past year: June 13, 2018; December 19, 2018; and May 1, 2019. The IOER is now set 15 basis points below the upper limit of the target range.

These changes weren’t changes in monetary policy (which affects the choice of target range), but rather were slight adjustments to where the FFR sits within the range. Chairman Jerome Powell explained that the adjustments were intended to “move the federal funds rate closer to the middle of the target range” in his press conference on June 13, 2018. The changes can be seen on the FRED graph below: Prior to the June 13, 2018, adjustment, the upper limit of the FFR target range and the IOER rate were indistinguishable because IOER rate was set at the upper limit of the target range. After June 13, 2018, the IOER rate (green line) is below the upper limit of the FFR target range (red line).

These changes have ensured that the FFR has remained between the upper and lower limits of the range throughout the period, as illustrated by the FRED graph below.

How these graphs were created: For the first graph: Search for “interest rate on excess reserves,” select “Effective Federal Funds Rate (daily)” and “Interest Rate on Excess Reserves,” and then click “Add to Graph.” Adjust the dates to reflect the indicated range: from December 16, 2008, to the current date. For the second graph: Search for “federal funds rate target” and select “Federal Funds Target Range – Upper Limit,” “Federal Funds Rate – Lower Limit,” and “Effective Federal Funds Rate (daily),” and then click “Add to Graph.” From the “Edit Graph” panel, use the “Add Line” option to search for “Interest Rate on Excess Reserves” and then select “Add data series.” Adjust the dates to reflect the indicated range: from January 1, 2018, to the current date. For the third graph: Search for “federal funds rate target” and select “Federal Funds Target Range – Upper Limit,” “Federal Funds Rate – Lower Limit,” and “Effective Federal Funds Rate (daily),” and then click “Add to Graph.” Adjust to date to show the entire period: from December 16, 2008, to the current date. In each case, you can adjust the colors to your liking by using the color palette in the “Edit Graph” panel’s “Format” tab.

For more information on this topic, see “A New Frontier: Monetary Policy with Ample Reserves.”

Suggested by Scott Wolla.

View on FRED, series used in this post: DFEDTARL, DFEDTARU, DFF, IOER


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