FRED can help us compare the relative cost of living across different regions in the US with data known as regional price parities (RPPs).

On February 19, 2026, the Bureau of Economic Analysis released RPPs for states and metro areas for the year 2024. Our FRED map above shows these new values.

Note that the data are reported as an index: A value of 100 equals the national average, and a value of 110, for example, indicates a cost of living 10% above the national average.

Highlights

• The highest value is 110.7, in California.
• The lowest value is 86.9, in Arkansas.
• Two states, Illinois and Arizona, have RPPs of 100, exactly equal to the national average.

These data can be incredibly useful for understanding cost differences around the nation, but they may not match an individual’s personal experience when moving from one location to another.

Things to consider

An RRP measures the cost of the same basket of goods and services of the average household in different locations. In reality, households’ baskets of goods and services vary based on factors such as their age and income.

The availability of certain goods and services is different in different locations, and people’s purchases often depend on their location. For example, does anyone in Miami own a snowblower?

Most importantly, the cost of housing varies significantly across the nation. In places where housing is more expensive, people will choose smaller lots and homes so they can afford other goods and services.

RPPs do not measure “affordability”

We shouldn’t think of RPPs (or the cost of living in general) as a measure of “affordability.” Affordability assumes that people living in the region have enough income to purchase the good or service in question. It’s often the case that higher-cost regions also have lower incomes.

In addition to RPPs, the BEA releases real per capita personal income, which is the average income in a region adjusted by its RPP.

After adjusting for cost of living, Wyoming has the highest real per capita income, at $75,501, followed by Connecticut at $74,254, both well above the national average of $59,195. Mississippi has the lowest real per capita income at $48,465.

How these maps were created: First map: Search FRED for and select “Regional Price Parities: Missouri” (series ID MORPPALL). In the right-hand corner, click the green “View Map.” Second map: Search FRED for and select “Real Per Capita Personal Income Missouri” (series ID MORPIPC). Click “View Map.”

Suggested by John Fuller and Charles Gascon.

FRED has data that allow us to track and compare changes in employment across states and metro areas.

Our first FRED map, above, shows the change in nonfarm employment in each state during the fourth quarter of 2025. The Bureau of Labor Statistics released these data a little later than usual (on January 28) due to the government shutdown last fall.

At the state level

• North Carolina led all states, adding 22,700 jobs in the fourth quarter.
• The largest declines were in Virginia, which lost 17,400 jobs, and Washington, DC, which lost 18,400.
• Missouri led the Eighth Federal Reserve District states with 10,600 jobs added, which was the fifth largest gain among all US states; Indiana was last in the Eighth District, losing 17,000 jobs.

If you sum up the individual states, you’ll see a net gain of 50,700 jobs. This is different from the reported number for the nation, which shed 51,000 at the end of the fourth quarter. This difference exists because the state level has different sampling and tends to have a larger margin of error than the national number.

Our second FRED map, above, shows employment changes at the metro level.

• The New York-Newark-Jersey City MSA led the nation with 31,200 jobs added in the fourth quarter.
• The Washington-Arlington-Alexandria MSA had the largest decline, losing 33,500 jobs.
• The St. Louis MSA gained 7,400 jobs.

These numbers for MSAs tend to vary greatly from quarter to quarter, with even greater sampling errors than the errors at the state and national levels. So, be careful not to read too much into the data.

NOTE: These data are subject to future revision by the source, with an annual revision the following March. Our ALFRED database records vintages of the data, so users can view the data as they appeared at various points in history: These links provide employment data for Missouri and St. Louis as of January 28, 2026.

How these maps were created: Search FRED for “total nonfarm employees in Missouri” (or any other state). Click “View Map” and then “Edit Map.” Change the units to “Change, Thousands of Persons” and the frequency to quarterly with aggregation method “End of Period.” Under “Format,” select “User Defined Method” for how to group the data: Switch the number of color groups to 3 and change the colors to red for states that shed jobs (or a value less than or equal to 0), light green for states with modest job growth (or less than 10), and dark green for states with strong growth (or a value large enough to incorporate the rest of the states). For the second map, repeat the process with an MSA—St. Louis, for example.

Suggested by John Fuller and Charles Gascon.

Today’s post explains the relationship between interest rates and exchange rates and how they’re involved in investment decisions.

The data

The FRED graph above tracks two rates:

• The solid red line shows the exchange rate between the US dollar and euro.
• The dashed blue line shows the difference in interest rates (or yields) between the long-term/10-year US Treasury bond and the German government bond.

We can see in the graph that these rates appear to be related: When this interest rate differential (US bond yield minus German bond yield) has increased, the US dollar has tended to appreciate.

But exchange rates are affected by many factors, especially shocks that alter market views about the long-run future exchange rate. Such a shock appears to have occurred after April 2, 2025 (a.k.a., “Liberation Day”).

The graph shows that, at the time, US Treasury yields rose sharply relative to German government bond yields. In theory, that would have implied a stronger US dollar. But instead, the dollar depreciated. Market participants seem to have revised down their expectations of the dollar’s long-run value, possibly due to concerns that large tariffs would erode US economic fundamentals.*

For a deeper look, read on…

Investing decisions

Economists see a tight link between these interest rate differentials across countries and the expected changes in the exchange rates. So, in theory, investing in domestic bonds or foreign bonds should yield roughly the same rate of return. Again, when the interest rate differential (US bond minus German bond) increases, the US dollar tends to appreciate. This pattern supports the validity of the economic concept known as uncovered interest parity, or UIP. UIP states that

Domestic interest rate ≈ Foreign interest rate + Expected depreciation of the foreign currency

or

Expected change in the exchange rate ≈ Interest rate difference between the home and foreign countries

Bond yields in both the home and foreign countries are known at the time of investment and therefore they involve little uncertainty. But exchange rates are another matter.

Investors in foreign bonds must first convert their funds into the foreign currency to buy those foreign bonds. Then they must convert their funds back to the domestic currency once the foreign bond matures. The future exchange rate isn’t known at the time of investment, so the return from investing abroad is uncertain because of that exchange rate risk.

Long-run theory versus short-run observations

These patterns still support the validity of a long-run UIP through a mechanism in which today’s exchange rate adjusts to maintain parity, rather than through a shift in the long-run average exchange rate. But empirical evidence shows that, in the short run, exchange rates are nearly unpredictable and behave close to a random walk. This suggests that UIP doesn’t hold in the short run.

The data support UIP much better in the long run. Over longer horizons, exchange rates tend to revert to the mean. When there’s an increase in the interest rate differential between the home and foreign countries, today’s exchange rate should appreciate immediately in the higher-interest-rate country so that the expected exchange rate depreciates in the future as it swings back toward its long-run average. In other words, long-run UIP can hold through an exchange rate adjustment occurring today, rather than through changes in the long-run average exchange rate.

Consider this example: Suppose the long-term domestic interest rate remains unchanged at 5%, while the foreign long-term interest rate suddenly falls from 4% to 3%. Long-run UIP implies that investing abroad should still yield roughly a 5% return on average, despite the lower foreign interest rate. The 1- percentage-point reduction in the foreign interest rate should therefore be compensated by an expected appreciation of the foreign currency of about 1% annually. To achieve this, the domestic currency must appreciate immediately, so that it is subsequently expected to depreciate as the exchange rate converges back to its long-run average.

*See Jiang et al. (2025).

How this graph was created: Search FRED for and select the US Dollars to Euro Spot Exchange Rate (DEXUSEU) series. Click on “Edit Graph”: Under the “Edit Line” tab, modify the frequency to monthly and scroll down to the formula box and enter 1/a. Thus, instead of a USD/EURO exchange rate we have a EURO/USD exchange rate. Next click on “Add Line” and enter DGS10 to add the yield for 10-year US government bonds. Modify the frequency to monthly. Under “Customize data,” add the series IRLTLT01DEM156N, which is the 10-year German government treasury bond yields. Change the formula to a-b. From the “Format” tab, under line 1, click customize and change the color to red. Under line 2, click customize and change the color to blue and place the axis on the right. Finally, edit the dates so that the series starts on January 1, 2024.

Suggested by YiLi Chien and Kevin Bloodworth.