Federal Reserve Economic Data

This is the FRED Blog’s 1000th post! So, today’s topic is brought to you by the letter M, which stands for 1000 in Roman numerals. M also stands for money and is used to label various technical measures of money in the economy.

First, a definition: Money is a good that’s generally accepted as 1) a store of value, 2) a means of exchange, and 3) a unit of account. Various goods have been considered money throughout history, most prominently precious metals. In this era of fiat money, money is harder to define and measure. Read more on what makes money, money.

Definitions differ from country to country, due to variations in their financial systems. So, today we concentrate on the United States, where the convention is to number the money definitions from the narrowest to the broadest, from M0 to M3:

• M0 is cash, a.k.a. currency in circulation in the form of bills and coins. (It’s labeled “Currency Component of M1” in the graph.) Currency in Federal Reserve and bank vaults doesn’t count.
• M1 adds to M0 all highly liquid bank accounts, such as checking accounts. Since 2020, M1 has also included savings accounts, which caused a jump in M1.
• M2 adds to M1 less-liquid small “time deposits” such as CDs and money market accounts for individuals.
• M3 adds to M2 large and institutional time deposits. The Federal Reserve discontinued collecting the necessary data for M3 in 2006, when the cost outweighed the policy relevance.

All these concepts, and there are more, can be thought of as money. Yet, their statistics vary widely, as does their policy relevance. Check back with the FRED Blog whenever you need data and definitions.

How this graph was created: Search FRED for “currency” and take the component of M1 series, to be consistent with the units of the rest of the graph. Click on “Edit Graph, open the “Add Line” tab, and search for “M1,” “M2,” and “M3.” Adjust the sample period to start on 1959-01-01.

Suggested by Christian Zimmermann.

Today, we compare the labor force participation rate of two groups of women. The FRED graph above shows that the rate for Black women is much more variable than the rate for White women, in both the short term and long term. Here, we’ll concentrate on the latter.

Before the 1990s, the labor force participation rate for White women was increasing at a faster rate than it was for Black women. Around the mid-1990s, the rate for White women began to flatten out; it began to fall after the Great Recession and dropped sharply during the COVID-19 recession. The rate for Black women has had a slightly different pattern after the 1990s, with substantial drops during and after recessions.

Now let’s look at the gap between these participation rates, which was at its lowest in the mid-1990s. Since then, the gap has tended to decrease when the labor force participation rate of Black women has fallen and increase when the rate has risen. Another way to put it is that the participation rate of White women is so stable that it doesn’t influence the gap. An exception is in the mid-2010s, when the rate for Black women flattened but the rate for White women decreased slightly.

How this graph was created: Search FRED for the series “Labor Force Participation Rate – 20 Yrs. & over, Black or African American Women.” Click “Edit Graph” and use the “Add Line” tab to search for and select the data series “Labor Force Participation Rate – 20 Yrs. & over, White Women.” Change the time frame to January 1, 1975, to the present.

Suggested by Victoria Gregory and Kevin Bloodworth.

Perennially, the five largest economies in Europe have been the United Kingdom, Germany, France, Italy, and Spain. The order in which we mention them has significance: This is how they rank when we look at them in terms of real GDP per capita, as in the FRED graph above.

Notice that the ranking has not changed in over 60 years, except for the most minor and temporary deviations. This period covers major economic events: the integration of these economies in the Economic Union, oil price shocks, the opening of Eastern Europe, and more recently a financial crisis, Brexit, Covid-19, and a war in Ukraine.

This ranking is different from the ranking of these economies by their total real GDP, as in the FRED graph below. First, Germany has a population that is significantly larger than the others, noting here that Germany encompasses East and West Germany before reunification in 1990 for these statistics. Second, the largest European economics have followed quite different demographic trajectories, leading to significant implications for the size of their economies: Notice how the UK was initially first and temporarily dropped to fourth, while Italy was second before suffering a significant slowdown that has currently brought it down to fourth.

In the end, the size of the economy matters little when countries are integrated economically and politically, as they are within the European Union, except for limited circumstances related to policy decisions.

How these graphs were created: Search FRED for “per capita GDP Germany” and take the series in constant prices. Click on “Edit Graph,” open the “Add Line” tab, and search for “per capita GDP France.” Repeat for the United Kingdom, Italy, and Spain. For the second graph, follow a similar procedure.

Suggested by Christian Zimmermann.