Federal Reserve Economic Data

FRED recently added data from the Senior Credit Officer Opinion Survey on Dealer Financing Terms (SCOOS). As the name of this series strongly suggests, there’s a survey involved: The Board of Governors currently sends this survey to the senior credit officers of at least 20 domestic financial institutions. The questions ask for their opinions on current availability and terms of credit in securities financing and over-the-counter derivatives. This qualitative information is used by monetary policymakers to gauge general conditions in those financial markets.

The FRED graph above shows the responses to the first question in the survey:

“Over the past three months, how has the amount of resources and attention your firm devotes to management of concentrated credit exposure to dealers and other financial intermediaries (such as large banking institutions) changed?”

The color represents the specific response and the length of the color segment is proportional to how many participants chose that response:

• Increased Considerably is blue
• Increased Somewhat is red
• Remained Basically Unchanged is green
• Decreased Somewhat is purple
• Decreased Considerably is teal

The latest data at the time of this writing are from the first quarter 2023 survey, which shows the survey respondents devoted an unchanged amount of resources and attention to managing credit risks from the group of financial intermediaries. Additional questions in the survey ask about the dealer financing terms for other types of financial intermediaries such as hedge funds and insurance companies, among others.

To learn more about the origins and design of the SCOOS survey, read this working paper from Matthew J. Eichner and Fabio M. Natalucci.

How this graph was created: First, note that the graph title is omitted above (to make more room for the stacked bars), but the graph with the title is here. Now, search the list of FRED releases for “Senior Credit Officer Opinion Survey on Dealer Financing Terms” and click on the first entry (which refers to “Table View”). Next, click on “Counterparty Types (Questions 1-40)” and on “Dealers and Other Financial Intermediaries (Question 1).” The text of the questions and possible answers will be displayed in a table. Select the five possible answers and click on “Add to Graph.” Next, click on the “Edit Graph” button and use the “Format” tab to change the graph type to “Bar” and the stacking to “Percent.”

Suggested by Diego Mendez-Carbajo.

During the COVID-19 pandemic, households accumulated significant savings, beyond the typical amount in a given year: In 2019, the personal saving rate* in the US averaged 8.8%. In 2020, it had almost doubled to 16.8%.

These additional savings were driven by two factors: a higher propensity to save and higher disposable income.

The first factor was the choice made by households to spend less, which could be due to a combination of health concerns, pandemic restrictions, and the prospects of lower future income, among others. (An earlier FRED Blog post offers more on this topic.) The second factor was the transfer payments from the federal government that generated a substantial increase in income for many households. Research by the Federal Reserve Board found that, from the first quarter of 2020 to the first quarter of 2021, about 40% of excess savings stemmed from a higher propensity to save and 60% stemmed from fiscal support that increased incomes.

The FRED graph above applies the Board analysis to show the trend rate of savings prior to the COVID-19 pandemic. Knowing where the trend line is allows us to depict excess savings, which is measured as the difference between actual savings (blue line) and trend savings (red dashed line). To measure accumulated savings, we add these differences each quarter through the third quarter of 2021. This calculation implies that households accumulated about $2.3 trillion in savings in excess of the pre-COVID savings trend.

Since the fourth quarter of 2021, the blue line has been below the red dashed line, which signifies a rundown in excess savings of around $1.3 trillion. It also suggests that, as of the first quarter of 2023, households still had excess savings of about $1 trillion. However, as Board researchers have noted, this growth and decline in excess savings has not been uniform across the income distribution, as most of the remaining excess savings is being held by the top of the income distribution. This trend is consistent with other analysis, such as the San Francisco Fed’s recent research and the Bank of America’s analysis of their internal data showing steeper declines in account balances of lower-income households, although balances for all income groups is above pre-pandemic levels.

*From the Bureau of Economic Analysis: Personal saving as a percentage of disposable personal income (DPI), frequently referred to as “the personal saving rate,” is calculated as the ratio of personal saving to DPI. Personal saving is equal to personal income less personal outlays and personal taxes; it may generally be viewed as the portion of personal income that is used either to provide funds to capital markets or to invest in real assets such as residences.

How this graph was created: Search FRED for “personal saving” (PSAVE is the series ID). Limit the dates using the upper right date boxes to “2014-10-01” to present. Next, click on the “Edit Graph” button and use the “Add Line” tab’s “Create line” button. Here, change the starting value to 882.159 and the ending value to 1735.176. This is the pre-pandemic trend line, estimated by a linear regression that is not included in FRED. Next, use the “Format” tab to change the style of Line 2 to “Dashed.”

Suggested by Charles Gascon.

Economic research has found that the neighborhood in which a child grows up can influence their adult outcomes,  such as educational attainment and income. That alone is a powerful enough reason for US households to pack up and move across the city or even around the country.

Every year, the US Census tracks movement (and other data) throughout the country by surveying a broad sample of households and records: Among other information, they track their current and previous counties of residence. With those data, the Census calculates a 5-year estimate of the difference between inflows and outflows of residents from  county to county. This is called net migration.

The FRED map above shows the estimated county-to-county net migration flows between the years 2016 and 2020. We customized the data groupings to sort all 3,140 US counties into two groups: counties that gained residents and thus registered positive net migration (shown in green) and counties that lost residents and thus registered negative net migration (shown in yellow). No clear pattern is visible to the naked eye, so we created a second data visualization to group the counties by state.

The second graph shows the percent of counties in each of the 50 states plus the District of Columbia that recorded positive net migration (blue bars) and the percent of counties in each state that recorded negative net migration (orange bars). The states are sorted from largest to smallest proportion of counties with net resident inflows. Keep in mind that different states have different numbers of counties. Note that all three counties in Delaware recorded positive net migration, so that state is listed at the top. Conversely, the District of Columbia is a county equivalent and, because it experienced negative net migration, it’s listed at the bottom.

Overall, the bar graph shows states such as Arizona, Nevada, and Florida had far more counties recording net resident inflows than outflows. The data do not show where the new residents came from or their demographic characteristics. We can’t say if those states gained residents from states such as Massachusetts, New Jersey, and Illinois, which lost residents. Finally, there are 4 states where the percent counts of counties is slightly off: Each of these states is home to one county that experienced zero net migration. You can see those counties, highlighted in red, in this FRED map.

How this map was created: In FRED, search for “Net County-to-County Migration Flow (5-year estimate) for Miami-Dade County, FL.” Click on “View Map.” To change the data groupings, use the “Data grouped by” dropdown menu to select “User Defined Method.” Change the “Number of color groups” to 2 and enter “0” in the topmost box.

Suggested by Diego Mendez-Carbajo.