The FRED Blog has examined how much people spend on recreation and what industries receive that spending. Today we’re having some more fun with data by comparing regional differences in spending on fees and admissions to entertainment events.

The FRED graph above shows annual data from the Consumer Expenditure Surveys reported by the Bureau of Labor Statistics. Data on household spending on fees and admissions to the arts, movies, sporting events, and other entertainment are available for each of the four regions defined by the Census Bureau. To compare data across regions, we present the dollar amount spent on fees and admissions as a fraction of overall expenditures in entertainment.

Between 1984, when data are first available, and the time of this writing, households in all regions gradually and unevenly spent less on fees and admissions to entertainment events. As expected, the COVID-19 pandemic represented a large-scale disruption to this type of spending.

Also noteworthy is the relatively low proportion of this type of spending in the South region (represented by the blue line) compared with the Midwest, West, and Northeast. This pattern could reflect several factors.

The BLS report on expenditures on fees and admissions to entertainment events by Bonnie Nichols documents higher spending among households with higher levels of educational attainment and income. Other factors beyond those explored in this regional analysis could also play a role: for example, the availability of entertainment options across the country (e.g., museums, amusement parks, sport venues) or regional preferences that could generate higher opportunity costs (e.g., outdoor activities such as boating or hunting vs. watching live sports or attending a concert).

And speaking of concerts, the FRED Blog can’t say for sure if there’ll be a “Taylor Swift effect” on household spending on entertainment during 2023. But be sure to come back and visit when we tour the data again. There’s no admission fee to the greatest show on FRED!

How this graph was created: Search for and select “Expenditures: Entertainment: Fees and Admissions by Region: Residence in the South Census Region.” From the “Edit Graph” panel, use the “Edit Line 1” tab to customize the data by searching for and selecting “Expenditures: Entertainment by Region: Residence in the South Census Region.” Next, create a custom formula to combine the series by typing in “a/b” and clicking “Apply.” Repeat the previous steps to add and customize expenditure data from the three other Census regions.

Suggested by Erica Wu and Diego Mendez-Carbajo.

This FRED graph chronicles the advent of “unconventional” monetary policy in the US since the 2007-08 financial crisis and the recent efforts by the Federal Reserve to normalize monetary policy. The graph shows the unemployment rate (in blue), the stock of mortgage-backed securities held by the Federal Reserve (in green), and the effective federal funds rate (in red). While the first series reflects an objective of monetary policy, the other two series reflect instruments of monetary policy: the federal funds rate being a “conventional” instrument and the large holdings of mortgage-backed securities being an “unconventional” instrument.

Three recessions are visible, represented by gray shaded areas. In each recession, the unemployment rate increased and, in response, the Federal Reserve lowered the federal funds rate to stimulate economic activity. After the 2007-08 financial crisis, the federal funds rate became so low (virtually zero) that there was no way to lower it any further. So, the Fed put in place alternative means of stimulating the economy—hence, the label “unconventional monetary policy,” which includes large purchases of mortgage-backed securities starting in late 2008 (again: the green line). These unconventional actions by the Federal Reserve are often referred to as quantitative easing (QE). By purchasing large quantities of assets, the Federal Reserve lowered their yields, which is a mechanism akin to lowering interest rates to stimulate economic activity.

As the unemployment rate declined from its 2010 peak, the Federal Reserve started, in 2016, to “normalize” its monetary policy first by raising the federal funds rate again and then, in 2018, by gradually reducing the stock of mortgage-backed securities it held.

In 2020, the COVID-19-induced crisis prompted the Federal Reserve to lower the federal funds rate to its lowest possible level once again and to further stock up on mortgage-backed securities.

The unemployment rate declined rapidly after 2020 and, in 2022, the Federal Reserve started to raise the federal funds rate and reduce its holdings of mortgage-backed securities again. In this instance, however, inflation (not represented on the graph) played an important role. Until 2021, inflation had changed little, particularly in comparison with the changes in the unemployment rate. With the rise of inflation in 2021, the Federal Reserve had an additional motivation to increase the federal funds rate.

How this graph was created: An “Unemployment Rate” link will likely be under the “Trending Search Terms” heading, which is below the search bar on FRED’s homepage. Click that link and then click the “Unemployment Rate” series link at the top of the results list. Click on “Edit Graph” and then “Add Line.” Use the series code EFFR in the search box and then “Add data series.” Click on “Edit Graph” and “Add Line” again and use the series code WSHOMCB in the search box and then “Add data series.” Click on “Edit Graph” yet again and use the “Format” tab to select “right” as “Y-axis position” for Line 3. Enter 2000-01-01 as the start date above the graph.

Suggested by Guillaume Vandenbroucke.

The FRED Blog has used US Bureau of Economic Analysis data to compare changes in the source of household income over time. That dataset showed, overall, that wages and salaries represent the single largest source of earnings for the average household. Today we tap into the Consumer Expenditure Survey (CES) dataset from the US Bureau of Labor Statistics to compare the very different sources of income for the lowest- and highest-earning households.

Our FRED graph above focuses on the lowest-earning 20% of households surveyed and tracks the percent of annual income (before taxes) from nine reported sources of earnings.*

For this group of households, social security and retirement income (the red area) has represented a larger share of earnings than wages and salaries (the blue area). Also, during most years between 1984 and 2014, the lowest-earning households reported negative income from self-employment (the light green area at the bottom of the graph). (The CES glossary defines self-employment income as the net difference between gross receipts and operating expenses, so it appears as if these households operate unincorporated businesses or farms at a loss. See this quick St. Louis Fed video for more background on recent self-employment trends.)

Our FRED graph below focuses on the highest-earning 20% of households surveyed and tracks the percent of annual income (before taxes) from the same nine reported sources of earnings.*

For this group of households, wages and salaries (the blue area) has represented the largest share of total earnings. Also, income from self-employment (the light green area at the bottom of the graph) wasn’t negative at any time between 1984 and the time of this writing.

What can explain these differences in the sources of income? The CES dataset reports several demographic characteristics of the households responding to the survey that can shed some light here. For example, the proportion of adults 65 and older in the lowest-earning households has historically been at least twice that recorded in the highest-earning households. Because the compostions of the two groups of households differ and include people at different stages of their earning lives, a direct comparison of their sources of income has its limitations.

* We removed the graph legends to leave more room for the data, but the legends are shown here for the first graph and here for the second graph.

How these graphs were created: In FRED, navigate the list of releases for the “Consumer Expenditure Surveys.” Next, click on “Tables by Different Characteristics” and select “Quintiles of Income Before Taxes.” Next, select “Lowest 20 Percent (1st to 20th Percentile)” and then click on “Income and Taxes.” Next, click on the boxes to the left of the nine data series names listed directly below the heading “Money Income Before Taxes.” Use the “Format” tab in the graph to change the graph type to “Area” and the stacking option to “Normal.” Repeat the steps described above to build the FRED graph for the “Highest 20 Percent (81st to 100th Percentile).”

Suggested by DeAndre Johnson and Diego Mendez-Carbajo.