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The lockdown’s effect on the alcoholic beverage market

March's "last call for alcohol" boosted demand but only nudged prices

As U.S. cities and states started locking down in response to the COVID-19 pandemic, retail alcohol sales spiked. And they did so despite various additional restrictions for retailers and their customers.

Clearly, consumers were at least in part shifting from consumption in restaurants and bars to consumption at home. (The FRED Blog previously reported a similarly strong substitution from meals in restaurants to meals at home.) So, given this spike in retail purchases, what happened to prices?

If demand shoots up like this, market forces should increase prices as well. And prices paid by consumers did rise, but only moderately, as shown by the consumer price index (CPI). This moderate increase is even more surprising given the much larger increase in prices paid by retailers, as shown by the producer price index (PPI). That is, the data suggest retailers did not pass the full increase in costs on to their customers.

Why would retailers reduce their profit margins despite such a boost in demand? Price gouging in times of distress can damage a business’s reputation and is even illegal in some U.S. states. The demand shock may also have been perceived as temporary, so retailers may have been willing to forgo a large amount of quick profit to reinforce better long-term prospects with their regular customers.

How this graph was created: Search for and select the “retail sales beer” series. From the “Edit Graph” panel, use the “Add Line” tab to search for and select “PPI beer.” Repeat with “CPI beverages.” Choose units “Index (scale value to 100 for chosen date)” for 2020-02-01 and select “Apply to all.” Finally, limit the graph to the past 10 years.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CUSR0000SAF116, MRTSSM4453USS, PCU44534453

Dating a recession

FRED marks the spot

A recession is a significant decline in general economic activity extending over a period of time. During recessions, unemployment increases and real income decreases.

FRED helps provide context to the data by showing when these recessions have occurred: Since 2006, every FRED series of U.S. data has included the option to display shaded areas on the graph to indicate the peaks and troughs of business cycles, as dated by the National Bureau of Economic Research (NBER).

The Business Cycle Dating Committee at the NBER dates the start of each recession after a lag of several months and dates the end of a recession after an even longer lag: According to the NBER, business cycle peaks are announced an average of 7.8 months after their dating and business cycle troughs are announced an average of 15.8 months after their dating.

The FRED team quickly updates its database with any new information. In fact, the recession that started in February 2020 is now visible on the FRED graph above. In graphs with data at a daily frequency, the peak of the business cycle is marked by a bar set on February 1, 2020. In graphs with monthly data, it is marked by a vertical line.

FRED can’t yet set a recession end date, and as of now only February 2020 is shaded. But if you want to gauge when the current recession may be over (ahead of official word from the NBER), consult these FRED series: a recession probability index computed by Marcelle Chauvet and Jeremy Piger and the real-time Sahm Rule Recession Indicator. When the recession probability index has substantially decreased or the Sahm indicator has peaked, the recession has likely ended. Check the FRED data regularly so you get that good news asap.

How this graph was created: Search for “10-Year Treasury Constant Maturity Minus 2-Year Treasury Constant Maturity” and expand the date range to include the recession that lasted from December 3, 2007, to June 3, 2009.

Suggested by Keith Taylor, Yvetta Fortova, and Diego Mendez-Carbajo.

View on FRED, series used in this post: T10Y2Y

Government spending on police

State and local expenditures data from the BEA

As police presence, tactics, and department funding are being discussed, the FRED Blog offers some data to add to the conversation.

The graph above shows a category of government expenditures, “public order and safety,” as listed in the national income and product accounts from the Bureau of Economic Analysis. One series (in blue) is total government, and one series (in red) is state and local government.

These expenditures, which include both police and fire departments, are a small part of government spending, but they have continually grown. This isn’t surprising, as the data aren’t adjusted for inflation, population growth, or economic growth.

The second graph shows state and local expenditures specifically for police as a share of all state and local government expenses. For 2018, police expenditures were 4.79%, which is at the higher end of the range. The low, in 1980, was 4.25%.

How many people are in the police force? The Current Population Survey helps us here, making the distinction between those who patrol and those in supervision and detective roles. As of 2019, the total was 766,000, with a slight increase in the former and stable if not decreasing numbers in the latter. Note that these numbers include both public and private police forces.

This fourth graph shows how much police are paid. The Current Population Survey doesn’t provide averages, but rather medians: So, half are paid more and half are paid less than the values shown. These values aren’t inflation-adjusted and do not include benefits. Overtime pay is included, though.

The final graph is the same as the previous one, but the wages are adjusted for inflation. There’s quite a bit of fluctuation, likely due to changes in overtime. And there’s a slight upward trend, which can come from higher hourly pay, more overtime, or a combination of the two.

How these graphs were created: First graph: Search FRED for “public order and safety” and click on the series encompassing all government levels. From the “Edit Graph” panel, use the “Add Line” tab to search for and select the state and local government series with the same keywords. Second graph: Start with the graph for state and local police expenses. From the “Edit Graph” panel, add a series through the “Customize data” search bar (different from the Add Line tab): Search for and select state and local government expenses and apply formula a/b*100. Third graph: Search for “employed police” and select the series. Fourth graph: Search for “median police earnings” and select the series. Fifth graph: Start with the fourth graph. Use “Customize data” to add the CPI for both series and apply the formula a/b/*255.651 (the last number being the average value of the CPI in 2019).

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CPIAUCSL, G160081A027NBEA, G160841A027NBEA, G160851A027NBEA, LEU0254491000A, LEU0254491900A, LEU0254544400A, LEU0254545300A, SLEXPND

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