Federal Reserve Economic Data

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Coronavirus effects on exchange rates

This FRED graph shows several exchange rates relative to the U.S. dollar. We start with the date January 6, 2020, where we set the index values equal to 100 for all these exchange rates so we can compare their relative changes since then. Through the end of February, most of these exchange rates have remained relatively stable; however, they began to increase in March. Brazil’s and Mexico’s exchange rates spiked, and their currencies have depreciated nearly 30% since the beginning of January.

In March, the COVID-19 pandemic became more severe, affecting overall economies as well as exchange rates. Reduced global demand for commodities such as oil has sent commodities prices crashing; Mexico and Brazil are major commodities-exporting countries. Canada’s and the U.K.’s exchange rates spiked at the beginning of March, but they seem to have recovered by the end of March. The euro seems to be unaffected by the global pandemic, at least compared with the U.S. dollar. China’s exchange rate, on the other hand, has remained constant despite the coronavirus originating there. Unlike the rest of the countries in our sample, which have floating exchange rates, China has a fixed exchange rate pegged to the U.S. dollar.

Large exchange rate movements can have consequences for economic growth, inflation, trade, and sovereign risk. Commodity-dependent economies and developing countries are most susceptible to this risk. It will be important to monitor the impacts of the coronavirus on international markets and economies because they will impact our interconnected, global economy.

How this graph was created: Start with a graph of any exchange rate. From the “Edit Graph” panel, use the “Add Line” tab to search for each exchange rate by its code and add it to the graph. Under “Edit Lines,” go to the dropdown box “Units” and select “Index (Scale value to 100 for chosen date).” Immediately below, under the heading “Select a date that will equal 100 for you custom index,” type in “2020-01-06.” Do this for all lines. For the euro and the pound, the original series have the U.S. dollar in the numerator, so we have to transform them to make them comparable to the other series. To do this, go to “Formula” and type 1/a and click “Apply.”

Suggested by Brian Reinhold and Yi Wen.

View on FRED, series used in this post: DEXBZUS, DEXCAUS, DEXCHUS, DEXMXUS, DEXUSEU, DEXUSUK

Oil prices and expected inflation

Since the end of the Great Recession, market-based measures of long-run inflation expectations have seemed highly correlated with the spot price of oil. To see what we mean, consider the FRED graph above, where we plot the price of oil (West Texas Intermediate) against the 5-year, 5-year forward expected inflation rate. This measure of expected inflation is calculated using measured yield differentials between nominal and inflation-protected Treasury securities (TIPs) at 10- and 5-year maturities. (To further highlight the correlation, consider the scatter plot of the same data below.)

The 5-year, 5-year forward rate is meant to capture the bond market’s 5-year average forecast of inflation beginning 5 years from now. In this way, anything expected to affect the economy over the next 5 years should not factor prominently in a long-run forecast made 5 years from now. But then, why should the contemporaneous price of oil correlate so highly with the long-run inflation rate which is, or should be, anchored by monetary and fiscal policy?

One possibility is that because the stock of oil is an asset, its price is likely to include a forward-looking element. If the long-run outlook for global growth weakens, the value of this asset should decline. In the event of a long-run forecast of low growth, low interest rates, and low inflation, investors will move away from private sector securities into safe assets, such as U.S. Treasury securities. If so, the value of the stock of oil declines along with expected inflation.

How these graphs were created: Search for “5-year, 5-year Forward Expectation Rate.” From the “Edit Graph” panel, use the “Add Line” tab to search for and add the “Crude Oil Prices: West Texas Intermediate” series. With the “Format” tab, change the “Y-axis position” option to “Right” for “LINE 2.” For the second graph, use the “Format” tab to select plot type “Scatter.”

Suggested by David Andolfatto and Mahdi Ebsim.

View on FRED, series used in this post: DCOILWTICO, T5YIFR

Social distancing and employment loss in leisure and hospitality

The FRED Blog has used the Current Employment Statistics from the Establishment Data Survey from the Bureau of Labor Statistics before. Past posts cover the ups-and-downs of payroll employment in the information industry and the increasing proportion of women in the workforce.

Today, we use that rich data source to learn more about the reduction in overall payroll employment in March 2020—the first reduction in ten years.

The FRED graph above compares the job losses in the goods-producing industry (mining & lodging; construction; and manufacturing) with the job losses in the service-providing industry (trade, transportation & utilities; information; financial activities; professional and business services; education and health services; leisure and hospitality; and other services).

The bulk of the recent reduction in payroll employment occurred among service-providing activities; during the onset of the 2007-2009 recession, the largest reductions in payroll employment took place among goods-producing activities.

The social distancing to manage the COVID-19 pandemic has changed the routines of millions of people, and their use of services has changed. The FRED graph below shows the change in employment for service-providing industries. These changes are presented in percentages to let us compare sectors of different size.

The loss of employment in leisure and hospitality has been the largest: They represent almost 3% of the employed workers in the industry and 65% of the overall reduction in payroll employment. Restaurants and bars are either exclusively offering take-out or temporarily shutting down, so some decline was expected.

How these graphs were created: From the FRED home page, browse data by category by clicking on the “Release” category. Search for “Employment Situation” and select “Current Employment Statistics (Establishment Data).” Click on “Table B-1. Employees on nonfarm payrolls by industry sector and selected industry detail, Not seasonally adjusted.”

For the first graph, select the following series by clicking the box to the left of their names: Goods-producing; and Private service-providing. Click “Add to Graph.” From the “Edit Graph” panel, change the units to “Change” and the format to “Bars,” selecting “Stacking > None.”

For the second graph, select the following series by clicking the box to the left of their names: Trade, transportation, and utilities; Information; Financial activities; Professional and business services; Education and health services; Leisure and hospitality; and Other services. Click “Add to Graph.” From the “Edit Graph” panel, change the units to “Change” and the format to “Bars,” selecting “Stacking > Normal.”

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: CES0800000001, USEHS, USFIRE, USGOOD, USINFO, USLAH, USPBS, USSERV, USTPU


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