All posts by RealEstate

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

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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

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Unexpected changes to the benchmark U.S. interest rate : Discretion is the better part of valor

Quoting from the Board of Governors of the Federal Reserve System website: “The Federal Open Market Committee (FOMC) is the monetary policymaking body of the Federal Reserve System… The FOMC schedules eight meetings per year, one about every six weeks or so. The Committee may also hold unscheduled meetings as necessary to review economic and financial developments.”

One of those unscheduled meetings took place on Sunday, March 15. At that time, the FOMC announced a reduction in the benchmark U.S. interest rate target range by a full percentage point. This decision was made ahead of the regularly scheduled March 17-18 meeting. How often does the FOMC do this? That is, how often does it change its monetary policy target without waiting for a regularly scheduled meeting? FRED can help us answer that question.

The purple bars in the FRED graph above show the change in the federal funds target rate (which is

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Bank Lending Standards and Loan Growth : Monitoring lending activity in troubled times

One of the many serious concerns about the ongoing coronavirus pandemic is that affected firms will find it difficult to continue to pay interest and principal on their outstanding bank loans, while many firms will require additional loans to tide them over until normal levels of economic activity resume. It’s likely banks will want to help their customers weather the downturn, but some might be reluctant or incapable of extending a large volume of new loans, particularly when the specter of a possible, perhaps likely, recession looms.
A reliable indicator of the willingness of banks to make loans is the Fed’s quarterly Senior Loan Officer Opinion Survey on Bank Lending Practices. Researchers find that bank lending tends to slow after an increase in the percentage of banks that are tightening lending standards. The FRED graph plots the compound annual rate of change in commercial and industrial loans alongside the net percentage

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The St. Louis Fed’s Financial Stress Index, Version 2.0

Economists, banking regulators, policymakers, and financial market analysts use a variety of indicators to monitor financial market conditions. Many indicators are constructed from market-based prices, since information about the health of the economy, a bank, or a firm is often reflected in equity and debt markets. So market prices are forward-looking indicators of potential changes in economic and financial conditions.
The best known macroeconomic measures are interest rate spreads between so-called “risk-free” and “risky” securities. For example, the spread between long-term and short-term Treasury yields—often termed the yield curve—tends to be a reliable forecaster of future economic growth. (See McCracken, 2018, and Owyang and Shell, 2016.)
To help the public monitor financial market conditions on a weekly basis, the St. Louis Fed unveiled a financial market stress index (FSI) in 2010. (See Kliesen and Smith, 2010.) Similar to other FSIs, the St. Louis Fed’s (STLFSI) measures different types of financial market stress.

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Fourth large-scale asset purchases program: A new hope

We’ve previously discussed the tapering of the three large-scale asset purchase programs popularly known as “quantitative easing.” On Sunday, March 15, the Federal Open Market Committee (FOMC) brought back this unconventional monetary policy tool. The FOMC directed the New York Fed’s Open Market Trading Desk (the Desk) to purchase at least $500 billion worth of Treasury securities and at least $200 billion worth of mortgage-backed securities. These asset purchases are called unconventional policy measures to distinguish them from the management of the federal funds rate through open market sales and purchases of short-term Treasury securities.
The graph above shows the purchase programs started on November 2008, November 2010, and September 2012. Each program had different sizes, which depended on the monetary policy projections, and their impact on the composition of the Federal Reserve System balance sheet can be seen as three distinctive increases in the levels of mortgage-backed securities (the green

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Tracking the U.S. economy and financial markets during the COVID-19 outbreak : Use FRED dashboards to monitor the economy

To help FRED users navigate the rapidly changing economic and financial environment, the Federal Reserve Bank of St. Louis has assembled two dashboards of FRED graphs. The first dashboard collects higher-frequency financial market variables. The second dashboard collects mostly monthly indicators that track expenditures, employment and unemployment, and key business and consumer surveys.

For some background on why and how economists and other analysts track
economic and financial variables during stressful times, read on:

The World Health Organization declared the novel coronavirus—known as COVID-19—a pandemic. Johns Hopkins University is monitoring the spread of the virus and mapping the number of confirmed COVID-19 cases and fatalities worldwide.

The number of confirmed cases in the United States is rising, and U.S. financial markets have been tumultuous. For example, since hitting an all-time high on February 12, the Dow Jones Industrial Average has fallen by about 33 percent as of the writing of this post. Yields on

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Population and income disparity in the St. Louis MSA

Comparing St. Louis City and MSA population growth
FRED lives at the St. Louis Fed, which is in St. Louis City, which is adjacent to St. Louis County, which are all part of the St. Louis metropolitan statistical area (MSA).* Population and income vary widely across the region, so let’s see what FRED’s Census data can show us.
The graph above shows population for St. Louis City in red (left axis) and the entire St. Louis MSA in blue (right axis).
The city’s population is less than half of what it was 50 years ago: down from 622,236 in 1970 to 302,838 in 2018. The most drastic population declines were in the early 1970s and right after the Great Recession. Despite some steadiness in the 2000s, the city’s population has consistently fallen.
The MSA’s population also declines in the early 1970s, but it stabilizes in the next decade and then steadily increases at a

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Pie charts for Pi Day : FRED offers a variety of keen ways to display data

March 14, aka 3/14, is Pi Day because the Greek letter pi represents 3.14 etc.
This post offers pie charts because the FRED Blog is not above using puns.
Now, these delectable pie charts cover a variety of topics from recent blog posts. Observe the appealing ways FRED can help you display data, and then click the headings to review the posts themselves.
Percentage of homeownership rate by racial and ethnic group in the U.S.

The price of a BLT sandwich

CO2 emissions from fuel by sector

How these graphs were created: It’s a simple recipe: To convert any FRED graph to a pie chart, go to the “Edit Graph” panel, open the “Format” tab, and select graph type “Pie.”
Suggested by Diego Mendez-Carbajo.

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Calculating the value of women’s unpaid work : U.S. women’s unpaid labor basically equals the state GDP of New York

Yesterday was International Women’s Day, so FRED is taking the opportunity to examine one economic contribution from women that’s often ignored: The value of women’s domestic labor that goes unpaid.
For this calculation, we use Oxfam’s methodology: We calculate the total amount of hours that women spend doing unpaid household work and then use the minimum wage to put a dollar value on that work: 

Take the number of women above age 16 and multiply by 26.7 hours, which is, according to the Bureau of Labor Statistics, the average number of hours per week women spend on unpaid household work.
Multiply this weekly value by 52, the number of weeks in a year.
Multiply the result by the federal minimum wage.
Divide this annual dollar amount by the consumer price index to adjust for inflation. (Note we use annual data here, aggregated at the end of each year, to make the graph easier to read.)


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