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Posts tagged with: "CUSR0000SETB01"

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Replicating economic research…on gasoline affordability

Here at the FRED Blog, we believe it’s important to be able to replicate economic analysis, which begins by identifying the data used in that analysis. That’s why FRED Blog posts include a list of the data series used to build the graphs. Moreover, all FRED data series themselves include a suggested citation.

The FRED graph above can help us reproduce some research published in our Economic Synopses series: “Gasoline Affordability.” The essay, published in 2004, compares wages with gasoline prices. To replicate the analysis, we searched for the two series mentioned in the essay: the CPI index for the price of gasoline and the average hourly wage rate of production workers.

The second FRED graph helps us test the robustness of the analysis by extending its conclusion about gasoline affordability and demand for SUVs past the original publication date. (Again, it was published in 2004.)

Between 2004 and 2009, when gasoline became gradually less affordable, the sales of lightweight trucks decreased. Nevertheless, despite the fact that gasoline was unevenly affordable between 2010 and 2020, the sales of lightweight trucks grew at a steady rate. Something other than gas prices must be driving demand for SUVs.

To learn more about auto sales, read Bill Dupor’s Economic Synopses essay “Auto Sales and the 2007-09 Recession.”

How this graph was created: Search for and select “Consumer Price Index for All Urban Consumers: Gasoline (All Types) in U.S. City Average.” From the “Edit Graph” panel, use the “Edit Line 1” tab to customize the data by searching for and selecting “Average Hourly Earnings of Production and Nonsupervisory Employees, Total Private.” Next, create a custom formula to combine the series by typing “a/b” and clicking on “Apply.” Next, use the “Add Line” tab to create a user-defined line. Create a line with start and end values of 10. Last, use the “Add Line” tab to search for “Motor Vehicle Retail Sales: Light Weight Trucks” and click on “Add data series.” To change the line colors, use the choices in the “Format” tab.

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: AHETPI, CUSR0000SETB01, LTRUCKSA

Riding the macroeconomic fluctuations

At the Federal Reserve, we follow closely the aggregate fluctuations in the U.S. economy, including the behavior of labor markets in general and the unemployment rate in particular. Our key policy instrument is the federal funds rate, which is used to influence all other interest rates, especially short-term rates, and thereby influence financial, labor, and goods markets to achieve our mandate of price stability and full employment.

Not surprisingly, some markets are more sensitive than others to both the cyclical behavior of the aggregate fluctuations and to monetary policy conducted by the Fed. Among those sensitive markets is the one for durable goods. The graph above illustrates this by showing total monthly sales of cars (thick blue line) from the late 1970s to today. Notice how volatile this series is, as spikes of high sales occur fairly often during the sample period. There’s also a clear pattern related to the unemployment rate (red line): Car sales plummet during periods of increasing unemployment, most notably during recessions (shaded bars).

But unemployment is far from the whole story. As the graph shows, car sales are also driven by two of the major costs of buying a car: the cost of gasoline (orange dashed line, right axis) and interest rates. The graph shows the bank prime loan rate (green line), which is used to set the interest rate charged for most car loans. Clearly, even when unemployment is low and declining, a rise in interest rates and the cost of gasoline is associated with a decline in car sales.

How this graph was created: First search for “total vehicle sales” and select the seasonally adjusted series. To highlight this series relative to the rest, select a solid line style with width 4. Next, use the “Add Data Series” option to search for and select “U.S. civilian unemployment rate”; again, select the seasonally adjusted series to keep the graph smoother. Next, add the series “bank prime loan rate” and “consumer price index for all urban consumers: gasoline.” To compare the time behavior of these series within the graph, place the y-axis for the last series on the right side. Finally, adjust the line colors and patterns to taste.

Suggested by Alexander Monge-Naranjo

View on FRED, series used in this post: CUSR0000SETB01, MPRIME, TOTALSA, UNRATE

The sound and fury of gasoline prices

Gasoline prices have really gone up and down lately. With such wide-ranging short-term fluctuations, it’s hard to tell whether gasoline has become more expensive over the long run. So we turn to FRED. The CPI includes a component that tracks gasoline used for private transportation. We can compare this gasoline component with the CPI to see how gasoline prices have risen in relation to prices in general. The graph clearly shows all the stormy fluctuations for gasoline. But it also clearly shows something we may not have expected: The price of gasoline is now at the same level it would have reached had it simply followed the smooth evolution of the overall price index. We can’t depend on these price levels to coincide, of course, given the typical fluctuations of gasoline. And if the past decade is any indication of the future, gasoline prices will return to their higher levels.

How this graph was created: Search for “CPI gasoline” and select the monthly seasonally adjusted series. Then add the series “CPI.” (You can also work from the relevant release table to select the series you want.) Finally, to start the series at the same level instead of the 1982-84 index year, edit both series as follows: Choose “Index (Scale value to 100 for chosen period)” under Units and “1967-01-01” under Observation Date.

Suggested by Christian Zimmermann

View on FRED, series used in this post: CPIAUCSL, CUSR0000SETB01

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