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Retail instalment* purchase patterns from the 1940s

The graph above traces outstanding instalment accounts from different retail categories: household appliance, furniture, and jewelry stores from 1941 to 1951. The groups follow a similar path. From 1943-1947, the series encounter a deep decline, which can be attributed to a number of factors, such as the 1945 recession, shifts in GDP, and changes in the employment rate. In 1947, the series for household appliance stores rises steeply then continues to rise steadily along with furniture stores.

There are also a few differences among the groups. Jewelry stores hit their highs in December of each year, unlike furniture and household appliance stores. This sharp increase at the end of the year is typically due to winter holidays, when consumers are spending more on gifts. We also notice that the series for household appliances stores lags behind the other categories until 1948, when it rises above furniture stores.

To examine more historical retail data, visit FRASER, where you can view other economic publications and the complete release from the graph above: G.17.2 Retail Instalment Credit.

How this graph was created: Search for “Instalment Accounts,” then select “Instalment Accounts Outstanding Household Appliance Stores,” “Instalment Accounts Outstanding Jewelry Stores,” and “Instalment Accounts Outstanding Furniture Stores.” Then click on “Add to Graph.”

*Editor’s note for careful readers: The spelling of instalment is taken directly from the Board of Governors’ release. The spelling of “installment” vs. “instalment” wasn’t standardized when these data were collected in the 1940s. People may have been occupied with other events at the time.

Suggested by Ebony Mosby.

View on FRED, series used in this post: G172IIFUN01, G172IIHA01, G172IIJA01

Holiday jewels

The holiday season has finally arrived! It’s a time to enjoy moments filled with joy, glee, and (according to historical data from the Board of Governors) jewelry. The graph above traces outstanding instalment* accounts for jewelry stores from 1941 to 1946. Each December there’s a sharp increase, presumably from holiday spending. This kind of consistent increase (every year at the same time) reminds us that it’s wise to take into account seasonality before analyzing data.

*Editor’s note for careful readers: The spelling of instalment is taken directly from the Board of Governors’ release. The spelling of “installment” vs. “instalment” wasn’t standardized when these data were collected in the 1940s. People may have been occupied with other events at the time.

How this graph was created: Search for “Instalment Accounts,” select “Instalment Accounts Outstanding Jewelry Stores,” and add it to the graph.

Suggested by Ebony Mosby.

View on FRED, series used in this post: G172IIJA01

Is Inflation Running Hot or Cold?

One popular measure of the price level is the consumer price index (CPI), which measures the average change over time in the prices paid by urban consumers for a market basket of goods and services. This index can be broken down into smaller component indexes, each representing a different subset of goods and services. So changes in the aggregate price level can be traced back to changes in the price levels of the underlying components. As described in a recent Economic Synopses essay, we have developed a “heat map” that visually represents CPI data in FRED: specifically, the relative inflation levels of various CPI components over the past 10 years. The heat map shown here lists the components in order according to their weight in the overall index as of July 17, 2015.

2015 July 20 FRED Blog post heat map x800

How this heat map was created: We used the FRED Add-In for Microsoft Excel (view instructions for installing the Add-In here) to download the FRED data: year-over-year percent change in each CPI component index over the past 10 years. We normalized each value by subtracting the series mean and dividing by its standard deviation calculated over the past 10 years to take into account differences in long-term trends and volatility across series. Each colored box in the heat map corresponds to the normalized inflation value for a given CPI component for a particular month. Blue represents an inflation value below the long-term trend of the index, and red represents an inflation value above the long-term trend. The darker the color, the greater the difference between that particular inflation value and the long-run average for the component index in terms of standard deviations.

Because we’re comparing series against their long-run averages, it’s possible for a “blue” series to have a higher inflation rate than a “red” series. For example, for June 2015, owners’ equivalent rent is red, with an inflation value of 2.95 percent; water, sewer, and trash is blue, and yet has a higher inflation value of 4.65 percent. The reason is that the June 2015 owners’ equivalent rent inflation is above its 10-year average of 2.16 percent; and the June 2015 water, sewer, and trash inflation is below its 10-year average of 5.11 percent.

An Excel file containing a version of this heat map can be found here, and anyone who downloads the FRED Excel Add-In has the ability to easily update the heat map when new data are released. Simply select the tab containing the raw data and press the “Update Data” button from the FRED Excel Add-in. (More instructions and details are provided in the Excel file.)

Suggested by Joseph T. McGillicuddy and Lowell R. Ricketts.

View on FRED, series used in this post: CPIAPPNS, CPIAUCNS, CPIEDUNS, CPIENGNS, CPILFENS, CPIRECNS, CPIUFDNS, CUUR0000SAF116, CUUR0000SAG1, CUUR0000SAH3, CUUR0000SAM1, CUUR0000SAM2, CUUR0000SAS4, CUUR0000SEGA, CUUR0000SEHA, CUUR0000SEHB, CUUR0000SEHC, CUUR0000SEHG, CUUR0000SETA01, CUUR0000SETA02


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