Getting an earlier look into current economic activity
FRED recently added a set of time series from the Census Bureau known as “advance retail sales.” This data set isn’t about making technological progress in the retail sector; rather, it’s about collecting preliminary information about retail sales statistics and releasing those statistics before they’re considered definitive. This advance information may be premliminary, but it’s also quite useful: Retail sales are a large part of the economic activity in a country, and knowing how well the sector is doing is a good proxy for other economic indicators that are released much later.
The graph shows one of the advanced series (in blue) along with the history of final releases (in red). In FRED, you can save a graph in your account and choose to have the graph automatically update to include the latest data. This way you can easily monitor how a particular indicator is doing over time. The FRED dashboard is a great tool for this.
How this graph was created: Search for “advance retail” or start with the release table linked above. Choose a series. Look in the notes for the code of the corresponding historical series. From the “Edit Graph” section, open the “Add Line” tab and use the series code. Select the last year of data.
Suggested by Christian Zimmermann.
View on FRED, series used in this post:
Different stories from hard and soft data
Leading up to the 2017:Q1 GDP release, the two GDP tracking indicators in FRED have told starkly different stories of expected growth. These indicators, also referred to as Nowcast indicators, combine higher-frequency (e.g., monthly) economic data released before the GDP data to estimate growth in the current quarter. As shown in the graph above, in the beginning of April the GDPNow indicator from the Atlanta Fed forecasted a significant slow-down in growth, predicting 0.638 percent annualized growth in the first quarter. In contrast, the St. Louis Fed Economic News Index forecasted annualized GDP growth to be higher, at 2.89 percent in Q1.
What is driving the difference? An analysis into the data underlying the GDP trackers identifies stark differences between “hard” data and “soft” data in the first months of 2017. The Nowcasts rely on both soft data such as consumer and business surveys and hard data such as retail sales and industrial production. The GDPNow indicator uses more hard data, taking an accounting approach to building a forecast; the St. Louis Fed’s News Index is based more on soft data, which is surveyed from news reports. (For more insight on this topic, see this recent Economic Synopses essay.)
The graph below illustrates the contrast between a soft data series and a few hard data series over the beginning of 2017. The blue line is the University of Michigan Consumer Confidence Index, and the red and green lines are industrial production and retail sales, respectively. Each series is indexed to 100 at October 2016 to show the progression over the end of 2016 and beginning of 2017. Since October 2016, consumer confidence has risen dramatically while retail sales and industrial production have risen steadily but slowly. Soft data in 2017 have so far told a much more positive story of economic growth than hard data. One reasons analysts identify as a possible cause for the divergence between survey and hard economic data is consumer and business optimism after the election of Donald Trump that is not yet reflected in the hard data.
How these graphs were created: Top graph: Search for “GDPNow” in the FRED search box and graph the first series that is returned. Click the “Edit Graph” button and select the middle “Add Line” menu. First, search for “St. Louis Fed Nowcast” and add the St. Louis Economic News Index as a new line. Repeat this process for real GDP, selecting the series with units in percent change from preceding period at an annualized rate. Adjust the date range to 2015:Q3 to 2017:Q1. Bottom graph: Search for “Consumer Sentiment” in the FRED search box and graph the first series that is returned. Repeat the process above to add industrial production and retail and food services as additional lines on the graph. Once all three lines are added, select “Edit Line 1” on the “Edit Graph” menu and change the units to “Index.” Set the date to October 2016 and click “Copy to all.”
Suggested by Maximiliano Dvorkin and Hannah Shell.
View on FRED, series used in this post: