The Big Four: April Real Retail Sales Up 0.05%

This article was originally written by Doug Short. From 2016-2022, it was improved upon and updated by Jill Mislinski. Starting in January 2023, AP Charts pages will be maintained by Jennifer Nash at Advisor Perspectives/VettaFi.

Note: With the release of April retail sales and the CPI, we've updated this commentary to include the latest real retail sales.

Official recession calls are the responsibility of the NBER Business Cycle Dating Committee, which is understandably vague about the specific indicators on which it bases its decisions. This committee statement is about as close as it gets to identifying its method.

There is, however, a general belief that there are four big indicators that the committee weighs heavily in their cycle identification process. They are:

The Latest Indicator Data

Month-over-month nominal retail sales in April were up 0.42% and up 1.60% YoY. However, after adjusting for inflation, real retail sales increased by 0.05% and were down 3.20% YoY.

The chart below gives us a close look at the monthly data points in this series since the end of the great recession in mid-2009. The linear regression helps us identify variance from the trend.

This indicator has been rising below trend since the end of 2015, with a swing above trend in 2021 as a result of the COVID-recession recovery. In November 2022, real retail sales dropped below the trendline.

Real Retail Sales

This indicator is a splicing of the discontinued retail sales series (RETAIL, discontinued in April 2001) with the Retail and Food Services Sales (RSAFS) and deflated by the seasonally adjusted Consumer Price Index (CPIAUCSL). We've used a splice point of January 1995 because that date was mentioned in the FRED notes. Our experiments with other splice techniques (e.g., 1992, 2001 or using an average of the overlapping years) didn't make a meaningful difference in the behavior of the indicator in proximity to recessions. We've chained the data to the latest CPI.

In the charts below we have illustrated three different data manipulations:

  1. A log scale plotting of the complete data series to ensure that distances on the vertical axis reflect true relative growth. This adjustment is particularly important for data series that have changed significantly over time.
  2. A year-over-year representation to help, among other things, identify broader trends over the years.
  3. A percent-off-high manipulation, which is particularly useful for better understanding of trend behavior and secular volatility.

Real Retail Sales

Real Retail Sales YoY

Real Retail Sales Percent Off Highs