Tomorrow’s retail sales report for September will be postponed due to the government shutdown. When (if?) this update is published, US retail sales are expected to rise 0.3%, according to The Capital Spectator’s average econometric forecast. Keep in mind that this forecast is impaired because it doesn’t reflect an update of the R-2 model (see definition below), which relies in part on the latest payrolls data to project retail sales. Unfortunately, the September employment report from the government is still a mystery due to the budget impasse in Congress. Using the available numbers, the Capital Spectator’s average forecast of a 0.3% rise for September retail sales represents a slight rise from the previously reported 0.2% gain in August. Meanwhile, the Capital Spectator’s average projection for September is above several consensus forecasts based on recent surveys of economists.
Here’s a closer look at the numbers, followed by brief definitions of the methodologies behind The Capital Spectator’s projections:
R-2: A linear regression model that analyzes two data series in context with retail sales: an index of weekly hours worked for production/nonsupervisory employees in private industries and the stock market (S&P 500). The historical relationship between the variables is applied to the more recently updated data to project retail sales. The computations are run in R.
ARIMA: An autoregressive integrated moving average model that analyzes the historical record of retail sales in R via the “forecast” package.
ES: An exponential smoothing model that analyzes the historical record of retail sales in R via the “forecast” package.
VAR-6: A vector autoregression model that analyzes six time series in context with retail sales. The six additional series: US private payrolls, industrial production, index of weekly hours worked for production/nonsupervisory employees in private industries, the stock market (S&P 500), disposable personal income, and personal consumption expenditures. The forecasts are calculated in R with the “vars” package.