Monday’s scheduled report on US retail sales for April is projected to remain unchanged vs. the previous month, according to The Capital Spectator’s average econometric forecast. That compares with a 0.4% decline reported by the Census Bureau for March. Meanwhile, the Capital Spectator’s average projection for April is slightly above a consensus forecast based on a recent survey 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.