238x Filetype XLSX File size 0.06 MB Source: www.census.gov
Sheet 1: Trading Day Methodology
NOTES ON TRADING DAY ADJUSTMENT |
METHODOLOGY |
The shipments data in the M3 survey are adjusted for calendar month variations, both length of |
month and number of trading days per month. The selection of these adjustment factors is based |
primarily on recognition of patterns contained in the data using the regression and spectral analysis |
capabilities of the X-13ARIMA-SEATS seasonal adjustment software. |
Factors are considered optimal when the daily weights assigned to the industry eliminate or |
diminish the peaks in the spectral plots, which are based on calendar frequencies, and lower the |
absolute value of the month-to-month change in the residual irregular component of the data |
series. |
New orders data in this publication are implicitly trading day adjusted by using the trading day |
adjusted shipments as input to their derivation. The difference in unfilled orders is typically not |
trading day adjusted. |
Because monthly stock series, such as inventories and unfilled orders data, may be considered |
to be accumulations of monthly flows, it is possible to adjust these series for trading day effects. |
Using diagnostics similar to those described above, particular inventory, stage-of-fabrication |
inventory, and unfilled orders series have been adjusted for stock trading day effects. |
For shipments series, the chi-square statistics for the 6-coefficient trading-day regressors are |
shown and should be compared to the appropriate upper percentile of the chi-square distribution |
with 6 degrees of freedom when testing for statistical significance at a specified level. For example, |
at the 10% level of significance, the critical value would be 10.64. For the particular stock series |
that have been adjusted for stock trading day effects, because the number of coefficients |
in the model could be either 1 or 6, similar diagnostics are not shown for these series, but are |
available upon request. |
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