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Adjusting for A Calendar Effect in Employment Time Series

Stephanie Cano, Patricia Getz, Jurgen Kropf, Stuart Scott, and George Stamas


The Bureau of Labor Statistics Current Employment Statistics (CES) program is a monthly survey of nearly 400,000 business establishments nationwide; its reference period is the pay period including the 12th of each month. Of paramount importance to most CES data users are over-the-month changes in total nonfarm employment levels, thus the seasonal adjustment of these data critically affects the analysis of national employment trends. This study investigates a calendar effect which may cause difficulties in interpreting movements in the current seasonally adjusted series. The effect arises because there are sometimes 4 and sometimes 5 weeks between the reference periods in any given pair of months (except February/March). This varying interval effect is estimated by an ARIMA model with regression variables, using the Bureau of the Census X-12 ARIMA procedure. Estimates of the interval effect are tested for significance. Series estimated with and without the interval adjustment are compared for smoothness and stability across successive time spans. Differences between over-the-month employment changes as previously published and as estimated with interval effect modeling are also examined.