1. Calendar Effects

2. Monthly production series are strongly affected by calendar effects. In particular, a close connection between production and the number of working days was always assumed Working day adjusted results have always been particularly important for the indices of industrial production users

3. Calendar effects in the Industrial Production Indices Length of the month Day-of-the-week composition Holidays Public holidays in Spain vary From one year to another From one Community to another

4. A straightforward use of ARIMA models is not sufficient to capture calendar variations in the indices, because they are not precisely periodic Regression models are used to handle calendar effects The overall models are a sum of ARIMA and regression models

5. Hillmer, Bell, Tiao

6. We try summarize all calendar effects using only two variables: Weighted working day (WD t ) Holy week (H t )

7. Weighted Working Days Instead of the most commonly used 7 trading day variables (number of Mondays, Tuesdays, etc.), one single variable, adapted to the behaviour of the Spanish Industrial Production, is constructed For the industrial production, the important matter is the distinction between a working day and a non- working day, and less important is the distinction within the working days (because the intensity of work is usually similar)

8. Weighted Working Day Variable (WD t ) (I) Tries to measure the number of working days, subtracting Saturdays, Sundays and holidays, taking into account the different behaviour of the Communities WD t = MF t - HOL t MF t =  Mondays to Fridays in month t HOLI ti I ijt j     1 17,,

9. Weighted Working Day Variable (WD t ) (II) 1 if the j th holidays is non- working the i th Community I i,j,t 0 otherwise  i : Weight of the i th Community in the 2000 industrial value added