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Selective Editing Techniques and Seasonal Adjustment of STS. Outline. Short presentation on the use of selective editing techniques in monthly production of short-term economic indicators Three main points : General Process of selective-editing for STS (time series)
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Outline • Short presentation on the use of selective editing techniques in monthly production of short-term economic indicators • Three main points : • General Process of selective-editing for STS (time series) • Score function for Seasonnal Adjustement Quality measures • Next steps : improve the process
Score function for SA Quality Measures • The score function is a combination of various criteria : · Number and concentration of outliers; · Statistical properties of the Reg-ARIMA residuals ; · Lack of residual seasonality and trading-day effects in the irregular component and in the seasonally adjusted series; · Similar to M and Q-statistics (Statistics Canada); · Revision analysis (stability of the model, stability of the components). • The global score is simple (-1,0,+1). The component scores show where the problem is. • The “alarm matrix”
Next steps • Improving the imputation of missing data using the dynamic of the business answers. • For the big companies which tend to be late, • => forecast their answer using an ARIMA modeling of their past answers, • possibly benchmarked on the estimated growth rate of the sector. • Improving the score function used to check the quality of the seasonal adjustment. • A principal component analysis could for example give a better set of criteria to check and a better linear combination of them.
Insee 18 bd Adolphe-Pinard 75675 Paris Cedex 14 www.insee.fr Informations statistiques : www.insee.fr / Contacter l’Insee 09 72 72 4000 (coût d’un appel local) du lundi au vendredi de 9h00 à 17h00 Thanks for your attention! Contact Dominique Ladiray Tél. 01 41 17 50 18 Courriel : dominique.ladiray@insee.fr