Overview of Main Quality Diagnostics
Anu PeltolaEconomic Statistics Section, UNECE
UNECE Workshop on Seasonal AdjustmentUNECE Workshop on Seasonal Adjustment20 – 23 February 2012, Ankara, Turkey
February 2012 UNECE Statistical Division Slide 2
Overview
Purpose of quality diagnostics Main quality issues Main results First visual checks Pre-processing Decomposition Main quality diagnostics
February 2012 UNECE Statistical Division Slide 3
Purpose of Quality Diagnostics
Seasonality is identified based on hypotheses • Seasonal component is estimated = is uncertain
Diagnostics will reveal any essential weaknesses in seasonal adjustment
Help draw attention to problematic issues• They prevent the use of misleading results that could
lead to false signals The automatic procedure in Demetra+ is
reliable! • But diagnostics are especially important for analysing
in detail the aggregate series
February 2012 UNECE Statistical Division Slide 4
Main Quality Issues
Appropriateness of the identified model and components
Number and type of outliersStability of the seasonal componentAbsence of residual seasonality and
residual calendar effectsMagnitude of the possible phase
delay
February 2012 UNECE Statistical Division Slide 5
Main results inform you about…
Estimation time span used for identifying the seasonal pattern
Application of log-transformation If there working day, Easter or Leap year
effects were identified If outliers were found and when A summary quality diagnostics
February 2012 UNECE Statistical Division Slide 6
Visual checks
To find seasonal breaks and high variability Problematic with moving averages, fitting the ARIMA model and finding
effects
February 2012 UNECE Statistical Division Slide 7
Pre-processing
Statistical properties of the ARIMA model
Regression variables The pre-adjusted series Residuals
• should be independent and random and follow normal distribution
February 2012 UNECE Statistical Division Slide 8
Decomposition
Stochastic series presents the results Cross-correlation of results
• In theory, components should be uncorrelated• A green p-value in Demetra+ would indicate
insignificant cross-correlation Estimator
Estimate
P-Value
Trend/Seasonal -0.1250 -0.1504 0.8018
Trend/Irregular -0.0450 -0.0856 0.7311
Seasonal/Irregular
0.0446 0.0195 0.5900
February 2012 UNECE Statistical Division Slide 9
Quality Diagnostics
Presence of seasonality Spectral graphics Revision history Sliding spans Model stability analysis
February 2012 UNECE Statistical Division Slide 10
Presence of Seasonality
Friedman test & Kruskall-Wallis test• Is there stable seasonality?
Evolutive seasonality test• Is there moving seasonality?
Combined seasonality test• Is there identifiable seasonality?
Residual seasonality test• Is there seasonality left in residuals in the entire series
or in the last 3 years of data?
February 2012 UNECE Statistical Division Slide 11
Spectral Graphics
Periodogram Auto-regressive
spectrum• Analyse the
residuals, irregular component and seasonally adjusted series for remaining seasonal or trading day effects
Spectral graphics of the residuals
February 2012 UNECE Statistical Division Slide 12
Revision History
Analyses revisions that happen when new observations are added at the end of the series
February 2012 UNECE Statistical Division Slide 13
Sliding Spans
Analyses stability of • Seasonal component• Trading day effect (if present) • Seasonally adjusted series
Slidings spans of the seasonal component
February 2012 UNECE Statistical Division Slide 14
Model Stability Analysis
Calculates ARIMA parameters and coefficients of regression variables for different periods
Computes the results on a moving window of eight years which slides by one year
The points correspond to the successive estimations
Strong movement of values from negative to positive indicates instability
February 2012 UNECE Statistical Division Slide 15
Problematic Issues
Which are the most essential tests? How to read and understand the
diagnostics? When does a result signify bad quality? What to do to improve results? Which poor results of quality diagnostics
could be accepted? Which quality diagnostics could be published
to the users?
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