United Nations Economic Commission for Europe Statistical Division Importance of Original Data and Fixed Base Indices – Data Example Artur Andrysiak Economic Statistics Section, UNECE

UNECE Statistical Division Slide 2September 2008 Overview  Original  Cumulative/Year-to-date  Fixed base Index  pp=100  sppy=100  sppy=100 cumulative  Seasonally adjusted  Trend  Remarks

UNECE Statistical Division Slide 3September 2008 UNECE Timeseries  UNECE fictional timeseries  Logarithmic (Multiplicative series)  2 major turning points  2 significant holiday effects (Jun and December)  Significant Western Easter Effect (moving between March and April)  Average magnitude of irregular  No outliers

UNECE Statistical Division Slide 4September 2008 Original Data/Discrete values

UNECE Statistical Division Slide 5September 2008 Original Data  Easy to understand the levels  Long term movement visible but not very clear  Difficult to interpret the latest observations  Difficult to draw short-term conclusions

UNECE Statistical Division Slide 6September 2008 Year-to-date/Cumulative data

UNECE Statistical Division Slide 7September 2008 Year-to-date/Cumulative data  Can appreciate the increasing and decreasing magnitudes  Very difficult to draw any other conclusions

UNECE Statistical Division Slide 8September 2008 Fixed base index

UNECE Statistical Division Slide 9September 2008 Fixed base index  Levels no longer visible  Scaled down  Long term movement visible but not very clear  Difficult to interpret the latest observations  Difficult to draw short-term conclusions

UNECE Statistical Division Slide 10September 2008 PP=100 (month on month)

UNECE Statistical Division Slide 11September 2008 PP=100 (month on month)  Difficult to draw any conclusions

UNECE Statistical Division Slide 12September 2008 SPPY=100

UNECE Statistical Division Slide 13September 2008 SPPY=100  Long term movement visible but not very clear  Difficult to interpret the latest observations  Easter effect for some periods (not all) very visible (due to moving Easter)  Possible to draw some mid-term conclusions (in relations to previous year)

UNECE Statistical Division Slide 14September 2008 Cumulative SPPY=100

UNECE Statistical Division Slide 15September 2008 Cumulative SPPY=100  Long term movement visible and clear but different from the original series (implies very drastic increases and decreases)  Latest observations can be only interpreted in reference to the sppy  Easter effect for some periods (not all) very visible (due to moving Easter)  Possible to draw some mid-term conclusions (in relations to previous year)

UNECE Statistical Division Slide 16September 2008 All indices

UNECE Statistical Division Slide 17September 2008 All indices  Confecting results/conclusions  Very difficult to clearly interpret the statistics

UNECE Statistical Division Slide 18September 2008 Seasonally adjusted

UNECE Statistical Division Slide 19September 2008 Seasonally adjusted  The underlying pattern clearly visible  No more trading day/holidays effect  No more Easter effect  Very easy to interpret the latest observations/draw short-term conclusions  But depending on the SA method the latest observations could be subject to future revised

UNECE Statistical Division Slide 20September 2008 Trend

UNECE Statistical Division Slide 21September 2008 Trend  The underlying trend clearly visible  Easy to comment on business cycle  Easy to comment on long term movements  Caution needs to be taken with the latest observations, as the trend will continue to change depending on the direction of future observations

UNECE Statistical Division Slide 22September 2008 Original, SA, Trend

UNECE Statistical Division Slide 23September 2008 Original, SA, Trend  Clear and consistent conclusions can be drawn  Results of the analysis can be easily supported with facts  Together they provide users with information about: short-term and long- term patterns

UNECE Statistical Division Slide 24September 2008 SPPY=100, SA, Trend

UNECE Statistical Division Slide 25September 2008 Cumulative SPPY=100, SA, Trend

UNECE Statistical Division Slide 26September 2008 Conclusion  Providing original data or fixed base indices to users will give them maximum flexibility and permit them the choice of their own methods for analysis  Maintaining and providing long timeseries is essential for correct analysis of statistics  Different ways of expressing statistics provide users with different information  We should be careful in our choice of method of publishing statistics as different ways of transforming the original data can provide users with different conclusions

UNECE Statistical Division Slide 27September 2008  Questions?  THANK YOU