Transcript Testing Seasonal Adjustment with Demetra+ Levan Gogoberishvili Head of National Accounts Division National Statistics Office of Georgia.

Testing Seasonal
Adjustment with
Demetra+
Levan Gogoberishvili
Head of National Accounts Division
National Statistics Office of Georgia
The original series
GDP by production approach in constant prices
(1996, base year)
Quarterly time series starting with 1st quarter of 2000.
GDP by production approach is calculated by several
types of economic activities. Production of such
activities like Agriculture, Construction services or
Electricity supply and other services have seasonal
features.
Methods and Specifications used
• X12 method were used for seasonal adjustments of following
quarterly series:
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GVA of Agriculture in constant prices
GVA of Industry in constant prices
GVA of Construction in constant prices
Total GDP at constant prices
We received the most stable results (according to automatic
quality checks made by software itself) by using automatic
RSA1 specification.
Pre-processing and Diagnostics
Graph of the results
Check for moving seasonality
Main Quality Diagnostics
Residual seasonality
Stability of model
Residuals
Some problematic series
• There is a problem of spectral peaks in the time
series of industry.
• We explained it as a result of aggregation (Industry =
Mining and quarrying + Manufacturing + Electricity,
Gas and Water production and distribution)
Possibilities to publish
the results
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At this stage following seasonally adjusted time series are
published:
Industrial production Indices (Base year = 2011, quarterly)
GDP in constant, 2003 prices (quarterly)
Industrial production Indices are available on Geostat
website and also in annual publication “National Accounts
of Georgia”
Seasonally adjusted GDP are not published on web-site in
order to avoid confusion of some users. However, this time
series are included in annual publication. Some users with
advanced knowledge of economics use this time series for
analysis. There are some users, which prefer to receive
original time series and do seasonal adjustments
themselves.
Conclusions
• Before the first meeteng we had used Demetra 2.0
software for seasonal adjustment of IPI time series.
• Now we use Demetra+ version. Despite the method of
Tramo/Seats is the same, the results are a little different
because of changes in specification.
• For GDP time series we started to use X12 method. Some
of the results are shown in this presentation.
• The basic problem for us is, that our time series are
quarterly and we do not take into account Easter and Trade
days effects.
• We hope that, experts in the second seminar will
additionally prepare specific recommendations for countries
with only quarterly time series.
Conclusions
• Another problem is that, some users do not understand
the meaning of seasonal adjustments. If we publish both
the original and seasonally adjusted GDP time series at
the same time, it might not be understood properly.
• We are planning to prepare some metadata and
explanations of seasonal adjustments for users.
• On the other hand we will continue work for improving
SA work. For this purpose the planned workshop will be
very useful.
Thank you!