1 out of 20 possible scenarios: how to perform temporal - - PowerPoint PPT Presentation

1 out of 20 possible scenarios: how to perform temporal disaggregation of annual sector accounts data

Dario Buono

Eurostat, Unit B1: Methodology and corporate architecture

Filippo Gregorini

Eurostat, Unit C1: National accounts methodology. Sector accounts. Financial indicators

Enrico Infante

Eurostat, Unit C1: National accounts methodology. Sector accounts. Financial indicators Università degli studi di Napoli Federico II, Dipartimento di scienze economiche e statistiche

NTTS, Brussels 11th March 2015

Eurostat

Summary

• Introduction
• Methods
• Results
• Conclusions

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Introduction

• Sector accounts data are to be provided by Member States on

both annual and quarterly bases

• Member States whose contribution to the EU GDP is below 1%

("small") have to provide only a partial matrix for quarterly data

• In such cases only annual data are available, but quarterly

estimates for "small" countries are needed for the production of quarterly data for the aggregates (EA, EU)

• The aim of this paper is to build an empirical application to

estimate missing quarterly series for the 5 "small" EU countries to produce EU28 aggregates

• The whole exercise is performed with JDemetra+ 2.0.0

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Methods

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• Accounting and temporal constraints
• Mathematical methods:
• Denton (1971)
• Regression based methods:
• Chow-Lin (1971) – AR(1)
• Fernández (1981) – Random Walk
• Litterman (1983) – Random Walk Markov
• Many other methods are available, as Di Fonzo and Marini (2012),

which takes into account both the two constraints

• Timing constraints
• The exercise is to be performed during the production round, where

the time constraint is really important

Soft Watch at the Moment of First Explosion, Dali (1954)

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Which method does what: possible scenarios

Temporal constraint (temporal disaggregation) Accounting constraint (benchmarking)

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Denton modified Cholette-Dagum-Bee Cholette modified Naïve Denton Chow-Lin (Fernández, Litterman) Wei-Stram DiFonzo-Marini

X

EU28 AGGREGATE

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Methods

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Target series: Quarterly EU28 aggregate

A B C

Quarterly EU28 figures, assuming the missing 5 countries behave like the other 23 countries Quarterly figures for each of the 5 missing countries Quarterly figures for the 5 missing countries aggregated "EU5"

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Methods

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Target series: Quarterly EU28 aggregate

A

Quarterly EU28 figures, assuming the missing 5 countries behave like the other 23 countries Quarterly EU23 data of the same variable

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Methods

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Target series: Quarterly EU28 aggregate

B

Quarterly figures for each of the 5 missing countries Related available quarterly data for each missing county (e.g. GDI)

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Methods

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Target series: Quarterly EU28 aggregate

C

Quarterly figures for the 5 missing countries aggregated "EU5"

• Quarterly EU23 data
• Seasonal component of EU23 data
• Trend and irregular component of EU23 data

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Results

• The series showed here is the compensation of employees paid by

non-financial corporations (S11_D1PAY)

• For this specific transaction, the weight of the 5 missing countries

among the total EU is 2.04%. In general the weight is between 1.5% and 3%

• The exercise has been performed by using approach "A"
• In the charts only the extrapolated "EU5" figures are presented, in
• rder to better show the differences between the different

methods

• The Denton and the Chow-Lin approaches are compared with the

naïve method (dividing the annual figures by 4)

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Results

• Although the differences between Denton and Chow-Lin methods

are small, the latter will allow us to look at goodness of fit statistics

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Conclusions

• Our exercise shows that with up-to-date software, different

approaches are fast and easily replicable, and therefore useful for production purposes

• Chow-Lin (and similar) statistical model is as fast as

mathematical models to be displayed but also has the key advantage of being a statistical method, so that its regression analysis enable to measure the goodness of fit of the estimates

• JDemetra+ is an user-friendly tool which allows the users to

modify the specifications according to specific needs in a quick and easy way

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Thank you for your attention!

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• ppmerksomheten!

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