Luxembourg: Office for Official Publications of the
European Communities, 2003
ISBN 92-894-5417-2
ISSN 1725-0048
Cat. No. KS-BE-03-002-EN-N
2003 EDITION
N O M E N C L A T U R E S
A N D
M E T H O D S
COPYRIGHT
© European Communities, 2003
Flash estimation of the
quarterly Gross Domestic
Product for the euro-zone
and the European Union
Eurostat methodology
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Luxembourg: Office for Official Publications of the European Communities, 2003
ISBN 92-894-5417-2
ISSN 1725-0048
© European Communities, 2003
EUROPEAN COMMISSION
EUROSTAT
Directorate B: Economic statistics and economic and monetary convergence
Flash Estimation of the quarterly Gross Domestic
Product for the euro-zone and the European Union
Eurostat methodology
SUMMARY
Flash Estimation of the quarterly Gross Domestic Product for
the euro-zone and the European Union
The methodology used for the “flash” estimate of the GDP growth rate for the European aggregates
(euro-zone and EU15) is based on the following principles:
G
indirect approach to the estimation of the European aggregates, i.e. using Member States flash
estimates and/or indicators, rather than indicators at European level;
G
use of all the available information:
• all Member States GDP estimates referring to the quarters preceding the reference quarter,
officially released;
• all Member States GDP “flash” estimates for the reference quarter which are available in
time for the European GDP flash estimate;
• other relevant indicators (as the Industrial Production Index) referring to major European
Union Member States for which no GDP “flash estimate” is available yet. These indicators
were selected according to the delay with which they are available, economic reasoning and
for their capacity to explain the GDP movements.
G
major countries coverage: Germany, France, Spain, Italy and the United Kingdom are always
taken into account in the estimation, either by using official GDP figures (if available) or other
related indicators that proved to be statistically significant for single Member States GDP
estimation;
G
revisions of euro-zone and EU15 figures: data till the quarter preceding the reference quarter are
not revised since the flash estimate concerns only the reference quarter.
G
the statistical model chosen to derive the estimates is a regression one in the framework of a
temporal disaggregation technique. This methodology is the same as that already used by
Eurostat for the regular estimations of the European aggregates.
G
reliability of the estimates: the method used is statistically robust. It showed a high goodness of
fit measure and passed all the usual statistical tests. Furthermore, it proved a good capacity of
anticipating the traditional Eurostat estimates: the root mean squared error, calculated with
respect to the first regular Eurostat estimates of the growth rate on the previous quarter and
measured over a period of nine quarters (from the fourth quarter of 2000 to the fourth quarter of
2002) in which the model was tested under real conditions, is equal to 0.04% for the euro-zone
and the EU15. The performance of the flash estimates in anticipating the first Eurostat estimate
is illustrated in figures 1 and 2.
2
Flash Estimation of the quarterly Gross Domestic Product for the eurozone and the European Union
1. Introduction
The increasing importance of the euro-zone as economic entity, the introduction of the euro, the
establishment of the single market have contributed in the recent years to increasing the attention
devoted to European statistics. In particular, economic and monetary policies are nowadays more
co-ordinated and centrally designed in the European context and require more and more reliable and
timely European statistics for an effective analysis of the economic behaviour.
The European Statistical System has evolved in a direction that gives concrete answers to these new
statistical requirements. As recently underlined by a Communication of the Commission to the
European Parliament and the Council on Euro-zone Statistics1 "… official statistics of a high quality
are essential for the conduct of monetary policy and the co-ordination of economic, in particular
fiscal, policies. A sufficiently detailed and comprehensive set of timely and reliable monthly and
quarterly statistics for the EU and the euro-zone is indispensable …".
Infra-annual macro-economic statistics are a key tool for economic and monetary policy making and
business cycle analysis and the demand for such statistics sharply increased in the last years. Despite
the improvements achieved in these areas, timeliness of the European key macro-economic statistics
is still a problem. In order to give a concrete answer especially to timeliness requirements, the
Ecofin Council endorsed in September 2000 the European Monetary Union (EMU) Action Plan, a
report that identifies for each Member States and for the euro-zone and the EU the major infraannual macro-economic statistical areas in which improvements were needed. One of the considered
areas was quarterly national accounts and in particular, timeliness and coverage.
Still, according to the results of a EU-US benchmarking exercise, the targets of the Action Plan,
although representing a substantial improvement in quarterly national accounts compilation, might
not be enough to match the US standards, notably in timeliness. For this reason a list of more
focused infra-annual macro-economic indicators (the Principal European Economic Indicators or
PEEIs), including quarterly GDP, has been set up with more challenging target release dates for EU
and euro-zone indicators. Concerning GDP, one of the major targets is a first estimate at 45 days
after the end of the reference quarter: the flash estimate.
Starting from these considerations and in the context of the general improvement of quarterly
European accounts, Eurostat developed a methodology for the compilation of a flash estimate of
quarterly GDP for the euro-zone and the European Union at 45-48 days after the end of the
reference quarter. The Eurostat project benefits from the results of a project on flash estimates of
quarterly national accounts co-ordinated and supervised by Eurostat in the framework of the
European Union Fifth Research Programme. This project analyses feasibility and suitable methods
to produce a flash estimate and proposes a methodology for compiling flash estimates at the
European level.
This document presents the methodology of compilation of the flash estimate of the European
quarterly GDP as developed by Eurostat.
1
Communication of the Commission to the European Parliament and the Council on euro-zone statistics "Towards
improved methodologies for euro-zone statistics and indicators".
3
2. Flash estimate of quarterly national accounts: terminology
As already mentioned, the need of reliable and timely quarterly European national accounts figures
has become more and more important in the recent years. Timeliness has notably been one of the
major requirements because the actual availability of the European aggregates (first estimate
between 60-70 days after the end of the reference quarter) does not answer to the needs of the users
(business cycle analysis and evaluation of economic and monetary policies).
User requirements cannot be satisfied by available short-term indicators (e.g., production indices,
prices, foreign trade, business surveys) because these do not have the homogeneity and consistency
of the quarterly national accounts system. Users' needs are synthesised in the wish of disposing of a
reliable and rapid system of preliminary-flash estimates that should ideally cover the main quarterly
accounts aggregates to have an early and consistent view of the developments of the economy.
A system of flash estimate of quarterly accounts is:
•
an earliest picture of the economy;
•
in accordance with national accounts concepts;
•
produced and published as soon as possible after the end of the quarter;
•
based on a more incomplete set of information than traditional quarterly accounts compilation.
According to this definition, flash estimates differ both from forecasts and leading indicators.
Indeed, flash estimates give a coherent picture of the whole economy, respecting the accounting
relations and focusing on the past.
The differences between flash estimates and traditional estimates of quarterly accounts can be
defined according to the following dimensions
•
Timeliness: flash estimates are available earlier than the traditional estimates (30-45 days).
•
Accuracy: there is a trade off between timeliness and accuracy. Flash estimates are in general
less accurate than the traditional ones. However the loss in terms of accuracy is kept as small as
possible;
•
Coverage: the number of variables covered by flash estimates is usually more limited.
•
Information available: flash estimates are based on a more limited set of information. Often
information from surveys is not available.
•
Estimation method: due to the lack of direct information, flash estimates are performed mostly
by resorting to statistical methods (indirect approach of compilation) where short-term
indicators are used in the framework of regression techniques.
The distinction between flash and traditional estimates is not always clear. For example, with
respect to timeliness, flash estimates for one country may be available later than the traditional first
estimates for another.
3. Quarterly national accounts compilation in the European Union
The legal framework for the compilation and transmission to Eurostat of quarterly national accounts
is fixed by the ESA 1995 at 120 days after the end of the reference quarter2. Nevertheless,
compilation policies and release calendars vary according to Member State (see Table 1).
2
A new European Parliament and Council Regulation amending ESA 1995 that should enter into force mid-2003 will
reduce the legal deadline for the transmission to 70 days.
4
Excluding the effects of derogations and late transmissions, a pure European aggregate, obtained as
a sum of the Member States figures, is obtainable theoretically at 120 days after the end of the
reference quarter.
Tab. 1: Regular delays in the transmission of the first GDP release
Country
GDP
Country
GDP
Belgium
57
Netherlands
45
Denmark
59
Austria
84
Germany
53*
Portugal
72
Greece
45
Finland
66
Spain
59
Sweden
64
France
50
United Kingdom
25
Ireland
127
EU and euro-zone
65
Italy
45
United States
25
Luxembourg
---
Japan
70
*The German National Statistical Institute (DESTATIS) is publishing a 45 days flash estimate of the
German GDP starting from the 1st quarter of 2003 figure.
In order to avoid such a long delay and to satisfy users' requirements Eurostat is currently publishing
3 estimates of Gross Domestic Product (and quarterly national accounts) each quarter, for both the
euro-zone and the EU15:
•
First release: 60-70 days after the end of the reference quarter. The release date depends on the
release dates of the major countries of the European Union (i.e., Germany, France, Italy and
United Kingdom);
•
Second release (revised): 100 days after the end of the reference quarter;
•
Third release (final): 120 days after the end of the reference quarter.
The flash estimate of GDP at 45 days complements this system by putting at the users’ disposal an
indicator of economic growth quite quickly after the end of the reference quarter.
Besides Eurostat, Member States too recognised the interest in flash estimates at the national level
and in some cases started to publish them. Furthermore, the idea of flash estimates is currently
developed in most of the countries that are not yet publishing a GDP flash estimate. Although
Member States follow different approaches in developing flash estimates, the common idea
underlying their compilation, and adopted also by Eurostat, is to apply the same methodology as for
the normal compilation of quarterly accounts on the basis of fewer basic information, trying to
anticipate the availability of basic statistics.
4. European quarterly national accounts methodology of estimation in use
The first estimate of quarterly national accounts, i.e. the reference target for the flash estimate,
covers GDP, expenditure components and output breakdown, usually at constant prices, raw and
seasonally adjusted. Data are disseminated to institutions and private clients; a news release is
produced, mainly devoted to the analysis of the growth rates and seasonally adjusted figures.
5
When performing the first estimation, data for a variable subset of Member States are available:
usually Belgium, Germany, France, Italy, the Netherlands and the United Kingdom.
Eurostat is compiling quarterly national accounts for the EU and euro-zone according to the socalled "indirect" approach, that is by aggregating or estimating the European aggregates on the base
of Member States figures and not by using direct basic statistics.
The compilation problem consists in the estimation of the quarterly values for the EU-15 and eurozone totals starting from the available information, i.e. annual totals (the EU-15 and euro-zone
annual totals correspond to the sum of the annual totals of the Members States up to the year
preceding the current one) and the available quarterly figures of those Member States that compile
quarterly accounts and provide them in time for the estimation. For GDP the share of the total
represented by the available countries on a quarterly basis is roughly 80% (see Table 2).
Tab 2: Relative weights of Member States in the European GDP (year 2001)
B
DK
D
GR
E
F
IRL
I
L
NL
A
P
FIN
S
UK
EUR-12
EU-15
countries' weights in the European aggregate
EUR-12 GDP
EU-15 GDP
EU-15 private consumption
current constant
current constant
current
constant price
price price 1995
price price 1995
price
PPS
PPS
1995 euros
PPS
euros
euros
euros
euros
euros
3.7%
3.9%
3.7%
2.9%
3.2%
2.9%
2.7%
2.9%
2.7%
---2.0%
2.1%
1.6%
1.6%
1.7%
1.3%
30.3%
33.2%
27.9%
23.4%
27.1%
22.3%
23.8%
26.8%
22.7%
1.9%
1.8%
2.3%
1.5%
1.5%
1.9%
1.7%
1.8%
2.2%
9.5%
8.9%
11.1%
7.4%
7.3%
8.9%
7.3%
7.4%
8.9%
21.4%
22.2%
20.5%
16.5%
18.1%
16.4%
15.5%
17.0%
15.4%
1.7%
1.4%
1.5%
1.3%
1.1%
1.2%
1.0%
1.0%
1.0%
17.9%
15.1%
19.6%
13.8%
12.3%
15.7%
14.1%
12.8%
16.1%
0.3%
0.3%
0.3%
0.2%
0.3%
0.2%
0.2%
0.2%
0.2%
6.3%
6.2%
6.0%
4.9%
5.1%
4.8%
4.1%
4.4%
4.1%
3.1%
3.3%
3.0%
2.4%
2.7%
2.4%
2.3%
2.6%
2.3%
1.8%
1.6%
2.3%
1.4%
1.3%
1.9%
1.4%
1.4%
1.9%
2.0%
2.0%
1.8%
1.5%
1.7%
1.4%
1.3%
1.4%
1.2%
---2.8%
3.0%
2.4%
2.3%
2.5%
2.0%
---18.1%
13.4%
16.0%
20.4%
16.1%
18.1%
100.0%
100.0% 100.0%
77.2%
81.6%
80.0%
75.6%
79.8%
78.6%
---100.0%
100.0% 100.0% 100.0%
100.0% 100.0%
share of indicator available at
70 days
79.7%
80.6%
100 days
94.3%
94.9%
120 days
96.1%
96.5%
79.5%
95.6%
97.0%
79.2%
95.8%
97.2%
80.7%
95.6%
97.1%
80.0%
95.6%
97.1%
The share of available indicators never reaches 100%. This implies that an aggregation by simple
summation of Member States data is not possible.
From a statistical point of view, a solution to this problem is the application of temporal
disaggregation techniques. Given an annual series and one or more quarterly indicators the aim is to
derive the quarterly figures (coherent with the annual series) in the context of a statistical model.
The main hypothesis is that the indicator series (the available quarterly series) are good indicators
for the movements of the variable of interest. This certainly is the case for the EU15 and euro-zone
aggregates. The indicator series is a part of the target series (as already stated, it usually represents
more than 75% of this series) and its movements are strictly related to the movements of the target
series (the influence of those countries that do not compile quarterly accounts may be deduced from
the annual relationships).
6
Eurostat's procedure for the estimation of EU15 and euro-zone quarterly totals consists of 2 steps:
1. the estimation of the quarterly value of euro-zone/EU15 GDP and preliminary estimation of its
components, on the expenditure and output sides, according to the regression model based
method of Chow and Lin. As an output quarterly time series fulfilling the time consistency
criteria (the sum of the quarters being equal to the annual values) are obtained.
2. the balancing of euro-zone/EU15 GDP components in an accounting framework, respecting
both the time and the accounting constraints, starting from the preliminary estimates obtained in
step 1 and using the multivariate method of Denton.
As an output, quarterly time series fulfilling both time consistency and accounting constraints
criteria are obtained.
5. GDP estimation: the Eurostat flash project
The aim of the Eurostat Flash project is to produce flash estimates of main quarterly national
account aggregates for the euro-zone and the European Union with a delay of 45-48 days after the
end of the reference period. This delay has been chosen because it seems to be “reasonable” for
European flash estimates, as suggested by the experience of certain countries (United Kingdom and
the United States: 25-30 days, Italy and the Netherlands: 45 days); trying to shorten it further at EU
level generally implies a considerable reduction in the available basic information.
The final project aim is to supply a coherent system of data to carry out short-term economic
analysis and help taking monetary policy decisions avoiding the delay of the official EU quarterly
figures and the lack of accounting homogeneity and consistency of other short-term basic statistics.
The first practical objective of the flash estimate project is to produce a flash estimate of GDP
growth (constant prices, seasonally adjusted) within 45-48 days after the end of the reference
quarter. The next steps of the project are:
§
to extend the flash estimate to the main expenditure and output components of GDP (always in
terms of growth rates);
§
to produce a coherent and complete system of quarterly accounts flash estimates;
§
to anticipate the flash estimate of GDP to 30 days.
6. The flash estimate methodology
In accordance with the results of the “Flash Project” (developed in the framework of the European
Union Fifth Research Programme) the identification of a suitable method for the estimation of the
euro-zone and the European Union GDP went through the following steps:
•
analysis of the available information;
•
choice of a methodology of flash estimates and model building;
•
nowcasting performance analysis.
As mentioned before, an indirect approach to the compilation of the European GDP has been taken
into consideration using Member States data as a basis of constructing indicators. Nevertheless, the
direct approach compilation has also been analysed and the results evaluated.
6.1.
Target variable
The target variable for the flash estimate is the quarterly growth rate on the previous quarter of GDP
for the euro-zone and the EU, seasonally adjusted, constant prices 1995, as published by Eurostat.
7
The choice of the growth rate on the previous quarter is in line with the objective of describing
short-term movements of the economy. Furthermore, the quarter on quarter growth rate is the main
indicator on which Eurostat's news releases focus.
The quarterly series for the euro-zone and the EU15 is currently available from the second quarter
1991 onwards.
The flash estimate result will be published for the latest quarter only, i.e. no revisions will be
applied to previous quarters. Previous quarters will only be revised with the three subsequent,
regular releases.
6.2.
Indicators: analysis of the available information
Several different sources of basic information are available within a reasonable delay after the end
of the reference quarter. The available information is made up by:
a)
the figures compiled by the National Statistical Institutes in the context of quarterly national
accounts as far as they are available 40-45 days after the end of the quarter (countries' flash
estimates);
b)
the figures estimated by other institutes like Central Banks, short-term analysis institutes,
etc. (but well recognised at the national level);
c)
other basic statistics normally compiled by National Statistical Institutes and usually
available at higher frequency than quarterly (for example, index of industrial production,
retail sales, prices, employment, external trade, etc.).
In particular, as far as GDP flash estimates are concerned, the situation is described in
Table 3.
Table 3: EU countries' Flash Estimates of GDP and delay of publication.
Country
Institution
Delay (days)
Germany*
DESTATIS
45
National Statistical Institute
45
ISTAT
45
Netherlands
CBS
45
United Kingdom
ONS
25
Greece
Italy
* The German statistical office (DESTATIS) is publishing a flash estimation of the German GDP starting
from the 1st quarter of 2003 figure. In order to test the model for the flash estimation of the European
aggregates, a flash estimate of the German GDP published by DIW (Deutsches Institut für
Wirtschaftsforschung) was used.
In accordance with the Eurostat methodology for the regular estimates of the European quarterly
national accounts aggregates and on the basis of the results coming from the "Flash Project", flash
estimations at country level are considered the best indicator for the nowcasting of the euro-zone
and the European Union GDP. For this reason, in the estimation process priority is given to
countries flash estimates. For those big Member States that are not producing flash GDP estimates,
related indicators are used. Countries flash estimates and indicators are combined for estimating
GDP in the context of a regression model based approach (similar to the approach of the first
regular estimation).
8
The related indicators have been chosen following a step process:
•
A first list of indicators suitable to produce the flash estimate has been identified by economic
reasoning, requiring that the indicators show a close correlation to the dependent variable;
•
Selection, inside the list, of the most suitable indicators on the basis of a bivariate pairwise
analysis of correlation with the target variable.
An analysis of the indicator correlation with GDP was the leading criterion in choosing the
indicators. The analysis was performed in order to identify those indicators most suitable for the
GDP flash estimation of the European aggregates, as a complement of the GDP flash estimates
available at 45 days at country level.
A bivariate strategy has been applied and indicators have been sorted according to their degree of
correlation with GDP.
6.3.
The model
As previously mentioned, the indirect method of estimation of the European aggregates (i.e., using
the sum of GDP of the countries as indicator) has been chosen in building the flash estimates. This
was considered the most suitable choice, ensuring the possibility of using all the available data
transmitted by Member States and the methodological coherence with the regular quarterly national
accounts estimation procedure currently used by Eurostat. Indeed flash estimates for Germany,
Greece, Italy, the Netherlands and the United Kingdom are available within 45 days, these countries
accounting for more than 50% of the European Union GDP;
For those major countries that do not yet produce a GDP flash estimate, suitable related indicators
have been used. Such indicators were required to satisfy the following criteria:
•
availability at 40-45 after the end of the reference quarter;
•
economic meaningfulness with respect to quarterly GDP;
•
official availability: preference has been given to official statistics;
•
statistical correlation with the target variable.
The final model was specified according to both statistical and economic considerations. In
particular the criteria applied were the following:
•
statistical meaningfulness of the model;
•
simplicity of the model;
•
possible economic interpretation of the model;
•
use of all the relevant available information
•
coherence with the methodology applied for the first regular estimate of Eurostat.
The selection process showed that the best model for the flash estimation of the GDP growth rate
(constant prices and seasonally adjusted) for the euro-zone and the European Union, compiled
according to the indirect approach, is based on the available GDP flash estimates for Germany, Italy,
United Kingdom, the Netherlands and Greece (constant prices, seasonally adjusted) and other
indicators, mainly industrial production indices (seasonally adjusted), for France and Spain (GDP
flash estimates are not yet available)
9
Flash estimates and indicators based estimates have been combined in a regression model, following
an approach similar to the one usually applied in estimating the first release of the European GDP.
The approach is in line with what is already done by Eurostat for the regular estimations of the
European aggregates, except for the French and the Spanish GDP, which, in the flash estimation, are
replaced by suitable related indicators, mainly Industrial Production Index, since for both countries a
GDP estimate is not yet available at the production deadline (t+45 days). As a consequence the
construction of a single indicator obtained by summing up the countries' GDP data is not possible.
The procedure used comprises two different steps:
Ø estimation of the French and Spanish GDP growth rate in the latest quarter (quarter Q) with a
regression model based on one or more available indicators (mainly the Industrial Production
Index);
Ø Euro-zone and European Union GDP estimation in quarter Q with a regression model in the
framework of a temporal disaggregation technique. Each of the two models is based on the
relation between the GDP of the European aggregates (euro-zone and EU-15) and an indicator
obtained as follows:
G
from the first quarter of 1991 to quarter Q-1, as the sum of the GDP of all the countries
available (all MS, except for Ireland and Luxembourg);
G
The latest quarter is derived by applying the weighted average growth rate observed for
Germany, France, Italy, Spain, the Netherlands and Greece (plus UK for the EU15 model) to
the series described in the previous point. In the case of France and Spain the GDP growth
figure is estimated by Eurostat, according to the method described before.
It should be pointed out that, according to the model presented, the latest quarter’s growth rate
figure for the European aggregates is estimated mainly on the basis of an indicator referring to 6
countries (7 for the EU15), while levels up to the Q-1 quarter depend on a broader indicator. This
method has been chosen in order to use all the information available.
The model presented in this paragraph has proven the most successful (according to the reference
criteria) among all the models tested.
6.4.
Performance under real conditions
In order to assess the performance of the model, a simulation under real conditions has been done.
The flash estimate figures for GDP of Germany, Italy, the Netherlands and the UK (and only
recently Greece), usually available within 45 days from the end of the reference quarter, together
with the indicators for France and Spain have been used to produce a flash estimate of the European
GDP under real conditions.
The nowcasting performance of the models has been tested by comparing the flash estimation with
the “traditional” Eurostat estimations over nine quarters from 2000Q4 to 2002Q4, both for the eurozone and the European Union (Table 4).
In the case of Germany the figure used for the estimation of the European aggregates is the one
produced by DIW, since the official one published by the German national statistical office
(DESTATIS) is available starting from the first quarter of 2003.
10
Results are quite satisfactory: as far as quarterly growth rates are concerned (Q/Q-1), the root mean
squared error (RMSE) calculated by comparing the first Eurostat estimate (60-70 days) with the
flash estimate is 0.04% both for the euro-zone and the European Union.
The success rate in predicting an acceleration/slowdown of the growth is satisfactory: 8 out of 9
cases for both the euro-zone and the European Union (compared with the 60-70 days estimate). The
forecasting performance remains almost unchanged when results are compared with the second and
third release of Eurostat estimates (100 and 120 days).
The model is also good in capturing annual growth rates (Q/Q-4): the root mean squared error
calculated with respect to the first Eurostat estimate is around 0.10 for both European aggregates
and it becomes even smaller with respect to the second and third estimates.
Very good results are obtained also in the prediction of data in levels, especially with respect to the
first Eurostat estimates (RMSE equal to 0.05% for the euro-zone and 0.04% for the European
Union).
The close approximation between the flash and the traditional estimates can also be appreciated in
figures 1 and 2.
Table 4:
Nowcasting performances of the European flash estimate for GDP Quarterly
(Q/Q-1), annual growth rate (Q/Q-4) and levels
GDP growth rate (q/q-1) - constant prices and seasonally adjusted
Eur12
2000Q4
2001Q1
2001Q2
2001Q3
2001Q4
2002Q1
2002Q2
2002Q3
2002Q4
flash
0.68
0.53
0.13
0.13
-0.19
0.20
0.38
0.31
0.14
Eurostat estimation
differences
60-70 days 100 days 120 days 60-70 days
100 days 120 days
0.72
0.70
0.66
0.04
0.02
-0.02
0.55
0.58
0.51
0.02
0.05
-0.02
0.05
0.09
0.10
-0.08
-0.04
-0.03
0.10
0.12
0.14
-0.03
-0.01
0.01
-0.17
-0.17
-0.20
0.02
0.02
-0.01
0.22
0.31
0.31
0.02
0.11
0.11
0.34
0.39
0.39
-0.04
0.01
0.01
0.33
0.33
0.31
0.02
0.02
0.00
0.17
0.14
0.03
0.00
RMSE
0.04
0.04
0.04
GDP growth rate (q/q-1) - constant prices and seasonally adjusted
EU15
2000Q4
2001Q1
2001Q2
2001Q3
2001Q4
2002Q1
2002Q2
2002Q3
2002Q4
flash
0.60
0.48
0.15
0.19
-0.12
0.19
0.46
0.37
0.18
Eurostat estimation
differences
60-70 days 100 days 120 days 60-70 days
100 days 120 days
0.67
0.66
0.63
0.07
0.06
0.03
0.53
0.53
0.46
0.05
0.05
-0.02
0.10
0.15
0.16
-0.05
0.00
0.01
0.17
0.16
0.19
-0.02
-0.03
0.00
-0.11
-0.12
-0.14
0.01
0.00
-0.02
0.18
0.29
0.28
-0.01
0.10
0.09
0.40
0.45
0.44
-0.06
-0.01
-0.02
0.40
0.45
0.44
0.03
0.08
0.07
0.19
0.17
0.01
-0.01
RMSE
0.04
0.05
0.04
11
GDP growth rate (q/q-4) - constant prices and seasonally adjusted
Eur12
2000Q4
2001Q1
2001Q2
2001Q3
2001Q4
2002Q1
2002Q2
2002Q3
2002Q4
flash
EU15
2000Q4
2001Q1
2001Q2
2001Q3
2001Q4
2002Q1
2002Q2
2002Q3
2002Q4
flash
3.09
2.56
1.83
1.32
0.58
0.28
0.62
0.82
1.21
2.93
2.54
1.83
1.43
0.74
0.41
0.78
0.99
1.38
Eurostat estimation
differences
60-70 days 100 days 120 days 60-70 days
100 days 120 days
2.99
2.97
2.96
-0.10
-0.12
-0.13
2.51
2.58
2.50
-0.04
0.02
-0.05
1.67
1.67
1.66
-0.17
-0.16
-0.17
1.28
1.35
1.36
-0.04
0.03
0.04
0.60
0.59
0.57
0.03
0.02
0.00
0.06
0.30
0.30
-0.22
0.02
0.02
0.57
0.68
0.70
-0.06
0.06
0.08
0.78
0.83
0.87
-0.04
0.02
0.05
1.28
1.26
0.07
0.05
RMSE
0.11
0.07
0.09
Eurostat estimation
differences
60-70 days 100 days 120 days 60-70 days
100 days 120 days
2.90
2.90
2.90
-0.03
-0.03
-0.03
2.55
2.57
2.50
0.00
0.02
-0.04
1.70
1.70
1.74
-0.13
-0.12
-0.08
1.39
1.43
1.44
-0.04
0.00
0.02
0.76
0.73
0.71
0.02
-0.01
-0.03
0.20
0.45
0.44
-0.21
0.04
0.04
0.72
0.83
0.84
-0.06
0.04
0.06
0.94
1.05
1.08
-0.06
0.06
0.09
1.41
1.40
0.02
0.02
RMSE
0.09
0.05
0.05
GDP levels - constant prices and seasonally adjusted
Eur12
2000Q4
2001Q1
2001Q2
2001Q3
2001Q4
2002Q1
2002Q2
2002Q3
2002Q4
flash
1540710.6
1550121.3
1551499.3
1554370.5
1551539.3
1555096.6
1564307.6
1570577.4
1572714.4
Eurostat estimation
60-70 days 100 days
1541009.5 1540850.9
1549665.1 1550313.1
1550850.8 1551657.3
1553667.2 1554349.1
1552406.8 1552262.7
1555614.4 1558290.0
1563994.5 1565812.5
1569683.8 1570734.8
1574138.4 1574325.6
% differences (Eurostat-flash)
120 days 60-70 days
100 days 120 days
1541899.9
0.02
0.01
0.08
1549497.5
-0.03
0.01
-0.04
1552402.8
-0.04
0.01
0.06
1554466.0
-0.05
0.00
0.01
1552002.2
0.06
0.05
0.03
1558426.4
0.03
0.21
0.21
1565748.1
-0.02
0.10
0.09
1570481.8
-0.06
0.01
-0.01
0.09
0.10
RMSE
0.05
0.08
0.09
EU15
2000Q4
2001Q1
2001Q2
2001Q3
2001Q4
2002Q1
2002Q2
2002Q3
2002Q4
flash
1882141.1
1893801.0
1896174.9
1903832.4
1902062.2
1905346.6
1917642.0
1925944.7
1933007.1
Eurostat estimation
60-70 days 100 days
1883675.3 1883567.8
1894108.3 1894204.8
1895740.1 1899469.6
1903235.2 1904051.1
1902886.8 1902144.0
1905376.9 1908695.9
1916932.5 1918914.0
1924734.2 1929631.8
1933629.7 1935233.6
% differences (Eurostat-flash)
120 days 60-70 days
100 days 120 days
1884705.8
0.08
0.08
0.14
1893389.1
0.02
0.02
-0.02
1900226.1
-0.02
0.17
0.21
1904378.9
-0.03
0.01
0.03
1901856.4
0.04
0.00
-0.01
1908819.2
0.00
0.18
0.18
1918807.3
-0.04
0.07
0.06
1929470.4
-0.06
0.19
0.18
0.03
0.12
RMSE
0.04
0.12
0.13
12
6.5.
Comparison with naïve models
In order to evaluate the forecasting performances of the model, the following three naïve models
were also used as benchmark and their nowcasting accuracy compared with that of the regression
model described above:
1. growth rate equal to the previous quarter
2. growth rate equal to the average of the previous 4 quarters
3. autoregressive method, with an automatic selection order
The three models all perform worse than the regression model: their RMSE calculated on the period
ranging from 2000Q4 to 2002Q4 is always higher than 0.2%, as can be seen in Table 5, and not
comparable to the one of the temporal disaggregation model (0.04% bor both the European
Aggregates).
Table 5: Naïve methods versus first Eurostat estimate, RMSE (out of the sample
2000Q4-2002Q4
random walk
EUR12
EU15
0.24
0.21
4 quarters
average
0.30
0.29
13
autoregressive
0.31
0.28
Figure 1:
Flash estimate vs. first estimate for the euro-zone growth rate (q/q-1),
seasonally adjusted and in constant prices.
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
-0.10
-0.20
-0.30
2000Q4
2001Q1
2001Q2
2001Q3
2001Q4
flash
Figure 2:
2002Q1
2002Q2
2002Q3
2002Q4
60-70 days
Flash estimates vs. first estimate for the European Union growth rate
(q/q-1), seasonally adjusted and in constant prices.
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
-0.10
-0.20
2000Q4
2001Q1
2001Q2
2001Q3
2001Q4
flash
6.6.
2002Q1
2002Q2
2002Q3
2002Q4
60-70 days
Lack of basic information
The target deadline for the release of the flash estimate of GDP is 45-48 days. The model proposed
above relies, in particular, on the availability of flash estimates of GDP for the major European
countries (Germany, Italy and the United Kigdom) as well as of French and Spanish indicators.
14
Occasionally these variables might be not available in time for the fixed deadline of the European
flash estimate. In order to ensure a continuity of publication at a pre-determined date and to avoid
further delays, the flash methodology foresees alternative models for estimating the quarterly
growth of the European GDP.
Indeed, the approach is the same as described before except for the available quarterly indicators.
Italian and German flash estimates can be replaced by related short-term indicators appropriately
selected (e.g., industrial production index, retail trade, …). If these indicators (usually monthly
based) are available only for two months over three of the quarter, a forecast for the last month is
calculated.
The test done during the real period showed that these alternative models performed quite well, but
worse than the model presented in the previous paragraphs. Anyway, Eurostat will regularly assess
all possible models.
6.7.
Validation
The results derived from the available information and the application of the described methodology
are validated according to three dimensions:
•
statistical validation: all the classical statistical tests and analysis on the results of the model
estimation are evaluated. In particular, the selection of the indicators is performed anew for each
flash estimate (the results in the test period showed stability in the relevant indicators), the
model is re-estimated each quarter and the results evaluated;
•
economic validation: the results obtained are compared to the available information on the
evolution of the European and Member States economies and the plausibility of the results
assessed. Official forecasts of the European GDP growth (published by DG ECFIN) are used as
a benchmark;
•
accounting validation: at present, only the coherence with the annual series is assessed. When
the flash project will enter in its second phase (flash estimate of the main output and expenditure
components) the accounting relationships among the components will be considered too.
6.8.
Publication strategy
The dissemination of the results of the flash estimates will be done through a specific news release.
The news release will be part of the "flash estimates" news release collection of Eurostat. It will
contain information about GDP growth during the reference quarter compared to the previous
quarter and the same quarter of the previous year. Growth rates will refer to constant prices and
seasonally adjusted figures. A methodological note will complete the information contained in the
news release.
7.
Conclusions
The flash estimate methodology is an evolving methodology. As mentioned in the previous sections,
the flash estimate of the growth of quarterly European GDP is the first step of the flash approach.
The flash estimate of the main components of the output and expenditure side and the publication of
the GDP flash estimate at 30 days are the next targets of the Eurostat flash project.
The methodology is, anyway, part of the general compilation process of quarterly accounts for the
euro-zone and the European Union. For this reason, all the methodological improvements foreseen
for the quarterly accounts compilation will be analysed in the flash context and their impact
evaluated.
15
Annex 1
Revisions of GDP growth rates
Table A.1:
Euro-zone, GDP, growth rates on the previous quarter, constant prices, seasonal adjusted, revisions
16
Table A.1:
European Union, GDP, growth rates on the previous quarter, constant prices, seasonal adjusted, revisions
17
Table A.3:
United States, GDP, growth rates on the previous quarter, constant prices, seasonal adjusted, revisions
18