Wo r k i n g Pa p e r S e r i e s
N o 9 0 0 / M ay 2 0 0 8
Forecasting inflation
and tracking
monetary policy in
the euro area
does national
information help?
by Riccardo Cristadoro,
Fabrizio Venditti
and Giuseppe Saporito
WO R K I N G PA P E R S E R I E S
N O 9 0 0 / M AY 20 0 8
FORECASTING INFLATION AND
TRACKING MONETARY POLICY
IN THE EURO AREA
DOES NATIONAL
INFORMATION HELP? 1
by Riccardo Cristadoro 2, Fabrizio Venditti
and Giuseppe Saporito
In 2008 all ECB
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taken from the
10 banknote.
This paper can be downloaded without charge from
http://www.ecb.europa.eu or from the Social Science Research Network
electronic library at http://ssrn.com/abstract_id=1126670.
1 The views expressed in this paper are solely the responsibility of the author and should not be interpreted as reflecting the views of the ECB
or Banca d’Italia.
2 All authors: Banca d’Italia, Research Department, via Nazionale 91, I – 00184 Rome, Italy; email: riccardo.cristadoro@bancaditalia.it,
fabrizio.venditti@bancaditalia.it; giuseppe.saporito@bancaditalia.it (Cagliari Branch at Banca d’Italia).
© European Central Bank, 2008
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ISSN 1561-0810 (print)
ISSN 1725-2806 (online)
CONTENTS
Abstract
4
Non-technical Summary
5
1 Introduction
7
2 Data and methodology
2.1 Data
2.1.1 Data transformation
2.1.2 Data Realignment
2.2 The econometric methodology
2.2.1 Direct and indirect core inflation
measures
2.2.2 Smooth factors and core infaltion
measures
2.2.3 Core inflation and forecasting
8
8
9
9
9
3 Dynamic Correlations and stylized facts
4 Forecasting euro area inflation: does national
information help?
4.1 Alternative GDFM forecasting exercises:
targeted predictors.
4.1.1 Commonality criterion
4.1.2 Threshold criterion
4.2 Results
4.2.1 Germany
4.2.2 France
4.2.3 Italy
4.2.4 Euro area
4.2.5 Does national information help in
forcasting euro area inflation
4.3 Comments
11
11
12
12
14
15
15
15
16
17
17
17
17
18
18
5 The ECB reaction function: does national
information matter?
5.1 The empirical strategy
5.2 Data issues
18
19
20
6 Conclusions
22
References
23
Tables and figures
25
European Central Bank Working Paper Series
37
ECB
Working Paper Series No 900
May 2008
3
Abstract
The ECB objective is set in terms of year on year growth rate of the Euro area HICP.
Nonetheless, a good deal of attention is given to national data by market analysts when they
try to anticipate monetary policy moves. In this paper we use the Generalized Dynamic Factor
model to develop a set of core inflation indicators that, combining national data with area
wide information, allow us to answer two related questions. The first is whether country
specific data actually bear any relevance for the future path of area wide price growth, over
and above that already contained in area wide data. The second is whether in order to track
ECB monetary policy decisions it is useful to take into account national information and not
only area wide statistics. In both cases our findings point to the conclusion that, once area
wide information is properly taken into account, there is little to be gained from considering
national idiosyncratic developments.
Keywords: forecasting, dynamic factor model, inflation, Taylor rule, monetary policy
JEL Classification: C25, E37, E52
4
ECB
Working Paper Series No 900
May 2008
Non-technical summary
The ECB monetary policy objective of maintaining price stability in the euro area is
defined in terms of the year on year rate of growth of the area wide Harmonized Index
of Consumer Prices (HICP) over the medium run. Given the forward-looking nature
of its objective, predicting inflation emerges as a crucial task both for the Central
Bank, whose interest rates decisions respond to changes in expected price growth, and
for analysts that want to track the ECB moves.
An important issue that naturally arises in forecasting euro area inflation is how to
deal with the availability of both aggregate and national information in an economic
area where a centralized monetary policy coexists with a decentralized fiscal policy
and segmented labour markets. In such a context looking at national data could in
principle provide some additional information on future inflation, over and above that
contained in area wide data.
The aim of this paper is to assess the value added of national information to forecast
euro area inflation and to track euro area interest rates. To gauge the predictive
content of national variables we propose a set of core inflation indicators, computed
using the Generalized Dynamic Factor Model, that combine both national and area
wide data to predict inflation at different horizons. As a corollary to this approach, we
also explore the issue recently raised in the related literature of whether “more data”
in factor models is always “better”. To do so we report a careful analysis of different
data-reduction methods and assess the gains in forecast accuracy arising from them.
To assess whether national information is relevant for tracking monetary policy we
proceed in two steps.
First, we compare the forecasting performance of our core indicators with that of
univariate models built with alternative predictors. In this context we also consider the
potential gains of using national information as summarized by national core indexes
or an area wide core measure estimated on a data set that does not include only area
wide statistics.
Second, we check whether one can “track” ECB monetary policy decision using the
euro core index and the output gap, in a simple Taylor rule framework, and test
whether national information helps in rationalizing interest rates developments.
The main results of our analysis can be summarized as follows.
x
Core inflation indexes based on common factors estimated on large datasets
have good forecasting properties both for national and area wide inflation
rates. Consistently with the ECB monetary policy objective we define our
inflation forecast target as the twelve month rate of change of the Harmonized
Index of Consumer Prices. When compared with simple univariate models or
with simple regression models that use variables routinely scrutinized by the
ECB Governing Council in their Monetary and Economic assessment, our
core inflation indexes almost always provide the best signals for future
inflation at the horizons relevant for monetary policy. The prediction of euro
ECB
Working Paper Series No 900
May 2008
5
x
x
6
area inflation does not improve when including national data in the
information set. Furthermore the use of different selection criteria does not
generally lead to more precise forecast than those obtained estimating the
common factors on the full information set.
The good forecasting performance of our core indicators allows us to consider
them as natural candidates for analyzing interest rate behaviour in the euro
area. We find that the core inflation index estimated on area wide data,
together with a survey based output gap measure, contributes significantly to
tracking short term interest rates movements. The use of national information,
proxied by our national core inflation indexes, on the other hand, does not add
any significant explanatory power to the baseline Taylor rule regression.
We conclude that the area wide core inflation index appropriately summarizes
all the relevant information, both for forecasting medium term inflation
developments and for tracking the ECB monetary policy. Conditioning on area
wide data, the use of national information turns out to be irrelevant for both
aims.
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ECB
Working Paper Series No 900
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Working Paper Series No 900
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Working Paper Series No 900
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Working Paper Series No 900
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Working Paper Series No 900
May 2008
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Working Paper Series No 900
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Working Paper Series No 900
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32
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Working Paper Series No 900
May 2008
All dataset
Germ any
0.7
0.7
0.6
0.6
0.5
0.5
0.4
0.4
0.3
0.3
0.2
0.2
0.1
0.1
0
0
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1
1.5
2
frequency
2.5
3
3.5
0
0
0.5
1
Italy
1.5
2
frequency
2.5
3
3.5
2.5
3
3.5
France
0.7
0.8
0.7
0.6
0.6
0.5
0.5
0.4
0.4
0.3
0.3
0.2
0.2
0.1
0
0.1
0
0.5
1
1.5
2
frequency
2.5
3
3.5
0
0
0.5
1
1.5
2
frequency
"?=KH; .F;9JH7B I>7F; E< J>; RHIJ ;?=>J :OD7C?9 ;?=;DL7BK;I
ECB
Working Paper Series No 900
May 2008
33
34
ECB
Working Paper Series No 900
May 2008
1995
1995
2000
Euro HICP - year on year growth rate
2000
2005
2005
HICP
CORE
2005
2005
2010
1
2000
1.5
0
1990
0
1990
1
3
2
2
0.5
5
4
2.5
1995
6
France HICP - year on year growth rate
2000
3
1995
-20
1990
-10
-5
-10
1990
0
0
HICP
CORE
10
0
1990
1
2
3
4
5
6
5
2010
2010
2010
-20
1990
-10
0
10
20
30
40
20
France HICP and CORE - annualized monthly growth rates
HICP
CORE
HICP
CORE
Euro HICP and CORE - annualized monthly growth rates
10
0
1990
1
2
3
4
-10
1990
-5
0
5
10
2000
1995
2000
Germany HICP - year on year growth rate
1995
2005
2005
HICP
CORE
HICP
CORE
1995
1995
2000
Italy HICP - year on year growth rate
2000
2005
2005
Italy HICP and CORE - annualized monthly growth rates
HICP
CORE
HICP
CORE
Germany HICP and CORE - annualized monthly growth rates
2010
2010
2010
2010
Interest rates in the euro area
6
MRO
3-month Euribor
5
4
3
2
1999
2000
2001
2002
2003
2004
2005
2006
2005
2006
Survey output gap in the euro area
200
100
0
-100
-200
1999
2000
2001
2002
2003
2004
"?=KH; )EDJ> !KH?8EH )7?D -;RD?D9?D= +F;H7J?ED H7J; )-+ 7D: !0 !9EDEC?9 .;DJ?
C;DJ %D:?97JEH
ECB
Working Paper Series No 900
May 2008
35
Correlation between the Survey output gap at time t and the 3-month-Euribor at time t+h
0.8
0.6
0.4
0.2
0
0
1
2
3
4
5
0
1
2
3
4
5
6 7 8 9 10 11 12
h
Correlation between the Survey output gap at time t and the y/y inflation rate at time t+h
0.6
0.4
0.2
0
-0.2
6
h
7
8
9 10 11 12
"?=KH; OD7C?9 9HEII
9EHH;B7J?EDI 8;JM;;D J>; !0 !9EDEC?9 .;DJ?C;DJ %D:?97JEH 7D: H;
IF;9J?L;BO J>; )EDJ> !KH?8EH 7D: J>; O;7H ED O;7H ;KHE 7H;7 ?DS7J?ED H7J;
36
ECB
Working Paper Series No 900
May 2008
European Central Bank Working Paper Series
For a complete list of Working Papers published by the ECB, please visit the ECB’s website
(http://www.ecb.europa.eu).
862 “Stock market volatility and learning” by K. Adam, A. Marcet and J. P. Nicolini, February 2008.
863 “Population ageing and public pension reforms in a small open economy” by C. Nickel, P. Rother
and A. Theophilopoulou, February 2008.
864 “Macroeconomic rates of return of public and private investment: crowding-in and crowding-out effects”
by A. Afonso and M. St. Aubyn, February 2008.
865 “Explaining the Great Moderation: it is not the shocks” by D. Giannone, M. Lenza and L. Reichlin,
February 2008.
866 “VAR analysis and the Great Moderation” by L. Benati and P. Surico, February 2008.
867 “Do monetary indicators lead euro area inflation?” by B. Hofmann, February 2008.
868 “Purdah: on the rationale for central bank silence around policy meetings” by M. Ehrmann and M. Fratzscher,
February 2008.
869 “The reserve fulfilment path of euro area commercial banks: empirical testing using panel data” by N. Cassola,
February 2008.
870 “Risk management in action: robust monetary policy rules under structured uncertainty” by P. Levine,
P. McAdam, J. Pearlman and R. Pierse, February 2008.
871 “The impact of capital flows on domestic investment in transition economies” by E. Mileva, February 2008.
872 “Why do Europeans work part-time? A cross-country panel analysis” by H. Buddelmeyer, G. Mourre
and M. Ward, February 2008.
873 “The Feldstein-Horioka fact” by D. Giannone and M. Lenza, February 2008.
874 “How arbitrage-free is the Nelson-Siegel model?” by L. Coroneo, K. Nyholm and R. Vidova-Koleva,
February 2008.
875 “Global macro-financial shocks and expected default frequencies in the euro area” by O. Castrén, S. Dées
and F. Zaher, February 2008.
876 “Are sectoral stock prices useful for predicting euro area GDP?” by M. Andersson and A. D’Agostino,
February 2008.
877 “What are the effects of fiscal policy shocks? A VAR-based comparative analysis” by D. Caldara and C. Kamps,
March 2008.
878 “Nominal and real interest rates during an optimal disinflation in New Keynesian models” by M. Hagedorn,
March 2008.
879 “Government risk premiums in the bond market: EMU and Canada” by L. Schuknecht, J. von Hagen
and G. Wolswijk, March 2008.
880 “On policy interactions among nations: when do cooperation and commitment matter?” by H. Kempf
and L. von Thadden, March 2008.
ECB
Working Paper Series No 900
May 2008
37
881 “Imperfect predictability and mutual fund dynamics: how managers use predictors in changing systematic risk”
by G. Amisano and R. Savona, March 2008.
882 “Forecasting world trade: direct versus “bottom-up” approaches” by M. Burgert and S. Dées, March 2008.
883 “Assessing the benefits of international portfolio diversification in bonds and stocks” by R. A. De Santis
and L. Sarno, March 2008.
884 “A quantitative perspective on optimal monetary policy cooperation between the US and the euro area”
by S. Adjemian, M. Darracq Pariès and F. Smets, March 2008.
885 “Impact of bank competition on the interest rate pass-through in the euro area” by M. van Leuvensteijn,
C. Kok Sørensen, J. A. Bikker and A. A. R. J. M. van Rixtel, March 2008.
886 “International evidence on sticky consumption growth” by C. D. Carroll, J. Slacalek and M. Sommer,
March 2008.
887 “Labor supply after transition: evidence from the Czech Republic” by A. Bičáková, J. Slacalek
and M. Slavík, March 2008.
888 “House prices, money, credit and the macroeconomy” by C. Goodhart and B. Hofmann, April 2008.
889 “Credit and the natural rate of interest” by F. De Fiore and O. Tristani, April 2008.
890 “Globalisation, domestic inflation and global output gaps: evidence from the euro area”
by A. Calza, April 2008.
891 “House prices and the stance of monetary policy” by M. Jarociński and F. Smets, April 2008.
892 “Identification of New Keynesian Phillips Curves from a global perspective” by S. Dées, M. H. Pesaran,
L. V. Smith and R. P. Smith, April 2008.
893 “Sticky wages: evidence from quarterly microeconomic data” by T. Heckel, H. Le Bihan and M. Montornès,
May 2008.
894 “The role of country-specific trade and survey data in forecasting euro area manufacturing production:
perspective from large panel factor models” by M. Darracq Pariès and L. Maurin, May 2008.
895 “On the empirical evidence of the intertemporal current account model for the euro area countries”
by M. Ca’Zorzi and M. Rubaszek, May 2008.
896 “The Maastricht convergence criteria and optimal monetary policy for the EMU accession countries”
by A. Lipińska, April 2008.
897 “DSGE-modelling when agents are imperfectly informed” by P. De Grauwe, April 2008.
898 “Central bank communication and monetary policy: a survey of theory and evidence” by A. S. Blinder,
M. Ehrmann, M. Fratzscher, J. De Haan and D.-J. Jansen, April 2008.
899 “Robust monetary rules under unstructured and structured model uncertainty” by P. Levine and J. Pearlman,
April 2008.
900 “Forecasting inflation and tracking monetary policy in the euro area: does national information help?”
by R. Cristadoro, F. Venditti and G. Saporito, May 2008.
38
ECB
Working Paper Series No 900
May 2008