An integrated system for euro area and member states turning points - - PowerPoint PPT Presentation

An integrated system for euro area and member states turning points detection

By: Gian Luigi Mazzi, Monica Billio and Laurent Ferrara

Brussels, 11 March 2015

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

Outline

• Introduction
• Choice of the reference cycle
• Methodological aspects
• Constructing composite indicators for turning points

detection

• Empirical results
• Outcome summary: comments
• Comments on latest results of coincident indicators
• Conclusion and future activities

Introduction (I)

• Accurate monitoring cyclical fluctuations is a key

component for short term macroeconomic analysis and forecasts

• Cyclical information is a crucial requirement for policy

makers, macroeconomic analysts, forecasters and analysts

• Timely and reliable turning point detection is the core of

modern business cycle analysis

• Since turning points are quite rare events and typically

appearing as discontinuities or breaks in the series, they are not easily estimated

• Non-linear modelling as the most promising approach for

turning points

• Binary regressions
• Univariate and multivariate non-linear time-series models

Introduction (II)

• In-depth theoretical and empirical investigation of

alternative non-linear modelling approaches

• Focusing on non-linear time-series models
• Higher flexibility in comparison with other non-linear

techniques

• Markov-switching models considered the most reliable tool

for turning points detection

• Outcome of an empirical comparison, especially with SETAR

models (Billio, Ferrara, Guegan, Mazzi, (2014))

• First attempt to compile euro area turning point indicators

started in 2006

• Ferrara, Mazzi (2008)

Choice of the reference cycle (I)

• Classical Business cycle (Burns and Mitchell definition)
• Very relevant for detecting recessions
• Not very informative during usually quite long expansion

phases

• Growth cycle (Output gap)
• Very relevant to understand the position with respect to the

potential output

• More informative also during the expansion phases of business

cycle

• Anticipating business cycle peaks
• Unable to detect the start and the end of recessions

Choice of the reference cycle (II)

• Growth rate cycle (Acceleration cycle )
• Highest number of fluctuations
• High degree of volatility
• Anticipating growth cycle peaks and business cycle troughs
• Jointly monitoring several reference cycles (Anas, Ferrara

2004)

• Growth cycle and Business cycle (ABCD sequence)
• Also including Acceleration cycle (αABβCD sequence)
• Approach retained by Eurostat

Methodological aspects (I)

• Multivariate Markov-Switching models to jointly estimate a

pair of probabilistic coincident indicators of the classical business cycle and growth cycle

• Euro Area as a whole (direct indicator)
• Largest Member Countries
• Unfeasible jointly modelling also of acceleration cycle for mathematical reasons
• Each pair satisfies, by construction, the ABCD approach
• Comparison of a huge number of alternative coincident

indicators obtained by combining a variety of

• model specifications
• number of regimes
• endogenous variables
• rules to associate regimes and economic cycles

Methodological aspects (II)

• Models only based on empirical results without any economic

hypothesis or restriction

• The accuracy of each pair of coincident indicators in locating

economic fluctuations measured with respect to a benchmark

• namely the historical turning points dating chronology developed by Eurostat
• For the direct EA indicators and for each Member Country, a pair
• f coincident indicators was identified
• ne expressing the probabilities of a recession of the classical cycle
• ne expressing the probabilities of a slowdown of the growth cycle
• Choice of each pair of indicators based on the Brier's score (QPS)

and the Concordance index

Methodological aspects (III)

• In addition, a pair of coincident indicators for the euro area’s

classical and growth cycles obtained as a weighted average of Member States ones was developed

• The considered Member Countries account for almost 90% of the Euro area GDP
• The indirect coincident indicators can shed light on the economic

fluctuations across the euro area

• They can be the basis for computing in real-time the degree of

diffusion and synchronisation of a given economic cyclical phase among member states

Constructing composite indicators for turning points detection (I)

• Step 1: middle-size dataset mainly based on PEEIs and
• pinion surveys data
• Performing most appropriate data transformation to highlight

cyclical movements

• Step 2: variable selection based on the ability of timely and

precisely detecting turning points within a real-time simulation exercise against the non-parametric historical turning point dating

Constructing composite indicators for turning points detection (II)

• Step 3: selected variables are used to identify and estimate

a number of autoregressive Markov-Switching models (MS- VAR) MSIH (K) – VAR (L)

Where H indicates the presence of heteroskedasticity, (K) is the number of regimes and (L) the number of lags of the autoregressive part

• Step 3 remark : dealing simultaneously with growth cycle and

business cycle implies a number of regimes not smaller than 4 , while the heteroskedastic part can or cannot be present depending

• n the degree of asymmetry of fluctuations

Constructing composite indicators for turning points detection (III)

• Step 4: from step 3, N best fitting models are identified,

each of them producing a pair of coincident indicators: MS-VAR GCCI (j) and MS-VAR BCCI (j) j=1 …n indicates the jth

• Step 4 remark 1: each composite indicator is defined between 0

and 1, and can be viewed as a composite probability of being in a recessionary phase for the MS-VAR BCCI (j) and in a slowdown phase for the MS-VAR GCCI (j)

• Recession/slowdown regions defined on the basis of a threshold, usually

equal to 0,5

• Step 4 remark 2: MS-VAR BCCI (j) > 0.5 = recession

MS-VAR GCCI (j) > 0.5 = slowdown By construction, MS-VAR BCCI (j) > 0.5  MS-VAR GCCI (j) > 0.5

• ABCD sequence always fulfilled

Constructing composite indicators for turning points detection (IV)

• Step 5: within a real-time simulation exercise, the N pair of

composite coincident indicators is compared with the non- parametric historical turning point dating

Constructing composite indicators for turning points detection (V)

• Step 6: identification of the best performing pair of

coincident indicators based on the outcome of step 5 using the following criteria:

• Maximisation of the Concordance Index
• Minimisation of the Brier's Score (QPS)
• Minimisation of type-2 errors: detection of false cycles
• Minimisation of type-1 errors: missing cycles
• Step 6 remark: due to the trade-off between type-2 and type-1

errors, the simultaneous minimisation of both is unachievable

• A conservative approach suggest to privilege the minimisation of type-2

errors: detection of false cycles

Empirical results

Model Summary for the EA direct

Country Model Recessions Slowdowns

Variables (differentiation order)

IPI UR NPCR INDEA7 EA MSIH(4)-VAR(0) R1 R1+R2 6 1 4+ MA(6) 1

Euro Area ACCI (direct)

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Probability of Being in a Deceleration of the Acceleration Cycle

Acceleration Cycle Reference Chronology Provisional Dating Chronology Ending Date of Provisional Chronology ACCI 0.5 Threshold

Euro Area MS-VAR GCCI & BCCI (direct)

Models Summary for the major MS

Country Model Recessions Slowdowns

Variables (differentiation order)

IPI UR BUIL IND CONS RETA Belgium MSI(4)-VAR(0) R1 R1+R2 6 3 6 3

• 3

France MSIH(4)-VAR(0) R1 R1+R2 6 1 3

• 1

12 Germany MSIH(4)-VAR(0) R1 R1+R2 3 3 3

• 6

12 Italy MSIH(5)-VAR(0) R1 R1+R2 3 3

• 12

12 3 Netherlands MSIH(4)-VAR(0) R1 R1+R2 12

• 6

3 1 1 Portugal MSI(5)-VAR(0) R1+R2 R1+R2+R3 6

• 3

3 12 1 Spain MSIH(4)-VAR(0) R1 R1+R2 12 12 3 6 12

Growth Cycle Outcome Summary

Country Slowdown missed False slowdown Average delay in locating Slowdowns start (in months) Accuracy in signalling slowdown Brier’s Score (QPS) Concordance Index Belgium 1 (2005) 0.7 0.16 0.83 France 1 (1998) 3.2 0.16 0.82 Germany 1 (1998) 2.5 0.20 0.79 Italy 4.3 0.22 0.77 Netherlands 1 (1995 – 1997) 2.0 0.18 0.80 Portugal 3 0.6 0.18 0.80 Spain 1 (1997-1998) 4.3 0.27 0.72 EA direct 1 (2004-2005) 2.0 0.15 0.83 EA indirect 1 (1998) 3.0 0.10 0.87

Business Cycle Outcome Summary

Country Recessions missed False recessions Average delay in locating peaks (in months) Accuracy in signalling recessions Brier’s Score (QPS) Concordance Index Belgium 2 (1998 - 2000) 6 0.15 0.84 France 1 (2012) 2.5 0.06 0.94 Germany 1 (2001 - 2002) 3.4 0.08 0.92 Italy 1 (2001) 2.8 0.12 0.87 Netherlands 3.5 0.12 0.88 Portugal 4.3 0.17 0.82 Spain 1.3 0.05 0.94 EA direct 2.3 0.06 0.94 EA indirect 1 (2011-2013) 2.5 0.06 0.90

Outcome summary: comments (I)

• Generally good concordance between historical dating

chronologies and turning point coincident indicators

• Few discrepancies emerged in the latest periods
• Ongoing revision process of macro-economic variables and

different vintages

• At the euro area level both direct and indirect indicators

perform similarly at least until 2011

• Indirect BCCI missed the last euro area recession while the direct
• ne correctly detected it
• For the GCCI one missed cycle observed for the indirect indicator

while one false signal appears for the direct one

Outcome summary: comments (II)

• After 2011, discrepancies appeared both for business cycle and

growth cycle

• Idiosynchratic behaviour of countries
• Lack of synchronisation and diffusion of turning points
• Direct euro area indicators more in line with historical turning

points dating chronologies

Outcome summary: comments (III)

• Both indicators developed for France are performing very well,
• nly with the exception of a false signal recorded by the GCCI
• Both for Germany and the Netherlands, the BCCI performed

very well while there are room for improvement concerning the GCCI

• Improvements required for GCCI of Spain and Portugal and for

the BCCI of Portugal

• Reducing the number of false signals
• Improving timeliness

Euro Area MS-VAR GCCI & BCCI (indirect)

2

Probability of Being in a Slowdown / Recession

Growth Cycle Reference Chronology GC Provisional Chronology Ending Date of Provisional Chronology Business Cycle Reference Chronology BC Provisional Chronology Indirect MS-VAR GCCI Indirect MS-VAR BCCI 0.5 Threshold

Euro Area

Direct

• vs. Indirect Approach

Peak Trough Peak Trough Peak Trough Peak Growth Cycle Provisional Dating 2008 Q1 2009 Q3

• 2011 Q3

2013 Q2 Direct MS-VAR GCCI

• Dec. 2007
• Sep. 2009
• May 2011

Indirect MS-VAR GCCI

• Nov. 2007

July 2009

• July 2011
• Apr. 2013

Business Cycle Provisional Dating 2008 Q1 2009 Q2

• 2011 Q3

2013 Q1 Direct MS-VAR BCCI

• Apr. 2008
• Sep. 2009
• July 2011

May 2013 Indirect MS-VAR BCCI June 2008 June 2009

• Acceleration

Cycle Provisional Dating 2006 Q2 2009 Q1 2010 Q2 2012 Q4 Direct ACCI June 2006

• Mar. 2009
• Dec. 2010
• Dec. 2011
• Mar. 2012
• Oct. 2012
• Dec. 2013

Indirect ACCI

Eurostat

Peak T rough Peak T rough Peak T rough Peak T rough Peak T rough Peak T rough Germany Growth Cycle

04/01 08/03 02/04 05/05 05/08 07/ 09 10/11 03/13

Business Cycle

11/ 02 04/03 11/08 06/09

France Growth Cycle

11/00 08/03 09/07 08/09 08/11 08/13

Business Cycle

07/08 05/09

Italy Growth Cycle

10/01 08/03 12/07 06/09 07/11 05/13

Business Cycle

01/03 05/03 12/07 04/09 08/11 04/13

Spain Growth Cycle

04/01 10/03 09/07 11/09 07/10 08/13

Business Cycle

02/ 08 11/09 07/11 04/13

the Netherlands Growth Cycle

02/01 10/03 06/08 12/09 03/11 02/13

Business Cycle

10/08 12/09 03/11 10/11

Belgium Growth Cycle

08/00 08/03 02/05 09/05 09/07 09/09 05/11

Business Cycle

10/01 12/01 09/08 04/09 05/12 06/12

Portugal Growth Cycle

07/98 05/03 10/04 09/05 01/06 07/06 07/07 05/09 07/10 07/13

Business Cycle

06/02 05/03 07/05 09/05 06/08 05/09 10/10 03/12

Comments on latest results of coincident indicators

• Based on the direct approach euro area exited the recession

phase in May 2013

• Slowdown phase still persisting
• The 2011-2013 recession didn't affect France and Germany

and only marginally the Netherlands

• The 2011-2013 slowdown was spread over all member

countries of the euro area

• Belgium is the only country having not yet exited the slowdown

phase

Conclusion and future activities

• Very satisfactory results obtained in constructing coincident

indicators for timely and reliable detection of turning points for euro area and some member states

• Innovative approach for jointly monitoring business and

growth cycle within a multivariate non-linear framework

• More detailed picture of the cyclical situation
• Further improvements of some coincident indicators for

member states

• Developing new coincident indicators for the remaining euro

area countries and the UK