Download presentation

Presentation is loading. Please wait.

Published byAmber Saunders Modified over 2 years ago

1
Eurostat – Unit C4 Key indicators for the European policies EU Workshop on Recent Developments in Business and Consumer Surveys Hotel Bedford, , Rue du Midi, 1000 Brussels November 2012

2
Eurostat – Unit C4 Key indicators for European policies On-going international work and prospects in the field of BCS A statistical overview of the economic situation in the euro area By Gian Luigi Mazzi Filippo Moauro Rosa Ruggeri-Cannata

3
Eurostat – Unit C4 Key indicators for European policies Outline Introduction PEEIs' nowcasts: a bridge modelling approach real time simulation exercise PEEIs' nowcasts: an unobserved component based approach performance of EuroMIND based on survey data The system of turning point detection Real time monitoring and the early warning system Conclusions

4
Background PEEIs: a tool for short term economic monitoring based on official statistics Picture for the euro area rather incomplete for few monthly data - quarterly GDP only for the second quarter - employment provided with delay Updated picture for the euro area - combining official statistics and econometric techniques Eurostat – Unit C4 Key indicators for European policies

5
Most recent evolution of main PEEIs Eurostat – Unit C4 Key indicators for European policies 2011q22011q32011q42012q12012q22012q3 GDP% (Q/Q-1) % (Q/Q-4) Employment% (Q/Q-1) % (Q/Q-4) m52012 m62012m72012m82012m92012m10 HICP% (M/M-1) % (M/M-12) PPI% (M/M-1) % (M/M-12) IPI% (M/M-1) % (M/M-12) Unemployment rate % ESIIndex Note: forecasts (in red) obtained by a bridge modelling approach

6
GDP growth by country Eurostat – Unit C4 Key indicators for European policies 2011q22011q32011q42012q12012q22012q3 Belgium Netherlands Spain Italy France Germany Euro area Note: forecasts (in red) obtained by a bridge modelling approach

7
Eurostat – Unit C4 Key indicators for European policies Quarterly GDP of the euro area

8
Some comments: the euro area in the first 3 quarters of negative signs of GDP growth in last 4 quarters Persisting slowdown of employment accompanied by a rising unemployment rate Pretty stable inflation Negative perception of the economic situation by producers and consumers as shown by the ESI Eurostat – Unit C4 Key indicators for European policies

9
Some comments: economic growth at country level Germany shows a recovery after the negative result in 2011Q4 The growth in France is rather weak Belgium shows a stop and go development in last quarters. Netherlands shows a positive growth in all quarters of 2012 after two consecutive negative quarters. Italy and Spain continue in their negative trend Trend in France is flat and never negative in last quarters Eurostat – Unit C4 Key indicators for European policies

10
PEEIs' nowcasts: the Eurostat BM approach (1) y t is the dependent variable observed over the sample period t = 1, …, T taken in its first (log-) differences, with Δ the difference operator such that Δy t = y t - y t-1 ; c is an intercept; α i and β jl are regression coefficients respectively related to Δy t-l and to a set of k predictors x jt, j=1, …, k, ; u t is a mean zero disturbance with variance σ 2. general specification adaptable to the case of cointegration among implied variables imposing suitable coefficient restrictions error correction (EC) terms.

11
Eurostat – Unit C4 Key indicators for European policies PEEIs' nowcasts: the Eurostat BM approach (2) BM approach in 3 steps: a)x it are projected over a forecast horizon by means of a univariate time series technique; b)the indicator is temporal aggregated at the same time span of the target variable; c)parameter estimation of model (1) is carried out to determine the coincident indicator over the full sample period t=1,2, …, T. Variable selection is carried through the least angle regression (LARS) algorithm by Bai and Ng (2008) able to selecting a set of targeted predictors to obtain the most accurate nowcasts.

12
Eurostat – Unit C4 Key indicators for European policies BM specification: GDP, Employment and IPI Δln(GDP t )Δln (Empl t )Δln(IPI t ) GDPln(y t-1 )-- Employment-ln(y t-1 )- IPIΔln(x t )ln(x t-1 )Δln(x t-1 ), Δln(x t-2 ) Retail Salesln(x t-1 ), Δln(x t )-- Exportsln(x t-1 ), Δln(x t )-- Construction outputΔln(x t )-- Unemployment rateΔln(x t ) - Exchange rate euro/$Δln(x t-1 ), Δln(x t-2 )-- Business and consumer surveys Present business situationΔ(x t )-- Major purchases over next 12 monthsx t-1 -- Industrial confidence-Δ(x t ) x t, Δx t-h ·|Δx t-h | with h=1,2,3 Construction confidence-Δ(x t-1 )- Construction opinion on activity-Δ(x t )- Construction employment expectation-x t-2 - Note: Δ denotes the difference operator, ln the logarithm and Δx t-h ·|Δx t-h | the squared difference with sign transformation

13
Eurostat – Unit C4 Key indicators for European policies Real time experiment and error statistics 2011 q q q q q q2 MAERMSE GDP 0.63 (-0.20) 0.44 (0.27) (-0.17) (-0.10) 0.00 (0.00) 0.00 (0.20) Employment 0.22 (0.17) 0.13 (-0.18) (0.11) (0.15) (0.11) (-0.19) Febr March 2012 April 2012 May 2012 June 2012 July MAERMSE IPI 0.50 (-0.01) 0.05 (0.34) 0.07 (0.89) 0.15 (-0.41) (0.22) (-1.09) Note: Nowcasts are in growth rates with, in parenthesis, errors computed as difference from respective first official Eurostat release. MAE is the mean absolute error and RMSE is the root mean squared error over the quarters from 2010q1 to 2012q2 for GDP and Employment and over the months from January 2010 to July 2012 for IPI

14
EuroMind: an overview Monthly indicator of economic activity Proxy of GDP Combining Stock and Watson approach with temporal disaggregation in the state-space framework Monthly EuroMind estimates calculated by aggregation of all output and expenditure sides component: recnciliation obtained by weigthed averages of the two monthly estimates Eurostat – Unit C4 Key indicators for European policies

15
EuroMind: main characteristics 1)use of a disaggregate approach output and expenditure breakdowns of quarterly GDP; 2)for each component, selection of indicators; 3)monthly and quarterly indicators modelled into the Stock and Watson single index model; 4)state space form allowing for temporal disaggregation; 5)use of a computational efficient procedure; 6)chain-linking is taken into account; 7)final estimate combining the estimates from the output and expenditure sides optimal weights; 8)benchmarking to official quarterly accounts 9)explicit measure of uncertainty around the indicator available. Eurostat – Unit C4 Key indicators for European policies

16
EuroMind extensions EuroMind-S: more coincident version of EuroMind based on a two factor Stock and Watson model where one factor models the effects of qualitative information EuroMind-C: medium size factor model simultaneously modelling euro area and largest countries EuroMind-B: back calculated version of EuroMind to 1970 –No back calculation of components available EuroMind-Gap: euro area output estimates derived from EuroMind by means of a state-space modelling of trend and cycle Eurostat – Unit C4 Key indicators for European policies

17
EuroMind-S: last 13 releases Eurostat – Unit C4 Key indicators for European policies

18
EuroMIND-S: ME, MAE and RMSE statistics (revisions errors over the quarters 2010q2-2012q2) Eurostat – Unit C4 Key indicators for European policies 1 step2 steps3 steps ME MAE RMSE

19
Growth rates: comparison among indicators AugSeptOctNovDec JanFebMarAprMay JunJulAugSept variations over previous period Quarterly GDP EuroMind EuroMind-S variations over same period of previous year Quarterly GDP EuroMind EuroMind-S Eurostat – Unit C4 Key indicators for European policies

20
The system of euro area turning point detection (1) Euro area dating: business, growth, and acceleration cycle –non-parametric dating rule Euro area system for turning point detection: three coincident indicators –BCCI: Business Cycle Coincident Indicator –GCCI: Growth Cycle Coincident Indicator –ACCI: Acceleration Cycle Coincident Indicator Eurostat – Unit C4 Key indicators for European policies

21
The system of euro area turning point detection (2) BCCI: averaging probability recessions returned by univariate Markov switching models fitted to each of the three component series: unemployement, industrial production index, new car registrations GCCI: averaging probability recessions returned by univariate Markov switching models fitted to each of the five component series: industrial production index, conctruction confidence indicator, financial situation of households during the last 12 months, imports of intermediate goods, employement expectations ACCI: recession probability returned by the Markov switching model fitted to the Economic Sentiment Indicator Eurostat – Unit C4 Key indicators for European policies

22
MS-VAR GCCI and MS-VAR BCCI MSIH(4) – VAR(0) model fitted on 4 variables 1) Industrial Production Index (differenced over 6 months) 2) Unemployment Rate (inverted diff. over 1 month) 3) New Passenger Car Registrations (diff. over 3 months) 4) Employment Expectations (diff. over 1 month) Both indicators jointly obtained as a by-product of model parameters estimation: MS-VAR BCCI filtered probabilities of the first regime of the state-variable (regimes of the latent Markov-chain are sorted in ascending order of the state-dependent intercept); MS-VAR GCCI sum of filtered probabilities of the first and second regimes. Eurostat – Unit C4 Key indicators for European policies

23
The αABβCD sequence Eurostat – Unit C4 Key indicators for European policies

24
Summary of most recent turning points Economic CycleCoincident IndicatorPeakTroughPeak Acceleration Cycle Provisional Dating2006 Q Q12010 Q2 ACCIJune 2006March 2009December 2010 December 2011March 2012 Growth Cycle Provisional Dating2008 Q12009 Q32011 Q1 GCCIMarch 2007July 2009August 2011 MultivariateDecember 2007September 2009May 2011 Classical Business Cycle Provisional Dating2008 Q12009 Q22011 Q3 BCCIAugust 2008October 2009January 2012 MultivariateApril 2008September 2009December 2011 Eurostat – Unit C4 Key indicators for European policies

25
Some comments Euro area growth cycle persists in slowdown phase started in middle 2011 Euro area business cycle entered in recession phase at the end of 2011 After a long deceleration phase the acceleration cycle entered in a new acceleration phase since January 2012 Synthesis the already achieved trough of the acceleration cycle could be a positive signal for a quite fast recovery from the new recession Eurostat – Unit C4 Key indicators for European policies

26
Thank you for your attention! Eurostat – Unit C4 Key indicators for European policies

Similar presentations

© 2016 SlidePlayer.com Inc.

All rights reserved.

Ads by Google