A system for a statistical dating and detection of euro area turning points

1. Asystemfor a statisticaldatinganddetection of euro areaturningpoints Presentation at the Euroindicators Working Group 10th Meeting – 3 & 4 December 2007 Luxembourg Jacques Anas Coe-Rexecode janas@coe-rexecode.fr Laurent Ferrara Banque de France laurent.ferrara@banque-france.fr Monica Billio Università di Venezia billio@unive.it Gian Luigi Mazzi Eurostat gianluigi.mazzi@ec.europa.eu

2. Outline • Comparative analysis of existing chronologies • Business Cycle turning points dating • Growth cycle turning points dating • Methodology for dating euro area business and growth cycles • The ABCD approach • A non-parametric algorithm • Deepness and duration assessment • Diffusion and synchronization assessment • Criteria of coherence • Current dating assessment • Early detection system • The proposed methodology • Current results • Real-time publication

3. Introduction The main aims of business cycle analysis are to detect, in real-time, and anticipate economic fluctuations with particular attention to turning points Results depend on: • Reliable historical analysis of main cyclical events • Accurate dating of past turning points • Detailed description of cyclical movements • Accurate comparison of convergence and synchronisation of cyclical fluctuations among sectors and countries

4. Three important aspects : • Clarify cycle definition • classical cycle • growth cycle • acceleration cycle • Detection model based on sufficiently long time-series - Major problem: availability of long time-series for the euro area - Use of provisional back recalculated data of euro area aggregates (Available at Eurostat, under assessment) 3. Statistical findings need economic and political validation

5. Objective: • Define an integrated framework for dating and detection of euro area’s turning points • Classical cycle • Growth Cycle • Exclusion of the acceleration cycle • But, first, have a look at existing chronologies

6. Comparative analysis of existing chronologies

7. Overview of existing chronologies • Great number of papers by experts on national chronology dating • Belgium, United Kingdom, Canada, Austria, Australia • Few countries have official dating procedure • US (NBER),Japan (EISR),Italy (ISAE) • An academic Dating Committee set up by CEPR • Several papers dedicated to the cyclical dating of the euro area • Since 2006 Eurostat is regularly monitoring existing turning point chronologies

8. Business Cycle Chronology-list • Artis, Krolzig and Toro, 1999 (AKT) • Krolzig and Toro, 2000 (KT) • Lommatzch, 2001 (LS) • Krolzig (MS-AR), 2001 (K1,K2), 2002 (K1,K2, K3) • Harding Pagan , 2001 (HP), 2004 (HP) • AWM (Fagan, Henry and Mestre), 2001 (FHM) • BDH (Beyer, Dornik, Hendry), 2001 (BDH) • Harding, Eurostat Colloquium, 2002 (H) • Artis, Marcellino and Proietti, 2002 (AMP1, AMP2) • CEPR, 2003 (CEPR) • Bengoechea, Camacho and Perez-Quiros, 2003 (BCP1, BCP2) • Mcadam, 2003 (M1, M2) • Anas and Ferrara, 2003 (AF) • Artis, Krolzig and Toro, 2004 (AKT) • Bengoechea and Perez-Quiros, 2004 (BP1, BP2) • Artis, Marcellino and Proietti, 2004 (AMP) • Mönch and Uhlig , 2005 (MU) • Benalal and al, 2006 (BA) • Anas and Ferrara, 2006 (AF)

11. Convergence of business cycle turning point dating of the euro area (Recession 1980-82)

12. Business Cycle turning points dating • The consensus chronology: • Recession in 1975 • Peak between 1974Q1 and 1974Q3 • Trough in 1975Q1 or 1975Q3 • Recession in 1980-1982 (double-dip) • Termination in 1982Q3 or 1982Q4 • Recession in 1993 • Peak in 1992Q1 • Trough between 1993Q1 and 1993Q3 • Industrial Recession in 2001 and 2003

13. Growth Cycle Chronology-list • Vanhaelan et al, 2000 • Peersman and Smets, 2001 • European Central Bank, 2001 • Harding , 2002 • Artis, Marcellino and Proietti, 2002 • Anas and Ferrara (2000, 2004 and 2006) • OECD (recurrent)

14. Convergence of growth cycle turning point dating of the euro area

15. Growth cycle turning points dating (1) Main findings: • Agreements • Peak (the onset of the second oil shock): 1979Q4-1980Q1 • Trough: 1982Q4-1983Q1 period (except for Harding: 1983Q3) • Trough: between 1993Q2 and 1993Q3 • A peak: 1995, a subsequent trough: 1996Q4 or 1997Q1 (Except OECD: 1997M10) • Asian crisis related cycle: a peak: 1998Q1 (except Vanhealan: 1998Q3) and a trough: 1999Q1 • The last identified peak: between 2000Q2 and 2000Q4

16. Growth cycle turning points dating (2) • Disagreements • Anas and Ferrara and OECD: intermediate cycle in 1981 (others: 1986) • Location of the peak - early 90’s, • First mini-cycle in 1986 and a second one in 1998 • The most recent trough (only identified by the OECD: 2001M11) and Anas-Ferrara: 2003Q2)

17. Limitations of existing chronologies - new proposal • More attention on classical business cycle • Less on the growth cycle • Three / four recessions detected • Business cycle high degree of asymmetry (based only on classical cycle) → limited informative power, policy making purposes • Presenting an approach to business cycle analysis integrating classical and growth cycles • In a common framework: classical and growth cycle turning points • More accurate description of the economic global cyclical fluctuations • "ABCD approach" by J. Anas and L. Ferrara (2004)

18. Advantages • The main advantage: • classical and growth cycle are jointly considered both in the dating and in the detecting stage • Key results: • A better description of different economic phases • More accurate investigation of the economic cyclical behaviour • Improves the relevance of information delivered to users in comparison with a standard analysis based only on classical or growth cycle component

19. Methodology for dating euro area business and growth cycles

20. Understanding the “ABCD” approach Business cycle: expansions and recessions, i.e. the fluctuations of the level of the series Growth cycle: (the deviation from trend) represents the fluctuations around the trend • estimate the trend - difficult in real time • useful for describing / analysing historical fluctuations Growth rate cycle (acceleration cycle): free of irregular movements, not so obvious to estimate

21. ABCD approach Three possible representations: • Classical cycle (in level) • Growth cycle (deviation from trend) • Growth rate cycle

22. The ABCD approach: since 2001, last US-recession

23. The ABCD approach: the case of the euro area

24. A non-parametric algorithm: (1) • Outliers disregarded in the seasonal adjustment step by Tramo-Seats/X12-Arima • Exclude irregular movements for monthly data (Trend-Cycle) • Do not smooth quarterly GDP data (use SWDA) • Apply the Bry and Boschan (1971) rule to identify candidates turning points: • Peak at t when relative maximum within the interval [t-k, t+k] • K = 5 for monthly data • K = 2 for quarterly data • Trough at t, same as before but relative minimum

25. A non-parametric algorithm: (2) • Disregard turning points within six months or two quarters at the beginning or end of the series • Rules to ensure peaks and troughs alternation • in the presence of a double through, the lowest value is chosen • in the presence of a double peak, the highest value is chosen

26. Assessment of cyclical fluctuations • Duration criteria: • Cycle phase: • business cycle min. 6 months • growth cycle min. 9 months • Complete cycle: • business cycle min. 15 months • growth cycle min. 18 months • Deepness: Deepness = |XP – XT| / XP (amplitude of the phase) • Severity of a recession: Triangle approximation to the cumulative movements S = 0.5 DeepnessDuration

27. Diffusion and synchronisation assessment (1) Indirect dating versus direct dating. Simultaneous measure of diffusion and synchronisation between N cycles (Boehm and Moore 1984 – Harding and Pagan 2006) • Compute a dating chronology for each euro area country • Compute distance to nearest turning points : • Aggregate the information relative to the countries for ex: • Identify a set of tPj and tTj (local minima of d) = central dates of clusters

28. Diffusion and synchronisation assessment (2) • Diffusion/synchronisation measure DSj • DSj measure the certainty around the turning point • High value  turning point well diffused and synchronised • Low value  turning point neither diffused nor synchronised • Intermediate value  cycle either not enough diffused or not enough synchronised

29. Criteria of coherence and results Three coherence criteria • Coherence between growth cycle and business cycle turning points • according to the ABCD approach • Coherence between direct and indirect dating • Coherence between industrial production and GDP cycles (no need to use other data for definitive dating)

30. Existence of a euro area cycle • Needed assumption to date and detect euro area turning points • Many studies show a convergence of cycles in the euro area • Statistical indicators : concordance index, standard deviation, mean and variance of bilateral cross-country correlations or dynamic correlations (comovements over a specified frequency band) over rolling windows. • Economic analysis of the rationale for convergence after 8 years of EMU experience • Average correlation robust to alternative filters (Commission) • Temporary de-synchronisation (cycles do not move in phase) around 2003 : highly discussed by Central Banks and the Economic Commission : diverging trends rather diverging cycles ? Diverging opinions among experts on the theoretical consequences of monetary union, however stylised facts point to cyclical convergence.

31. Standard deviation of euro area IPI growth cycles (5 and 11 countries) Reduction in cyclical dispersion would mean that individual cycles cluster together. However it may be linked to a decreasing amplitude of cyclical fluctuations rather than a higher synchronisation.

32. Standard deviation of euro area GDP growth cycles (6 countries)

33. Mean euro area correlations by decade - Estimations through GMM would be more precise (use of variance covariance matrix) - Rolling windows (see Dopke) are better than comparing periods of time. - Convergence of mean towards 1 is not sufficient: variance must also decrease (see Mitchell and Massmann, 2004)

34. Current dating assessment(since early 2000)

35. 5 main euro area countries IPI from m1 1999 to m8 2007

36. One industrial recession followed by a gradual recovery Euro area IPI and its trend (dotted line) from m1 1999 to m8 2007 September 11

37. - A slowdown from mid-2004 to mid-2005 Euro area IPI growth cycle from m1 1999 to m8 2007

38. Euro area GDP and its trend (dotted line) from Q1 1999 to Q2 2007 No global recession and a very gradual recovery

39. No Recession synchronisation in 2001-2004(study on 6 countries) • Germany • France • Italy • Netherlands • Spain • Belgium

40. Diffusion-Synchronisation for GDP business cycle peaks based on the 6 main euro area countries from Q1 1978 to Q3 2007

41. Diffusion-Synchronisation for GDP business cycle troughs based on the 6 main euro area countries from Q1 1978 to Q3 2007

42. Diffusion-Synchronisation for GDP business cycle peaks based on the 4 main euro area countries from Q1 1970 to Q3 2007

43. Diffusion-Synchronisation for GDP business cycle troughs based on the 4 main euro area countries from Q1 1970 to Q3 2007

44. - Slight decrease of GDP in the USA - No decrease in the euro area • Investment decrease in the USA • Investment decrease in the euro area - Reduction of employment in the USA - No reduction in the euro area

45. Euro area GDP growth cycle from Q1 1995 to Q3 2007 The location of last trough still uncertain (preference to 2003Q2)

46. Further cyclical deterioration in Germany and Italy in 2005 ? (end-point uncertainty of filters) 6 main euro area countries GDP growth cycle from Q1 1995 to Q3 2007

47. Growth cycle

48. Diffusion- Synchronization for GDP growth cycle peaks based on the 6 main euro area countries from Q1 1995 to Q3 2007

49. Diffusion- Synchronization for GDP growth cycle peaks based on the 6 main euro area countries from Q1 1995 to Q3 2007 (no weights)

50. Diffusion-Synchronisation for GDP growth cycle troughs based on the 6 main euro area countries from Q1 1995 to Q3 2007 Trough in 2005