Composite Leading Indicators and Growth Cycles in Major OECD Non-Member Economies and Recently New OECD Member Countr

1. Composite Leading Indicators and Growth Cycles inMajor OECD Non-Member Economies and Recently New OECD Member Countries  Ronny Nilsson Statistics Directorate OECD

2. Topics Composite Leading Indicators for Individual Countries - Evaluation of Indicators (Non-OECD) - Characteristics of leading indicators - Cyclical properties of CLIs Growth Cycles and Reference Series - New and old Reference series for OECD Area and OECD Europe Area - New Area Aggregates - Timing Relationship of Individual Countries with New Area Aggregates Composite Leading Indicators for New Zone Aggregates

3. Evaluation of Indicators -Major OECD Non-Member Economies Methods used to evaluate Cyclical Performance Turning Point Analysis - Mean/median lead, standard deviation at turning points, extra or missing cycles Cross-correlation – Average lead at max correlation Cross Spectral Analysis - Coherence (explained variance) and Mean Delay Dynamic Factor Analysis - Common component variance/indicator variance, - Cross-correlation between common components - Cyclical timing classification (mean delay)

4. Criteria used for Timing Classification ofindicators by country and subject area Cross Spectral Analysis Mean delay leading = value > 1 NBER Analysis Median lead leading = > 2 periods Dynamic Factor Analysis Common component cross-correlation leading = coef. > 0.50 and positive lag

5. Cyclical Evaluation Results by Country

6. Cyclical Evaluation Results by Subject

7. Selection of Potential Component Series for Construction of Composite Indicators Criteria Cyclical behaviour at turning points - median lead - standard deviation at turning points - number of extra and missing turning points Practical issues - timeliness of the latest data available (t+2) - frequency (delay for timely data, if quarterly frequency) - smoothness (irregular series (MCD 5 or 6) will imply revisions due to smoothing)

8. Characteristics of Leading Indicators General problems Data Availability restricted to few subject areas and indicators (see table below) Short time period of available data for many indicators back to 1990/96 in all countries except Brazil (79), South Africa (75), New Zealand (80) and China (83) Frequency of many good indicators is quarterly, this concerns most business and consumer tendency series (South Africa and New Zealand) Timeliness a particular problem for series with quarterly frequency (Brazil, India, South Africa and New Zealand)

9. Characteristics of CLIsMajor OECD Non-member Economies

10. Characteristics of CLIsRecently New OECD Member Countries

11. Characteristics of CLIs for New Countries Compared to CLIs for Major OECD Countries  General fit (peak-correlation) with reference series is rather good for most countries – for Eastern European countries a weaker correlation is noted Median and peak-correlation leads show inconsistent results for several countries (Indonesia, Russia, New Zealand) Variability of lead at all TPs as measured by standard variation is high in several countries (China, Indonesia, Russia, South Africa, New Zealand and Hungary)

12. Composite Leading Indicator - Brazil

13. Composite Leading Indicator - China

14. Composite Leading Indicator - India

15. Composite Leading Indicator- Russia

16. Composite Leading Indicator – South Africa

17. Composite Leading Indicator – Korea

18. Composite Leading Indicator – Hungary

19. Composite Leading Indicator – Poland

20. Conclusions CLI evaluation results encouraging – but they are based on a very short time period with only 2 or 3 growth cycles registered in all countries (except Brazil) CLI components restricted to a few subject areas - financial indicators (> 50% in India and Indonesia) - tendency surveys (> 50% in Russia and South Africa) Timeliness and revisions is a problem for the calculation of regular monthly CLIs with quarterly components from business or consumer tendency surveys Coverage of component series in OECD databases is a condition for the calculation of regular monthly CLIs – - High share of selected component for several countries require special data collection arrangements

21. New and Old Reference Series for OECD Area and OECD Europe Area

22. New Regional or Area Aggregates OECD Eastern Europe - share is 7.5 % of OECD Europe Area - country weights (GDP at PPP) in %, Czech R. 21.1, Hungary 15.8, Poland 52.6, Slovak R. 10.5 Major Five Asian Economies - share is close to 35% of World Proxy - country weights, China 44.4, India 20.9, Indonesia 4.9, Japan 23.6, Korea 6.2 World Proxy (OECD + major 6 OECD non-members) - covers 83.1 % of World GDP (OECD 57.1) - country weights, Brazil 3.2, China 15.3. India 7.2, Indonesia 1.7, Russia 3.0, South Africa 1.1, United States 25.0, Japan 8.1 ……………………

23. Timing Relationship of Individual Countries with New Area Aggregates OECD Eastern Europe - Hungary and Poland coincident and well correlated - Czech and Slovak better against Europe as a whole - Russia shows leading tendency, but weak correlation - no major difference against Europe and Euro Area Asia Major 5 Area - China, India and Japan coincident and well correlated - Korea coincident, but weak correlation - Australia, New Zealand and Indonesia show weak or not significant correlation

24. Timing Relationship of Growth Cycles in Individual Countries with New Area Aggregates World Proxy (OECD Area + Major 6 OECD Non members) - China and India show leading tendency against World Proxy and median leads of 5-3 months against OECD Area - Korea and New Zealand show leading tendency against World Proxy and OECD Area, but weak correspondence with OECD Area - Brazil, Russia and South Africa show lagging tendency and Russia and South Africa also shows weak correspondence against World Proxy and OECD area - Eastern European countries show lagging tendency and extremely weak correspondence against World Proxy and OECD Area with exception of Poland

25. Hungary, Poland and OECD Eastern Europe

26. Czech R., Slovak R., Russia andOECD Eastern Europe

27. OECD Europe, Euro Area and OECD Eastern Europe

28. China, India andAsia Major 5 Economies

29. Japan, Korea and Asia Major 5 Economies

30. Australia, New Zealand, Indonesia andAsia Major 5 Economies

31. Timing Relationship of Growth Cycles in New and Established Area Aggregates against OECD Area and World Proxy Euro Area/OECD Europe/OECD Eastern Europe - All European aggregates show a tendency to lag against both OECD Area and World Proxy NAFTA (North American Free Trade Area) - shows a coincident behaviour against both OECD Area and World Proxy Asia Major 5 Area - shows a leading tendency against both OECD Area and World Proxy with clear median lead of 4 months against the OECD Area

32. OECD Area, OECD Europe Area, NAFTA and Asia Major 5 Economies

33. World Proxy, OECD Area, Brazil and South Africa

34. CLIs for New Area AggregatesCyclical Characteristics 1995-2005 World Proxy - CLI shows a median lead of 2 months and a peak- correlation of 0.92 at a lead of 3 months Asia Major 5 Area - CLI shows a median lead of 3 months and a peak- correlation of 0.85 at a lead of 3 months OECD Eastern Europe - CLI shows a median lead of 4 months, but a peak- correlation of only 0.39 at a lead of 7 months

35. World ProxyOECD area + Major 6 NMEs

36. Asia Major 5 Economies

37. OECD Eastern Europe

38. Publication and References http://www.oecd.org/std/cli Nilsson Ronny and Olivier Brunet, 2006. Composite Leading Indicators for Major OECD Non-Member Economies: Brazil, China, India, Indonesia, Russian Federation and South Africa, OECD Statistics Working Paper STD/DOC(2006)1, available at http://www.olis.oecd.org/olis/2006doc.nsf/LinkTo/std-doc(2006)1 OECD, 2006. Composite Leading Indicators for Major OECD Non-Member Economies and Recently New OECD Member Countries, Unclassified Document available at http://www.oecd.org/document/60/0,2340,en_2649_34349_36674300_1_1_1_1,00.html