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€ coin PowerPoint Presentation

€ coin

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€ coin

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  1. €coin A real time coincident indicator for the euro area business cycle Filippo Altissimo (Bank of Italy and CEPR), Antonio Bassanetti (Bank of Italy), Riccardo Cristadoro (Bank of IFtaly), Mario Forni (University of Modena and CEPR), Marc Hallin (ECARES), Marco Lippi (University of Rome), Lucrezia Reichlin (ECARES and CEPR), Giovanni Veronese (Bank of Italy)

  2. What can €coin be used for? • To assess the current state of the business cycle in the euro area in a timely way • To establish historical dating of the euro area business cycle.

  3. Why use a coincident index instead of industrial production or GDP? Real data, eg. Industrial production and GDP are released with a lag For example, information available in January 2002: • GDP Third quarter 2001 • Industrial Production November 2001 • Surveys-confidence indexes December 2001

  4. “unlike weather forecasters, economists have to forecast not only whether it will be rainy tomorrow, but also whether it is rainy today” (The Economist, ????)

  5. GDP is only available at quarterly frequencies

  6. Fig. 1 The Euro area GDP(3 month changes)

  7. Industrial production only captures a small part of economic activity (28.9% of GDP in the euro area) • Industrial production is very noisy

  8. Fig. 2 The Euro area industrial production(3-month changes)

  9. Why use a coincident index instead of confidence indexes based on surveys ? • Confidence indicators provide a noisy signal of the state of the business cycle. • They are often leading, but they are not strongly correlated with real variables, are very volatile and often identify turning points incorrectly.

  10. Fig. 3 - IFO business climate indicator (3-month changes)

  11. Fig. 4 - The European Commission’s Business Climate Indicator

  12. Which series should we believe?

  13. A zoom

  14. What is €coin? • €coinrepresents monthly GDP for the Euro area after the removal ofmeasurement error and short run fluctuations (ie. those lasting less than one year). The resulting series is the cyclical component of GDP growth. • €coin is updated using the most recent information available and will be published each month by CEPR.

  15. How is €coin constructed? It relies on two pillars • a data set covering about 1000 monthly variables from the six largest economies of the euro area, obtained from a variety of sources.

  16. Datastream Reuters Bank for International Settlements (BIS) OECD EUROPEAN OFFICIAL STATISTICS COMMERCIAL DATA 12 Statistical Institutes 12 Central Banks Eurostat ECB European Commission Other National Institutes (IFO,ISAE..)

  17. The methodology • Use filters to remove measurement errors, inconsistencies in national statistics and short run volatility from the GDP data • Exploit optimally information contained in the leading variables in the data set to forecast the value of current data which are not yet released

  18. Optimal Aggregation

  19. How €coin and other indicators track GDP

  20. A zoom

  21. Fig. 6 – Peaks and troughs in the euro area business cycle according to €coin(3-month changes)

  22. How to read €coin • €coin is expressed in terms ofa three monthly growth rate, so it tracks the quarterly growth rate of GDP, not its level • If the indicator is greater (less) than zero, the level of the cyclical component of GDP is rising (falling). • If €coin is positive but less (more) than the historicalaverage of GDP, it is rising at a slower (faster) rate than average • If it has a positive (negative) slope, the growth of the cyclical component of GDP is accelerating (decelerating)

  23. What are recessions and expansions Shaded areas are classified as expansions,i.e.prolonged periods of increasing growth.  According to this definition, the euro area economy may be considered in recession even in periods when GDP still grows, though decelerating.

  24. History • Since 1988 the euro economy has experienced three full cycles (peak to peak), before the current one, of twelve months average duration • The volatility of the business cycle has decreased since the early nineties.

  25. €coin: The Building Blocks • €coin can be decomposed into the components which represent the contributions of industrial production, survey data, financial variables etc. to the indicator • Each component tells us what the value of €coin if all other components where equal to their average value

  26. Interpreting the components • If a component has a value less (larger) than zero, that component is tending to reduce (increase) the value of the indicator • If the component has value less than zero but the month on month change in the component is positive, it is contributing to a recovery of the indicator by tending its value back towards zero

  27. Historical contribution of selected components

  28. Industrial Production

  29. Surveys

  30. Interest Rates

  31. The Euro area economy: January 23 2002

  32. Interpretation • Before September the indicator was positive, but moving towards zero: euro area GDP cyclical component was still rising, but its growth was decelerating • In September, the indicator fell below zero: the level fell for the first time. The fall continued in October and accelerated in November. • The fall moderated in December and there is evidence of a return to zero, which suggests that the level of the cyclical component of GDP is beginning to stabilize

  33. Contribution of the main components to the last signal

  34. Interpretation • All components are negative  they reduce the value of the indicator • All but industrial production and financial variables are contributing to a recovery of the indicator by tending to push its value back towards zero • However 

  35. CATEGORY Number of variables Months Sep Oct Nov Dec Industrial Production 37 1 6 30 0 Production Prices 51 1 8 42 0 Consumption Prices 5 0 0 5 0 Survey 92 2 1 43 46 Trade 7 0 3 4 0 Labour Market 16 0 6 5 5 Monetary Aggregates 16 0 0 16 0 Interest Rates 64 0 2 17 45 Financial Variables 10 0 0 1 9 Other Indicators 6 0 0 4 2 GDP 7 7 0 0 0 ALL VARIABLES 311 11 26 167 107 No. of variables available in recent months

  36. How important are revisions to the data?