1. Coupled Economies, Decoupled Forecasters? Presentation at George Washington University, Research Program on Forecasting & Federal Forecasters Consortium February 21, 2008 Prakash Loungani and Jair Rodriguez

2. Disclaimers and Acknowledgments The views expressed here are those of the authors and must not be attributed to the IMF Some of the work discussed here builds on work with co-authors: Isiklar, Lahiri & Loungani (Journal of Applied Econometrics, 2006) Juhn & Loungani (IMF Staff Papers 2002);

3. What is “decoupling”? Dictionary definition: decouple (verb): uncouple; disconnect; separate; detach. Decoupling view (from financial market participants): “the rest of the world (or emerging markets) will decouple from the US economy in the sense that a slowdown in the US growth will not necessarily undermine the growth prospects in the rest of the world (or in emerging markets)” Source: Kose (2008)

4. Decoupling, we hardly knew you … (evolving assessments of financial markets) “We believe in decoupling…” August 2007 “We subscribe to a particular form of … decoupling…” January 5, 2008 "The rest of the world will not decouple from the US…" January 23, 2008 “Decoupling is the latest macro fad...” January 24, 2008 Source: Adapted from Kose (2008)

5. Story line Economies appear to be ‘coupled’ (real GDP growth in one country is linked to growth in others) –Specifically: U.S. growth affects growth elsewhere, particularly when the U.S. is in a recession (IMF, World Economic Outlook) Main questions addressed in this talk: –How well are recessions forecast and how do forecasts for other countries change when U.S. goes into a recession? –How well do forecasters take into account this interdependence in making their growth forecasts? E.g. Do forecasts for Canada’s growth take into account fully its dependence on U.S. growth?

6. Organization of the talk Forecast data & raw correlations slides 7-11 Empirical strategy for systematic test of decoupling in forecasts: panel VARs Slides 12-16 Evidence from panel VARs Slides 17-28 Forecasting during recessions Slides 29-36

7. Forecast Data Consensus Forecasts Horizon –Year-Ahead forecasts –Current-Year forecasts Countries (14 large economies) –G7 –Emerging Markets (EM): Brazil, China, India, Korea, Mexico, Russia, and Turkey

8. Example of forecast data (1)

9. Example of forecast data (2)

10. Correlations among G7 GDP: actual data and forecasts

11. Correlation of U.S. with EMs: actual data and forecasts

12. Basic idea Successive forecasts of the same event should be uncorrelated Intuition: “If I can look at your most recent forecasts and accurately say, “Your next forecast will be 2% lower than today’s, then you can surely improve your forecast” [Nordhaus (1987)]

13. Strong efficiency

14. Weak efficiency

15. Evidence for G7 Test for weak efficiency Extension of weak efficiency test to see how well forecasters take into account interdependencies

16. Country β1β1 t-stat (OLS)t-stat (GMM) Canada0.305.34 ** 4.04 ** France0.335.99 ** 4.54 ** Germany0.5210.55 ** 7.00 ** Italy0.417.80 ** 6.49 ** Japan0.254.37 ** 3.69 ** UK0.489.44 ** 6.38 ** USA0.254.44 ** 3.46 **

17. From weak efficiency test to VAR

18. Complicated error structure

26. Impulse responses: domestic

27. Variance decompositions: Domestic and Foreign Components

28. Principal Components Analysis: A Digression Notes: Table presents three factor patterns using forecast revisions. Presented factor patterns are rotated using an orthogonal transformation (varimax). Cumulative variance explained by the first three eigenvalues are 68 percent. Entries greater than 0.5 are shown in bold.

29. Impact of U.S. recessions and slowdowns (Change in GDP growth; median for region) Source: IMF World Economic Outlook

30. “Recession” Episodes

31. Forecast Performance

32. Recession Episodes Source: Juhn and Loungani (2002)

33. Forecast Performance Source: Juhn and Loungani (2002)

35. 1991 Recession

36. 2001 Recession