10 years experience in forecasting turning points Jacques Anas Director, Economic Indicators and Statistical Models INTERNATIONAL SEMINAR ON EARLY WARNING AND BUSINESS CYCLE INDICATORS December 2009, Scheveningen, The Netherlands

December 14, years experience in forecasting turning points Introduction In 1996, The Chamber of Commerce of Paris decided to investigate the development of a leading indicator for the French economy. This has been the starting point of this detecting system I will present : methodology and real time results. The concept of turning point must be clearly defined : A hidden event (local extrema, change of regime), quite difficult to predict. Expectations of users (Government, Central Banks, corporate sector, economists for their prediction) are not identical. If the goal is clear (anticipate an economic upturn or downturn), the communication is an issue (probability, threshold and signal, risk, quantitative implication). There is a need to simplify the messages and to link the signal to an economic analysis. A tool to be used in complement of other tools (modelisation, short-term analysis by economists). It must be considered as a safety net. Validation is an issue (ex-post dating to have a reference chronology)

December 14, years experience in forecasting turning points The concept of detection 1. We consider here the follow-up of cyclical movements through cyclical indicators with the purpose to be timely or even leading the movements; 2. It is different than using warning indicators, more structural (imbalances for ex) and potentially leading to crises. Past TPs Dating (chronology) Present TPs Real time detection (implicitly predicting the future also!) Future TPs Predicting turning points (there is an interesting topic: what is a false alarm? It may happen that the signal is invalidated by an external shock or by a quick policy-mix answer.

December 14, years experience in forecasting turning points Turning point detection system A conceptual framework: the ABCD approach 3 indicators: IARC: Indicateur avancé de retournement conjoncturel (to predict A and D) IESR: Indicateur dentrée-sortie de récession (to detect B and C) IRC: Indicateur de croissance sous-jacente To validate the signals of the IARC and IESR indicators

December 14, years experience in forecasting turning points The framework: the ABCD approach What kind of a cycle? Classical business cycle Level Growth cycle Deviation to trend Growth rate cycle Variation Vocabulary issue: phases of BC : recession and upturn phases of GC: slowdown and rebound phases of AC : deceleration and re-acceleration

December 14, years experience in forecasting turning points Three possible representations Classical cycle (in level) Growth cycle (deviation from trend) Growth rate cycle ABCD approach

December 14, years experience in forecasting turning points

December 14, years experience in forecasting turning points Three possible sequences of downturn movements Pure acceleration cycle (« trou dair ») αβ Growth cycle: αA(β)D αA(βαβ)D with an acceleration cycle during the slowdown Business cycle: ( β is the first optimistic signal) αAB(β)CD αAB(βαβ)CD with an acceleration cycle during the recession αAB(βCαBβ)CD case of a double-dip recession

December 14, years experience in forecasting turning points United States

December 14, years experience in forecasting turning points Euro area

December 14, years experience in forecasting turning points A couple of probabilistic indicators applied to France, the euro area and United States Importance of non linear processes in business cycle analysis A leading indicator of the growth cycle (IARC) Based on Neftçis a posteriori probability method applied to leading series (Neftçi, 1982, 1984). A coincident indicator of the business cycle (IESR) Based on the univariate Markov switching model applied to coincident series (Hamilton, 1989, 1990). An important step is the selection of indicators on which the model is applied. An aggregation method has been developed to combine the probabilities

December 14, years experience in forecasting turning points 1. IARC indicator predicting A and D Recursive bayesian algorythm of Neftçi (1982) Computed since 1997 Need of a preliminary dating of the growth cycle turning points to select the candidate leading indicators Multiple criteria (statistical, practical and economic) to select the leading indicators (real, financial and surveys)

December 14, years experience in forecasting turning points Each « k » component allows for the computation of the probability of a coming economic turning point (R t =1) Prediction of a global turning point based on one component

December 14, years experience in forecasting turning points Components of US IARC Consumers anticipations Manufacturing Inventories (inverse) New Construction Permits Stock Market Index (MA3) Interest Rate Differential (MA3) Chief Executives Polls

December 14, years experience in forecasting turning points Weighted aggregation of the «a posteriori probabilities» (a priori weights)

December 14, years experience in forecasting turning points 2. IESR indicator (coincident for B and C) Modelling coincident variables by Markov Switching models (S t ) t K-state first order Markov chain with transition probabilities p ij where p 11 + p 12 + …+ p 1K =1 Parameters estimation: maximum likelihood in conjunction with Expectation-Maximization Choice of K: comparison of 2 and 3 regimes in terms of cycle replication measured by:

December 14, years experience in forecasting turning points Decision rules for communication Empirical thresholds for aggregate probabilities IARC 60% and 80% for the aggregate IARC SERI 50% for filtered probabilities and the aggregate probability

December 14, years experience in forecasting turning points 3. IRC indicator (temporal disaggregation 3. IRC indicator (temporal disaggregation ) Goal : we need to validate quicly a signal Answer: by estimating a monthly GDP underlying growth rate ( few revisions, increased timeliness, reduced volatility) General form of ADL models (Autoregressive Distributive Lag)- is the matrix of k endogenous series of size (n x k) are vectors of size (n x 1) and are constant

December 14, years experience in forecasting turning points Selection process of the best model Univariate selection of the best series for estimating the last three years period of definitive GDP ( ) Selection of the best three series (in level or in difference) The choice The choice : - Estimate and extrapolate the model using all past quarterly GDP available at the cost of revising the estimate or - Estimate and extrapolate using only »final» data at the cost of missing strong movements which cant be captured with surveys (present case)

December 14, years experience in forecasting turning points The selected modelfor the United States The selected model for the United States - Housing Index - manufacturing ISM - Household confidence index (Conference Board) : monthly variation of GDP

December 14, years experience in forecasting turning points Performance analysis IARC of France ( )

December 14, years experience in forecasting turning points 4 recessions in France since 1970

December 14, years experience in forecasting turning points 9 slowdowns (4 are related to a recession)

December 14, years experience in forecasting turning points Slowdowns happen when growth is below trend growth rate 1 2 3

December 14, years experience in forecasting turning points Asian Crisis Signal for the related slowdown Asian Crisis Signal for the related slowdown At the end of May we could say : the economic slowdown may have been of short duration, probably three quarters, and also of low amplitude

December 14, years experience in forecasting turning points Slowdown of 2001 As early as September 2000, the 80 threshold was reached in the euro area October 2000 IARC indicator for the euro area published on November 23, 2000

December 14, years experience in forecasting turning points Signal of slowdown exit in July-August 2003 Signal of slowdown exit in July-August 2003 A signal was given however in February 2002 but in October 2002, we could say that the rebound was aborting August 2003 IARC indicator for France published on October 3, 2003

December 14, years experience in forecasting turning points Acceleration cycle in 2005 A slowdown was anticpated in June but the signal was weak and cacelled out as soon as September 2005

December 14, years experience in forecasting turning points Performance of the indicators IARC, IESR and IRC during the current cycle How they work together

December 14, years experience in forecasting turning points EURO area EURO area -Signal of slowdown with June 2007 IARC -Signal of recession with August 2008 IESR (published 14th of October) -Signal of exit of slowdown with May 2009 IARC -Signal of exit of recession with September 2009 IESR

December 14, years experience in forecasting turning points IARC, IRC and GDP for France IARC of August 2007 >80 Peak of the growth cycle in the coming 3 months September 18,2007 signal ! Start of the recession according to IRC!

December 14, years experience in forecasting turning points IARC, IRC and GDP for France (real time analysis, even for GDP) IARC of May 2009 <-80 Trough of the growth cycle in the coming 3 months June 5, 2009 signal ! End of recession according to IRC

December 14, years experience in forecasting turning points IARC, IRC, IESR and GDP in the United States (real time analysis, except for GDP) IARC of May 2009 <-80 Trough of the growth cycle in the coming 3 months June 3, 2009 signal ! August 28, 2009 statement : End of recession according to a markovian model based on initial claims for unemployment (date : June) End of recession according to IRC IESR = 0.65 in October still no sign of exit of the recession

December 14, years experience in forecasting turning points Improvements for the future The results of the indicators were quite useful to complement the short-term economic analysis. When the indicator is not going in the same direction of an analysis, it stimulates the discussion and imposes some cautiousness in assertions. At times, it may correct the prediction. But there is a real difficulty to communicate. The communication with the sequential Netçis approach is not easy because it is a recursive process with a discontinuity (semi-parametric approach). A times series approach would be preferable. We may also consider a multivariate approach. Models with more than two regimes may help to consider anticipating A,B, C and D at the same time. It is rather difficult to make a difference between anticipating a deceleration and anticipating a slowdown. We have not been successful in making this difference but at least we could quickly detect the re-acceleration (which may be an abortion of a rebound for exemple). A particular example is the signal of economic upturn in United States given during the summer 2001 but which was invalidated by September 11. A route to improve the pertinence of the signal is to increase the threshold from 80 to 90 for example, but we may lose on lead. There is a trade-off between timeliness and minimizing first-type errors.