1. Indicators to measure cyclical movements Julian Chow United Nations Statistics Division

2. Scope of chapter 5 Describe conventional approaches that define business cycleDescribe conventional approaches that define business cycle Address specific statistical and data issues in cyclical movement measurementAddress specific statistical and data issues in cyclical movement measurement Focus on the phase of data compilationFocus on the phase of data compilation

3. Key points Reference variables (real statistical variables versus latent variables)Reference variables (real statistical variables versus latent variables) Advantages and drawbacks of referring to alternative cyclical definitionAdvantages and drawbacks of referring to alternative cyclical definition The usefulness of simultaneous monitoring of classical and growth cycleThe usefulness of simultaneous monitoring of classical and growth cycle Limits of detrending techniques (e.g. instabilities of current estimates)Limits of detrending techniques (e.g. instabilities of current estimates) combining cyclical estimates (subjective versus statistical aggregation)combining cyclical estimates (subjective versus statistical aggregation)

4. Outline of chapter 5 The choice of target variablesThe choice of target variables The choice of the reference cycle (classical, growth or acceleration cycle)The choice of the reference cycle (classical, growth or acceleration cycle) Filtering techniques to achieve noise minimization and a proper estimation of trend-cycle componentFiltering techniques to achieve noise minimization and a proper estimation of trend-cycle component Detrending methods: Parametric versus non parametric (univariate versus multivariate)Detrending methods: Parametric versus non parametric (univariate versus multivariate) Aggregation of individual signals: choice of the weights versus combining forecastsAggregation of individual signals: choice of the weights versus combining forecasts Multivariate detrending methods and filteringMultivariate detrending methods and filtering Some examplesSome examples

5. The choice of target variables Real statistical variables versus latent variablesReal statistical variables versus latent variables Choice of variables that are used as components of composite business cycle composite indexesChoice of variables that are used as components of composite business cycle composite indexes Subject to the agreement, the section may recommend a harmonized set of component indicators that can be used for the construction of business cycle composite indicatorsSubject to the agreement, the section may recommend a harmonized set of component indicators that can be used for the construction of business cycle composite indicators

6. The choice of the reference cycle The section aims to clarify the kind of business cycle people are referring to.The section aims to clarify the kind of business cycle people are referring to. 1.Classical cycle 2.Growth cycle 3.Acceleration cycle Usefulness of simultaneous monitoring of classical and growth cycleUsefulness of simultaneous monitoring of classical and growth cycle

7. Filtering techniques and detrending methods Two parts: Filtering techniques to achieve noise minimization and a proper estimation of trend-cycle componentFiltering techniques to achieve noise minimization and a proper estimation of trend-cycle component Trend-cycle decomposition to obtain the cyclical componentTrend-cycle decomposition to obtain the cyclical component

8. Detrending methods Non-parametric methodsNon-parametric methods 1.First differencing filter 2.Henderson filter 3.Phase Average Trend Method (NBER) Parametric methodsParametric methods 1.Beveridge-Nelson decomposition (1981) 2.Unobserved component model (Havery 1985) 3.Stock and Watson decomposition (1986) 4.Hodrick-Prescott filter (1997) 5.Baxter-King filter (1999). 6.Christiano-Fitzgerald filter (1999)

9. Aggregation of individual signals Describes the methodology of different types of weighting and aggregation methods that use to combine individual component series into composite indicators.Describes the methodology of different types of weighting and aggregation methods that use to combine individual component series into composite indicators. 1.Equal weights 2.Standardization factors (Conference Board) 3.Weights based on principal component analysis and factor analysis 4.Regression analysis 5.Unobserved component models 6.Weights based on public/expert opinion The underlying assumptions, advantage and disadvantage of each method will be discussed.The underlying assumptions, advantage and disadvantage of each method will be discussed.

10. Multivariate detrending methods and filtering Rationale of multivariate detrending methodsRationale of multivariate detrending methods Methodology of different types of multivariate detrending procedure. The proposed methods are listed as followsMethodology of different types of multivariate detrending procedure. The proposed methods are listed as follows 1.Multivariate Hordrick and Prescott Filter (Laxton and Telow 1992) 2.Multivarate Beveridge and Nelson decomposition (Evans and Reichlin 1994) 3.Multivariate unobserved component decomposition (Harvey 1985)

11. Discussion 1 Is it possible to recommend a common approach to define business cycle in the handbook?Is it possible to recommend a common approach to define business cycle in the handbook? Should indicators be based on a common set of basis statistics?Should indicators be based on a common set of basis statistics? Should the compilation based on a standard methodology or countries should choose among a set of recommended approaches by selecting the one giving the best performance with respect to specificities of each country?Should the compilation based on a standard methodology or countries should choose among a set of recommended approaches by selecting the one giving the best performance with respect to specificities of each country?

12. Discussion 2 What is our opinion on the dilemma between subjective approach and statistical approach in the process of variable selection and weight definition to construct composite indicators?What is our opinion on the dilemma between subjective approach and statistical approach in the process of variable selection and weight definition to construct composite indicators? Please recommend methods, such as filtering techniques, detrending and aggregation method, that are appropriate to be included in this chapter.Please recommend methods, such as filtering techniques, detrending and aggregation method, that are appropriate to be included in this chapter.

13. Discussion 3 Please suggest any other key points needed to be addressed in this chapter.Please suggest any other key points needed to be addressed in this chapter. Please recommend documents/papers that can be used as basis for the eventual text in this chapter.Please recommend documents/papers that can be used as basis for the eventual text in this chapter.