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A Reduced Rank Regression Approach to Coincident and Leading Indexes Building

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  • Gianluca Cubadda

Abstract

This paper proposes a reduced rank regression framework for constructing a coincident index (CI) and a leading index (LI). Based on a formal definition that requires that the first differences of the LI are the best linear predictor of the first differences of the CI, it is shown that the notion of polynomial serial correlation common features can be used to build these composite variables. Concepts and methods are illustrated by an empirical investigation of the US business cycle indicators.

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  • Gianluca Cubadda, 2007. "A Reduced Rank Regression Approach to Coincident and Leading Indexes Building," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(2), pages 271-292, April.
    • Handle: RePEc:bla:obuest:v:69:y:2007:i:2:p:271-292
    DOI: 10.1111/j.1468-0084.2006.00196.x
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    1. Cubadda, Gianluca, 1999. "Common Cycles in Seasonal Non-stationary Time Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 273-291, May-June.
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    1. Cubadda, Gianluca, 2007. "A unifying framework for analysing common cyclical features in cointegrated time series," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 896-906, October.
    2. Cubadda, Gianluca & Guardabascio, Barbara & Hecq, Alain, 2013. "A general to specific approach for constructing composite business cycle indicators," Economic Modelling, Elsevier, vol. 33(C), pages 367-374.
    3. Centoni, Marco & Cubadda, Gianluca & Hecq, Alain, 2007. "Common shocks, common dynamics, and the international business cycle," Economic Modelling, Elsevier, vol. 24(1), pages 149-166, January.
    4. Hassan Mohammadi & Daniel Rich, 2013. "Dynamics of Unemployment Insurance Claims: An Application of ARIMA-GARCH Models," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 41(4), pages 413-425, December.
    5. Haddad, Hedi Ben & Mezghani, Imed & Al Dohaiman, Mohammed, 2020. "Common shocks, common transmission mechanisms and time-varying connectedness among Dow Jones Islamic stock market indices and global risk factors," Economic Systems, Elsevier, vol. 44(2).

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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