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A Reduced Rank Regression Approach to Coincident and Leading Indexes Building

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  • Cubadda, Gianluca

Abstract

This paper proposes a reduced rank regression framework for constructing coincident and leading indexes. Based on a formal definition that requires that the first differences of the leading index are the best linear predictor of the first differences of the coincident index, 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.

Suggested Citation

  • Cubadda, Gianluca, 2004. "A Reduced Rank Regression Approach to Coincident and Leading Indexes Building," Economics & Statistics Discussion Papers esdp04022, University of Molise, Department of Economics.
  • Handle: RePEc:mol:ecsdps:esdp04022
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    1. Cubadda, Gianluca & Hecq, Alain, 2001. "On non-contemporaneous short-run co-movements," Economics Letters, Elsevier, vol. 73(3), pages 389-397, December.
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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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    More about this item

    Keywords

    Coincident and Leading Indexes; Polynomial Serial Correlation Common Feature; Reduced Rank Regression.;
    All these keywords.

    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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