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Generalized Efficient Inference on Factor Models with Long-Range Dependence

Author

Listed:
  • Yunus Emre Ergemen

    (Aarhus University and CREATES)

Abstract

A dynamic factor model is considered that contains stochastic time trends allowing for stationary and nonstationary long-range dependence. The model nests standard I(0) and I(1) behaviour smoothly in common factors and residuals, removing the necessity of a priori unit-root and stationarity testing. Short-memory dynamics are allowed in the common factor structure and possibly heteroskedastic error term. In the estimation, a generalized version of the principal components (PC) approach is proposed to achieve efficiency. Asymptotics for efficient common factor and factor loading as well as long-range dependence parameter estimates are justified at standard parametric convergence rates. The use of the method for the selection of number of factors and testing for latent components is discussed. Finite-sample properties of the estimates are explored via Monte-Carlo experiments, and an empirical application to U.S. economy diffusion indices is included.

Suggested Citation

  • Yunus Emre Ergemen, 2016. "Generalized Efficient Inference on Factor Models with Long-Range Dependence," CREATES Research Papers 2016-05, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2016-05
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    References listed on IDEAS

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    Cited by:

    1. Ergemen, Yunus Emre & Haldrup, Niels & Rodríguez-Caballero, Carlos Vladimir, 2016. "Common long-range dependence in a panel of hourly Nord Pool electricity prices and loads," Energy Economics, Elsevier, vol. 60(C), pages 79-96.

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    More about this item

    Keywords

    Factor models; long-range dependence; principal components; efficiency; hypothesis testing;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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