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Estimation of Large Dimensional Factor Models with an Unknown Number of Breaks

Author

Listed:
  • Shujie Ma

    (Department of Statistics, University of California, Riverside)

  • Liangjun Su

    (Singapore Management University)

Abstract

In this paper we study the estimation of a large dimensional factor model when the factor loadings exhibit an unknown number of changes over time. We propose a novel three-step procedure to detect the breaks if any and then identify their locations. In the first step, we divide the whole time span into subintervals and fit a conventional factor model on each interval. In the second step, we apply the adaptive fused group Lasso to identify intervals containing a break. In the third step, we devise a grid search method to estimate the location of the break on each identified interval. We show that with probability approaching one our method can identify the correct number of changes and estimate the break locations. Simulation studies indicate superb finite sample performance of our method. We apply our method to investigate Stock and Watson’s (2009) U.S. monthly macroeconomic data set and identify five breaks in the factor loadings, spanning 1959-2006.

Suggested Citation

  • Shujie Ma & Liangjun Su, 2016. "Estimation of Large Dimensional Factor Models with an Unknown Number of Breaks," Working Papers 05-2016, Singapore Management University, School of Economics.
    • Handle: RePEc:siu:wpaper:05-2016
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    File URL: http://ink.library.smu.edu.sg/soe_research/1789
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    Cited by:

    1. Barigozzi, Matteo & Cho, Haeran & Fryzlewicz, Piotr, 2018. "Simultaneous multiple change-point and factor analysis for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 206(1), pages 187-225.

    More about this item

    Keywords

    Break point; Convergence rate; Factor model; Fused Lasso; Group Lasso; Information criterion; Principal component; Structural change; Super-consistency; Time-varying parameter.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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