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Estimation of Approximate Factor Models: Is it Important to have a Large Number of Variables?

Author

Listed:
  • Chris Heaton

    (Department of Economics, Macquarie University)

  • Victor Solo

    (University of New South Wales)

Abstract

The use of principal component techniques to estimate approximate factor models with large cross-sectional dimension is now well established. However, recent work by Inklaar, Jacobs and Romp (2003) and Boivin and Ng (2005) has cast some doubt on the importance of a large cross-sectional dimension for the precision of the estimates. This paper presents some new theory for approximate factor model estimation. Consistency is proved and rates of convergence are derived under conditions that allow for a greater degree of cross-correlation in the model disturbances than previously published results. The rates of convergence depend on the rate at which the cross-sectional correlation of the model disturbances grows as the cross-sectional dimension grows. The consequences for applied economic analysis are discussed.

Suggested Citation

  • Chris Heaton & Victor Solo, 2006. "Estimation of Approximate Factor Models: Is it Important to have a Large Number of Variables?," Research Papers 0605, Macquarie University, Department of Economics.
    • Handle: RePEc:mac:wpaper:0605
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    File URL: http://www.econ.mq.edu.au/research/2006/HeatonEstimtnOfApproxFactorModels.pdf
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    More about this item

    Keywords

    Factor analysis; time series models; principal components;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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