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A Dynamic Index Model for Large Cross Sections

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  • Danny Quah
  • Thomas J. Sargent

Abstract

This paper shows how standard methods can be used to formulate and estimate a dynamic index model for random fields - stochastic processes indexed by time and cross section where the time-series and cross section dimensions are comparable in magnitude. We use these study dynamic co-movements of sectoral employment in the US economy. The dynamics of employment in sixty sectors is well explained using only two unobservable factors; those factors are also strongly correlated with GNP growth.

Suggested Citation

  • Danny Quah & Thomas J. Sargent, 1993. "A Dynamic Index Model for Large Cross Sections," CEP Discussion Papers dp0132, Centre for Economic Performance, LSE.
    • Handle: RePEc:cep:cepdps:dp0132
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    References listed on IDEAS

    as
    1. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    2. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
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