Identification, Estimation and Testing of Conditionally Heteroskedastic Factor Models.Versión Revisada

• Enrique Sentana ^[1] ; Gabriele Fiorentini ^[2]
  1. [1] Centro de Estudios Monetarios y Financieros

     Centro de Estudios Monetarios y Financieros

     Madrid, España

     
  2. [2] Universitat d'Alacant

     Universitat d'Alacant

     Alicante, España

     
• Localización: Documentos de Trabajo ( CEMFI ), Nº. 9 (CEMFI Working Paper No. 9709, July 1997), 1997
• Idioma: inglés
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• Resumen

  • We investigate several important inference issues for factor models with dynamic heteroskedasticity in the common factors. First, we show that such models are identifed if we take into account the time-variation in the variances of the factors. Our results also apply to dynamic versions of the APT, dynamic factor models, and vector auto regressions. Secondly, we propose a consistent two-step estimation procedure which does not rely on knowledge of any factor estimates, and explain how to compute correct standard errors. Thirdly, we develop a simple preliminary LM test for the presence of ARCH effects in the common factors. Finally, we conduct a Monte Carlo analysis of the finite sample properties of the proposed estimators and hypothesis tests.