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Empirical-Likelihood-Based Confidence Intervals For Conditional Variance In Heteroskedastic Regression Models


  • Chan, Ngai Hang
  • Peng, Liang
  • Zhang, Dabao


Fan and Yao (1998) proposed an efficient method to estimate the conditional variance of heteroskedastic regression models. Chen, Cheng, and Peng (2009) applied variance reduction techniques to the estimator of Fan and Yao (1998) and proposed a new estimator for conditional variance to account for the skewness of financial data. In this paper, we apply empirical likelihood methods to construct confidence intervals for the conditional variance based on the estimator of Fan and Yao (1998) and the reduced variance modification of Chen et al. (2009). Simulation studies and data analysis demonstrate the advantage of the empirical likelihood method over the normal approximation method.

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  • Chan, Ngai Hang & Peng, Liang & Zhang, Dabao, 2011. "Empirical-Likelihood-Based Confidence Intervals For Conditional Variance In Heteroskedastic Regression Models," Econometric Theory, Cambridge University Press, vol. 27(01), pages 154-177, February.
  • Handle: RePEc:cup:etheor:v:27:y:2011:i:01:p:154-177_00

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    Cited by:

    1. Otsu, Taisuke & Xu, Ke-Li & Matsushita, Yukitoshi, 2015. "Empirical likelihood for regression discontinuity design," Journal of Econometrics, Elsevier, vol. 186(1), pages 94-112.
    2. repec:cep:stiecm:/2014/573 is not listed on IDEAS

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