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Improved Nonparametric Confidence Intervals in Time Series Regressions

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Author Info
Joseph P. Romano
Michael Wolf
Abstract

Confidence intervals in econometric time series regressions su er from notorious coverage problems. This is especially true when the dependence in the data is noticeable and sample sizes are small to moderate, as is often the case in empirical studies. This paper suggests using the studentized block bootstrap and discusses practical issues, such as the choice of the block size. A particular data-dependent method is proposed to automate the method. As a side note, it is pointed out that symmetric confidence intervals are preferred over equal-tailed ones, since they exhibit improved coverage accuracy. The improvements in small sample performance are supported by a simulation study.

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Paper provided by Institute for Empirical Research in Economics - IEW in its series IEW - Working Papers with number iewwp273.

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Date of creation: Feb 2006
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Handle: RePEc:zur:iewwpx:273

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Related research
Keywords: Bootstrap; Confidence Intervals; Studentization; Time Series Regressions; Prewhitening;

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Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Politis, D. N. & Romano, Joseph P. & Wolf, Michael, 1997. "Subsampling for heteroskedastic time series," Journal of Econometrics, Elsevier, vol. 81(2), pages 281-317, December. [Downloadable!] (restricted)
  2. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-58, May. [Downloadable!] (restricted)
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  3. Horowitz, Joel L., 2001. "The bootstrap and hypothesis tests in econometrics," Journal of Econometrics, Elsevier, vol. 100(1), pages 37-40, January. [Downloadable!] (restricted)
  4. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-66, July. [Downloadable!] (restricted)
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  5. Newey, Whitney K & West, Kenneth D, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Blackwell Publishing, vol. 61(4), pages 631-53, October. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Joseph P. Romano & Azeem M. Shaikh & Michael Wolf, 2008. "Control of the False Discovery Rate under Dependence using the Bootstrap and Subsampling," IEW - Working Papers iewwp337, Institute for Empirical Research in Economics - IEW. [Downloadable!]
  2. Oliver Ledoit & Michael Wolf, 2008. "Robust Performance Hypothesis Testing with the Sharpe Ratio," IEW - Working Papers iewwp320, Institute for Empirical Research in Economics - IEW. [Downloadable!]
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