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Robust Fixed-b Inference in the Presence of Time-Varying Volatility

Author

Listed:
  • Demetrescu, Matei
  • Hanck, Christoph
  • Kruse-Becher, Robinson

Abstract

Time-varying volatility arises in many macroeconomic and financial applications. While “fixed-b” arguments provide refinements in the use of estimators for the asymptotic variance of GMM estimators, the resulting fixed-b distributions of test statistics are not pivotal under time-varying volatility. Three approaches to robustify inference are investigated: (i) wild bootstrapping, (ii) time transformations and (iii) selection of test statistics and critical values according to the outcome of a pretest for heteroskedasticity. Simulations quantify the distortions from using the original fixed-b approach and compare the effectiveness of the proposed corrections. Overall, the wild bootstrap is to be recommended. An empirical application to the Fama & French five factor model illustrates the relevance of the procedures.

Suggested Citation

  • Demetrescu, Matei & Hanck, Christoph & Kruse-Becher, Robinson, 2026. "Robust Fixed-b Inference in the Presence of Time-Varying Volatility," Econometrics and Statistics, Elsevier, vol. 37(C), pages 154-173.
    • Handle: RePEc:eee:ecosta:v:37:y:2026:i:c:p:154-173
    DOI: 10.1016/j.ecosta.2023.05.003
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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: 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

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