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Simultaneous inference for time-varying models

Author

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  • Sayar Karmakar
  • Stefan Richter
  • Wei Biao Wu

Abstract

A general class of time-varying regression models is considered in this paper. We estimate the regression coefficients by using local linear M-estimation. For these estimators, weak Bahadur representations are obtained and are used to construct simultaneous confidence bands. For practical implementation, we propose a bootstrap based method to circumvent the slow logarithmic convergence of the theoretical simultaneous bands. Our results substantially generalize and unify the treatments for several time-varying regression and auto-regression models. The performance for ARCH and GARCH models is studied in simulations and a few real-life applications of our study are presented through analysis of some popular financial datasets.

Suggested Citation

  • Sayar Karmakar & Stefan Richter & Wei Biao Wu, 2020. "Simultaneous inference for time-varying models," Papers 2011.13157, arXiv.org, revised Mar 2021.
    • Handle: RePEc:arx:papers:2011.13157
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    Cited by:

    1. Demirer, Riza & Gupta, Rangan & Salisu, Afees A. & van Eyden, Reneé, 2023. "Firm-level business uncertainty and the predictability of the aggregate U.S. stock market volatility during the COVID-19 pandemic," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 295-302.
    2. Karmakar, Sayar & Demirer, Riza & Gupta, Rangan, 2021. "Bitcoin mining activity and volatility dynamics in the power market," Economics Letters, Elsevier, vol. 209(C).
    3. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).
    4. Rangan Gupta & Sayar Karmakar & Christian Pierdzioch, 2024. "Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 487-513, July.
    5. David Gabauer & Rangan Gupta & Sayar Karmakar & Joshua Nielsen, 2022. "Stock Market Bubbles and the Forecastability of Gold Returns (and Volatility)," Working Papers 202228, University of Pretoria, Department of Economics.

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