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A New Jackknife Variance Estimator for Time-Series and Panel Regressions

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Abstract

We introduce a new jackknife variance estimator for time-series and panel-data regressions. The novelty in our approach is that we first rotate the data using a particular choice of trigonometric basis functions. This rotation removes serial correlation in a broad class of time-series processes, including random walks, and enables the use of the conventional leave-one-out jackknife on the transformed space of the regressors and residuals. The procedure is tuning-parameter free and naturally adapts to the degree of persistence of the data. We prove the asymptotic validity of our variance estimator under general conditions and demonstrate excellent finite-sample properties in extensive simulation experiments, spanning a wide range of time-series and panel-data designs.

Suggested Citation

  • Richard K. Crump & Nikolay Gospodinov & Ignacio Lopez Gaffney, 2024. "A New Jackknife Variance Estimator for Time-Series and Panel Regressions," Staff Reports 1133, Federal Reserve Bank of New York.
    • Handle: RePEc:fip:fednsr:99064
    DOI: 10.59576/sr.1133
    Note: Revised February 2026. Previous title: “A Jackknife Variance Estimator for Panel Regressions.”
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    References listed on IDEAS

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    1. Richard K. Crump & Nikolay Gospodinov & Ignacio Lopez Gaffney, 2024. "A Simple Diagnostic for Time-Series and Panel-Data Regressions," Staff Reports 1132, Federal Reserve Bank of New York.

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    Keywords

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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