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HARREG: Stata module to estimate time-series regression with HAR standard errors and fixed-b inference

Author

Listed:
  • Eben Lazarus

    (UC Berkeley)

  • Daniel J. Lewis

    (University College London)

Programming Language

Abstract

harreg fits a time-series regression by OLS and reports heteroskedasticity- and autocorrelation-robust (HAR) standard errors based on fixed-b asymptotics, as recommended by Lazarus, Lewis, Stock, and Watson (LLSW, 2018) and Lazarus, Lewis, and Stock (LLS, 2021). The default estimator is the equal-weighted cosine (EWC) with nu = floor(0.41*T^(2/3)), as recommended by LLSW (2018). Alternative long-run variance (LRV) estimators include equal-weighted periodogram (EWP), Newey-West/Bartlett (NW), and quadratic spectral (QS). The default rules for the truncation parameter (nw, qs) and degrees of freedom (ewc, ewp) are designed to optimize the tradeoff between test size (controlling the probability of false rejection) and size-adjusted power, following LLSW (2018). For ewc and ewp, inference uses t(nu) and F(m,nu-m+1) reference distributions, where m is the number of restrictions tested. For nw and qs, harreg simulates the fixed-b null distribution to obtain p-values and critical values.

Suggested Citation

  • Eben Lazarus & Daniel J. Lewis, 2026. "HARREG: Stata module to estimate time-series regression with HAR standard errors and fixed-b inference," Statistical Software Components S459711, Boston College Department of Economics.
  • Handle: RePEc:boc:bocode:s459711
    Note: This module should be installed from within Stata by typing "ssc install harreg". The module is made available under terms of the MIT license (https://opensource.org/licenses/MIT).
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