Revisiting simple linear regression with autocorrelated errors

By Jaechoul Lee, Robert B. Lund. 2004

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Global temperature evolution 1979–2010 (2011, background): “For a generic autocorrelation structure ordinary least squares regression still gives an unbiased estimate of the trend rate, but the correction factor for standard errors of the coefficients is (Lee and Lund 2004) ν = 1+ 2 ∑ j ρj, (A.5) where ρj is the autocorrelation at lag j.”
Comparison of algorithms for incoming atmospheric long‐wave radiation (2009, methodology): “Effective sample sizes were computed from the expression given by Lee and Lund [2004] adjusting for the lag-one autocorrelation of the residual time series.”