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• W3003898858 abstract "This paper develops a finite-sample corrected inference for the efficient generalized method of moments (GMM) in time series. To capture a higher-order uncertainty embodied in estimating the time series GMM weight matrix, we extend the finite-sample corrected variance formula of Windmeijer (2005) to heteroskedasticity autocorrelated robust (HAR) inference. Using fixed-smoothing asymptotics, we show that our finite-sample corrected test statistics lead to standard asymptotic t or F critical values and suffer from less over-rejection of the null hypothesis than existing GMM procedures on finite-samples, including continuously updating GMM. Not only does our finite-sample corrected variance formula correct for the bias arising from the plugged-in long-run variance estimation, but it is also not exposed to a potential side effect of Windmeijer’s formula, which can introduce an additional source of over-rejection after the correction." @default.
• W3003898858 created "2020-02-07" @default.
• W3003898858 creator A5015202601 @default.
• W3003898858 creator A5057209508 @default.
• W3003898858 date "2023-05-01" @default.
• W3003898858 modified "2023-09-25" @default.
• W3003898858 title "Finite-sample corrected inference for two-step GMM in time series" @default.
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• W3003898858 doi "https://doi.org/10.1016/j.jeconom.2021.12.007" @default.
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