2008The New Palgrave Dictionary of EconomicsRequires access

Heteroskedasticity and Autocorrelation Corrections

Kenneth D. West

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Abstract

Many time series studies, including in particular those estimated by generalized method of moments, involve disturbances that are serially correlated and, possibly, conditionally heteroskedastic. The serial correlation and heteroskedasticity often are of unknown form. Corrections for serial correlation and heteroskedasticity are required for inference and efficient estimation. This article surveys procedures to implement such corrections.

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Many time series studies, including in particular those estimated by generalized method of moments, involve disturbances that are serially correlated and, possibly, conditionally heteroskedastic. The serial correlation and heteroskedasticity often are of unknown form. Corrections for serial correlation and heteroskedasticity are required for inference and efficient estimation. This article surveys procedures to implement such corrections.

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Available abstract

Many time series studies, including in particular those estimated by generalized method of moments, involve disturbances that are serially correlated and, possibly, conditionally heteroskedastic. The serial correlation and heteroskedasticity often are of unknown form. Corrections for serial correlation and heteroskedasticity are required for inference and efficient estimation. This article surveys procedures to implement such corrections.

Key concepts: Heteroscedasticity, Autocorrelation, Econometrics, Inference, Statistics, Mathematics, Series (stratigraphy), Estimation

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