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Is there a function for the Newey West estimator?
Software implementations. In R, the packages sandwich and plm include a function for the Newey–West estimator. In Stata, the command newey produces Newey–West standard errors for coefficients estimated by OLS regression. In MATLAB, the command hac in the Econometrics toolbox produces the Newey–West estimator (among others).
How does the Newey West method handle autocorrelation?
The Newey-West method handles autocorrelation with lags up to h, and so it is assumed that lags larger than h can be ignored. Note too that Newey-West not only corrects for autocorrelation it also corrects for heteroscedasticity (heterogeneity of variances).
How to find Newey-West standard errors in SAS?
In Gretl, the option –robust to several estimation commands (such as ols) in the context of a time-series dataset produces Newey–West standard errors. In SAS, the Newey-West corrected standard errors can be obtained in PROC AUTOREG and PROC MODEL
Which is the first sum in the Newey West formula?
The first sum in the formula is the value of XTSX when there is no autocorrelation (i.e. h = 0). The Newey-West method handles autocorrelation with lags up to h, and so it is assumed that lags larger than h can be ignored.
When did Whitney Newey and Kenneth West create the estimator?
It was devised by Whitney K. Newey and Kenneth D. West in 1987, although there are a number of later variants. The estimator is used to try to overcome autocorrelation (also called serial correlation), and heteroskedasticity in the error terms in the models, often for regressions applied to time series data.
What are the functions of the Newey and West function?
A set of functions implementing the Newey & West (1987, 1994) heteroscedasticity and autocorrelation consistent (HAC) covariance matrix estimators.
Is the Newey-West standard error heteroskedastic?
newey produces Newey–West standard errors for coefficients estimated by OLS regression. The error structure is assumed to be heteroskedastic and possibly autocorrelated up to some lag. Model lag(#) specifies the maximum lag to be considered in the autocorrelation structure.