What is Newey West lag?
The Newey–West (1987) variance estimator is an extension that produces consistent estimates when there is autocorrelation in addition to possible heteroskedasticity. The Newey–West variance estimator handles autocorrelation up to and including a lag of m, where m is specified by stipulating the lag() option.
What do Newey West standard errors do?
Newey-West standard error method is a robust method/estimator which is very accurate when there is presence of heteroskedasticity and autocorrelation. Also, when in the panel model there is a lagged value of an indicator then this method is very consistent.
What is HAC estimate?
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. The abbreviation “HAC,” sometimes used for the estimator, stands for “heteroskedasticity and autocorrelation consistent.”
What is prais winsten regression?
Statistics > Time series > Prais-Winsten regression. Description. prais uses the generalized least-squares method to estimate the parameters in a linear regression model in which the errors are serially correlated. Specifically, the errors are assumed to follow a first-order autoregressive process.
Why do we use HAC standard errors?
We got to appoint that HAC standard errors (also called HAC estimators) are derived from the work of Newey & West (1987) where the objective was to build a robust approach to handle the usual problems of time series associated with serial correlation and heteroskedasticity.
What is HC1 R?
The HC stands for Heteroskedasticity-Consistent. Heteroskedasticity is another word for non-constant. The formula for “HC1” is as follows: HC1:nn−kˆμ2i. where ˆμ2i refers to squared residuals, n is the number of observations, and k is the number of coefficients.
What does robust command do in Stata?
robust is a programmer’s command that computes a robust variance estimator based on varlist of equation-level scores and a covariance matrix.
How do I choose Max lag?
There is no theory behind the max lag. But according to the rule of thumb, the max lag number can be set to log of the number of observations. Once you set max lag number based on the number of observations then info criteria like AIC or BIC help to identify optimal lag order.