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How do I get to Newey-West in eviews?
To use the Newey-West HAC method, select the Options tab and select HAC (Newey-West) in the Coefficient covariance matrix drop-down. As before, you may use the checkbox to remove the default d.f. Adjustment. Press the HAC options button to change the options for the LRCOV estimate.
What happens if errors are serially correlated?
Serial correlation occurs in time-series studies when the errors associated with a given period carry over into future periods. For example, when predicting the growth of stock dividends, an overestimate in one year will lead to overestimates in succeeding years.
Is Multicollinearity same as autocorrelation?
Autocorrelation refers to a correlation between the values of an independent variable, while multicollinearity refers to a correlation between two or more independent variables.
How to let Stata choose the optimal lag for Newey-West?
Can you confirm that it performs OLS regression with Newey-West robust standard errors, automatically choosing an optimal lag, for the regression of one y variable and three x variables (which I put in). I don’t understand what “Kernel=Bartlett” and “Bandwith=17” means, for example.
How to display the lag length employed by neweywest?
However, you can easily display the lag length employed by NeweyWest () and also extract it using bwNeweyWest (). For simple replication, let’s consider the following (non-sensical because non-time-series) linear model:
How do you choose the optimal laglength in a time series?
Join ResearchGate to ask questions, get input, and advance your work. Lag determination always goes with data and an underlying model. At the end of the day the issue is that the data given follow the given model with order equal to the lag. In general, we use all criteria cited above and after that we take the smallest lag length from them.
Is there a rule of thumb or simple method to get the lag?
However is there a rule of thumb or a simple method to get the lag? I don’t think that you necessarily need to fix the lag length across regressions. Due to the different model specifications there may be slightly different amounts of autocorrelation in the residuals that you have to adjust for.