This Article Investigates The Construction Of Skewness-Adjusted Confidence Intervals
And Joint Confidence Bands For Impulse Response Functions From Vector
Autoregressive Models. Three Different Implementations Of The Skewness Adjustment
Are Investigated. The Methods Are Based On A Bootstrap Algorithm That
Adjusts Mean And Skewness Of The Bootstrap Distribution Of The Autoregressive
Coefficients Before The Impulse Response Functions Are Computed. Using Extensive
Monte Carlo Simulations, The Methods Are Shown To Improve The Coverage
Accuracy In Small And Medium Sized Samples And For Unit Root Processes For
Both Known And Unknown Lag Orders
