ECON 3350/7350: Applied Econometrics for Macroeconomics and Finance
Tutorial 9: VAR Models – I
The data file money dem.csv contains quarterly observations for the following vari- ables from 1959Q1 to 2001Q1
• RGDP: real US GDP
• GDP: nominal GDP
• M2: Money supply
• Tb3mo: Three-month rate on US Treasury Bills
Load the data in Stata and generate the following variables:
• Real GDP Growth: dlrgdpt = ln(RGDPt/RGDPt−1);
• GDP Deflator: pricet = GDPt/RGDPt;
• Real Money supply growth: dlrm2t = ln(M2t/pricet) − ln(M2t−1/pricet−1); • Changes in the short-term interest rate: drst = tb3mot − tb3mot−1.
Answer the following questions:
1. FitaVAR(p)modeltothesystem(dlrgdpt,dlrm2t,drst)withaninterceptvector. In this question, we conduct tests to decide on an adequate lag order.
(a) Use the AIC, BIC and LR test to select the lag order of the VAR up to a maximum of 16 lags.
(b) Fit the VAR(4) and VAR(8) models to the data and compute the residual autocorrelations.
(c) As a final check, estimate the VAR(4) and VAR(8) and provide the AIC, BIC, and log-likelihood ratio.
(d) Check the stationarity of the chosen VAR(p).
(e) How many intercept and slope coefficients do you estimate for the the cho-
sen VAR(p)?
(f) Write out the companion form of the chosen VAR(p)? What is the advantage
of working with the VAR companion form?
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