ECON 3350/7350: Applied Econometrics for Macroeconomics and Finance
Tutorial 10: VAR Models – II
We continue with the data file money dem.csv we were using last week.
• 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.
We had determined the lag length of the (reduced) VAR model for the system of vari-
ables (dlrgdpt, dlrm2t, drst) to be p = 8. We will continue using this lag length.
1. Using the VAR(8) model estimated in Tutorial 9, we now study the impulse re- sponse function (IRF) and forecast error variance decomposition (FEVD) to ex- plore the dynamic effects in the system. We first use a Cholesky decomposition and thus we need to decide on an ordering.
(a) Write the VAR(p) in the notation A(L)xt = a0 + et.
(b) Compute the IRFs for all the possible orderings of the system and study the responses. Is the system sensitive to ordering? Choose the most reasonable ordering and explain your answer.
(c) Using the ordering chosen in Part (b), compute the FEVDs and comment on your findings.
2. Consider the following set of restrictions to identify the structural system.
e1t 1 0 0ε1t e2t =c21 1 c23 ε2t ,
e3t 001 ε3t
where c21 and c23 are the corresponding elements of the B−1 matrix. Provide a
plausible economic interpretation for these restrictions. Is this system identified?
3. Test the existence of Granger causality among (dlrgdpt, dlrm2t, drst). What is the null hypothesis for the test? State your conclusions.
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