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ECMT6003: Applied Business Forecasting

Practice Questions and Data Application (Week 9)

1. Obtain the reduced forms of the following two VAR models:

 =  +  ,    VaT(ut ) = I2

\             \            \                     \                \                                  \           

Interpret your findings.

2.  (Data Exercise) Download the dataset named “Kilian2009old.dta”. Again, oil indicates the % change in global oil production and output is the measure of real economic activities. The variable price denotes the logged real crude oil price.

(a) In the last tutorial, you ordered the variables Yt  = (oil, output, price)\ .  Estimate the responses of the oil price in responding to a structural shock on the oil supply.

(b) Instead, order the variables as (output,oil, price)\  and estimate the responses of the oil price in responding to a structural shock on the oil supply.  Compare your estimation result from that in (a). What does it imply?

3.  (Data Exercise) Download the dataset named “SWecmt.dta”. It is quarterly data from FRED and has three variables: the growth rate of hours of worked, hwg, the growth rate of the real GDP, gdpg and the change in inflation difinf.

(a) Suppose that, in the long run, (i) hours of work are not affected by a shock on output

or inflation and (ii) GDP is not affected by the inflation. This implies a recursive order in the variables.  Obtain the optimal lag by using AIC or BIC criteria and estimate a

reduced form VAR.

(b) Impose a long run restriction in (a) and estimate the structural impulse response IRF(h) for h = 1, . . . , 10. Visualize the estimated impulse responses with their confidence band. Interpret your finding.

(c) Estimate the forecast error decomposition due to a change in outputs.  Interpret your finding.