Virginia TechHomework Assignment No. 3Due date: June 27, XXXXXXXXXXUse the IPGFN dataset. It contains monthly industrial production data. The observations are notseasonally adjusted. Test and correct...

Virginia TechHomework Assignment No. 3Due date: June 27, 20201. Use the IPGFN dataset. It contains monthly industrial production data. The observations are notseasonally adjusted. Test and correct for:a. Seasonalityb. Structural breaksc. Parameter instabilityReport your fingings and explain what you have done.2. Use the dataset Unemployment.xls. It contains the following variables: unemployment rate, 1-year T-Bond rate, BBB-AAA bond spread, changes in monthly housing starts. Caution: you mayhave to perform some data transformation. Which variables should be included? What is theoptimal lag-length? Do you achieve an improvement in fitting the data?a. Fit the unemployment rate data in file using an AR or ARMA model. Describe how youchoose the lag-lengths (number of lags) in each case, and which model you choose (asthe best fit of the data) and why?b. Then proceed to include the following variables in your regression, effectivelyestimating ARX or ARMAX models: 1-year T-Bond rate, BBB-AAA bond spread, changesin monthly housing starts. Do you improve your estimation? Explain.3. Now fit the Unemployment.xls using VAR analysis. Write down the structural and the standardVAR representations of the data.a. Explain the logic behind your choice of variables and their ordering.b. Assume that the optimal lag length is p = 1. Derive the identification requirements forthe structural VAR parameters. Use the Choleski decomposition.c. Still assuming that p =1 is optimal, change the order of variables (by switching the firstand the last variable in part a) in your VAR. Show how your results change.d. Show how you choose the optimal lag length for your standard VAR mode.e. Estimate your standard VAR model. Can you recover the structural parameters? Explain.Try this for both variable ordering specifications in b. and c. sections.f. Derive the impulse-response functions for your chosen model. You need to recover theimpact multipliers first.g. Conduct an empirical impulse response analysis. Explain your findings.
Jun 27, 2021
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