I have some problem to solve this problem. Can I ask for what command I should use?
Q. This problem set illustrates the estimation of VAR models using monthly time series of the growth of the hourly earnings of Manufacturing (hwages t), inflation rate (infla t) and unemployment rate
(unrate t) for the United States.The data is obtained from the Federal Reserve Bank of St.Louis (https://fred.stlouisfed.org) database, seasonally adjusted, monthly frequency, from 1961:m1 to 2022:m2.
Let yt = (infla t, unrate t, hwages t)' be an (3 × 1) - vector that collects the information concerning the variables of interest:
1. Estimate the order of the VAR(p) model for yt, using a constant for the determinstic component (default option of varsoc command).
2. Estimate the VAR(p) model for yt using varbasic command.
3. Analyze the estimation output: statistical significance of parameters, VAR stability and IRF analysis.
4. Granger causality analysis (vargranger command). Based on the slides of the theory, discuss the interpretation of the output that is obtained.
Q. This problem set illustrates the estimation of VAR models using monthly time series of the growth of the hourly earnings of Manufacturing (hwages t), inflation rate (infla t) and unemployment rate
(unrate t) for the United States.The data is obtained from the Federal Reserve Bank of St.Louis (https://fred.stlouisfed.org) database, seasonally adjusted, monthly frequency, from 1961:m1 to 2022:m2.
Let yt = (infla t, unrate t, hwages t)' be an (3 × 1) - vector that collects the information concerning the variables of interest:
1. Estimate the order of the VAR(p) model for yt, using a constant for the determinstic component (default option of varsoc command).
2. Estimate the VAR(p) model for yt using varbasic command.
3. Analyze the estimation output: statistical significance of parameters, VAR stability and IRF analysis.
4. Granger causality analysis (vargranger command). Based on the slides of the theory, discuss the interpretation of the output that is obtained.
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