Consider the GDFM with one factor and two lags, (boldsymbol{z}_{t}=boldsymbol{P}_{0} f_{t}+boldsymbol{P}_{1} f_{t-1}+boldsymbol{P}_{2} f_{t-3}+boldsymbol{n}_{t}), where the factor follows
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Consider the GDFM with one factor and two lags, \(\boldsymbol{z}_{t}=\boldsymbol{P}_{0} f_{t}+\boldsymbol{P}_{1} f_{t-1}+\boldsymbol{P}_{2} f_{t-3}+\boldsymbol{n}_{t}\), where the factor follows \(f_{t}=\phi f_{t-1}+u_{t}\). Prove that this model can be written as a DFM with one factor, \(\boldsymbol{z}_{t}=\boldsymbol{P}^{*} f_{t}^{*}+\boldsymbol{n}_{t}^{*}\) with \(f_{t}^{*}=\phi f_{t-1}^{*}+u_{t}^{*}\).
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Related Book For
Statistical Learning For Big Dependent Data
ISBN: 9781119417385
1st Edition
Authors: Daniel Peña, Ruey S. Tsay
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