Essay
To estimate dynamic causal effects, your textbook presents the distributed lag regression model, the autoregressive distributed lag model, and a quasi-difference representation of the distributed lag model with autoregressive errors. Using a simple example, such as a distributed lag model with only the current and past value of X and an AR(1)model for the error term, discuss how these models are related. In each case suggest estimation methods and evaluate the relative merit in using one rather than the other.
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Q6: It has been argued that Canada's
Q7: The distributed lag regression model requires estimation
Q8: The impact effect is the<br>A)zero period dynamic
Q9: Quasi differences in Y<sub>t</sub> are defined as<br>A)Y<sub>t</sub>
Q10: Sensitivity analysis of the results may include
Q12: A seasonal binary (or indicator or dummy)variable,
Q13: The long-run cumulative dynamic multiplier<br>A)cannot be calculated
Q14: (Requires Appendix material)Your textbook states that in
Q15: A model that attracted quite a bit
Q16: In time series data, it is useful