Explain how increasing f1 in an AR(1) model changes the behavior of time series Yt…

Question 1. Explain how increasing f1 in an AR(1) model changes the behavior of time series Yt

.

Question 2. Define an AR(2) model and describe how its AC and PAC functions look like.

Question 3. Define an MA(4) model and describe how its AC and PAC functions look like.

Question 4. Explain the role of the adjusted R2

, AIC and SIC, in model selection.

Question 5. Consider Fed forecasting inflation. Is it likely to have (1) a symmetric loss function, or (2)

an asymmetric loss function with larger losses for negative forecast errors, or (3) an asymmetric loss

function with larger losses for positive forecast errors? Explain.

Question 6. Declare the lowest forecast horizon h where the forecast of an MA(5) process is equal to

the unconditional mean.

Question 7. Declare the lowest forecast horizon h where the forecast of an AR(8) process is equal to

the unconditional mean.

Question 8. Define an ARMA(1,3) model and describe how its AC function is different from an MA(3)

model.

Question 9. Define an ARMA(2,1) model and describe how its PAC function is different from an AR(2)

model.

Question 10. Write down the four criteria we use to select the best model among candidates of AR,

MA, and ARMA models.

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