6. Consider the MA (1) process yt = 2.3 0.95et-1 + et a. What is the optimal forecast for time periods T+1, T+2, and T+3. Write your answer as a function of y₁, Y2, Y3, ... YT e₁,e₂, and or ... eT b. Now suppose that et = 0.4 and ET-1 = -1.2. Re-answer part (a).

Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter14: Discrete Dynamical Systems
Section14.3: Determining Stability
Problem 18E
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6. Consider the MA(1) process yt
2.3 — 0.95ер-1+ et
a. What is the optimal forecast for time periods T+1, T+2, and T+3. Write
аnd
your answer as a function of y1, y2, Y3, ... YT
e1, e2,
or
... eT
b. Now suppose that er = 0.4 and er-1 = -1.2. Re-answer part (a).
7. The FRED codes for housing starts in the Midwest are HOUSTMW and
HOUSTMWNSA (seasonally adjusted and not seasonally adjusted, respectively).
For the South they are HOUSTS and HOUSTSNSA. Graph the autocorrelation
functions for these four series. Comment and discuss.
8. Use the real GDP growth data from FRED code A191RL1Q225SBEA. Run an
AR(1) regression on these data (with constant). Save the residuals from that
regression (predict e, residuals). Graph the time series of the residuals. Graph
the autocorrelation function of the residuals. Comment and discuss.
Transcribed Image Text:6. Consider the MA(1) process yt 2.3 — 0.95ер-1+ et a. What is the optimal forecast for time periods T+1, T+2, and T+3. Write аnd your answer as a function of y1, y2, Y3, ... YT e1, e2, or ... eT b. Now suppose that er = 0.4 and er-1 = -1.2. Re-answer part (a). 7. The FRED codes for housing starts in the Midwest are HOUSTMW and HOUSTMWNSA (seasonally adjusted and not seasonally adjusted, respectively). For the South they are HOUSTS and HOUSTSNSA. Graph the autocorrelation functions for these four series. Comment and discuss. 8. Use the real GDP growth data from FRED code A191RL1Q225SBEA. Run an AR(1) regression on these data (with constant). Save the residuals from that regression (predict e, residuals). Graph the time series of the residuals. Graph the autocorrelation function of the residuals. Comment and discuss.
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