Use AIC and BIC to select an ARIMA(p, d, q) model. Estimate the AR and MA parameters and report… 1 answer below »
Use AIC and BIC to select an ARIMA(p, d, q) model. Estimate the AR and MA parameters and report… 1 answer below » | savvyessaywriters.org
(c) (2 points) Use AIC and BIC to select an ARIMA(p, d, q) model. Estimate the AR and MA parameters and report the estimated model. (d) (3 points) Draw a time series plot of the residuals you obtain via estimating the ARIMA model selected in (c). Run the Ljung-Box test (at significance level a = 5%) for the white noise hypothesis and report test results. Do you think the ARIMA is adequate? Explain your answer. (e) (2 points) Test if processes {lnkt}, {lnyt}, {lnwt} and {lnot} have unit roots. For each process, implement the Augmented Dickey-Fuller (ADF) tests to regression equations (4.20)–(4.22) in Enders pp. 206. Report your test results (i.e., test statis- tics, critical values and/or p-values, etc.) as well as rejection decision. (f) (2 points) Use BIC to choose a best fitting ARDL(p, q, l, m) model of the form: a(L)lnyt = a0 + d0t + d1D01 + d2D0 + d3D77 + ?(L)lnkt + ?(L)lnwt + f(L)lnot + Et Report the estimated modelHint: Just try models with max{p, q, l, m} = 3. (g) (2 points) Write out the ECM representation of the ARDL model estimated in Part (f). Comment on your findings. (h) (3 points) Use the Engle-Granger testto test if (lnkt, lnyt, lnwt, lnot) are cointe- grated. Report your test results and rejection decision. Explain your answer. Hint: In Stata, it helps to install the egranger package and use its egranger command.
Attachments:
Assignment-qu….docx
data-Assignme….xlsx
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