econometrics, statistics

econometrics, statistics

1. Use augmented Dickey-Fuller tests to determine whether your chosen series is a unit root process. Transform and re-test as appropriate to determine the order of integration
2. Define and estimate the ACF and PACF for your stationary time series (i.e. after differencing your data if appropriate).
3. Select the most appropriate ARIMA time series model for your data on the basis of ACF and PACF plots and appropriate experimentation.
4. Withhold ten per cent of the most recent data and re-estimate two of the equations you estimated in (3). Using the re-estimated equations calculate forecasts (for the withheld data) for each model using Excel. Judge which forecasts are ‘best’ using a criterion such as RMSE. .
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