Forecasting Using Eviews

2841 Words May 15th, 2012 12 Pages
Data

The variables of interest are oil imports to Germany, and temperature in Germany. The latter is used as a leading indicator for the former, to improve on the forecast obtained by the univariate model. Both variables are collected over a time range from January 1985 until and including December 1997, whereas the last year is not used for constructing the optimal forecast, obtained by fitting a model through the data until the end of 1996. This will enable us to forecast the year 1997 using our model, and then comparing it to the actual data. Assuming no large one time shock, meaning that it is not captured by seasonality or cyclical behaviour in the data, occurs in this year, a graphical comparison of our forecast and the whole data
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The insignificant December month can be explained by the little temperature difference compared to the base month January, and roughly the same oil is consumed therefore. Moreover the negative signs of their coefficients are in line with intuition, that in the coldest month January more oil is needed than in all the other month.
The last step before fitting autoregressive and moving averages terms to the data, is to check for unit roots. We will use the augmented Dickey-Fuller test to decide whether the data has a unit root or not. The H0 of the test is that the data has a unit root against the Ha, that the data has no unit root. Table 1.1 shows the result of the augmented Dickey-Fuller test. The p-value of the test is less than 0.01%, so we can

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