Chapter Summary:
Any time series have four different components, i.e. trend, cycles, seasonality and irregular pattern. Irregular pattern is too hard to define for any time series. On the other hand, often seasonal data is used for the analysis, but mostly we found seasonally adjusted data set. The reaming elements of the time series are trend and cycles, which we have to see deeply.
These components to be focused deeply because economic theory just tell us the direction of relationship between different variables, but not the magnitude. The accuracy of the magnitude depends upon how accurately we estimate the trend and the cycles of the series. One of the main objective of the macro-econometrian is forecasting, and reliability of the forecasting also depends upon, how accurately we estimated the trend and cycles. Hence, the more deeply and accurately we estimate the trend and cycles of series the more accurately and reliable would be our conclusion.
The knowledge of the magnitude is important for the decision because it varies from country to country, for example Okun’s law. Hence on the bases of the magnitude of the relationship decision maker give their suggestions.
There are some major issues which are mainly focus by the macro-econometrican, i.e. identification of time trend and cyclic component of the time series, unit root testing, structural changes etc.