INTRODUCTION TO ECONOMETRICS II
ECO 306
NOUN
127
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…[4.25] Now it is reasonable to suppose that lies between 0 and 1, in which case (1 – ) will also lie between 0 and 1. Thus (becomes progressively smaller as s increases. Eventually, there will be a point where the term
( is so small that it can be neglected and we have a model in which all the variables are observable. A lag structure with geometricallydeclining weights, such as this one, is described as having a Koyck distribution. It is highly sparing regarding its constraint, requiring only one parameter more than the static version. Since it is nonlinear in the parameters, OLS should not be used to fit it, for two reasons. First, multicollinearity would almost certainly make the estimates of the coefficients so erratic that they would be worthless – it is precisely this problem that caused us to search for another way of specifying a lag structure. Second, the point estimates of the coefficients would yield conflicting estimates of the parameters.
4.3.4.0 SUMMARY
In this unit, an indirect technique known as the adaptive expectations process is explained as a makeshift solution used in some models. This involves simple learning process for which, in each period, the size of adjustment is proportional to the discrepancy between the actual and expected value.
4.3.5.0 CONCLUSION
The unit introduces the application of regression analysis to time series data, starting with static models and then proceeding to dynamic models with lagged variables used as descriptive variables. In this unit, the adaptive expectations process was mainly used for explanation but the multicollinearity problem in time series models, especially dynamic ones with lagged descriptive variables was also explained. The students may use the reference materials for more understanding and further readings.
4.3.6.0 TUTOR-MARKED ASSIGNMENT
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