Question

1. To see if the variable Xi2 belongs in the model Yi=β1+β2Xi+ui, Ramsey’s RESET test would estimate the linear model, obtaining the estimated Y_i values from this model [i.e., Yi=β1+β2Xi ] and then estimating the model Yi=β1+β2Xi+α3Yi2+ui and testing the significance of α3. Prove that, if α3 turns out to be statistically significant in the preceding (RESET) equation, it is the same thing as estimating the following model directly: Yi=β1+β2Xi+β3Xi2+ui

Answer 1

Solution:-

Given

a)

The multicolinearity problem arises due to collinearity between independent variable and error term. This multicollinearity problem as nothing to do with model but problem due to deficiency in data.

b)

The limited data means having limited information's which may give biased or insignificant results. This caused by deficiency of data can be resolved with suitable model.

c)

The multicollinearity problem arises due to collinearity between independent variable and error term. This multicollinearity problem as nothing to do with model but problem due to deficiency in data.

d)

In time series data, only time is sole independent variable, other than this, it has no significance. which is a deficiency in the data.