2833 Words12 Pages

MULTICOLLINEARITY
Questions:
1. What is the nature of multicollinearity?
2. Is multicollinearity really a problem?
3. What are the theoretical consequences of multicollinearity?
4. What are the practical consequences of multicollinearity?
5. In practice, how does one detect multicollinearity?
6. If it is desirable to eliminate the problem of multicollinearity, what remedial measures are available?
1. THE NATURE
In cases of perfect linear relationship or perfect multicollinearity among explanatory variables, we cannot obtain unique estimates of all parameters. Since we cannot obtain unique estimates, we cannot draw any statistical inferences about them from a given sample. Estimation and hypothesis testing about individual regression coefficients are therefore not possible. It is a dead end issue.
2. NEAR OR IMPERFECT MULTICOLLINEARITY
Perfect multicollinearity seldom arises with actual data. Its occurance often results from correctable mistakes such as the dummy variable trap, or including variables such as 1n(x) and in the same equation. Once spotted, corrections can be made. The real problem is with imperfect multicollinearity.
Multicollinearity is not a condition that either exists or does not exist in economic functions, but rather a phenomenon inherent in most relationships due to the nature of economic magnitudes. It can arise because there is a tendency for economic variables to move together over time. Also, there is an increasing tendency to use lagged variables of some explanatory variables e.g. in investment functions, distributed lags concerning past levels of economic activity are introduced.
We will get results, but are they to be believed? The determinant of will exist and hence its inverse. Can see that the inverse will have very large elements which will lead to very large

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