National open university of nigeria introduction to econometrics II eco 356

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Introduction to Econometrics ECO 356 Course Guide and Course Material
Introduction to Econometrics ECO 356 Course Guide and Course Material

2.3.4.0 MULTICOLLINEARITY

2.3.3.4 Consistency
Once the fourth Gauss–Markov condition is satisfied, OLS yields consistent estimates in the multiple regression models, as is the casein thesimple regression model. One condition for consistency is that when n becomes large, the population variance of the estimator of each regression coefficient tends to 0, and the distribution falls to a spike. The other condition for consistency is since the estimator is unbiased, the spike would be located at the true value.
2.3.4.0 MULTICOLLINEARITY
In most situations, the available data for use in multiple regression analysis would not provide significant solutions to problems at hand. The reason being that the standard errors are very high, or the t test ratios are very low.Which means the confidence intervals for such parameters are very wide. A situation of this nature occurs when the explanatory variables show little variation and high intercorrelations. Multicollinearity is the aspect of the situation where the explanatory variables are highly intercorrelated.

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