Collinearity is sometimes described as a problem with the data, not the model. Rather than filling the scatterplot of X1

Question:

Collinearity is sometimes described as a problem with the data, not the model. Rather than filling the scatterplot of X1 on X2, the data concentrate along a diagonal. For example, the following plot shows monthly percentage changes in the whole stock market and the S&P 500 (in excess of the risk-free rate of return). The data span the same period considered in the text, running monthly from 1995 through 2011.
Collinearity is sometimes described as a problem with the data,

(a) Data for two months (February and March of 2000, identified as × in the plot) deviate from the pattern evident in other months. What makes these months unusual?
(b) If you were to use both returns on the market and those on the S&P 500 as explanatory variables in the same regression, would these two months be leveraged?
(c) Would you want to use these months in the regression or exclude them from the multiple regression?

This problem has been solved!


Do you need an answer to a question different from the above? Ask your question!

Step by Step Answer:

Related Book For  answer-question
View Solution
Create a free account to access the answer
Cannot find your solution?
Post a FREE question now and get an answer within minutes. * Average response time.
Question Posted: July 14, 2015 09:49:15