According to Gujarat, D. N and Porter, D. C (2009) Basic Econometrics

Remedial measures for multicollinearity include;

Do nothing about it.

Rule of thumb procedures like,

1. A priori information

2. Combining cross-sectional and time series data.

3. Dropping a variable(s) and specification bias.

4. Transformation of variables.

5. Addition of new data.

6. Reducing collinearity in polynomial regressions

If you've never seen Art Goldberger's commentary on multicollinearity, take a look at this--and prepare for a good laugh.

• http://davegiles.blogspot.ca/2011/09/micronumerosity.html

thanks dr Bruce for answer

Use Partial Least Squares Regression (PLS) or Principal Components Analysis, regression methods that cut the number of predictors to a smaller set of uncorrelated components

thanks Dr harit

According to Gujarat, D. N and Porter, D. C (2009) Basic Econometrics

Remedial measures for multicollinearity include;

Do nothing about it.

Rule of thumb procedures like,

1. A priori information

2. Combining cross-sectional and time series data.

3. Dropping a variable(s) and specification bias.

4. Transformation of variables.

5. Addition of new data.

6. Reducing collinearity in polynomial regressions

fine dr olutosin

I support Dr Otekunrin's submission

thanks dr Harry