Diagnose and fix multicollinearity in income regression

Q: Diagnose and fix multicollinearity in income regression

This question evaluates understanding of multicollinearity and regression diagnostics within the Statistics & Math domain, targeting applied regression modeling skills at an intermediate data scientist level.

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Question

You want to estimate the relationship between gender and income using a regression model, while controlling for other covariates such as:

age
education (e.g., degree level or years of schooling)
years_since_degree

Questions:

What is multicollinearity, and is it likely to be present among these predictors? Why?
How would you diagnose multicollinearity in practice (specific checks/metrics)?
If multicollinearity exists, what are practical ways to address it while still answering the question about gender and income? Discuss tradeoffs (interpretability vs prediction).

Diagnose and fix multicollinearity in income regression

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