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When a regression model leaves out relevant independent variables, the estimated coefficients can suffer from: Group of answer choices -low R-squared value -reverse causality -omitted

When a regression model leaves out relevant independent variables, the estimated coefficients can suffer from:

Group of answer choices

-low R-squared value

-reverse causality

-omitted variable bias

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