X 3 etc are various controls he retains the residuals

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, X 3 , etc. are various controls.  He retains the residuals from this regression for  subsequent analysis.  Which of his conclusions are correct?  (More than one can be  correct) a. He constructs a scatter plot of the residuals versus computers/worker.  He sees  very little relationship.  Because in order for there to be omitted variables bias  there must be a relationship between computers per worker and the error, he  concludes that his OLS estimate of  β 1  is likely to be close to the causal effect. Page      1     of 3 **DONT FORGET BACK OF PAGE**    
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b. The R 2  in this regression is large, 0.94.  Because most of the variation in y is  already explained, he concludes there is unlikely to be any omitted variables bias. c. Controlling for other things could help reduce omitted variables bias, and would  almost definitely increase the R 2  of the regression. d. He shows that other city-level variables, like capital per worker and  R&D  spending, are uncorrelated with computers per worker.  He argues this helps make  the case that his slope estimates are unbiased. 4. [3 points] A small slope estimate with a large standard error could mean (select one) a. The true effect is small b. The true effect is large c. Both
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