Question 6 Consider the multiple regression model: Yi = b0 + b1 X1i + b2 X2i + ui . a) Which least squares assumptions are required so that the OLS estimator ^ b1 and ^ b 2 are unbiased? b) Assume...

Hi, Trying to work my head around this question any ideas?

Question 6<br>Consider the multiple regression model: Yi = b0 + b1 X1i + b2 X2i + ui .<br>a) Which least squares assumptions are required so that the OLS estimator ^ b1 and ^ b 2<br>are unbiased?<br>b) Assume that the regression model satisfies the least-squares assumptions. We are<br>interested in b1, the causal effect of X1 on Y. Suppose that X1 and X2 are uncorrelated. We<br>estimate b1 by regressing Y onto X1 (so that X2 is not included in the regression). Does this<br>estimator suffer from omitted variable bias? Explain<br>

Extracted text: Question 6 Consider the multiple regression model: Yi = b0 + b1 X1i + b2 X2i + ui . a) Which least squares assumptions are required so that the OLS estimator ^ b1 and ^ b 2 are unbiased? b) Assume that the regression model satisfies the least-squares assumptions. We are interested in b1, the causal effect of X1 on Y. Suppose that X1 and X2 are uncorrelated. We estimate b1 by regressing Y onto X1 (so that X2 is not included in the regression). Does this estimator suffer from omitted variable bias? Explain

Jun 08, 2022

SOLUTION.PDF

Question 6 Consider the multiple regression model: Yi = b0 + b1 X1i + b2 X2i + ui . a) Which least squares assumptions are required so that the OLS estimator ^ b1 and ^ b 2 are unbiased? b) Assume...

Get Answer To This Question

Related Questions & Answers

Submit New Assignment