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Author Question: By including another variable in the regression, you will A) decrease the regression R2 if that ... (Read 206 times)

2125004343

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By including another variable in the regression, you will
 
  A) decrease the regression R2 if that variable is important.
  B) eliminate the possibility of omitted variable bias from excluding that variable.
  C) look at the t-statistic of the coefficient of that variable and include the variable only if the coefficient is statistically significant at the 1 level.
  D) decrease the variance of the estimator of the coefficients of interest.

Question 2

If you included both time and entity fixed effects in the regression model which includes a constant, then
 
  A) one of the explanatory variables needs to be excluded to avoid perfect multicollinearity.
  B) you can use the before and after specification even for T > 2.
  C) you must exclude one of the entity binary variables and one of the time binary variables for the OLS estimator to exist.
  D) the OLS estimator no longer exists.



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ecabral0

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Answer to Question 1

Answer: B

Answer to Question 2

Answer: C




2125004343

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Reply 2 on: Jun 29, 2018
Great answer, keep it coming :)


marict

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Reply 3 on: Yesterday
Gracias!

 

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