Suppose that you estimate the regression function $\text { Stock Price } _ { i } = \beta _ { 0 } + \beta _ { 1 } \text { Wealth } _ { i } + \beta _ { 2 } \text { Earnings } _ { i } + \beta _ { 3 } \text { Rainfall } _ { i } + \varepsilon _ { i }$
You might be concerned that $\hat { \beta } _ { 2 }$
May have a large standard error because
A)investor wealth is likely an irrelevant independent variable.
B)the amount of rainfall is likely an irrelevant independent variable.
C)investor wealth is likely measured with error.
D)the first letter in the firm's name is likely an omitted variable.

Question

Quizplus · Accepted Answer

Rainfall is likely an irrelevant independent variable for predicting stock prices, which could lead to a large standard error for the coefficient estimate of a relevant variable like earnings due to noise or spurious correlations introduced by including irrelevant variables in the model.

Suppose That You Estimate the Regression Function You Might Be Concerned That