Question

To study the effect of $X_1$ and $X_2$ on Y, the following regression model is estimated using a large sample:
$Y = a + \beta_1 X_1 + \beta_2X_2 + ∈$
The OLS estimates and standard errors are presented below:
| $a$| $\beta_1$| $\beta_2$
---|---|---|---
Estimates| 2.3| 0.39| 1.8
Standard errors| 1.15| 0.13| 1

Given the above information, which of the following is CORRECT?

• A. $a$ is statistically significant at 1% level, $\beta_1$ is statistically significant at 5% level, and $\beta_2$ is statistically significant at 10% level
• B. $a$ is statistically significant at 1% level, $\beta_1$ is statistically significant at 10% level, and $\beta_2$ is statistically significant at 5% level
• C. $a$ is statistically significant at 5% level, $\beta _1$ is statistically significant at 1% level, and $\beta _2$ is statistically significant at 10% level
• D. $a$ is statistically significant at 5% level, $\beta_1$ is statistically significant at 10% level, and $\beta_2$ is statistically significant at 5% level

Answer 1

Answer: (C)

$a$ is statistically significant at 5% level, $\beta _1$ is statistically significant at 1% level, and $\beta _2$ is statistically significant at 10% level

Answer 2

The correct answer is (C): $a$ is statistically significant at 5% level, $\beta _1$ is statistically significant at 1% level, and $\beta _2$ is statistically significant at 10% level