Econometrics

In a linear regression model, the constant variance of error (residual) refers to the assumption of

• Zero mean value of error term

• Homoscedasticity

• No autocorrelation

• No multicollinearity

In the model

• ꞵ1 measures the effect of X1 on Y after controlling the effect of X2 on Y

• ꞵ2 measures the effect of X2 on Y after controlling the effect of ꞵ0 on Y

• ꞵ2 measures the effect of X2 on Y after controlling the effect of ꞵ0 and ꞵ1 on Y

• ꞵ1 measures the effect of X1 on Y after controlling the effect of ꞵ0 and ꞵ2 on Y

The measure of the proportion of variance (change) in dependent  variable (Y) explained by the independent variables (X2, X3….) is given by

• F

• R

• t

• R2 (R square)

Multiple co-efficient of determination measures the

• Goodness of fit of multiple regression model

• Homoscedasticity of multiple regression model

• Autocorrelation of multiple regression model

• Multicollinearity of multiple regression model

The value of Adjusted R2 is always less than R2. This statement is

• Incorrect

• Correct

• Depends on k value

• Depends on n value

In the equation, the partial regression coefficients are given by

• ꞵ1 and ꞵ2

• ꞵ0 and ꞵ1

• ꞵ0 and ꞵ2

• X1 and X2