Multiple Regression – 3

When pooling the samples over multiple economic environments in a multiple
regression model, which of the following errors is most likely to occur?

Which model misspecification is most likely to cause multicollinearity?

A multiple regression model has included independent variables that are not linearly
related to the dependent variable. The model is most likely misspecificed due to:

Which of the following misspecifications is most likely to cause serial correlation in
residuals?

In a multiple regression model, the true relationship between the dependent variable (Y) and three independent variables (X1, X2, X3) is:

$Y=2X1+3X2-4X3+5$

However, a researcher misspecifies the model as:

$Y=2X1+3X2+5$

What is the omitted variable bias for the coefficient of X3 in the misspecified model?

If a researcher fails to include a relevant independent variable in a multiple regression model, what is likely to happen to the estimated coefficient for the included variables?

What is the term used to describe the situation where the relationship between the dependent variable and an independent variable is incorrectly specified in a multiple regression model?

How does model misspecification affect the precision of coefficient estimates in a multiple regression model?

In the context of multiple regression, what is the consequence of omitted variable bias due to model misspecification?

What does model misspecification in a multiple regression context refer to?