FINA3050_Revision 1

A dependent variable is also known as a(n) _____.

• explanatory variable

• control variable

• predictor variable

• response variable

If a change in variable x causes a change in variable y, variable x is called the _____.

• dependent variable

• explained variable

• explanatory variable

• response variable

In the equation y = β₀ + β₁x + u, β₀ is the _____.

• dependent variable

• independent variable

• slope parameter

• intercept parameter

In the equation c = β₀ + β₁ i + u, where c denotes consumption and i denotes income, what is the residual for the 5th observation if c = $500 and predicted ĉ = $475?

• $975

• $300

• $25

• $50

What does the equation ŷ = β₀ + β₁x denote if the regression equation is given?

• The explained sum of squares

• The total sum of squares

• The sample regression function

• The population regression function

If xi and yi are positively correlated in the sample, then the estimated slope is _____.

• Less than zero

• Greater than zero

• Equal to zero

• Equal to one

Consider the following regression model: y = β₀ + β₁x₁ + u. Which of the following is a property of Ordinary Least Square (OLS) estimates?

• The sum, and therefore the sample average of the OLS residuals, is positive.

• The sum of the OLS residuals is negative.

• The sample covariance between the regressors and the OLS residuals is positive.

• The point (x̄, ŷ̄) always lies on the OLS regression line

Which assumption is NOT required for the unbiasedness of OLS?

• The relationship between x and y is linear in parameters.

• The independent variable x has some variation.

• The sample size must be large enough depending on the fields of research, e.g. greater than 1,000 in economics

• The error term has a zero conditional mean given x.

We have a regression model that: wage = β₀ + β₁ education + u. Which of the following best describes heteroskedasticity in the model?

• The variance of u remains constant across different levels of education.

• The estimated impact of education on wage is always unbiased.

• Some education levels have a higher variance of u than the others.

• The OLS residuals always sum to zero.

Given a regression model: wage = β₀ + β₁ education + u. Which condition is necessary for β₁ to be interpreted as a causal effect?

• wage and education must be strongly correlated.

• The sample size must be large enough to apply central limit theorem and law of large number.

• Education must be uncorrelated with the error term u

• The regression must have a high R-squared, i.e. the variation in education explain well the variation in wage.