Test on Applied Econometrics

When an important variable is dropped from a regression model then resultant problem is termed as

• Problem of multicollinearity

• Model misspecification

• Problem of estimation

• Problem of non-normality

Which of the following is not a model selection criteria?

• Adjusted R²

• Akaike Information Criteria (AIC)

• Schwarz information criterion (SIC)

• Residual sum square criterion

Given the regression model: lnY_i = α + βX_i + u_i,

What will be the interpretation of β?

• When X increases by 1 unit then Y will increase by β unit

• When X increases by 1% unit then Y will increase by β%

• When X changes by 1 unit Y changes by β%

• If X increases by 1% then Y increases by β unit

In which form of regression model, the slope coefficient represents elasticity of the dependent variable with respect to the independent variable?

• Linear Regression Model

• Log - Linear Regression Model

• Log-log regression model

• Lin-log regression model

What is the consequence of missing an important variable from a regression model?

• Multicollinearity

• Estimated coefficients may be biased

• Estimated coefficients are BLUE

• Adjusted R square will be more

Which of the following is correct regarding the source of model misspecification?

• Missing an important variable from the model

• Choosing wrong functional form

• Errors committed in computing dependent variable

• All of the above

What is the problem of endogeneity in a regression model?

• When the correlation between the explanatory variables is non-zero

• When exogenous variables are not defined properly

• When there is simultaneous relationship between dependent and independent variable

• When dependent variable is correlated with the error term

What is the consequence of estimating a regression model by overlooking the problem of endogeneity?

• OLS estimator is unbaised and efficient

• OLS estimators are biased and inconsistent

• OLS estimators are consistent and unbiased

• None of the above

Given the following structural equations identify the endogenous variables:

Y = α + β₁X + β₂Z + u_i

Z_{i =} λ + λ₁X + λ₂Y + v_i

• Y and X

• X and Z

• Y and Z

• Only Y

Mention one test to identify a model is mis-specified due to omitted variable.

• Perk test

• Glejer test

• Ramsey RESET test

• Durbin-Watson test