Introductory
Econometrics 2025/2026 Actual
Exam Complete All Questions And
Correct Detailed Answers (Verified
Answers) |Already Graded A+
Adjusted R-Squared - CORRECT ANSWER-A goodness-of-fit measure in multiple
regression analysis that penalizes additional explanatory variables by using a degrees
of freedom adjustment in estimating the error variance.
Alternative Hypothesis - CORRECT ANSWER-The hypothesis against which the null
hypothesis is tested.
Base Group - CORRECT ANSWER-The group represented by the overall intercept in a
multiple regression model that includes dummy explanatory variables.
Benchmark Group - CORRECT ANSWER-The group represented by the overall
intercept in a multiple regression model that includes dummy explanatory variables.
Best Linear Unbiased Estimator (BLUE) - CORRECT ANSWER-Among all linear
unbiased estimators, the one with the smallest variance. That is the case, conditional on
the sample values of the explanatory variables, under the Gauss-Markov assumptions.
Beta Coefficients - CORRECT ANSWER-Regression coefficients that measure the
standard deviation change in the dependent variable given a one standard deviation
increase in an independent variable.
Bias - CORRECT ANSWER-The difference between the expected value of an estimator
and the population value that the estimator is supposed to be estimating
Biased Toward Zero - CORRECT ANSWER-A description of an estimator whose
expectation in absolute value is less than the value of the population parameter
Binary Variable - CORRECT ANSWER-A variable that takes on the value zero or one.
Bootstrap - CORRECT ANSWER-A resampling method that draws random samples,
with replacement, from the original data set.
Bootstrap Standard Error - CORRECT ANSWER-A standard error obtained as the
sample standard deviation of an estimate across all bootstrap samples
, Breusch-Pagan Test for Heteroskedasticity (BP Test) - CORRECT ANSWER-A test for
heteroskedasticity where the squared OLS residuals are regressed on the explanatory
variables in the model.
Causal Effect - CORRECT ANSWER-A ceteris paribus change in one variable that has
an effect on another variable
Ceteris Paribus - CORRECT ANSWER-All other relevant factors are held fixed
Chow Statistic - CORRECT ANSWER-An F statistic for testing the equality of
regression parameters across different groups (say, men and women) or time periods
(say, before and after a policy change).
Classical Linear Model - CORRECT ANSWER-The multiple linear regression model
under the full set of classical linear model assumptions.
Classical Linear Model (CLM) Assumptions - CORRECT ANSWER-The ideal set of
assumptions for multiple regression analysis: for cross-sectional analysis, assumptions
MLR.1-6, and for time series analysis, Assumptions TS.1-6. The assumptions include
linearity in the parameters, no perfect collinearity, the zero conditional mean
assumption, homoskedasticity, no serial correlation, and normality of the errors.
Coefficient of Determination - CORRECT ANSWER-In a multiple regression model, the
proportion of the total sample variation in the dependent variable that is explained by
the independent variable.
Conditional Expectation - CORRECT ANSWER-The expected or average value of one
random variable, called the dependent or explained variable, that depends on the
values of one or more other variables, called the independent or explanatory variables.
Confidence Interval - CORRECT ANSWER-A rule used to construct a random interval
so that a certain percentage of all data sets, determined by critical level, yields an
interval that contains the population value.
Constant Elasticity Model - CORRECT ANSWER-A model where the elasticity of the
dependent variable, with respect to an explanatory variable, is constant; in multiple
regression, both variables appear in logarithmic form.
Control Group - CORRECT ANSWER-In program evaluation, the group that does not
participate in the program.
Control Variable - CORRECT ANSWER-In regression analysis, a variable that is used
to explain variation in the dependent variable.
Covariate - CORRECT ANSWER-In regression analysis, a variable that is used to
explain variation in the dependent variable.
Econometrics 2025/2026 Actual
Exam Complete All Questions And
Correct Detailed Answers (Verified
Answers) |Already Graded A+
Adjusted R-Squared - CORRECT ANSWER-A goodness-of-fit measure in multiple
regression analysis that penalizes additional explanatory variables by using a degrees
of freedom adjustment in estimating the error variance.
Alternative Hypothesis - CORRECT ANSWER-The hypothesis against which the null
hypothesis is tested.
Base Group - CORRECT ANSWER-The group represented by the overall intercept in a
multiple regression model that includes dummy explanatory variables.
Benchmark Group - CORRECT ANSWER-The group represented by the overall
intercept in a multiple regression model that includes dummy explanatory variables.
Best Linear Unbiased Estimator (BLUE) - CORRECT ANSWER-Among all linear
unbiased estimators, the one with the smallest variance. That is the case, conditional on
the sample values of the explanatory variables, under the Gauss-Markov assumptions.
Beta Coefficients - CORRECT ANSWER-Regression coefficients that measure the
standard deviation change in the dependent variable given a one standard deviation
increase in an independent variable.
Bias - CORRECT ANSWER-The difference between the expected value of an estimator
and the population value that the estimator is supposed to be estimating
Biased Toward Zero - CORRECT ANSWER-A description of an estimator whose
expectation in absolute value is less than the value of the population parameter
Binary Variable - CORRECT ANSWER-A variable that takes on the value zero or one.
Bootstrap - CORRECT ANSWER-A resampling method that draws random samples,
with replacement, from the original data set.
Bootstrap Standard Error - CORRECT ANSWER-A standard error obtained as the
sample standard deviation of an estimate across all bootstrap samples
, Breusch-Pagan Test for Heteroskedasticity (BP Test) - CORRECT ANSWER-A test for
heteroskedasticity where the squared OLS residuals are regressed on the explanatory
variables in the model.
Causal Effect - CORRECT ANSWER-A ceteris paribus change in one variable that has
an effect on another variable
Ceteris Paribus - CORRECT ANSWER-All other relevant factors are held fixed
Chow Statistic - CORRECT ANSWER-An F statistic for testing the equality of
regression parameters across different groups (say, men and women) or time periods
(say, before and after a policy change).
Classical Linear Model - CORRECT ANSWER-The multiple linear regression model
under the full set of classical linear model assumptions.
Classical Linear Model (CLM) Assumptions - CORRECT ANSWER-The ideal set of
assumptions for multiple regression analysis: for cross-sectional analysis, assumptions
MLR.1-6, and for time series analysis, Assumptions TS.1-6. The assumptions include
linearity in the parameters, no perfect collinearity, the zero conditional mean
assumption, homoskedasticity, no serial correlation, and normality of the errors.
Coefficient of Determination - CORRECT ANSWER-In a multiple regression model, the
proportion of the total sample variation in the dependent variable that is explained by
the independent variable.
Conditional Expectation - CORRECT ANSWER-The expected or average value of one
random variable, called the dependent or explained variable, that depends on the
values of one or more other variables, called the independent or explanatory variables.
Confidence Interval - CORRECT ANSWER-A rule used to construct a random interval
so that a certain percentage of all data sets, determined by critical level, yields an
interval that contains the population value.
Constant Elasticity Model - CORRECT ANSWER-A model where the elasticity of the
dependent variable, with respect to an explanatory variable, is constant; in multiple
regression, both variables appear in logarithmic form.
Control Group - CORRECT ANSWER-In program evaluation, the group that does not
participate in the program.
Control Variable - CORRECT ANSWER-In regression analysis, a variable that is used
to explain variation in the dependent variable.
Covariate - CORRECT ANSWER-In regression analysis, a variable that is used to
explain variation in the dependent variable.
