Adjusted R-Squared Correct Answer-A goodness-of-fit measure in multiple regression analysis that penalises 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 hypot...
Glossary Introductory Econometrics – Wooldridge
Adjusted R-Squared Correct Answer-A goodness-of-fit measure in
multiple regression analysis that penalises 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.
AR(l) Serial Correlation Correct Answer-The errors in a time series
regression model follow an AR(l) model.
Attenuation Bias Correct Answer-Bias in an estimator that is always
toward zero; thus, the expected value of an estimator with attenuation
bias is less in magnitude than the absolute value of the parameter.
Autocorrelation Correct Answer-See serial correlation.
Autoregressive Process of Order One [AR(l)] Correct Answer-A time
series model whose current value depends linearly on its most recent
value plus an unpredictable disturbance.
Auxiliary Regression Correct Answer-A regression used to compute a
test statistic-such as the test statistics for heteroskedasticity and serial
correlation or any other regression that does not estimate the model of
primary interest.
,Average Correct Answer-The sum of n numbers divided by n.
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-See base group.
Bernoulli Random Variable Correct Answer-A random variable that
takes on the values zero or one.
Best Linear Unbiased Estimator (BLUE) Correct Answer-Among all
linear unbiased estimators, the estimator with the smallest variance. OLS
is BLUE, conditional on the sample values of the explanatory variables,
under the Gauss-Markov assumptions.
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 Estimator Correct Answer-An estimator whose expectation, or
sampling mean, is different from the population value it is supposed to
be estimating.
,Biased Towards Zero Correct Answer-A description of an estimator
whose expectation in absolute value is less than the absolute value of the
population parameter.
Binary Response Model Correct Answer-A model for a binary (dummy)
dependent variable.
Binomial Distribution Correct Answer-The probability distribution of
the number of successes out of n independent Bernoulli trials, where
each trial has the same probability of success.
Bivariate Regression Model Correct Answer-See simple linear
regression model.
BLUE Correct Answer-See best linear unbiased estimator.
Causal Effect Correct Answer-A ceteris paribus change in one variable
has an effect on another variable.
Ceteris Paribus Correct Answer-All other relevant factors are held fixed.
, Chi-Square Distribution Correct Answer-A probability distribution
obtained by adding the squares of independent standard normal random
variables. The number of terms in the sum equals the degrees of freedom
in the distribution.
Classical Errors-in-Variables (CEV) Correct Answer-A measurement
error model where the observed measure equals the actual variable plus
an independent, or at least an uncorrelated, measurement error.
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. 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-See R-squared.
Conditional Distribution Correct Answer-The probability distribution of
one random variable, given the values of one or more other random
variables.
Conditional Expectation Correct Answer-The expected or average value
of one random variable, called the dependent or explained variable, that
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