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Chapter 6
Adjusted R -Squared
A goodness-of-fit measure in multiple regression analysis that
penalizes additional explanatoryvariables by using a degrees of
freedom adjustment in estimating the error variance.
BetaCoefficients
See standardized coefficients.
Bootstrap A resampling method that draws random samples, with
replacement, from the original dataset.
BootstrapStandardError
A standard error obtained as the sample standard deviation of an
estimate across all bootstrapsamples.
InteractionEffect
In multiple regression, the partial effect of one explanatory
variable depends on the value of adifferent explanatory
variable.
NonnestedModels
Two (or more) models where no model can be written as a special
case of the other byimposing restrictions on the parameters.
OverControlling
In a multiple regression model, including explanatory variables
that should not be held fixedwhen studying the ceteris paribus
effect of one or more other explanatory variables; this canoccur
when variables that are themselves outcomes of an intervention or a
policy are includedamong the regressors.
Population R -Squared
In the population, the fraction of the variation in the
dependent variable that is explained by theexplanatory
variables.
Prediction The estimate of an outcome obtained by plugging
specific values of the explanatory variablesinto an estimated
model, usually a multiple regression model.
PredictionError The difference between the actual outcome and a
prediction of that outcome.
PredictionInterval
A confidence interval for an unknown outcome on a dependent
variable in a multipleregression model.
QuadraticFunctions
Functions that contain squares of one or more explanatory
variables; they capture diminishingor increasing effects on the
dependent variable.
ResamplingMethod
A technique for approximating standard errors (and distributions
of test statistics) whereby aseries of samples are obtained from
the original data set and estimates are computed for
eachsubsample.
ResidualAnalysis
A type of analysis that studies the sign and size of residuals
for particular observations after amultiple regression model has
been estimated.
SmearingEstimate
A retransformation method particularly useful for predicting the
level of a response variablewhen a linear model has been estimated
for the natural log of the response variable.
StandardizedCoefficients
Regression coefficients that measure the standard deviation
change in the dependent variablegiven a one standard deviation
increase in an independent variable.
Variance ofthe PredictionError
The variance in the error that arises when predicting a future
value of the dependent variablebased on an estimated multiple
regression equation.
Chapter 7
Base Group The group represented by the overall intercept in a
multiple regression model that includesdummy explanatory
variables.
BenchmarkGroup
See base group.
BinaryVariable
See dummy variable.
ChowStatistic
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).
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Control Group In program evaluation, the group that does not
participate in the program.
Difference inSlopes A description of a model where some slope
parameters may differ by group or time period.
DummyVariable A variable that takes on the value zero or
one.
DummyVariable Trap
The mistake of including too many dummy variables among the
independent variables; itoccurs when an overall intercept is in the
model and a dummy variable is included for eachgroup.
ExperimentalGroup
See treatment group.
InteractionTerm An independent variable in a regression model
that is the product of two explanatory variables.
Intercept Shift The intercept in a regression model differs by
group or time period.
LinearProbabilityModel (LPM)
A binary response model where the response probability
OrdinalVariable A variable where the ordering of the values
conveys information but the magnitude of thevalues does not.
PercentCorrectlyPredicted
In a binary response model, the percentage of times the
prediction of zero or one coincideswith the actual outcome.
PolicyAnalysis
An empirical analysis that uses econometric methods to evaluate
the effects of a certainpolicy.
ProgramEvaluation
An analysis of a particular private or public program using
econometric methods to obtain thecausal effect of the program.
ResponseProbability
In a binary response model, the probability that the dependent
variable takes on the value one,conditional on explanatory
variables.
Self-Selection Deciding on an action based on the likely
benefits, or costs, of taking that action.
TreatmentGroup In program evaluation, the group that
participates in the program.
Uncentered R -Squared
The R -squared computed without subtracting the sample average
of the dependent variablewhen obtaining the total sum of squares
(SST).
