Econometrics Final MC
the general form for the t-statistic is
t = estimate - hypothesized value / standard error
which of the following is a statistic that can be used to test hypotheses about a single population parameter
t statistic
which of the following assumptions is needed for the unusual standard errors to be valid when differencing with more than two time periods
the differenced idiosyncratic error or delta u unrestrcited is uncorrelated over time
the average treatment effect measures
the effect of a policy or program on the dependent variable
a test for heteroskedasticity can be significant if
the functional form of the regression model is misspecified
weighted least squares estimation is used only when
the functional forms of the error variances is known
consider the following simple regression model y=β0 + β1x1 + u. The variable z is a poor instrument for x if ____
there is a low correlation between z and x
which of the following is true
a functional form misspecification can occur if the level of a variable is used when the logarithm is more appropriate
which of the following statements is true of hypothesis testing
a restricted model will always have fewer parameters than its unrestricted model
the order condition for identification of an equation requires that there should be
at least as many excluded exogenous explanatory variables as there are included endogenous explanatory variables
R^2 is the ratio of the explained variation compared to the total variation
true
econometrics is the branch of economics that
develops and uses statistical methods for estimating economic relationships
a _______ variable is used to incorporate qualitative information in a regression model
dummy
the inclusion of another binary variable in this model that takes a value of 1 if a person is uneducated, will give rise to the problem of
dummy variable trap
sample selection based on the dependent variable is called
endogenous sample selection
which of the following types of sampling always causes bias or inconsistency in the OLS estimators
endogenous sampling
the random effects estimate is identifcal to the fixed effects estimate if the estimated transformation parameter is generalized least squares estimation that eliminates serial correlaton between error terms is _____
equal to one
the error term "u" is usually referred to as the
error term
which of the following is true of experimental data
experimental data are collected in laboratory environments in the natural sciences
if a change in variable x causes a change in variable y, variable x is called the
explanatory variable
two stage least squares estimation cannot be applied to a panel data set
false
whenever the dependent variables takes on just a few values it is close to a normal distribution
false
an economist want to study the effect of income on savings, he collected data on 120 identical twins. which of the following methods of estimation is the most suitable method, if income is correlated with the unobserved family effect
fixed effects estimation
a pooled OLS estimaator that is based on the time-demeaned variables is called the
fixed effects estimator
a MLR suffers from functional form misspecification when it does not properly account for the realtionship between the dependent and the observed explanatory variables
true
a data set is called an unbalanced panel if it has missing years for at least some cross-sectional units in the sample
true
a larger error variance makes it difficult to estimate the partial effect of any of the independent variables on the dependent variable
true
a natural measure of the association between two random variables is the correlation coefficient
true
a problem that often arises in policy and program evaluation is that individuals choose whether or not to participate in certain behaviors or programs
true
an economic model consists of mathematical equations that describe various relationships between economic variables
true
if a new independent variable is added to a regression equation, the adjusted R2 increases only if the absolute value of the t stasitic of the new variable is greater than 1
true
a change in the unit of measurement of the dependent variable in a model does not lead to a change in
goodness of fit of the regression
if the calculated value fo the t statistic is greater than the critical value, the null hypothesis is rejected is favor of the alternative hypothesis
true
increasing the number of overidentifying restrictions can cause severe biases in two stage least squares estimators
true
multicollinearity among the independent variables in a linear regression model causes the heteroskedasticity-robust standard errors to be large
true
one way of organizing two periods of panel data is to have only one record per cross-sectional unit
true
pooled ordinary least squares estimation is commonly applied to cluster samples when eliminating a cluster effect via fixed effects is infeasible or undesirable
true
predictions of a dependent variable are subject to sampling variation
true
standard errors must always be positive
true
studentized residuals are obtained for the original OLS residuals by dividing them by an estimate of their standard deviation
true
the MLR regression model with a binary dependent variable is called the linear probability model
true
the dummy variable coefficient for a particular group represents the estimated difference in intercepts between that group and the base group
true
the generalized least squares estimators for correcting heteroskedasticity are called WLS estimators
true
the linear probability model always contains heteroskedasticity when the dependent variable is a binary variable unless all of the slopes parameters are zero
true
the measurement error is the difference between the actual value of a variable and its reported value
true
the notion of ceteris paribus means "all factors being equal"
true
the term linear in a MLR model means that the equation is linear in parameters
true
the two stage least squares estimator is less efficient than the OLS estimator when the explanatory variables are exogenous
true
the value of the estimated transformation parameter in generalized least square estimation that eliminates serial correlation in error term indicated whether the estimates are likely to be closer to the pooled OLS or the fixed effects estimates
true
two period panel data is used for program evaluationa and policy analysis
true
what should be the degrees of freedom for fixed effects estimation if the data set includes "N" cross sectional units over "T" time periods and the regression model has "k" independent variables
NT-N-k
if a regression equation has only one explanatory variable, say x1, its standardized coefficient must lie in the range of
-1 to 1
if the SSR is 66 and the SST is 90, what is the R-squared vvalue (co-efficient of determination)
.27
if the SSE is 35 and the SST is 49 what is the SSR
14
find the degrees of freedom in a regression model that has 10 observations and 7 independent variable
2
if there are 5 ethnic groups, how many dummy variables should be included in the regression equation
4
to make predictions of logarithmic dependent variables, they first have to be converted to their level forms
false
if the total sum of squares (SST) in a regression equation is 81, and the residual sum of squares (SSR) is 25, what is the explained sum of squares (SSE)
56
what does B1 imply
B1 measures the cetris paribus effect of x1 on y
Consider the following simple regression model: y = β0 + β1x1 + u. Suppose z is an instrument for x. Which of the following conditions denotes instrument exogeneity
Cov(z,u) = 0
Consider the following simple regression model y=β0 + β1x1 + u. Suppose z is an instrument for x. Which of the following conditions denotes instrument relevance
Cov(z,x) ≠ 0
the estimator obtained through regression on quasi-demeaned data is called the _______
random effects estimator
the heteroskedasticity robust ____ is also called the heteroskedasticity robust Wald statistic
F statistic
which of the following indicates a functional form misspecfiication in E(y/x)
OLS estimates are positive while WLS estimates are negative
which of the following is a difference between least absolute deviations and OLS estimation
OLS is more sensitive to outlying observations than LAD
The sampling variance for the instrumental variables (IV) estimator is larger than the variance for the ordinary least square estimators (OLS) because ____
R2<1
what is the equation for adjusted R2
R2 = 1 - [SSR/(n -k - 1)]/[SST/(n - 1
which of the following is true of R^2
R^2 shows what percentage of the total variation in the dependent variable, Y, is exlpained by the explanatory variables
Consider the following simple regression model y=β0 + β1x1 + u. Suppose z is an instrument for x. Which of the following statements is true
The instrumental variables estimator is always biased if Cov(x,u)≠0
if the first four Gauss Markov assumptions hold true, and the error term contain heteroskedasticity, then
Var(ui|xi) = σi2
Consider the equation, Y = β1 + β2X2 + u. A null hypothesis, H0: β2 = 0 states that:
X2 has no impact on Y
which of the following is true of dependent variables
a dependent variable can be binary
which of the following is a difference between panel and pooled cross-sectional data
a panel data set consists of data on the same cross-sectional units over a given period of time while a pooled data set conists of data on different cross-sectional units over a given period of time
changing the unit of measurement of any independent varibale, where log of the dependent variable appears in the regression
affects only the intercept coefficient
the linear probability model contains heteroskedasticity unless
all the slode parameters are zero
which of the following is a nonlinear regression model
y = 1 / (β0 + β1x) + u
standardized coefficients are also referred to as
beta coefficients
a variable is standardized in the sample
by subtracting off its mean and dividing by its standard deviation
the general approach to obtaining fully robust standard errors and test statistics in the context of panel data is known as
clustering
which of the following statements is true about confidence intervals
confidence intervals in a CLM provide a range or likely values for the population parameter
a data set is a balanced panel if it
consists of data for each cross sectional unit over the same time period
which of the following is true of a natural experiment
control and treatment groups in a natural experiment arise dddue to an exogenous event
Consider the following simple regression model y=β0 + β1x1 + u. Suppose z is an instrument for x. if Cov(z,u) = 0 and Cov(z,x) ≠ 0, the value of β1 in terms of population covariances is ____
cov(z,y)/cov(z,x)
data on the income of law graduates collected at different times during the same year is
cross sectional data
a data set that consists of a sample of individuals, households, firms, cities, states, countries, or a variety of other units, taken at a given point in time, is called a
cross-sectional data set
the sample covariance between the regressors and the OLS residuals is always positive
false
an empirical analysis relies on _____ to test a theory
data
which of the following refers to panel data
data on the birth rate, death rate, and population growth rate in developing countries over a 10-year period
which of the following is an example of time series data
data on the gross domestic product of a country over a period of 10 years
the parameters of an econometric model _____
describe the strength of the relationship between the variable under study adn the factors affecting it
the variance of the slope estimator increases as the error variance decreases
false
t-stat is
estimate - hypothesized value / standard error
residual analysis refers to the process of
examining individual observations to see whether the actual value of a dependent variable differs from the predicted value
there are n-1 degrees of freedom in OLS residuals
false
which of the following is used to test multiple linear restrictions
f test
A cross-sectional data set consists of observations on a variable or several variables over time
false
H1: B1 doesnt = 0, where B1 is a regression coefficient associated with an explanatory vairable, represents a one-sided alternative hypothesis
false
R^2 decreases when an independent variable is added to a MLR model
false
a binary variable is a variable whose value changes with a change in the number of observations
false
a dummy variable trap arises when a single dummy variable describes a given number of groups
false
a natural experiment occurs when an endogenous event changes the environment in whcih individuals, famiies, firms, or cities operate
false
a time series data is also called a longitudinal set
false
an explanatory variable is called exogenous if it is correlated with the error term
false
an explanatory variable is said to be exogeneous if it is correlated with the error term
false
beta coefficients are always greater than standardized coefficients
false
experimental data are sometimes called retrospective data
false
f statistic can be used to test nonnested models
false
first differenced estimation gives unbiased estimators if the regression model includes a lagged dependent variable
false
if a random sample is drawn at each time period, pooling the resulting random samples gives us a panel data set
false
if the Breusch-Pagan test for heteroskedasticity results in a large p-value, the null hypothesis of homoskedasticity is rejected
false
if the instrumental variable estimator has an upward bias, the OLS estimator always has a downward bias
false
in a random effects model, we assume that the unobserved effect is correlated with each explanatory variables
false
instrumental variables cannot be used for estimating a regression equation if the regression model suffers from the measurement error problem
false
the correlated random effects approach cannot be applied to models with many time-varying explanatory variables
false
the interpretatoin of goodness-of-fit measures changes in the presence of heteroskedasticity
false
the key assumption for the general MLR model is that all factors in the unobserved error term be correlated with the explanatory variables
false
the least absolute deivations estimators in a linear model minimize the sum of squared residuals
false
which of the following correctly identifies a reason why some authors prefer to report the SE rather than t stat
having standard errors makes it easier to compute confidence intervals
which of the following is true of measurement error
if measurement error in an independent variables is uncorrelated with the variable, the OLS estimators are unbiased
which of the following is true
in weighted least squares estimation, less weight is given to oberservations with a higher error variance
______ has a causal effect on ____
incomefi, consumption
indiosyncratic error is the error that occurs due to
incorrect measurement of an economic variable
Consider the following simple regression model: y = β0 + β1x1 + u. In order to obtain consistent estimators of β0 and β1, when x and u are correlated, a new variable z is introduced into the model which satisfies the following two conditions: Cov(z,x)≠0 and Cov (z,u)=0. The variable z is called a(n) _____ variable.
instrumental
In the equation y = β0+β1x + u,β0 is the ____
intercept parameter
the random effects approach
is preferred to pooled OLS because RE is generally more efficient
a Chow test
is used to determine how much multiple regression differs across two groups
a proxy variable______
is used when data on a key independent variable is unavailable
which of the following is a drawback of including proxy variables in a regression model
it exacerbates multicollinearity
the error term in a regression equation is said to exhibit homoskedasticity if
it has the same variance for all values of the explanatory variable
which of the following si true of Chow test
it is only valid under homoskedasticity
which of the following is a reason for using the correlated random effects approach
it provides a way to include time-constant explanatory variables in a fixed effects analysis
which of the following true of RESET test
it tests if the function form of a regression model is misspecified
the value of R^2 always
lies between 0 and 1
which of the following correctly identifies a limitation of log transformation of vairables
log transformations cannot be used if a variable takes on zero or negative values
the term _____ refers to the problem of a small sample size
micronumerosity
exclusion of a relevant variable from a multiple linear regression model leads to the problem of
misspecification of the model
which of the following statements is true when y>0
models using log(y) as the dependent variable will satisfy CLM assumptions more closely than models using the leel of y
which of the following models is sued quite often to capture decreasing or increasing marginal effects of a variable
models with quadratic functions
high, but not perfect, correlation between two or more independent variables is called ________
multi-collinearity
two equations form a nonnested model when
neither equation is a special case of the other
the assumption that there are no exact linear relationships among the independent variables in a multiple linear regression model fails if _____, where n is the sample size and k is the number of parameters
n<k+1
the procedure of comparing different instrumental variables estimates of the same parameter is an example of testing _____
overidentifying restrictions
first differenced estimation in a panel data analysis is subject to serious biases if
one or more of the explanatory variables are measured incorrectly
the necessary condition for identification of an equation is called the
order condition
rating is an _____ variable
ordinal
if an independent variable in a multiple linear regression model is an exact linear combinaton of other independent vairables, the model suffers from the problem of
perfect collinearity
a predicted value of a dependent variable
represents the expected value of the dependent variable given particular values for the explanatory variables
a dependent variable is also known as a
response variable
if the simple regression has hats over the parameters this is the
sample regression function
what is the estimated value of the slope parameter when the regression equation passes through the origin
sigma (xi,yi)/ sigma x^2
B2 is a
slope parameter
which of the following is the first step in empirical economic analysis
specification of an econometric model
the method of data collection in which the population is divided into nonoverlapping, exhaustive groups is called
stratified sampling
a normal variable is standardized by
subtracting off its mean form it and dividing by its standard deviation
The explained sum of squares for the regression function, yi=β0+β1x1+u1 , is defined as _____
sum of (yi -yhat)^2
which of the following statemetns is true
taking a log of a nonnormal distribution yields a distribution that is closer to normal
which of the following is true of the correlated random effects approach
the CRE approach considers that the unobserved effect is correlated with the average level of explanatory variables
which of the following statements is true
the F statistic is always nonnegative as SSRrestricted is never smaller than SSRunrestricted
which of the following tests is used to compare the OLS estimates and the WLS estimates
the Hausman test
which of the following is true of heteroskedasticity
the OLS estimators are not the best linear unbiased estimators iff heteroskedasticity is present
which of the following statements is true
the OLS standard errors are incorrect when there is cluster effect
which of the following is true of the White test
the White test assumes thata the square of the error term ina regression model is uncorrelated with all the independent variables, their squares and cross products
which of the following Gauss Markov assumptions is violated by the linear probability model
the assumption of constant variance of the error term
which of the following assumptions is known as exclusion restrictions
the assumption that an exogenous explanatory variable is excluded from a regression model and is uncorrelated with the error term
which of the following test helps in the detection of heteroskedasticity
the breusch pagan test
which of the following assumptions is required for two-stage least squares estimation method
the error term has a zero mean
which of the following is assumed for establishing the unbiasedness of OLS estimates
the error term has the same variance given any value of the explanatory variable
which of the following assumptions is needed for the plug-in solution to the ommited variable problem to provide consisent estimators
the error term in the regression model is uncorrelated with all the independent variables
which of the following assumptions is required for two stage least squares estimation with time series data but not required for two-stage least square estimation with cross sectional data
the error terms are not serially correlated
which of the following assumptions is required for obtaining unbiased fixed effect estimators
the explanatory variables are strictly exogenous
which of the following is a difference between a fixed effects estimators and a first-difference estimator
the fixed effects estimator is more efficient thana the first-difference estimator when the idiosyncratic errors are serially uncorrelated
which of the following is true of the OLS t statistic
the heteroskedasticity robust t statistics are justified only if the sample size is large
which of the following assumptions is required to obtain a first-differenced estimator in a two period panel data analysis
the idiosyncratic error at each time period is uncorrelated with the explanatory variables in both time periods
the gauss-markov theorum will not hold if _____
the independent variables have exact linear relationships among them
a regression model suffers from functional form misspecification if _______
the interaction term is omitted
which of the following is a property of dummy variable regression
the major statistics obtained form this method are identical to that obtained from regression on time-demeaned data
the classical errors-in-variables assumption is that
the measurement error is uncorrelated with the unobserved explanatory variable
which of the following problems can arise in policy analysis and program evaluation using a MLR model
the model can produce predicted probabilities that are less than zero and greater than one
what will you conclude about a regression model if the Breusch Pagan test results in a small p-value
the model contains heteroskedasticity
the assumption of strict exogeneity in a regression model means that
the model does not include a lagged dependent variable as a regressor
which of the following is true
the notion of 'ceteris paribus' plays an important role in causal analysis
which of the following is a difference between the White test and the Breusch Pagan test
the number of regressors used in the White test is larger than the number of regressors used in the Breusch Pagan test
a measurement error occurs in a regression model when
the observed value of a variable used in the model differs from its actul value
which of the following correctly identifies an advantage of using adjusted R2 over R2
the penalty of adding new independetn variables is bettter understood through adjusted R2
Consider the following regression model: y = β0 + β1x1 + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics
the point (x',y') always lies on the OLS regression line
the normality assumption implies that
the population error u is independent of the explanatory variables and is normally distributed with mean zero and variance
the significance level of a test is
the probability of rejecting the null hypothesis when it is true
the test for overidentifying restrictions is valid if ______
the regression model exhibits homoskedasticity
pooling independent cross sections across time is useful in prodiving precise estimators if ______
the relationship between the dependent variable and at least some of the independent variables remains constant over time
which of the following is true of two stage least squares estimators
the two stage least squares estimators are biased if the regression model exhibits multicollinearity
if OLS estimation is subject to a heterogeneity bias if ________
the unobserved effect is correlated with the observed explanatory variables
which of the following assumptions is required for obtaining unbiased random effect estimators
the unobserved effect is independent of all explanatory variables in all time periods
which of the following statements is true
the upper bound of the confidence interval for a regression coefficient is given by B + (critical value x standard error)(B1)
a regression model exhibits heterogeneity if
there are unobserved factors affecting the dependent variable that do not changes overtime
in the correlated random effects approach, the regression model includes
time averages as seperate explanatory variables
a data set that consists of observations on a variable or several variables over time is called a _____ data set
time series
nonexperimental data is called
time series data
which of the following types of variables cannot be included in a fixed effects model
time-constant independent variable
which of the following is a reason for using independently pooled cross sections
to increase the sample size
composite error is the error that occurs due to
unobserved factors affecting a dependent variable
which of the following is true of dummy variables
value of 0/1
in the regression of y on x, the error term exhibits heteroskedastiity if
var(y/x) is a function of x
in a regression modell, which of the following will be described using a binary variable?
whether it rained on a particular day or it did not
onsider the following regression model: log(y) = β0 + β1x1 + β2x1^2 + β3x3 + u. This model will suffer from functional form misspecification if ____
x1^2 is omitted from the model
in which of the following cases, is y a discrete variable
y indicates the number of children in a family
in which of the following cases, the dependent variable is binary
y indicates whether an adult is a college drop out
In the equation y = β0 +β1x + u, what is the estimated value of β0
y−β1x