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