Question

True or False:

a. ( ) One advantage of fixed effects estimation is that inferences are more robust to measurement error in the explanatory variables of interest compared with OLS estimation.

b. ( ) The consistency of Fixed Effects estimators relies on weaker (more realistic) assumptions than those required for consistency of the Random Effects estimator. In this sense, we can say that Fixed Effects estimation is more robust than Random Effects estimation.

c. ( ) Estimating a model using the Within Estimator is equivalent to estimating the same model using the OLS Estimator after all variables have been transformed through time-demeaning.

d. ( ) Assumptions about the time series dimension are never necessary for the validity of panel data methods.

Answer #1

a. This is true that One advantage of fixed effects estimation is that inferences are more robust to measurement error in the explanatory variables of interest compared with OLS estimation, because OLS is gives best linear unbiased estimation of parameters.

b.this is false that The consistency of Fixed Effects estimators relies on weaker (more realistic) assumptions than those required for consistency of the Random Effects estimator. In this sense, we can say that Fixed Effects estimation is more robust than Random Effects estimation.

c. This is false that Estimating a model using the Within Estimator is equivalent to estimating the same model using the OLS Estimator after all variables have been transformed through time-demeaning.

d. This is false that the Assumptions about the time series dimension are never necessary for the validity of panel data methods.

True or False:
1) ____ In the context of a 2SLS estimation, it is usually risky
to use models that are non-linear in the parameters to produce
first-stage estimates, since in this case we can no longer
guarantee that the first-stage residuals will be uncorrelated with
the regressors included in the second-stage.
2) ____ Using first differencing or deviations from means
(time-demeaning) to eliminate the "unobserved effect" generally
yields identical coefficient estimates and inferences for the
variables of interest.
3)...

Because fixed effects allow arbitrary correlation between
ai and the xitj, while random effects do not,
FE is widely thought to be a more convincing tool for estimating
ceteris paribus effects. Let’s say you are concerned about the
correlation between a i and the key explanatory variable
that is constant over time. Then what is your modeling strategy?
Use FE or RE?

MATHEMATICS
1. The measure of location which is the most likely to
be
influenced by extreme values in the data set is the a. range
b.
median c. mode d. mean
2. If two events are independent, then a. they must be
mutually
exclusive b. the sum of their probabilities must be equal to one
c.
their intersection must be zero d. None of these alternatives
is
correct. any value between 0 to 1
3. Two events, A and B,...

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