name the four types of specification errors correct answers choice of independent variables, functional form, misspecification of error term, measurement error
what assumptions are satisfied when a model is overspecified? correct answers MLR1-4
what is the consequence of overspecification? co...
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name the four types of specification errors correct answers choice of independent variables,
functional form, misspecification of error term, measurement error
what assumptions are satisfied when a model is overspecified? correct answers MLR1-4
what is the consequence of overspecification? correct answers the included variable may be
correlated with other explanatory variable. No cost in terms of bias but increases sampling
variance
what assumption does Omitted variable bias violate? correct answers zero conditional mean
assumption
what can cause omitted variable bias? correct answers lack of data or ignorance
where does the omitted variable go? correct answers error term
what is the implication of the omitted variable being in the error term? correct answers if the
variables are correlated all coefficients will be biased
what is the sign of the bias when correlation is positive and beta is greater than zero correct
answers positive
what is the sign of the bias when correlation is positive and beta is less than zero correct answers
negative
what is the sign of the bias when correlation is negative and beta is greater than zero correct
answers negative
what is the sign of the bias when correlation is negative and beta is less than zero correct answers
positive
what are the two conditions that will cause OVB NOT to arise correct answers omitted factors
are unrelated (correlation = 0), they have no impact (beta=0)
when there is a positive bias do we over or underestimate? correct answers overestimate
when there is negative bias do we over or underestimate? correct answers underestimate
expected beta is greater than the population beta- what type of bias do we have? correct answers
upward bias (overestimate)
expected beta is less than population beta- what type of bias do we have? correct answers
downward bias
, does the correlation between the explanatory variables affect standard errors in OVB? correct
answers no
does OVB lead to inconsistency? correct answers yes
when should a variable be included? correct answers directly affects y or is correlated with x
what is the key difference between OVB and over-specification of of the model? correct answers
OVB causes bias, over-specification does not
where beta =0, and both omitted beta and included beta are biased- should we include the
variable? correct answers no, as this will increase multicollinearity
where beta is not 0, and omitted beta is biased, but included beta is not should we include the
variable? correct answers Yes- leaving out will cause OVB, including will increase the variance.
We can simply increase n to try and reduce variance and therefore make induced
multicollinearity less relevant.
is variance greater in the included or omitted variable model? correct answers included
Define endogeneity correct answers correlation between x and u (violation of zero conditional
mean assumption)
what are the three sources of endogeneity? correct answers OVB, measurement error,
simulateneity
implications of endogeneity correct answers biased and inconsistent
why can't unobserved explanatory variables just be put in the error term? correct answers they
may be correlated with other variables so this will cause endogeneity
what are the two necessary assumptions for an appropriate proxy variable? correct answers error
term is uncorrelated with all variables including the proxy, proxy correlated with omitted
variable
discuss lagged dependent variables as proxy variables correct answers proxy can be the value of
a dependent variable form an earlier time period in the absence of other available proxies. partly
controls for omitted factors by controlling for historical factors that cause current differences in
the dependent variable
what do lagged dependent variables control for correct answers omitted factors by controlling for
historical factors that cause current differences in the dependent variable
define heteroskedasticity correct answers variance of error terms varies across observations
(MLR 5 fails)
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