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21 Cards in this Set

  • Front
  • Back
Sampling error
Arises by chance, esp. in small samples
Omitted variable bias
Bias is systematically correlated with error
Latent variables
Affect the model but are not directly observable
Endogenous variable
How aquired value provides info that tells us more about dependent variable
Exogenous variable
Process would not provide any additional information
Two conditions for instrumental variables
1) Correlation between z and x
2) z is uncorrelated with u
Problem with 2SLS
Produces larger error terms
Structural equation
The original equation, including the endogenous variable(s)
Reduced form equation
Endogenous variable in written in terms of exogenous variables
First stage of 2SLS
Regress endogenous variable(s) on exogenous variables, including z
Exclusion restrictions
Need as many excluded instruments as there are endogenous variables
Finite sample bias
As n approaches infinity, endogeneity approaches 0
What happens when you do the first stage incorrectly?
The influence of the variables that were lefft out goes into error term.
Why 2SLS errors are bigger than OLS errors
1) Only use some info
2) Variation in the error term
3) The more corr there is in the orig. model, the harder it is to detect indiv. influences
Test for endogeneity
Hausman Test
Hausman Test
2 estimators:
-consistent & efficient under Ho
-consistent under Ho and Ha
Consistenct estimator
As n --> infinity, coefficients converge toward true values
Inconsistent estimator
As n --> infinity, coefficients converge on wrong value
Efficient estimator
Results in smaller standard errors than any other estimator of its type (ie, linear)
Hausman Ho
Independent variables are exogenous
Hausman Ha
At least one independent variable is endogenous