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21 Cards in this Set

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 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