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Mardi 6 Juin 2017


(University of Amsterdam)

présentera une communication :

"Efficient size correct subset inference in linear instrumental variables regression" 


de 14 h à 15 h 30 en salle S016 au CREST, 15 Boulevard Gabriel Péri, 92245 MALAKOFF (Métro : Malakoff/Plateau de Vanves (Immeuble "Malakoff 2)).



Abstract: We show that Moreira's (2003) conditional critical value function for the likelihood ratio statistic conducting tests on the structural parameter in the iid linear instrumental variables regression model with one included endogenous variable extends to the subset likelihood ratio statistic testing one structural parameter in an iid linear instrumental variables regression model with several included endogenous variables. The only adjustment concerns the usual degrees of freedom correction for subset tests of the involved chi-squared distributed random variables. The conditional critical value function makes the subset likelihood ratio test size correct under weak identification of the structural parameters and efficient under strong identification. When the hypothesized value of the parameter
of interest is distant from the true one, the subset Anderson-Rubin and likelihood ratio statistics are invariant with respect to the parameter of interest and equal statistics that test the identification of all parameters in the model. The value of the statistic testing a distant value of any of the structural parameters is therefore the same. All results extend to tests on the parameters of the included exogenous variables.