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Conditional distribution functions are important statistical objects for the analysis of a wide class of problems in econometrics and statistics. We propose flexible Gaussian representations for conditional distribution functions and give a concave likelihood formulation for their global...
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calibration, and lead to only minor differences between the estimators employed. Finally, a simulation study confirms the …
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further simulation evidence that GMM estimators with a large number of instruments can be severely biased in finite samples …
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