Estimating the link function in multinomial response models under endogeneity and quadratic loss
This paper considers estimation and inference for the multinomial response model in the case where endogenous variables are arguments of the unknown link function. Semiparametric estimators are proposed that avoid the parametric assumptions underlying the likelihood approach as well as the loss of precision when using nonparametric estimation. A data based shrinkage estimator that seeks an optimal combination of estimators and results in superior risk performance under quadratic loss is also developed.
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- Judge, George G. & Mittelhammer, Ronald C, 2003.
"A semi-parametric basis for combining estimation problems under quadratic loss,"
CUDARE Working Paper Series
948, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
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- Judge, George G. & Mittelhammer, Ron C, 2003. "A Semi-Parametric Basis for Combining Estimation Problems Under Quadratic Loss," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt8z25j0w3, Department of Agricultural & Resource Economics, UC Berkeley.
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- Mittelhammer, Ron C & Judge, George G. & Schoenberg, Ron, 2003.
"Empirical Evidence Concerning the Finite Sample Performance of EL-Type Structural Equation Estimation and Inference Methods,"
Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series
qt2xm0n02g, Department of Agricultural & Resource Economics, UC Berkeley.
- Mittelhammer, Ronald C. & Judge, George G. & Schoenberg, Ron, 2003. "Empirical evidence concerning the finite sample performance of El-type structural equation estimation and inference methods," CUDARE Working Paper Series 945, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
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