Cross-Validation Selection of Regularization Parameter(s) for Semiparametric Transformation Models
Senay Sokullu () and
Sami Stouli ()
Bristol Economics Discussion Papers from Department of Economics, University of Bristol, UK
We propose cross-validation criteria for the selection of regularisation parameter(s) in the semiparametric instrumental variable transformation model proposed in Florens and Sokullu (2016). In the presence of an endogenous regressor, this model is characterized by the need to choose two regularisation parameters, one for the structural function and one for the transformation of the outcome. We consider two-step and simultaneous criteria, and analyze the finite-sample performance of the estimator using the corresponding regularisation parameters by means of several Monte-Carlo simulations. Our numerical experiments show that simultaneous selection of regularisation parameters provides significant improvements in the performance of the estimator. We also apply our methods to the choice of regularisation parameters in the estimation of two-sided network effects in the German magazine industry.
Keywords: Nonparametric IV Regression; Transformation models; Cross-Validation; Tikhonov Regularization; Ill-posed inverse problems. (search for similar items in EconPapers)
JEL-codes: C14 C26 L14 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2016-03-21, Revised 2017-11-08
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Journal Article: Cross-Validation Selection of Regularisation Parameter(s) for Semiparametric Transformation Models (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:bri:uobdis:16/672
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