Local Identification of Nonparametric and Semiparametric Models∗

Supplement to LOCAL IDENTIFICATION OF NONPARAMETRIC AND SEMIPARAMETRIC MODELS by

LOCAL IDENTIFICATION OF NONPARAMETRIC AND SEMIPARAMETRIC MODELS by

In parametric models a su cient condition for local identi cation is that the vector of moment conditions is di erentiable at the true parameter with full rank derivative matrix. We show that there are corresponding su cient conditions for nonparametric models. A nonparametric rank condition and di erentiability of the moment conditions with respect to a certain norm imply local identi cation. ...

Non- and Semiparametric Identification of Seasonal Nonlinear Autoregression Models

Nonor semiparametric estimation and lag selection methods are proposed for three seasonal nonlinear autoregressive models of varying seasonal flexibility+All procedures are based on either local constant or local linear estimation+ For the semiparametric models, after preliminary estimation of the seasonal parameters, the function estimation and lag selection are the same as nonparametric estim...

Local Independence Feature Screening for Nonparametric and Semiparametric Models by Marginal Empirical Likelihood.

We consider an independence feature screening technique for identifying explanatory variables that locally contribute to the response variable in high-dimensional regression analysis. Without requiring a specific parametric form of the underlying data model, our approach accommodates a wide spectrum of nonparametric and semiparametric model families. To detect the local contributions of explana...

Nonparametric Identifiability of Finite Mixtures

Finite mixture models are useful in applied econometrics. They can be used to model unobserved heterogeneity, which plays major roles in labor economics, industrial organization and other fields. Mixtures are also convenient in dealing with contaminated sampling models and models with multiple equilibria. Most of the currently available estimation methods for mixtures are entirely parametric; o...