Similar Search Results

Optimal uniform convergence rates and asymptotic normality for series estimators under weak dependence and weak conditions

Chen, Xiaohong; Christensen, Timothy M. - 2014 - Rev.

We show that spline and wavelet series regression estimators for weakly dependent regressors attain the optimal uniform (i.e. sup-norm) convergence rate (n= log n)..p=(2p+d) of Stone (1982), where d is the number of regressors and p is the smoothness of the regression function. The optimal rate...

Persistent link: https://www.econbiz.de/10010458629

Estimation of stochastic volatility models by nonparametric filtering

Kanaya, Shin; Kristensen, Dennis - 2015

A two-step estimation method of stochastic volatility models is proposed. In the first step, we nonparametrically … estimate the (unobserved) instantaneous volatility process. In the second step, standard estimation methods for fully observed … diffusion processes are employed, but with the filtered/estimated volatility process replacing the latent process. Our …

Persistent link: https://www.econbiz.de/10010487528

Let's get LADE : robust estimation of semiparametric multiplicative volatility models

Koo, Bonsoo; Linton, Oliver - 2013

We investigate a model in which we connect slowly time varying unconditional long-run volatility with short …-run conditional volatility whose representation is given as a semi-strong GARCH (1,1) process with heavy tailed errors. We focus on … robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility …

Persistent link: https://www.econbiz.de/10009719116

Testing for a general class of functional inequalities

Lee, Sokbae; Song, Kyungchul; Whang, Yoon-jae - 2014

In this paper, we propose a general method for testing inequality restrictions on nonparametric functions. Our framework includes many nonparametric testing problems in a uni ed framework, with a number of possible applications in auction models, game theoretic models, wage inequality, and...

Persistent link: https://www.econbiz.de/10010254852

Averaging of moment condition estimators

Chen, Xiaohong; Jacho-Chàvez, David T.; Linton, Oliver - 2012

We establish the consistency and asymptotic normality for a class of estimators that are linear combinations of a set of √n– consistent estimators whose cardinality increases with sample size. A special case of our framework corresponds to the conditional moment restriction and the implied...

Persistent link: https://www.econbiz.de/10009620338

Local identification of nonparametric and semiparametric models

Chen, Xiaohong; Chernozhukov, Victor; Lee, Sokbae; … - 2012 - Rev.

In parametric models a sufficient condition for local identification is that the vector of moment conditions is differentiable at the true parameter with full rank derivative matrix. We show that additional conditions are often needed in nonlinear, nonparametric models to avoid nonlinearities...

Persistent link: https://www.econbiz.de/10009667984

Maximum score estimation with nonparametrically generated regressors

Chen, Le-Yu; Lee, Sokbae; Sung, Myung Jae - 2014

The estimation problem in this paper is motivated by maximum score estimation of preference parameters in the binary choice model under uncertainty in which the decision rule is affected by conditional expectations. The preference parameters are estimated in two stages: we estimate conditional...

Persistent link: https://www.econbiz.de/10010358923

Testing exogeneity in nonparametric instrumental variables identified by conditional quantile restrictions

Fu, Jia-Young Michael; Horowitz, Joel; Parey, Matthias - 2015

This paper presents a test for exogeneity of explanatory variables in a nonparametric instrumental variables (IV) model whose structural function is identified through a conditional quantile restriction. Quantile regression models are increasingly important in applied econometrics. As with...

Persistent link: https://www.econbiz.de/10011350133

High dimensional semiparametric moment restriction models

Dong, Chaohua; Gao, Jiti; Linton, Oliver - 2018

Moment restriction semiparametric models, where both the dimension of parameter and the number of restrictions are divergent and an unknown function is involved, are studied using the generalized method of moments (GMM) and sieve method dealing with the nonparametric parameter. The consistency...

Persistent link: https://www.econbiz.de/10011775182

High dimensional semiparametric moment restriction models

Dong, Chaohua; Gao, Jiti; Linton, Oliver - 2018

We consider nonlinear moment restriction semiparametric models where both the dimension of the parameter vector and the number of restrictions are divergent with sample size and an unknown smooth function is involved. We propose an estimation method based on the sieve generalized method of...

Persistent link: https://www.econbiz.de/10011938037