Xiaohong Chen

Nonparametric Identification and Estimation of Nonclassical Errors-in-Variables Models Without Additional Information (2007)

This note considers nonparametric identification of a general nonlinear regression model with a dichotomous regressor subject to misclassification error. The available sample information consists of...

Semiparametric efficiency in GMM models with auxiliary data (2007)

This paper considers identification and estimation of a nonparametric regression model with an unobserved discrete covariate. The sample consists of a dependent variable and a set of covariates, one...

Chen, Xiaohong, Hong, Han, Tarozzi, Alessandro

We study semiparametric efficiency bounds and efficient estimation of parameters defined through general moment restrictions with missing data. Identification relies on auxiliary data containing...

Abstract (2006)

Xiaohong Chen, Yingyao Hu Y, Arthur Lewbel Z

This note considers nonparametric identi…cation of a general nonlinear regression model with a dichotomous regressor subject to misclassi…cation error. The available sample information consists...

Simple tests for models of dependence between multiple financial time series, with applications to U.S. equity returns and exchange rates (2004)

Chen, Xiaohong, Fan, Yanqin, Patton, Andrew J.

Evidence that asset returns are more highly correlated during volatile markets and during market downturns (see Longin and Solnik, 2001, and Ang and Chen, 2002) has lead some researchers to propose...

Evaluation of a theory-based stop-smoking program / (2004)

Estimation of semiparametric models when the criterion function is not smooth (2003)

Appendices: leaves 141-169.

Chen, Xiaohong, Linton, Oliver, Van Keilegom, Ingrid

We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard...

Estimation of semiparametric models when the criterion function is not smooth (2003)

Chen, Xiaohong, Linton, Oliver, Van Keilegom, Ingrid

We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard...

A web-based approach for myofascial pain syndrome patient monitoring in the home / (2003)

Weighted and Two Stage Least Squares Estimation of Semiparametric Truncated Regression Models (2003)

Thesis (M.S.)--Major in Engineering/Computer Science, South Dakota State University, 2003.

Shakeeb Khan, Arthur Lewbel, Jim Powell, Richard Blundell, Bo Honoré, Jim Heckman, ...

This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of the coe#cients in the truncated regression model. The distribution of the errors is unknown and...

Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space (2002)

Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space (2002)

Let H be an infinite-dimensional real separable Hilbert space. Given an unknown mapping M:H (r)H that can only be observed with noise, we consider two modified Robbins-Monro procedures to estimate...

Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space (2002)

Let H be an infinite-dimensional real separable Hilbert space. Given an unknown mapping M:H (r)H that can only be observed with noise, we consider two modified Robbins-Monro procedures to estimate...

Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space (2002)

Let H be an infinite-dimensional real separable Hilbert space. Given an unknown mapping M:H (r)H that can only be observed with noise, we consider two modified Robbins-Monro procedures to estimate...

Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space (2002)

Let H be an infinite-dimensional real separable Hilbert space. Given an unknown mapping M:H (r)H that can only be observed with noise, we consider two modified Robbins-Monro procedures to estimate...

Higher educartion research in China: Past, present, and prospect (2002)

Let H be an infinite-dimentional real separable Hilbert space. Given an unknown mapping M : H (arrow) H that can only be observed with noise, we consider two modified Robbins-Monro procedures to...

Pan, Maoyuan, Li, Jun, Chen, Xiaohong

Higher educartion research in China: Past, present, and prospect (2002)

Pan, Maoyuan, Li, Jun, Chen, Xiaohong

The estimation of conditional densities (2001)

Chen, Xiaohong, Linton, Oliver, Robinson, Peter

We discuss a number of issues in the smoothed nonparametric estimation of kernel conditional probability density functions for stationary processes. The kernel conditional density estimate is a ratio...

The estimation of conditional densities (2001)

Chen, Xiaohong, Linton, Oliver, Robinson, Peter

We discuss a number of issues in the smoothed nonparametric estimation of kernel conditional probability density functions for stationary processes. The kernel conditional density estimate is a ratio...

Application of ion chromatography for analysis of mine waste water /--by Xiaohong Chen. (1999)

Constitutive relations, toughening mechanisms and fracture characterization of polymeric materials /--by Xiaohong Chen. (1999)

Typescript (photocopy).

Correlation of Ordovician regional chitinozoan biozonations. (1999)

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 1999.

PARIS, F, Verniers, Jacques, ACHAB, A, ALBANI, A, ANCILLETTA, A, ASSELIN, E, ...

Nonparametric Adaptive Learning with Feedback (1994)

Chemistry of ruthenium and osmium polypyridyl complexes / (1992)

and the participants of the SITE workshop for encouragement and helpful discussions. 1.

A discussion of the development of woodblock printmaking in China /--by Xiaohong Chen. (1989)

Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 1992.

Land of Addicts? An Empirical Investigation of Habit-Based Asset Pricing Models

Typescript.

Sydney Ludvigson, Xiaohong Chen

A leading explanation of aggregate stock market behavior suggests that assets are priced as if there were a representative investor whose utility is a power function of the difference between...

Estimation of copula-based semiparametric time series models

Evaluating Density Forecasts via the Copula Approach

Estimation of semiparametric models when the criterion function is not smooth

In this paper, we develop a general approach for constructing simple tests for the correct density forecasts, or equivalently, for i.i.d. uniformity of appropriately transformed random variables. It...

Xiaohong Chen, Oliver Linton, Ingred Van Keilegom

We provide easy to verify suffcient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard...

Estimation of Semiparametric Models when the Criterion Function Is Not Smooth

Xiaohong Chen, Oliver Linton, Ingrid Van Keilegom

We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard...

Estimation of semiparametric models when the criterion function is not smooth

Xiaohong Chen, Oliver Linton, Ingred Van Keilegom

We provide easy to verify suffcient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard...

A Model Selection Test for Bivariate Failure-Time Data

Estimation of Copula-Based Semiparametric Time Series Models

In this paper, we address two important issues in survival model selection for censored data generated by the Archimedean copula family; method of estimating the parametric copulas and data reuse. We...

Estimation and Model Selection of Semiparametric Copula-Based Multivariate Dynamic Models under Copula Misspecification

This paper studies the estimation of a class of copula-based semiparametric stationary Markov models. These models are characterized by nonparametric invariant (or marginal) distributions and...

Efficient Estimation of Semiparametric Multivariate Copula Models

Recently Chen and Fan (2003a) introduced a new class of semiparametric copula-based multivariate dynamic (SCOMDY) models. A SCOMDY model specifies the conditional mean and the conditional variance of...

Xiaohong Chen, Yanqin Fan, Victor Tsyrennifov

We propose a sieve maximum likelihood (ML) estimation procedure for a broad class of semiparametric multivariate distribution models. A joint distribution in this class is characterized by a...

Principal Components and the Long Run

Xiaohong Chen, Lars Peter Hansen, Jos´e A. Scheinkman

Phosphorylation of Jak2 on Ser523 Inhibits Jak2-Dependent Leptin Receptor Signaling†

Ishida-Takahashi, Ryoko, Rosario, Felicia, Gong, Yusong, Kopp, Keely, Stancheva, Zlatina, Chen, Xiaohong, ...

The leptin receptor, LRb, and other cytokine receptors are devoid of intrinsic enzymatic activity and rely upon the activity of constitutively associated Jak family tyrosine kinases to mediate...

Estimation and model selection of semiparametric copula-based multivariate dynamic models under copula misspecification

CENTRAL LIMIT AND FUNCTIONAL CENTRAL LIMIT THEOREMS FOR HILBERT-VALUED DEPENDENT HETEROGENEOUS ARRAYS WITH APPLICATIONS

Identification and Inference of Nonlinear Models Using Two Samples with Arbitrary Measurement Errors

We obtain new central limit theorems (CLT s) and functional central limit theorems (FCLT s) for Hilbert-valued arrays near epoch dependent on mixing processes, and also new FCLT s for general...

Xiaohong Chen, Yingyao Hu

This paper considers identification and inference of a general latent nonlinear model using two samples, where a covariate contains arbitrary measurement errors in both samples, and neither sample...

Phosphorylation of Jak2 on Ser523 Inhibits Jak2-Dependent Leptin Receptor Signaling

Ishida-Takahashi, Ryoko, Rosario, Felicia, Gong, Yusong, Kopp, Keely, Stancheva, Zlatina, Chen, Xiaohong, ...

Phosphorylation of Jak2 on Ser523 Inhibits Jak2-Dependent Leptin Receptor Signaling†

Ishida-Takahashi, Ryoko, Rosario, Felicia, Gong, Yusong, Kopp, Keely, Stancheva, Zlatina, Chen, Xiaohong, ...

The leptin receptor, LRb, and other cytokine receptors are devoid of intrinsic enzymatic activity and rely upon the activity of constitutively associated Jak family tyrosine kinases to mediate...

Phosphorylation of Jak2 on Ser523 Inhibits Jak2-Dependent Leptin Receptor Signaling

Ishida-Takahashi, Ryoko, Rosario, Felicia, Gong, Yusong, Kopp, Keely, Stancheva, Zlatina, Chen, Xiaohong, ...

Land of Addicts? An Empirical Investigation of Habit-Based Asset Pricing Behavior

Xiaohong Chen, Sydney C. Ludvigson

This paper studies the ability of a general class of habit-based asset pricing models to match the conditional moment restrictions implied by asset pricing theory. We treat the functional form of the...

Nonparametric Identification of Regression Models Containing a Misclassified Dichotomous Regressor Without Instruments

Nonparametric Identification and Estimation of Nonclassical Errors-in-Variables Models Without Additional Information

This note considers nonparametric identification of a general nonlinear regression model with a dichotomous regressor subject to misclassification error. The available sample information consists of...

MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS

This paper considers identification and estimation of a nonparametric regression model with an unobserved discrete covariate. The sample consists of a dependent variable and a set of covariates, one...

Carrasco, Marine, Chen, Xiaohong

This paper first provides some useful results on a generalized random coefficient autoregressive model and a generalized hidden Markov model. These results simultaneously imply strict stationarity,...

Efficient Estimation of Semiparametric Conditional Moment Models with Possibly Nonsmooth Residuals

Semiparametric Efficiency in GMM Models of Nonclassical Measurement Errors, Missing Data and Treatment Effects

For semi/nonparametric conditional moment models containing unknown parametric components (theta) and unknown functions of endogenous variables (h), Newey and Powell (2003) and Ai and Chen (2003)...

Xiaohong Chen, Han Hong, Alessandro Tarozzi

We study semiparametric efficiency bounds and efficient estimation of parameters defined through general nonlinear, possibly non-smooth and over-identified moment restrictions, where the sampling...

Identification and SQRT N Efficient Estimation of Semiparametric Panel Data Models with Binary Dependent Variables and a Latent Factor

Xiaohong Chen, James J. Heckman, Edward Vytlacil

No abstract.

The Estimation of Conditional Densities

Xiaohong Chen, Oliver Linton, Peter M Robinson

We discuss a number of issues in the smoothed nonparametric estimation of kernel conditional probability density functions for stationary processes. The kernel conditional density estimate is a ratio...

Estimation of Semiparametric Models when the Criterion Function is not Smooth

Xiaohong Chen, Oliver Linton, Ingrid Van Keilegom

We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard...

Nonparametric Adaptive Learning with Feedback

Estimation of semiparametric models when the criterion function is not smooth

Xiaohong Chen, Oliver Linton, Ingred Van Keilegom

We provide easy to verify suffcient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard...

CENTRAL LIMIT AND FUNCTIONAL CENTRAL LIMIT THEOREMS FOR HILBERT-VALUED DEPENDENT HETEROGENEOUS ARRAYS WITH APPLICATIONS

Laws of Large Numbers for Hilbert Space-Valued Mixingales with Applications.

We obtain new central limit theorems (CLT s) and functional central limit theorems (FCLT s) for Hilbert-valued arrays near epoch dependent on mixing processes, and also new FCLT s for general...

An Estimation of Economic Models with Recursive

To obtain consistency results for nonparametric estimators based on stochastic processes relevant in econometrics, we introduce the notions of Hilbert space-valued L[subscript p] mixingales and...

Sydney C. Ludvigson, Xiaohong Chen, Jack Favilukis

This paper presents estimates of key preference parameters of the Epstein and Zin (1989, 1991) and Weil (1989) (EZW) recursive utility model, evaluates the model’s ability to fit asset return data...

On Rate Optimality for Ill-posed Inverse Problems in Econometrics

Xiaohong Chen, Markus Reiss

In this paper, we clarify the relations between the existing sets of regularity conditions for convergence rates of nonparametric indirect regression (NPIR) and nonparametric instrumental variables...

Estimation of Nonparametric Conditional Moment Models with Possibly Nonsmooth Moments

Large Sample Sieve Estimation of Semi-Nonparametric Models

This paper studies nonparametric estimation of conditional moment models in which the residual functions could be nonsmooth with respect to the unknown functions of endogenous variables. It is a...

Chen, Xiaohong, J.J. Heckman, E.E. Leamer

Often researchers find parametric models restrictive and sensitive to deviations from the parametric specifications; semi-nonparametric models are more flexible and robust, but lead to other...

On rate optimality for ill-posed inverse problems in econometrics

Xiaohong Chen, Markus Reiss

In this paper, we clarify the relations between the existing sets of regularity conditions for convergence rates of nonparametric indirect regression (NPIR) and nonparametric instrumental variables...

Nonparametric identification and estimation of nonclassical errors-in-variables models without additional information

Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments

This paper considers identification and estimation of a nonparametric regression model with an unobserved discrete covariate. The sample consists of a dependent variable and a set of covariates, one...

Efficient Estimation of Semiparametric Multivariate Copula Models

This note considers nonparametric identification of a general nonlinear regression model with a dichotomous regressor subject to misclassification error. The available sample information consists of...

Chen, Xiaohong, Fan, Yanqin, Tsyrennikov, Viktor

Semi-Nonparametric IV Estimation of Shape-Invariant Engel Curves

Richard Blundell, Xiaohong Chen, Dennis Kristensen

This paper studies a shape-invariant Engel curve system with endogenous total expenditure, in which the shape-invariant specification involves a common shift parameter for each demographic group in a...

A MODEL SELECTION TEST FOR BIVARIATE FAILURE-TIME DATA

Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables

In this paper, we address two important issues in semiparametric survival model selection for censored data generated by the Archimedean copula family: method of estimating the parametric copulas and...

Ai, Chunrong, Chen, Xiaohong

Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models

Chen, Xiaohong, Hong, Han, Shum, Matthew

Measurement Error Models with Auxiliary Data

Xiaohong Chen, Han Hong, Elie Tamer

We study the problem of parameter inference in (possibly non-linear and non-smooth) econometric models when the data are measured with error. We allow for "arbitrary" correlation between the true...

Estimation of Copula-Based Semiparametric Time Series Models

Yanqin Fan, Xiaohong Chen

This paper studies the estimation of a class of copula-based semiparametric stationary Markov models. These models are characterized by nonparametric invariant (or marginal) distributions and...

An Empirical Investigation of Habit-Based Asset Pricing Models

Sydney C. Ludvigson, Xiaohong Chen

A leading explanation of aggregate stock market behavior suggests that assets are priced as if there were a representative investor whose utility is a power function of the difference between...

Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions

Chunrong Ai, Xiaohong Chen

We propose an estimation method for models of conditional moment restrictions, which contain finite dimensional unknown parameters (theta) and infinite dimensional unknown functions (h). Our proposal...

Sieve Extremum Estimates for Weakly Dependent Data

Xiaohong Chen, Xiaotong Shen

Many non/semiparametric time series estimates may be regarded as different forms of sieve extremum estimates. For stationary absolute regular mixing observations, the authors obtain convergence rates...

Consistent hypothesis testing in semiparametric and nonparametric models for econometric time series

Iterative and Recursive Estimation in Structural Nonadaptive Models: Comment.

Chen, Xiaohong

Nonparametric IV estimation of shape-invariant Engel curves

Richard Blundell, Xiaohong Chen, Dennis Kristensen

This paper concerns the identification and estimation of a shape-invariant Engel curve system with endogenous total expenditure. The shape-invariant specification involves a common shift parameter...

(IAM Series No 003) Simple Tests for Models of Dependence Between Multiple Financial Time Series, with Applications to U.S. Equity Returns and Exchange Rates

Yanqin Fan, Xiaohong Chen, Andrew Patton

Evidence that asset returns are more highly correlated during volatile markets and during market downturns (see Longin and Solnik, 2001, and Ang and Chen, 2002) has lead some researchers to propose...

Model check by kernel methods under weak moment conditions

Ahmad, Ibrahim, Chen, Xiaohong, Li, Qi

Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space

Improved Rates and Asymptotic Normality for Nonparametric Neural Network Estimators

Let H be an infinite-dimentional real separable Hilbert space. Given an unknown mapping M : H (arrow) H that can only be observed with noise, we consider two modified Robbins-Monro procedures to...

Nonparametric Adaptive Learning with Feedback

Barron (1993) obtained a deterministic approximation rate (in L2-norm) of r-1/2 for a class of single hidden layer feedforward artificial neural networks (ANN) with r hidden units and sigmoid...

Asymptotic Properties of Some Projection-based Robins-Monro Procedures in a Hilbert Space

Central Limit and Functional Central Limit Theorems for Hilbert-Valued Dependent Heterogeneous Arrays with Applications

Weak and Strong Laws of Large Numbers for Hilbert Space - Valued Mixingales

We obtain new CLTs and FCLTs for Hilbert-valued arrays near epoch dependent on mixing processes, as well as new FCLTs for general Hilbert-valued adapted dependent heterogeneous arrays. These theorems...

Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space

Nonlinearity and Temporal Dependence

Let H be an infinite-dimensional real separable Hilbert space. Given an unknown mapping M:H (r)H that can only be observed with noise, we consider two modified Robbins-Monro procedures to estimate...

Xiaohong Chen, Lars P. Hansen, Marine Carrasco

Nonlinearities in the drift and diffusion coefficients influence temporal dependence in scalar diffusion models. We study this link using two notions of temporal dependence: beta-mixing and...

Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments

Efficient Estimation of Semiparametric Conditional Moment Models with Possibly Nonsmooth Residuals

We observe a dependent variable and some regressors, including a mismeasured binary regressor. We provide identification of the nonparametric regression model containing this misclassified...

Estimation of nonparametric conditional moment models with possibly nonsmooth moments

This paper greatly extends the results of Ai and Chen (2003) on efficient estimation of conditional moment models containing unknown parametric components (theta) and unknown functions of endogenous...

Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals

This paper studies nonparametric estimation of conditional moment models in which the residual functions could be nonsmooth with respect to the unknown functions of endogenous variables. It is a...

Copula-Based Nonlinear Quantile Autoregression

For semi/nonparametric conditional moment models containing unknown parametric components θ and unknown functions of endogenous variables (h), Newey and Powell (2003) and Ai and Chen (2003) propose...

Copula-Based Nonlinear Quantile Autoregression

Parametric copulas are shown to be attractive devices for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific copula-based time series models...

Estimation and Model Selection of Semiparametric Multivariate Survival Functions under General Censorship

Parametric copulas are shown to be attractive devices for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific copula-based time series models...

Xiaohong Chen, Yanqin Fan, Demian Pouzo, Zhiliang Ying

Many models of semiparametric multivariate survival functions are characterized by nonparametric marginal survival functions and parametric copula functions, where different copulas imply different...

CENTRAL LIMIT AND FUNCTIONAL CENTRAL LIMIT THEOREMS FOR HILBERT-VALUED DEPENDENT HETEROGENEOUS ARRAYS WITH APPLICATIONS

MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS

We obtain new central limit theorems (CLT s) and functional central limit theorems (FCLT s) for Hilbert-valued arrays near epoch dependent on mixing processes, and also new FCLT s for general...

Carrasco, Marine, Chen, Xiaohong

This paper first provides some useful results on a generalized random coefficient autoregressive model and a generalized hidden Markov model. These results simultaneously imply strict stationarity,...

A MODEL SELECTION TEST FOR BIVARIATE FAILURE-TIME DATA

A note on the closed-form identification of regression models with a mismeasured binary regressor

In this paper, we address two important issues in semiparametric survival model selection for censored data generated by the Archimedean copula family: method of estimating the parametric copulas and...

Efficient Estimation of Semiparametric Conditional Moment Models with Possibly Nonsmooth Residuals

This note considers the identification of a nonparametric regression model with an unobserved 0-1 dichotomous regressor. The sample consists of a dependent variable and a 0-1 dichotomous proxy of the...

Chen, Xiaohong, Pouzo, Demian

For semi/nonparametric conditional moment models containing unknown parametric components (theta) and unknown functions of endogenous variables (h), Newey and Powell (2003) and Ai and Chen (2003)...

Semiparametric E±ciency in GMM Models of Nonclassical Measurement Errors, Missing Data and Treatment Effects

Chen, Xiaohong, Hong, Han, Tarozzi, Alessandro

We study semiparametric efficiency bounds and efficient estimation of parameters defined through general nonlinear, possibly non-smooth and over-identified moment restrictions, where the sampling...

Estimation of Nonparametric Conditional Moment Models with Possibly Nonsmooth Moments

Chen, Xiaohong, Pouzo, Demian

This paper studies nonparametric estimation of conditional moment models in which the residual functions could be nonsmooth with respect to the unknown functions of endogenous variables. It is a...

Nonlinearity and Temporal Dependence

Chen, Xiaohong, Hansen, Lars Peter, Carrasco, Marine

Nonlinearities in the drift and diffusion coefficients influence temporal dependence in scalar diffusion models. We study this link using two notions of temporal dependence: beta-mixing and...

Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space

Efficient Estimation of Copula-based Semiparametric Markov Models

Let H be an infinite-dimensional real separable Hilbert space. Given an unknown mapping M:H (r)H that can only be observed with noise, we consider two modified Robbins-Monro procedures to estimate...

Xiaohong Chen, Wei Biao Wu, Yanping Yi

This paper considers efficient estimation of copula-based semiparametric strictly stationary Markov models. These models are characterized by nonparametric invariant distributions and parametric...

Laws of Large Numbers for Hilbert Space-Valued Mixingales with Applications

Copula-based nonlinear quantile autoregression

To obtain consistency results for nonparametric estimators based on stochastic processes relevant in econometrics, we introduce the notions of Hilbert space-valued Lp mixingales and near-epoch...

Simple Tests for Models of Dependence Between Multiple Financial Time Series, with Applications to U.S. Equity Returns and Exchange Rates

Parametric copulas are shown to be attractive devices for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific copula-based time series models...

Andrew Patton, Yanqin Fan, Xiaohong Chen

Principal Components and Long Run Implications of Multivariate Diffusions

Xiaohong Chen, Lars Peter Hansen, Jose Scheinkman

We investigate a method for extracting nonlinear principal components. These principal components maximize variation subject to smoothness and orthogonality constraints; but we allow for a general...

Nonlinearity and Temporal Dependence

Xiaohong Chen, Lars P. Hansen, Marine Carrasco

Nonlinearities in the drift and diffusion coefficients influence temporal dependence in scalar diffusion models. We study this link using two notions of temporal dependence: β−mixing and...

Copula-based nonlinear quantile autoregression

Estimation of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals

Parametric copulas are shown to be attractive devices for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific copula-based time series models...

Principal components and the long run

This paper studies nonparametric estimation of conditional moment models in which the generalized residual functions can be nonsmooth in the unknown functions of endogenous variables. This is a...

Xiaohong Chen, Lars Peter Hansen, Jose A. Scheinkman

We investigate a method for extracting nonlinear principal components. These principal components maximize variation subject to smoothness and orthogonality constraints; but we allow for a general...

Efficient estimation of copula-based semiparametric Markov models

Xiaohong Chen, Wei Biao Wu, Yanping Yi

This paper considers efficient estimation of copula-based semiparametric strictly stationary Markov models. These models are characterized by nonparametric invariant distributions and parametric...

Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals

Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals

This paper considers semiparametric efficient estimation of conditional moment models with possibly nonsmooth residuals in unknown parametric components (Θ) and unknown functions (h)of endogenous...

Chen, Xiaohong, Pouzo, Demian

This paper considers semiparametric efficient estimation of conditional moment models with possibly nonsmooth residuals in unknown parametric components ([theta]) and unknown functions (h) of...

Semiparametric Efficiency Bound for Models of Sequential Moment Restrictions Containing Unknown Functions

Chunrong Ai, Xiaohong Chen

This paper computes the semiparametric efficiency bound for finite dimensional parameters identified by models of sequential moment restrictions containing unknown functions. Our results extend those...

Viewing chemokines as a third major system of communication in the brain

Adler, Martin W., Geller, Ellen B., Chen, Xiaohong, Rogers, Thomas J.

There is irrefutable proof that opioids and other classes of centrally acting drugs have profound effects on the immune system. Evidence is mounting that products of the immune system, such as...

Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space