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Efficient estimation of copula-based semiparametric Markov models

Chen, Xiaohong; Wu, Wei Biao; Yi, Yanping - 2009

This paper considers efficient estimation of copula-based semiparametric strictly stationary Markov models. These models are characterized by nonparametric invariant distributions and parametric copula functions; where the copulas capture all scale-free temporal dependence and tail dependence of...

Persistent link: https://www.econbiz.de/10003817253

Optimal uniform convergence rates for sieve nonparametric instrumental variables regression

Chen, Xiaohong; Christensen, Timothy - 2013 - rev.

We study the problem of nonparametric regression when the regressor is endogenous, which is an important nonparametric … instrumental variables (NPIV) regression in econometrics and a difficult ill-posed inverse problem with unknown operator in … spline and wavelet least squares regression estimators under weakly dependent data and heavy-tailed error terms. This upper …

Persistent link: https://www.econbiz.de/10010197046

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 … smoothness of the regression function. The optimal rate is achieved even for heavy-tailed martingale difference errors with …

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

Penalized estimation of high-dimensional models under a generalized sparsity condition

Horowitz, Joel; Huang, Jian - 2012

We consider estimation of a linear or nonparametric additive model in which a few coefficients or additive components are "large" and may be objects of substantive interest, whereas others are "small" but not necessarily zero. The number of small coefficients or additive components may exceed...

Persistent link: https://www.econbiz.de/10009567830

Locally- but not globally-identified SVAR

Bacchiocchi, Emanuele; Kitagawa, Toru - 2020 - This draft: 20 July 2020

This paper analyzes Structural Vector Autoregressions (SVARs) where identification of structural parameters holds locally but not globally. In this case there exists a set of isolated structural parameter points that are observationally equivalent under the imposed restrictions. Although the...

Persistent link: https://www.econbiz.de/10012251913

Efficient estimation of conditional risk measures in a semiparametric GARCH model

Yan, Yang; Shang, Dajing; Linton, Oliver - 2012

This paper proposes efficient estimators of risk measures in a semiparametric GARCH model defined through moment constraints. Moment constraints are often used to identify and estimate the mean and variance parameters and are however discarded when estimating error quantiles. In order to prevent...

Persistent link: https://www.econbiz.de/10009620388

Extremal quantile regression : an overview

Chernozhukov, Victor; Fernández-Val, Iván; Kaji, Tetsuya - 2017

Extremal quantile regression, i.e. quantile regression applied to the tails of the conditional distribution, counts … and empirics of extremal quantile regression. The advances in the theory have relied on the use of extreme value … approximations to the law of the Koenker and Bassett (1978) quantile regression estimator. Extreme value laws not only have been …

Persistent link: https://www.econbiz.de/10011775216

Quantile graphical models : prediction and conditional independence with applications to systemic risk

Belloni, Alexandre; Chen, Mingli; Chernozhukov, Victor - 2017 - This version December 4, 2017

The understanding of co-movements, dependence, and influence between variables of interest is key in many applications. Broadly speaking such understanding can lead to better predictions and decision making in many settings. We propose Quantile Graphical Models (QGMs) to characterize prediction...

Persistent link: https://www.econbiz.de/10011775380

Optimal two-sided tests for instrumental variables regression with heteroskedastic and autocorrelated errors

Moreira, Humberto; Moreira, Marcelo J. - 2016 - This version: June 10, 2016

This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the finite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We...

Persistent link: https://www.econbiz.de/10011485564

Treatment effects with many covariates and heteroskedasticity

Cattaneo, Matias D.; Jansson, Michael; Newey, Whitney K. - 2015

The linear regression model is widely used in empirical work in Economics. Researchers often include many covariates in …

Persistent link: https://www.econbiz.de/10011295589