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Displaying results 1 to 25 of 57.

  1. Efficient estimation of multivariate semi-nonparametric GARCH filtered copula models
    Author: Chen, Xiaohong; Huang, Zhuo; Yi, Yanping
    Published: 2019
    Publisher:  Cowles Foundation for Research in Economics, Yale University, New Haven, Connecticut

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    Format: Online
    Edition: Revised October 2019
    Series: Cowles Foundation discussion paper ; no. 2215 (Revised October 2019)
    Scope: 1 Online-Ressource (circa 78 Seiten), Illustrationen
  2. Asymptotic properties of some projection-based Robbins-Monro procedures in a Hilbert space
    Author: Chen, Xiaohong; White, Halbert
    Published: 2002

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    Series: Discussion paper / University of California, San Diego, Department of Economics ; 2002,07
    Subjects: Schätztheorie; Nichtlineare Regression
    Scope: 76 Bl
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  3. Estimation of semiparametric models when the criterion function is not smooth
    Author: Chen, Xiaohong; Linton, Oliver; Keilegom, Ingrid Van
    Published: 2003
    Publisher:  STICERD, London

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    Niedersächsische Staats- und Universitätsbibliothek Göttingen
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    Series: Discussion paper / Suntory-Toyota International Centres for Economics and Related Disciplines ; EM/03/450 : Econometrics
    Subjects: Nichtparametrisches Verfahren; Theorie; Bootstrap-Verfahren
    Scope: 19 S
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  4. Land of addicts?
    an empirical investigation of habit-based asset pricing behavior
    Author: Chen, Xiaohong; Ludvigson, Sydney C.
    Published: 2004
    Publisher:  National Bureau of Economic Research, Cambridge, Mass.

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    Language: English
    Media type: Book
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    Series: NBER working paper series ; 10503
    Subjects: CAPM; Diskontierung; Anlageverhalten; Aktienmarkt; Schätzung; USA; Capital assets pricing model
    Scope: 59, [9] S, graph. Darst
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    Internetausg.: papers.nber.org/papers/w10503.pdf - lizenzpflichtig

    Literaturverz. S. 50 - 55
  5. Simple tests for models of dependence between multiple financial time series, with applications to US equity returns and exchange rates
    Author: Patton, Andrew J.; Chen, Xiaohong; Fan, Yanqin
    Published: 2004

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    Series: Discussion paper series / LSE Financial Markets Group ; 483
    IAM paper ; 003
    Subjects: Zeitreihenanalyse; Nichtparametrisches Verfahren; ARCH-Modell
    Scope: 36 S
  6. Principal components and the long run
    Author: Chen, Xiaohong; Hansen, Lars Peter; Scheinkman, José Alexandre
    Published: 2009
    Publisher:  Centre for Microdata Methods and Practice, London

    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 class of constraints and densities, including... more

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    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 class of constraints and densities, including densities without compact support and even densities with algebraic tails. We provide primitive sufficient conditions for the existence of these principal components. We also characterize the limiting behavior of the associated eigenvalues, the objects used to quantify the incremental importance of the principal components. By exploiting the theory of continuous-time, reversible Markov processes, we give a different interpretation of the principal components and the smoothness constraints. When the diffusion matrix is used to enforce smoothness, the principal components maximize long-run variation relative to the overall variation subject to orthogonality constraints. Moreover, the principal components behave as scalar autoregressions with heteroskedastic innovations. Finally, we explore implications for a more general class of stationary, multivariate diffusion processes.

     
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    Format: Online
    Other identifier:
    hdl: 10419/64671
    Series: Cemmap working paper / Centre for Microdata Methods and Practice ; 07/09
    Subjects: Multivariate Analyse; Markov-Kette; Theorie
    Scope: Online-Ressource (PDF-Datei: 51 S.), graph. Darst.
  7. Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments
    Author: Chen, Xiaohong; Hu, Yingyao; Lewbel, Arthur
    Published: 2007
    Publisher:  Boston College, Dept. of Economics, Chestnut Hill, Mass.

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Edition: rev.
    Series: Working papers in economics ; 675
    Subjects: Regressionsanalyse; Statistischer Fehler; Nichtparametrisches Verfahren
    Scope: Online-Ressource, (15 S.)
  8. Nonparametric identification and estimation of nonclassical errors-in-variables models without additional information
    Author: Chen, Xiaohong; Hu, Yingyao; Lewbel, Arthur
    Published: 2007
    Publisher:  Boston College, Dept. of Economics, Chestnut Hill, Mass.

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Edition: rev.
    Series: Working papers in economics ; 676
    Subjects: Nichtparametrisches Verfahren; Maximum-Likelihood-Schätzung; Statistischer Fehler
    Scope: Online-Ressource, ([44] S.)
  9. Copula-based nonlinear quantile autoregression
    Author: Chen, Xiaohong; Koenker, Roger; Xiao, Zhijie
    Published: 2008
    Publisher:  Boston College, Dept. of Economics, Chestnut Hill, Mass.

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    Language: English
    Media type: Book
    Format: Online
    Series: Working papers in economics ; 691
    Subjects: Zeitreihenanalyse; Nichtlineare Regression; Multivariate Verteilung; Regressionsanalyse
    Scope: Online-Ressource, (31 S.)
  10. Efficient estimation of copula-based semiparametric Markov models
    Author: Chen, Xiaohong; Wu, Wei Biao; Yi, Yanping
    Published: 2009
    Publisher:  Centre for Microdata Methods and Practice, London

    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... more

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    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 the processes. The Markov models generated via tail dependent copulas may look highly persistent and are useful for financial and economic applications. We first show that Markov processes generated via Clayton, Gumbel and Student’s t copulas (with tail dependence) are all geometric ergodic. We then propose a sieve maximum likelihood estimation (MLE) for the copula parameter, the invariant distribution and the conditional quantiles. We show that the sieve MLEs of any smooth functionals are root-n consistent, asymptotically normal and efficient; and that the sieve likelihood ratio statistics is chi-square distributed. We present Monte Carlo studies to compare the finite sample performance of the sieve MLE, the two-step estimator of Chen and Fan (2006), the correctly specified parametric MLE and the incorrectly specified parametric MLE. The simulation results indicate that our sieve MLEs perform very well; having much smaller biases and smaller variances than the two-step estimator for Markov models generated by Clayton, Gumbel and other copulas having strong tail dependence -- Copula ; Tail dependence ; Nonlinear Markov models ; Geometric ergodicity ; Sieve MLE ; Semiparametric efficiency ; Sieve likelihood ratio statistics ; Value-at-Risk

     
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    Format: Online
    Other identifier:
    hdl: 10419/64729
    Series: Cemmap working paper / Centre for Microdata Methods and Practice ; 06/09
    Subjects: Multivariate Verteilung; Markov-Kette; Nichtparametrisches Verfahren; Risikomaß; Zeitreihenanalyse; Theorie
    Scope: Online-Ressource (PDF-Datei: 44 S.), graph. Darst.
  11. Semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions
    Author: Ai, Chunrong; Chen, Xiaohong
    Published: 2009
    Publisher:  Cowles Foundation for Research in Economics, Yale Univ., New Haven, Conn.

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    Series: Cowles Foundation discussion paper ; 1731
    Subjects: Nichtparametrisches Verfahren; Sequentialtest; Momentenmethode; Theorie
    Scope: Online-Ressource, (40 S.)
  12. An alternative way of computing efficient instrumental variable estimators
    Author: Chen, Xiaohong; Jacho-Chávez, David T.; Linton, Oliver
    Published: 2009
    Publisher:  LSE, STICERD, London

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    Niedersächsische Staats- und Universitätsbibliothek Göttingen
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Econometrics publications ; 536
    Subjects: IV-Schätzung; Nichtparametrisches Verfahren; Schätztheorie
    Scope: Online-Ressource (PDF-Datei: 32 S.)
  13. Semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions
    Author: Ai, Chunrong; Chen, Xiaohong
    Published: 2009
    Publisher:  Centre for Microdata Methods and Practice, London

    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 of Chamberlain (1992b) and Ai and Chen (2003) for... more

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    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 of Chamberlain (1992b) and Ai and Chen (2003) for semiparametric conditional moment restriction models with identical information sets to the case of nested information sets, and those of Chamberlain (1992a) and Brown and Newey (1998) for models of sequential moment restrictions without unknown functions to cases with unknown functions of possibly endogenous variables. Our bound results are applicable to semiparametric panel data models and semiparametric two stage plug-in problems. As an example, we compute the efficiency bound for a weighted average derivative of a nonparametric instrumental variables (IV) regression, and find that the simple plug-in estimator is not efficient. Finally, we present an optimally weighted, orthogonalized, sieve minimum distance estimator that achieves the semiparametric efficiency bound. -- Sequential moment models ; Semiparametric efficiency bounds ; Optimally weighted orthogonalized sieve minimum distance ; Nonparametric IV regression ; Weighted average derivatives ; Partially linear quantile IV

     
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    hdl: 10419/64640
    Series: Cemmap working paper / Centre for Microdata Methods and Practice ; 28/09
    Subjects: Nichtparametrisches Verfahren; Sequentialtest; Momentenmethode; Theorie
    Scope: Online-Ressource (PDF-Datei: 40 S.)
  14. Sieve inference on semi-nonparametric time series models
    Author: Chen, Xiaohong; Liao, Zhipeng; Sun, Yixiao
    Published: 2012
    Publisher:  Cowles Foundation for Research in Economics, Yale Univ., New Haven, Conn.

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    Series: Cowles Foundation discussion paper ; 1849
    Scope: Online-Ressource (20 S., 210,86 KB), graph. Darst.
  15. Sieve inference on semi-nonparametric time series models
    Author: Chen, Xiaohong; Liao, Zhipeng; Sun, Yixiao
    Published: 2012
    Publisher:  Centre for Microdata Methods and Practice, London

    The method of sieves has been widely used in estimating semiparametric and nonparametric models. In this paper, we first provide a general theory on the asymptotic normality of plug-in sieve M estimators of possibly irregular functionals of... more

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    The method of sieves has been widely used in estimating semiparametric and nonparametric models. In this paper, we first provide a general theory on the asymptotic normality of plug-in sieve M estimators of possibly irregular functionals of semi/nonparametric time series models. Next, we establish a surprising result that the asymptotic variances of plug-in sieve M estimators of irregular (i.e., slower than root-T estimable) functionals do not depend on temporal dependence. Nevertheless, ignoring the temporal dependence in small samples may not lead to accurate inference. We then propose an easy-to-compute and more accurate inference procedure based on a "pre-asymptotic" sieve variance estimator that captures temporal dependence. We construct a "pre-asymptotic" Wald statistic using an orthonormal series long run variance (OS-LRV) estimator. For sieve M estimators of both regular (i.e., root-T estimable) and irregular functionals, a scaled "pre-asymptotic" Wald statistic is asymptotically F distributed when the series number of terms in the OS-LRV estimator is held fixed. Simulations indicate that our scaled "pre-asymptotic" Wald test with F critical values has more accurate size in finite samples than the usual Wald test with chi-square critical values.

     
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    hdl: 10419/64726
    Series: Cemmap working paper / Centre for Microdata Methods and Practice ; 06/12
    Scope: Online-Ressource (PDF-Datei: 53 S., 1053 KB), graph. Darst.
  16. Sensitivity analysis in semiparametric likelihood models
    Author: Chen, Xiaohong; Tamer, Elie T.; Torgovitsky, Alexander
    Published: 2011
    Publisher:  Cowles Foundation for Research in Economics, Yale Univ., New Haven, Conn.

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    Series: Cowles Foundation discussion paper ; 1836
    Scope: Online-Ressource ( 58 S., 662,47 KB), graph. Darst.
  17. A practical asymptotic variance estimator for two-step semiparametric estimators
    Author: Ackerberg, Daniel A.; Chen, Xiaohong; Hahn, Jinyong
    Published: 2010
    Publisher:  Centre for Microdata Methods and Practice, London

    The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using... more

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    The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the already-well-known parametric literature. This means that for computational purposes, an empirical researcher can ignore the semiparametric nature of the problem and do all calculations "as if" it were a parametric situation. We hope that this simplicity will promote the use of semiparametric procedures.

     
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    hdl: 10419/64722
    Edition: Final Version: July, 2010
    Series: Cemmap working paper / Centre for Microdata Methods and Practice ; 22/11
    Subjects: Nichtparametrisches Verfahren; Induktive Statistik; Theorie
    Scope: Online-Ressource (PDF-Datei: 44, 6 S., 641 KB)
  18. Penalized sieve estimation and inference of semi-nonparametric dynamic models
    a selective review
    Author: Chen, Xiaohong
    Published: 2011
    Publisher:  Centre for Microdata Methods and Practice, London

    In this selective review, we first provide some empirical examples that motivate the usefulness of semi-nonparametric techniques in modelling economic and financial time series. We describe popular classes of semi-nonparametric dynamic models and... more

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    In this selective review, we first provide some empirical examples that motivate the usefulness of semi-nonparametric techniques in modelling economic and financial time series. We describe popular classes of semi-nonparametric dynamic models and some temporal dependence properties. We then present penalized sieve extremum (PSE) estimation as a general method for semi-nonparametric models with cross-sectional, panel, time series, or spatial data. The method is especially powerful in estimating difficult ill-posed inverse problems such as semi-nonparametric mixtures or conditional moment restrictions. We review recent advances on inference and large sample properties of the PSE estimators, which include (1) consistency and convergence rates of the PSE estimator of the nonparametric part; (2) limiting distributions of plug-in PSE estimators of functionals that are either smooth (i.e., root-n estimable) or non-smooth (i.e., slower than root-n estimable); (3) simple criterion-based inference for plug-in PSE estimation of smooth or non-smooth functionals; and (4) root-n asymptotic normality of semiparametric two-step estimators and their consistent variance estimators. Examples from dynamic asset pricing, nonlinear spatial VAR, semiparametric GARCH, and copula-based multivariate financial models are used to illustrate the general results. -- Nonlinear time series ; Temporal dependence ; Tail dependence ; Penalized sieve M estimation ; Penalized sieve minimum distance ; Semiparametric two-step ; Nonlinear ill-posed inverse ; Mixtures ; Conditional moment restrictions ; Nonparametric endogeneity ; Dynamic asset pricing ; Varying coefficient VAR ; GARCH ; Copulas ; Value-at-risk

     
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    Other identifier:
    hdl: 10419/64736
    Series: Cemmap working paper / Centre for Microdata Methods and Practice ; 23/11
    Subjects: Zeitreihenanalyse; Nichtparametrisches Verfahren; VAR-Modell; ARCH-Modell
    Scope: Online-Ressource (PDF-Datei: 54 S., 411 KB)
  19. An estimation of economic models with recursive preferences
    Author: Chen, Xiaohong; Favilukis, Jack; Ludvigson, Sydney C.
    Published: 2011

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    Series: NBER working paper series ; 17130
    Subjects: CAPM; Kapitaleinkommen; Faktorsubstitution; Konsumtheorie; Theorie; CCAPM
    Scope: 54, [14] S., graph. Darst.
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    Parallel als Online-Ausg. erschienen
  20. A practical asymptotic variance estimator for two-step semiparametric estimators
    Author: Ackerberg, Daniel A.; Chen, Xiaohong; Hahn, Jinyong
    Published: 2011
    Publisher:  Cowles Foundation for Research in Economics, Yale Univ., New Haven, Conn.

    The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using... more

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    VS 29 (1803)
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    The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the already-well-known parametric literature. This means that for computational purposes, an empirical researcher can ignore the semiparametric nature of the problem and do all calculations "as if" it were a parametric situation. We hope that this simplicity will promote the use of semiparametric procedures.

     
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    Series: Cowles Foundation discussion paper ; 1803
    Subjects: Nichtparametrisches Verfahren
    Scope: Online-Ressource (PDF-Datei: 44, 6 S., 334,82 KB)
  21. Penalized sieve estimation and inference of semi-nonparametric dynamic models
    a selective review
    Author: Chen, Xiaohong
    Published: 2011
    Publisher:  Cowles Foundation for Research in Economics, Yale Univ., New Haven, Conn.

    In this selective review, we first provide some empirical examples that motivate the usefulness of semi-nonparametric techniques in modelling economic and financial time series. We describe popular classes of semi-nonparametric dynamic models and... more

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    In this selective review, we first provide some empirical examples that motivate the usefulness of semi-nonparametric techniques in modelling economic and financial time series. We describe popular classes of semi-nonparametric dynamic models and some temporal dependence properties. We then present penalized sieve extremum (PSE) estimation as a general method for semi-nonparametric models with cross-sectional, panel, time series, or spatial data. The method is especially powerful in estimating difficult ill-posed inverse problems such as semi-nonparametric mixtures or conditional moment restrictions. We review recent advances on inference and large sample properties of the PSE estimators, which include (1) consistency and convergence rates of the PSE estimator of the nonparametric part; (2) limiting distributions of plug-in PSE estimators of functionals that are either smooth (i.e., root-n estimable) or non-smooth (i.e., slower than root-n estimable); (3) simple criterion-based inference for plug-in PSE estimation of smooth or non-smooth functionals; and (4) root-n asymptotic normality of semiparametric two-step estimators and their consistent variance estimators. Examples from dynamic asset pricing, nonlinear spatial VAR, semiparametric GARCH, and copula-based multivariate financial models are used to illustrate the general results.

     
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    Format: Online
    Series: Cowles Foundation discussion paper ; 1804
    Subjects: Zeitreihenanalyse; Nichtparametrisches Verfahren; VAR-Modell; ARCH-Modell
    Scope: Online-Ressource (PDF-Datei: 54 S., 410,83 KB)
  22. Principal components and long run implications of multivariate diffusions
    Author: Chen, Xiaohong; Hansen, Lars Peter; Scheinkman, José Alexandre
    Published: 2009
    Publisher:  Cowles Foundation for Research in Economics, Yale Univ., New Haven, Conn.

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    Series: Cowles Foundation discussion paper ; 1694
    Scope: Online-Ressource, (49 S.), graph. Darst.
  23. Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals
    Author: Chen, Xiaohong; Pouzo, Demian
    Published: 2009
    Publisher:  Centre for Microdata Methods and Practice, London

    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 variables. We show that: (1) the penalized sieve... more

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    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 variables. We show that: (1) the penalized sieve minimum distance(PSMD) estimator (ˆΘ, ˆh) can simultaneously achieve root-n asymptotic normality of ˆΘ and nonparametric optimal convergence rate of ˆh, allowing for noncompact function parameter spaces; (2) a simple weighted bootstrap procedure consistently estimates the limiting distribution of the PSMD ˆΘ; (3) the semiparametric efficiency bound formula of Ai and Chen (2003) remains valid for conditional models with nonsmooth residuals, and the optimally weighted PSMD estimator achieves the bound; (4) the centered, profiled optimally weighted PSMD criterion is asymptotically chi-square distributed. We illustrate our theories using a partially linear quantile instrumental variables (IV) regression, a Monte Carlo study, and an empirical estimation of the shape-invariant quantile IV Engel curves. -- Penalized sieve minimum distance ; Nonsmooth generalized residuals ; Nonlinear nonparametric endogeneity ; Weighted bootstrap ; Semiparametric efficiency ; Confidence region ; Partially linear quantile IV regression ; Shape-invariant quantile IV Engel curves

     
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    Other identifier:
    hdl: 10419/64653
    Series: Cemmap working paper / Centre for Microdata Methods and Practice ; 20/09
    Subjects: Nichtparametrisches Verfahren; Bootstrap-Verfahren; Schätztheorie
    Scope: Online-Ressource (PDF-Datei: 32 S.), graph. Darst.
  24. Averaging of moment condition estimators
    Author: Chen, Xiaohong; Jacho-Chàvez, David T.; Linton, Oliver
    Published: 2012
    Publisher:  Centre for Microdata Methods and Practice, London

    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... more

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 243 (2012,26)
    Inter-library loan:
    No inter-library loan

     

    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 estimator in that case is shown to achieve the semiparametric efficiency bound. The proofs do not rely on smoothness of underlying criterion functions.

     
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    Content information
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/64693
    Series: Cemmap working paper / Centre for Microdata Methods and Practice ; 26/12
    Scope: Online-Ressource (PDF-Datei: 36 S., 401 KB), graph. Darst.
  25. Asymptotic efficiency of semiparametric two-step GMM
    Author: Chen, Xiaohong; Hahn, Jinyong; Liao, Zhipeng
    Published: 2012
    Publisher:  Cowles Foundation for Research in Economics, Yale Univ., New Haven, Conn.

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    VS 29 (1880)
    Inter-library loan:
    No inter-library loan
    Export to reference management software   RIS file
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    Content information
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Cowles Foundation discussion paper ; 1880
    Scope: Online-Ressource (23 S., 207,19 KB)