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  1. Varying coefficient model with correlated error components and application to disparities between mental health service by councils in England
    Autor*in: Wongs-arta, Pipat; Kim, Namhyun; Xia, Yingcun; Moscone, Francesco
    Erschienen: January 2022
    Verlag:  Cardiff Business School, Cardiff University, Cardiff, United Kingdom

    In this paper, we discuss estimation procedure and various inferential methods for varying coefficient panel data models that include spatially correlated error components. Our estimation procedure is an extension of the quasi-maximum likelihood... mehr

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    DS 159
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    In this paper, we discuss estimation procedure and various inferential methods for varying coefficient panel data models that include spatially correlated error components. Our estimation procedure is an extension of the quasi-maximum likelihood method for spatial panel data regression to the conditional local kernel-weighted likelihood. We allow both relevant and irrelevant regressors in our model and propose a variable selection procedure that we show to perform well for models that involve spatial error dependence. We also extend our procedure so that it allows empirical modelling and testing of the so-called semi-varying coefficient specification. To ensure the statistical validity of our methods, we derive a set of asymptotic properties based on a collection of primitive assumptions that appear regularly in the nonparametric literature. Finally, we use the proposed model and methods to analyse the municipal disparities in mental health service spending by local authorities in England in order to illustrate practicability and empirical relevance.

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/261229
    Schriftenreihe: Cardiff economics working papers ; no. E2022, 1
    Schlagworte: Spatial models; Error components; Local maximum likelihood; Varying coefficient; Variable selection; Mental health services and expenditures
    Umfang: 1 Online-Ressource (circa 63 Seiten), Illustrationen
  2. Optimal smoothing for a computationally and statistically efficient single index estimator
    Autor*in: Xia, Yingcun; Härdle, Wolfgang; Linton, Oliver
    Erschienen: 2009
    Verlag:  SFB 649, Economic Risk, Berlin

    In semiparametric models it is a common approach to under-smooth the nonparametric functions in order that estimators of the finite dimensional parameters can achieve root-n consistency. The requirement of under-smoothing may result as we show from... mehr

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    Staats- und Universitätsbibliothek Bremen
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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    In semiparametric models it is a common approach to under-smooth the nonparametric functions in order that estimators of the finite dimensional parameters can achieve root-n consistency. The requirement of under-smoothing may result as we show from inefficient estimation methods or technical difficulties. Based on local linear kernel smoother, we propose an estimation method to estimate the single-index model without under-smoothing. Under some conditions, our estimator of the single-index is asymptotically normal and most efficient in the semi-parametric sense. Moreover, we derive higher expansions for our estimator and use them to define an optimal bandwidth for the purposes of index estimation. As a result we obtain a practically more relevant method and we show its superior performance in a variety of applications. -- ADE ; Asymptotics ; Bandwidth ; MAVE method ; Semi-parametric efficiency

     
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    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/25344
    Schriftenreihe: SFB 649 discussion paper ; 2009,028
    Schlagworte: Schätztheorie; Nichtparametrisches Verfahren; Theorie
    Umfang: Online-Ressource (30 S.), graph. Darst.
  3. Global Bahadur representation for nonparametric censored regression quantiles and its applications
    Autor*in: Kong, Efang; Linton, Oliver; Xia, Yingcun
    Erschienen: 2011
    Verlag:  Centre for Microdata Methods and Practice, London

    This paper is concerned with the nonparametric estimation of regression quantiles where the response variable is randomly censored. Using results on the strong uniform convergence of U-processes, we derive a global Bahadur representation for the... mehr

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    This paper is concerned with the nonparametric estimation of regression quantiles where the response variable is randomly censored. Using results on the strong uniform convergence of U-processes, we derive a global Bahadur representation for the weighted local polynomial estimators, which is sufficiently accurate for many further theoretical analyses including inference. We consider two applications in detail: estimation of the average derivative, and estimation of the component functions in additive quantile regression models. -- Bahadur representation ; Censored data ; Kernel smoothing ; Quantile regression ; Semiparametric models

     
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    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/64649
    Schriftenreihe: Cemmap working paper / Centre for Microdata Methods and Practice ; 33/11
    Schlagworte: Nichtparametrisches Verfahren; Regressionsanalyse; Schätztheorie
    Umfang: Online-Ressource (PDF-Datei: 30 S., 182 KB)
  4. Uniform Bahadur representation for local polynomial estimates of m-tegression and its application to the additive model
    Autor*in: Kong, Efang; Linton, Oliver; Xia, Yingcun
    Erschienen: 2009
    Verlag:  LSE, STICERD, London

    Standort:
    Niedersächsische Staats- und Universitätsbibliothek Göttingen
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: Econometrics publications ; 535
    Schlagworte: Regressionsanalyse; Schätztheorie
    Umfang: Online-Ressource (PDF-Datei: 41 S.)
  5. Optimal smoothing for a computationally and statistically efficient single index estimator
    Autor*in: Xia, Yingcun; Härdle, Wolfgang; Linton, Oliver
    Erschienen: 2009
    Verlag:  LSE, STICERD, London

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    Niedersächsische Staats- und Universitätsbibliothek Göttingen
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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: Econometrics publications ; 537
    Schlagworte: Schätztheorie; Nichtparametrisches Verfahren; Theorie
    Umfang: Online-Ressource (PDF-Datei: 30 S.), graph. Darst.
  6. Semi-parametric estimation of generalized partially linear single-index models
    Autor*in: Xia, Yingcun; Härdle, Wolfgang
    Erschienen: 2002
    Verlag:  Humboldt-Universität, Berlin

    One of the most difficult problems in applications of semiparametric generalized partially linear single-index model (GPLSIM) is the choice of pilot estimators and complexity parameters which may result in radically different estimators. Pilot... mehr

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    Staats- und Universitätsbibliothek Bremen
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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 20 (2002,56)
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    One of the most difficult problems in applications of semiparametric generalized partially linear single-index model (GPLSIM) is the choice of pilot estimators and complexity parameters which may result in radically different estimators. Pilot estimators are often assumed to be root-n consistent, although they are not given in a constructible way. Complexity parameters, such as a smoothing bandwidth are constrained to a certain speed, which is rarely determinable in practical situations. In this paper, efficient, constructible and practicable estimators of GPLSIMs are designed with applications to time series. The proposed technique answers two questions from Carroll et al. (1997): no root-n pilot estimator for the single index part of the model is needed and complexity parameters can be selected at the optimal smoothing rate. The asymptotic distribution is derived and the corresponding algorithm is easily implemented. Examples from real data sets (credit-scoring and environmental statistics) illustrate the technique and the proposed methodology of minimum average variance estimation (MAVE). -- Asymptotic distribution ; Generalized partially linear model ; Local linear smoother ; Optimal consistency rate ; Single-index model

     
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    Sprache: Englisch
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    Format: Online
    Weitere Identifier:
    hdl: 10419/65301
    Schriftenreihe: Discussion papers of interdisciplinary research project 373 ; 2002,56
    Umfang: Online-Ressource (PDF-Datei: 36 S., 676,41 KB), graph. Darst.
  7. New semiparametric estimation procedure for functional coefficient longitudinal data models
    Autor*in: Chen, Jia; Li, Degui; Xia, Yingcun
    Erschienen: 2015
    Verlag:  Department of Economics and Related Studies, University of York, York

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    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: Discussion papers in economics ; no. 15/17
    Umfang: 1 Online-Ressource (41 Seiten), Illustrationen