Arbeitspapier
Penalized sieve estimation and inference of semi-nonparametric dynamic models: A selective review
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.
- Language
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Englisch
- Bibliographic citation
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Series: cemmap working paper ; No. CWP23/11
- Classification
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Wirtschaft
Estimation: General
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: General
- Subject
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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
Zeitreihenanalyse
Nichtparametrisches Verfahren
VAR-Modell
ARCH-Modell
- Event
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Geistige Schöpfung
- (who)
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Chen, Xiaohong
- Event
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Veröffentlichung
- (who)
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Centre for Microdata Methods and Practice (cemmap)
- (where)
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London
- (when)
-
2011
- DOI
-
doi:10.1920/wp.cem.2011.2311
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Chen, Xiaohong
- Centre for Microdata Methods and Practice (cemmap)
Time of origin
- 2011
Other Objects (12)
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Optimal sup-norm rates and uniform inference on nonlinear functionals of nonparametric IV regression
Optimal sup-norm rates and uniform inference on nonlinear functionals of nonparametric IV regression
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Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments
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Local identification of nonparametric and semiparametric models
Sieve inference on semi-nonparametric time series models
Optimal uniform convergence rates for sieve nonparametric instrumental variables regression
Sieve Wald and QLR inferences on semi/ nonparametric conditional moment models
Optimal sup-norm rates, adaptivity and inference in nonparametric instrumental variables estimation
Optimal sup-norm rates and uniform inference on nonlinear functionals of nonparametric IV regression
Optimal sup-norm rates and uniform inference on nonlinear functionals of nonparametric IV regression
Estimation of nonparametric conditional moment models with possibly nonsmooth moments
Semi-nonparametric IV estimation of shape-invariant Engel curves
Likelihood inference in some finite mixture models
Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments
Nonparametric identification and estimation of nonclassical errors-in-variablles models without additional information
Local identification of nonparametric and semiparametric models
Sieve inference on semi-nonparametric time series models
Optimal uniform convergence rates for sieve nonparametric instrumental variables regression
Sieve Wald and QLR inferences on semi/ nonparametric conditional moment models
Optimal sup-norm rates, adaptivity and inference in nonparametric instrumental variables estimation
Optimal sup-norm rates and uniform inference on nonlinear functionals of nonparametric IV regression
Optimal sup-norm rates and uniform inference on nonlinear functionals of nonparametric IV regression
Estimation of nonparametric conditional moment models with possibly nonsmooth moments
Semi-nonparametric IV estimation of shape-invariant Engel curves
Likelihood inference in some finite mixture models
Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments
Nonparametric identification and estimation of nonclassical errors-in-variablles models without additional information