Arbeitspapier
Empirical Likelihood Block Bootstrapping
Monte Carlo evidence has made it clear that asymptotic tests based on generalized method of moments (GMM) estimation have disappointing size. The problem is exacerbated when the moment conditions are serially correlated. Several block bootstrap techniques have been proposed to correct the problem, including Hall and Horowitz (1996) and Inoue and Shintani (2006). We propose an empirical likelihood block bootstrap procedure to improve inference where models are characterized by nonlinear moment conditions that are serially correlated of possibly infinite order. Combining the ideas of Kitamura (1997) and Brown and Newey (2002), the parameters of a model are initially estimated by GMM which are then used to compute the empirical likelihood probability weights of the blocks of moment conditions. The probability weights serve as the multinomial distribution used in resampling. The first-order asymptotic validity of the proposed procedure is proven, and a series of Monte Carlo experiments show it may improve test sizes over conventional block bootstrapping.
- Sprache
-
Englisch
- Erschienen in
-
Series: Queen's Economics Department Working Paper ; No. 1156
- Klassifikation
-
Wirtschaft
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Thema
-
generalized methods of moments
empirical likelihood
block-bootstrap
Momentenmethode
Bootstrap-Verfahren
Monte-Carlo-Simulation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Allen, Jason
Gregory, Allan W.
Shimotsu, Katsumi
- Ereignis
-
Veröffentlichung
- (wer)
-
Queen's University, Department of Economics
- (wo)
-
Kingston (Ontario)
- (wann)
-
2008
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Allen, Jason
- Gregory, Allan W.
- Shimotsu, Katsumi
- Queen's University, Department of Economics
Entstanden
- 2008
Ähnliche Objekte (12)
Empirical likelihood block bootstrapping
Bootstrapping the Likelihood Ratio Cointegration Test in Error Correction Models with Unknown Lag Order
Bootstrapping INAR models
Heteroskedasticity-and-Autocorrelation-Consistent Bootstrapping
Bootstrapping density-weighted average derivatives
Bootstrapping Non-Stationary Stochastic Volatility
Count data models with unobserved heterogeneity: An empirical likelihood approach
Higher order properties of GMM and generalized empirical likelihood estimators
Empirical likelihood-based model selection criteria for moment condition models
An empirical likelihood goodness-of-fit test for time series
Bootstrapping GARCH models under dependent innovations
Bootstrapping impulse responses in VAR analyses
Empirical likelihood block bootstrapping
Bootstrapping the Likelihood Ratio Cointegration Test in Error Correction Models with Unknown Lag Order
Bootstrapping INAR models
Heteroskedasticity-and-Autocorrelation-Consistent Bootstrapping
Bootstrapping density-weighted average derivatives
Bootstrapping Non-Stationary Stochastic Volatility
Count data models with unobserved heterogeneity: An empirical likelihood approach
Higher order properties of GMM and generalized empirical likelihood estimators
Empirical likelihood-based model selection criteria for moment condition models
An empirical likelihood goodness-of-fit test for time series
Bootstrapping GARCH models under dependent innovations
Bootstrapping impulse responses in VAR analyses
Empirical likelihood block bootstrapping
Bootstrapping the Likelihood Ratio Cointegration Test in Error Correction Models with Unknown Lag Order
Bootstrapping INAR models
Heteroskedasticity-and-Autocorrelation-Consistent Bootstrapping
Bootstrapping density-weighted average derivatives
Bootstrapping Non-Stationary Stochastic Volatility
Count data models with unobserved heterogeneity: An empirical likelihood approach
Higher order properties of GMM and generalized empirical likelihood estimators
Empirical likelihood-based model selection criteria for moment condition models
An empirical likelihood goodness-of-fit test for time series
Bootstrapping GARCH models under dependent innovations