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Bayesian Estimation for Partially Linear Models with an Application to Household Gasoline Consumption
Chen, Haotian; Zhang, Xibin - Department of Econometrics and Business Statistics, … - 2014
A partially linear model is often estimated in a two-stage procedure, which involves estimating the nonlinear component conditional on initially estimated linear coefficients. We propose a sampling procedure that aims to simultaneously estimate the linear coefficients and bandwidths involved in...
Persistent link: https://www.econbiz.de/10011105011
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Bayesian Bandwidth Estimation In Nonparametric Time-Varying Coefficient Models
Cheng, Tingting; Gao, Jiti; Zhang, Xibin - Department of Econometrics and Business Statistics, … - 2015
Bandwidth plays an important role in determining the performance of nonparametric estimators, such as the local … constant estimator. In this paper, we propose a Bayesian approach to bandwidth estimation for local constant estimators of time …-varying coefficients in time series models. We establish a large sample theory for the proposed bandwidth estimator and Bayesian estimators …
Persistent link: https://www.econbiz.de/10011188646
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Non Parametric Confidence Intervals for Receiver Operating Characteristic Curves
Hall, Peter G.; Hyndman, Rob J.; Fan, Yanan - Department of Econometrics and Business Statistics, … - 2003
impaired. A theoretical analysis of the problem suggests an empirical, plug-in rule for bandwidth choice, optimising the …
Persistent link: https://www.econbiz.de/10005427623
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Nonparametric Kernel Estimation of the Impact of Tax Policy on the Demand for Private Health Insurance in Australia
Gong, Xiaodong; Gao, Jiti - Department of Econometrics and Business Statistics, … - 2015
This paper is motivated by our attempt to answer an empirical question: how is private health insurance take-up in Australia affected by the income threshold at which the Medicare Levy Surcharge (MLS) kicks in? We propose a new difference de-convolution kernel estimator for the location and size...
Persistent link: https://www.econbiz.de/10011262824
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Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity
Dong, Chaohua; Gao, Jiti; Peng, Bin - Department of Econometrics and Business Statistics, … - 2015
In this paper, we consider a partially linear panel data model with cross-sectional dependence and non-stationarity. Meanwhile, we allow fixed effects to be correlated with the regressors to capture unobservable heterogeneity. Under a general spatial error dependence structure, we then...
Persistent link: https://www.econbiz.de/10011262825
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Semiparametric Localized Bandwidth Selection in Kernel Density Estimation
Cheng, Tingting; Gao, Jiti; Zhang, Xibin - Department of Econometrics and Business Statistics, … - 2014
Since conventional cross-validation bandwidth selection methods do not work for the case where the data considered are … serially dependent, alternative bandwidth selection methods are needed. In recent years, Bayesian based global bandwidth … selection methods have been proposed. Our experience shows that the use of a global bandwidth is however less suitable than …
Persistent link: https://www.econbiz.de/10010958940
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Semiparametric Single-Index Panel Data Models with Cross-Sectional Dependence
Peng, Bin; Dong, Chaohua; Gao, Jiti - Department of Econometrics and Business Statistics, … - 2014
In this paper, we consider a semiparametric single index panel data mode with cross-sectional dependence, high-dimensionality and stationarity. Meanwhile, we allow fixed effects to be correlated with the regressors to capture unobservable heterogeneity. Under a general spatial error dependence...
Persistent link: https://www.econbiz.de/10010958943
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Semiparametric Model Selection in Panel Data Models with Deterministic Trends and Cross-Sectional Dependence
Chen, Jia; Gao, Jiti - Department of Econometrics and Business Statistics, … - 2014
In this paper, we consider a model selection issue in semiparametric panel data models with fixed effects. The modelling framework under investigation can accommodate both nonlinear deterministic trends and cross-sectional dependence. And we consider the so-called "large panels" where both the...
Persistent link: https://www.econbiz.de/10010958955
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Estimation for Single-index and Partially Linear Single-index Nonstationary Time Series Models
Dong, Chaohua; Gao, Jiti; Tjostheim, Dag - Department of Econometrics and Business Statistics, … - 2014
Estimation in two classes of popular models, single-index models and partially linear single-index models, is studied in this paper. Such models feature nonstationarity. Orthogonal series expansion is used to approximate the unknown integrable link function in the models and a profile approach...
Persistent link: https://www.econbiz.de/10010958956
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Local Linear Forecasts Using Cubic Smoothing Splines
Hyndman, Rob J; King, Maxwell L.; Pitrun, Ivet; Billah, Baki - Department of Econometrics and Business Statistics, … - 2002
We show how cubic smoothing splines fitted to univariate time series data can be used to obtain local linear forecasts. Our approach is based on a stochastic state space model which allows the use of a likelihood approach for estimating the smoothing parameter, and which enables easy...
Persistent link: https://www.econbiz.de/10005087585