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Nonlinear Time Series: Semiparametric and Nonparametric Methods
TLDR
"Nonlinear Time Series: Semiparametric and Nonparametric Methods" focuses on various semiparametrical methods in time series analysis and provides the necessary theoretical details. Expand
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Bandwidth Selection in Nonparametric Kernel Testing
We propose a sound approach to bandwidth selection in nonparametric kernel testing. The main idea is to find an Edgeworth expansion of the asymptotic distribution of the test concerned. Due to theExpand
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Semiparametric Trending Panel Data Models with Cross-Sectional Dependence
A semiparametric fixed effects model is introduced to describe the nonlinear trending phenomenon in panel data analysis and it allows for the cross-sectional dependence in both the regressors and theExpand
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Non�?Parametric Time�?Varying Coefficient Panel Data Models with Fixed Effects
This paper is concerned with developing a nonparametric time-varying coefficient model with fixed effects to characterize nonstationarity and trending phenomenon in nonlinear panel data analysis. WeExpand
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Empirical comparisons in short-term interest rate models using nonparametric methods
This study applies the nonparametric estimation procedure to the diffusion process modeling the dynamics of short-term interest rates. This approach allows us to operate in continuous time,Expand
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Asymptotic theory for partly linear models
This paper considers a partially linear model of the form y = x beta + g(t) + e, where beta is an unknown parameter vector, g(.) is an unknown function, and e is an error term. Based on aExpand
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Econometric estimation in long-range dependent volatility models: Theory and practice
It is commonly accepted that some financial data may exhibit long-range dependence, while other financial data exhibit intermediate-range dependence or short-range dependence. These behaviours may beExpand
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Nonparametric specification testing for nonlinear time series with nonstationarity
This paper considers a nonparametric time series regression model with a nonstationary regressor. We construct a nonparametric test for whether the regression is of a known parametric form indexed byExpand
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Estimation in semiparametric spatial regression
Nonparametric methods have been very popular in the last couple of decades in time series and regression, but no such development has taken place for spatial models. A rather obvious reason for thisExpand
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Adaptive testing in continuous-time diffusion models
We propose an optimal test procedure for testing the marginal density functions of a class of nonlinear diffusion processes. The proposed test is not only an optimal one but also avoidsExpand
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