We consider a model with both a parametric global trend and a nonparametric local trend. This model may be of interest in a number of applications in economics, finance, ecology, and geology. We first propose two hypothesis tests to detect whether two nested special cases are appropriate. For the case where both null hypotheses are rejected, we propose an estimation method to capture certain aspects of the time trend. We establish consistency and some distribution theory in the presence of a large sample. Moreover, we examine the proposed hypothesis tests and estimation methods through both simulated and real data examples. Finally, we discuss some potential extensions and issues when modelling time effects
A restriction on a semiparametric or nonparametric econometric time series model determines the valu...
Thesis (Ph. D.)--University of Rochester. Department of Economics, 2015.This dissertation is a colle...
Abstract. In this paper we consider semiparametric inference methods for the time scale parameters i...
Power law or generalized polynomial regressions with unknown real-valued exponents and coefficients,...
Hypothesis testing in models allowing for trending processes that are possibly nonstationary and non...
A semiparametric model is proposed in which a parametric filtering of a nonstationary time series, i...
Many time series in applied sciences obey a time-varying spectral structure. In this article, we foc...
In this article, we construct the uniform confidence band (UCB) of nonparametric trend in a partiall...
Many time series in applied sciences obey a time-varying spectral structure. In this article, we foc...
My dissertation consists of six essays which contribute new theoretical resultsto two econometrics f...
In recent decades, semiparametric and nonparametric models have received increasing interest, which ...
We propose the use of indirect inference estimation to conduct inference in complex locally stationa...
The econometric literature of high frequency data often relies on moment estimators which are derive...
This thesis is concerned with various non- and semiparametric estimation problems in a locally stati...
This paper proposes a nonparametric test for common trends in semiparametric panel data models with ...
A restriction on a semiparametric or nonparametric econometric time series model determines the valu...
Thesis (Ph. D.)--University of Rochester. Department of Economics, 2015.This dissertation is a colle...
Abstract. In this paper we consider semiparametric inference methods for the time scale parameters i...
Power law or generalized polynomial regressions with unknown real-valued exponents and coefficients,...
Hypothesis testing in models allowing for trending processes that are possibly nonstationary and non...
A semiparametric model is proposed in which a parametric filtering of a nonstationary time series, i...
Many time series in applied sciences obey a time-varying spectral structure. In this article, we foc...
In this article, we construct the uniform confidence band (UCB) of nonparametric trend in a partiall...
Many time series in applied sciences obey a time-varying spectral structure. In this article, we foc...
My dissertation consists of six essays which contribute new theoretical resultsto two econometrics f...
In recent decades, semiparametric and nonparametric models have received increasing interest, which ...
We propose the use of indirect inference estimation to conduct inference in complex locally stationa...
The econometric literature of high frequency data often relies on moment estimators which are derive...
This thesis is concerned with various non- and semiparametric estimation problems in a locally stati...
This paper proposes a nonparametric test for common trends in semiparametric panel data models with ...
A restriction on a semiparametric or nonparametric econometric time series model determines the valu...
Thesis (Ph. D.)--University of Rochester. Department of Economics, 2015.This dissertation is a colle...
Abstract. In this paper we consider semiparametric inference methods for the time scale parameters i...