1 citations · 2 across the 4 of their papers we have counts for
5 papers
Simultaneous Inference of a Partially Linear Model in Time Series
Jiaqi Li, Likai Chen, Kun Ho Kim +1
We introduce a new methodology to conduct simultaneous inference of the nonparametric component in partially linear time series regression models where the nonparametric part is a…
A New Test for Market Efficiency and Uncovered Interest Parity
Richard T. Baillie, Francis X. Diebold, George Kapetanios +1
We suggest a new single-equation test for Uncovered Interest Parity (UIP) based on a dynamic regression approach. The method provides consistent and asymptotically efficient parame…
Bayesian estimation of the autocovariance of a model error in time series
Yoon Bae Jun, Chae Young Lim, Kun Ho Kim
Autocovariance of the error term in a time series model plays a key role in the estimation and inference for the model that it belongs to. Typically, some arbitrary parametric stru…
On Robust Inference in Time Series Regression
Richard T. Baillie, Francis X. Diebold, George Kapetanios +2
Least squares regression with heteroskedasticity consistent standard errors ("OLS-HC regression") has proved very useful in cross section environments. However, several major diffi…
Specification Test based on Convolution-type Distribution Function Estimates for Non-linear Auto-regressive Processes
Kun Ho Kim, Jiwoong Kim
The paper proposes a specification test based on two estimates of distribution function. One is the traditional kernel distribution function estimate and the other is a newly propo…