We investigate some estimation and testing issues for a class of high-dimensional near unit root time series models. We first study the asymptotic behavior of the first k largest eigenvalues of the sample covariance matrices of the time series model. Then we propose a new estimator for the...

This paper establishes asymptotic properties for spiked empirical eigenvalues of sample co- variance matrices for high-dimensional data with both cross-sectional dependence and a dependent sample structure. A new finding from the established theoretical results is that spiked empirical...

China has recently overtaken the US to become the world largest importer of crude oil. In light of this fact, we formally compare contributions of demand shocks from China, the US and the rest of the world. We find that China's influence on the real price of oil has increased over the past two...

This paper proposes a new near-unit root test for a class of high-dimensional nonstationary time series. A central limit theorem for the proposed test is proposed and then evaluated by an extensive simulation study

Accurate estimation for extent of cross-sectional dependence in large panel data analysis is paramount to further statistical analysis on the data under study. Grouping more data with weak relations (cross--sectional dependence) together often results in less efficient dimension reduction and...

We introduce a new class of stochastic volatility models with autoregressive moving average (ARMA) innovations. The conditional mean process has a flexible form that can accommodate both a state space representation and a conventional dynamic regression. The ARMA component introduces serial...

Recent research shows that matching between contemporaneous revenues and expenses has declined over the past 40 years. We argue that this decline in matching reduces the contracting usefulness of earnings and affects managerial effort allocation and performance measure choice. Based on a...