This paper develops a wavelet (spectral) approach to testing the presence of a unit root in a
stochastic process. The wavelet approach is appealing, since it is based directly on the …

We propose a testing-based procedure to determine the number of common trends in a
large nonstationary dataset. Our procedure is based on a factor representation, where we …

Traditional tests of hypotheses on the cointegrating vector are well known to suffer from
severe size distortions in finite samples, especially when the data are characterized by large …

A bias-corrected nonparametric estimator of daily quadratic variations is proposed. The
estimator is a convex combination of two realized kernels with different bandwidths. It …

We propose a procedure to decide between the null hypothesis of (strict) stationarity and the
alternative of nonstationarity, in the context of a random coefficient autoregression (RCAR) …

This paper proposes a new portmanteau-type statistic by combining several lags of the
sample autocorrelations to test for the presence of a unit-root of an autoregressive model …

Traditional inference in cointegrating regressions requires tuning parameter choices to
estimate a long-run variance parameter. Even in case these choices are" optimal", the tests …

It is prominently stated in the literature that local asymptotic power properties serve as a
useful indicator for the performance of residual‐based no‐cointegration tests in finite …

In this paper, we propose a test statistic to determine the cointegration rank of VAR
processes in panel data allowing for cross-section dependence among the time series in the …

This paper develops a wavelet (spectral) approach to test the presence of a unit root in a
stochastic process. The wavelet approach is appealing, since it is based directly on the …