While the limiting null distributions of cointegration tests are invariant to a certain amount of conditional heteroskedasticity as long as global homoskedasticity conditions are fulfilled, they are certainly affected when the innovations exhibit time-varying volatility. Worse yet, distortions...

A new stationarity test for heterogeneous panel data with large cross-sectional dimension is developed and used to examine a panel with growth rates of unit labor cost in the USA. The test allows for strong cross-unit dependence in the form of unbounded long-run correlation matrices, for which a...

In many forecast evaluation applications, standard tests as well as tests allowing for time‐variation in relative forecast ability build on heteroskedasticity‐and‐autocorrelation consistent (HAC) covariance estimators. Yet, the finite‐sample performance of these asymptotics is often...

The so-called Cauchy estimator uses the sign as instrument for the first lag in autoregressions, and the resulting t-type statistic has a standard normal distribution even in the unit root case. Thus, nonstandard asymptotics of the usual unit root tests such as the augmented Dickey-Fuller [ADF]...

The fixed-b asymptotic framework provides refinements in the use of heteroskedasticity and autocorrelation consistent variance estimators. We show however that the fixed-b limiting distributions of t-statistics are not pivotal when the variance of the underlying data generating process changes...

The Cauchy estimator of an autoregressive root uses the sign of the first lag as instrumental variable. The resulting IV <italic>t</italic>-type statistic follows a standard normal limiting distribution under a unit root case even under unconditional heteroscedasticity, if the series to be tested has no...

We propose an IV panel unit root test robust to nonstationary error volatility. Its finite-sample performance is convincing even for many units and strong cross-correlation. An application to GDP prices illustrates the inferential impact of nonstationary volatility.

The paper examines the behavior of a generalized version of the nonlinear IV unit root test proposed by Chang (<CitationRef CitationID="CR6">2002</CitationRef>) when the series’ errors exhibit nonstationary volatility. The leading case of such nonstationary volatility concerns structural breaks in the error variance. We show that the...</citationref>