In regression models, appropriate bootstrap methods for inference robust to heteroskedasticity of unknown form are the wild bootstrap and the pairs bootstrap. The finite sample performance of a heteroskedastic-robust test is investigated with Monte Carlo experiments. The simulation results suggest that one specific version of the wild bootstrap outperforms the other versions of the wild bootstr...

Recent asset-pricing models incorporate jump risk through Lévy processes in addition to diffusive risk. This paper studies how to detect stochastic arrivals of small and big Lévy jumps with new nonparametric tests. The tests allow for robust analysis of their separate characteristics and facilitate better estimation of return dynamics. Empirical evidence of both small and big jumps based on the...

The paper investigates asymptotically efficient inference in general time series likelihood models with time varying parameters. Inference procedures for general loss functions are evaluated by a weighted average risk criterion. The weight function focusses on persistent parameter paths of moderate magnitude, and is proportional to the distribution function of a Gaussian random walk. It is show...

We make use in this article of a testing procedure suggested by Robinson (1994) for testing deterministic seasonality versus seasonal fractional integration. A new test statistic is developed to simultaneously test both, the order of integration of the seasonal component and the need of seasonal dummy variables. Finite-sample critical values of the tests are computed and, an empirical applicati...

Modern, high dimensional data has renewed investigation on instrumental variables (IV) analysis, primary focusing on estimation of the included endogenous variable under sparsity and little attention towards specification tests. This paper studies in high dimensions the Durbin-Wu-Hausman (DWH) test, a popular specification test for endogeneity in IV regression. We show, surprisingly, that the D...

This article investigates power and size of some tests for exogeneity of a binary explanatory variable in count models by conducting extensive Monte Carlo simulations. The tests under consideration are Hausman contrast tests as well as univariate Wald tests, including a new test of notably easy implementation. Performance of the tests is explored under misspecification of the underlying model a...

The two-break unit root test of Lumsdaine and Papell (1997) is examined and found to suffer from bias and spurious rejections in the presence of structural breaks under the null. A two-break minimum LM unit root test is proposed as a remedy. The two-break LM test does not suffer from bias and spurious rejections and is mostly invariant to the size, location, and misspecification of the breaks. ...

This paper introduces a Lagrange Multiplier (LM) test for testing an autoregressive structure in a binary time series model proposed by Kauppi and Saikkonen (2008). Simulation results indicate that the two versions of the proposed LM test have reasonable size and power properties when the sample size is large. A parametric bootstrap method is suggested to obtain approximately correct sizes also...

We agree that either mistaking a stochastic trend for a deterministic trend (or vice-versa) is consequential for unit root tests and for tests of nonlinear serial dependence. In addition, we comment that similar results obtain for ordinary parameter inference in simple linear models. In particular, we note that detrending stochastically trended data with a deterministic polynomial or by applyin...

We show how temporal aggregation affects the size and power of the DOLS residualbased KPSS test of the null of cointegration. Size is effectively controlled by setting the minimum number of leads equal to one – as opposed to zero – when selecting the lag/lead order of the DOLS regression, but at a cost to power in finite samples. If highfrequency data for one or more series are available, we sh...