We develop a new test of a parametric model of a conditional mean function against a nonparametric alternative. The test adapts to the unknown smoothness of the alternative model and is uniformly consistent against alternatives whose distance from the parametric model converges to zero at the...

In this paper we introduce a bootstrap procedure to test parameter restrictions in vector autoregressive models which is robust in cases of conditionally heteroskedastic error terms. The adopted wild bootstrap method does not require any parametric specification of the volatility process and...

The use of asymptotic critical values in stationarity tests against the alternative of a unit rot process is known to lead to overrejections in finite samples when the considered process is stationary but highly persistent. We claim that in recent parametric tests this is caused by estimation...

A major application of rescaled adjusted range analysis (RS analysis) is the study of price fluctuations in financial markets. There, the value of the Hurst constant, H, in a time series may be interpreted as an indicator of the irregularity of the price of a commodity, currency or similar...

The small sample properties of two types of Chow tests are investigated in the context of multiple time series models. It is found that the tests may have substantially distorted size if the sample size is not large relative to the number of parameters in the model under study. In particular the...

Tests for unit roots and other nonstationary hypotheses that were proposed by Robinson (1994) are applied in this article to the Nelson and Plosser's (1982) series. The tests can be expressed in a way allowing for structural breaks under both the null and the alternative hypotheses. When...

The paper derives an algorithm for computing leave-k-out diagnostics for the detection of patches of outliers for stationary and non-stationary state space models with regression effects. The algorithm is based on a reverse run of the Kalman filter on the smoothing errors and is both efficient...

The testing of a computing model for a stationary time series is a standard task in statistics. When a parametric approach is used to model the time series, the question of goodness-of-fit arises. In this paper, we employ the empirical likelihood for an a-mixing process and formulate a statistic...