This paper uses wavelet theory to propose a frequency domain nonparametric and tuning parameter free family of unit root tests indexed by the fractional parameter d. The proposed test exploits the wavelet power spectrum of the observed series and its fractional partial sum to construct a test of...

This article addresses unit root testing on regulated series through the variance ratio (VR) statistic of Nielsen (2009). The asymptotic distribution of the regulated VR statistic is developed with and without OLS detrending. Results of Cavaliere and Xu (2011) are extended by also developing the...

This article provides an introduction to methods and challenges underlying application of the bootstrap in econometric modelling of economic and financial time series. Validity, or asymptotic validity, of the bootstrap is discussed as this is a key element in deciding whether the bootstrap is...

One important question in the DSGE literature is whether we should detrend data when estimating the parameters of a DSGE model using the moment method. It has been common in the literature to detrend data in the same way the model is detrended. Doing so works relatively well with linear models,...

We introduce a wild multiplicative bootstrap for M and GMM estimators in nonlinear models when autocorrelation structures of moment functions are unknown. The implementation of the bootstrap algorithm does not require any parametric assumptions on the data generating process. After proving its...

A new test for hysteresis based on a nonlinear unobserved components model is proposed. Observed unemployment rates are decomposed into a natural rate component and a cyclical component. Threshold type nonlinearities are introduced by allowing past cyclical unemployment to have a different...

A non-stationary regression model for financial returns is examined theoretically in this paper. Volatility dynamics are modelled both exogenously and deterministic, captured by a nonparametric curve estimation on equidistant centered returns. We prove consistency and asymptotic normality of a...

We present a general method to detect and extract from a finite time sample statistically meaningful correlations between input and output variables of large dimensionality. Our central result is derived from the theory of free random matrices, and gives an explicit expression for the interval...

In this paper we first investigate the validity of a general Value at Risk approach, which is widely used for risk management in banking and insurance companies. We discuss and widely reject the conventional assumptions, e.g. independent identically distributed normal returns, and as consequence...

In this paper, we study the asymptotic behavior of the sequential empirical process and the sequential empirical copula process, both constructed from residuals of multivariate stochastic volatility models. Applications for the detection of structural changes and specification tests of the...