The paper assesses the impact of adding information on financial cycles on the output gap estimates for eight advanced economies using two unobserved components models: a reduced form extended Hodrick-Prescott filter, and a standard semi-structural unobserved components model. To complement...

This paper studies the evolution of long-run output and labour productivity growth rates in the G-7 countries during the post-war period. We estimate the growth rates consistent with a constant unemployment rate using time-varying parameter models that incorporate both stochastic volatility and...

In this paper we investigate bootstrap-based methods for bias-correcting the first-stage parameter estimates used in some recently developed bootstrap implementations of the co-integration rank tests of Johansen (1996). In order to do so we adapt the framework of Kilian (1998) which estimates...

This paper provides a survey and synthesis of econometric tools that have been employed to study economic growth. While these tools range across a variety of statistical methods, they are united in the common goals of first, identifying interesting contemporaneous patterns in growth data and...

This paper investigates the effect of the nonzero autocorrelation coefficients on the sampling distributions of the Durbin-Watson test estimator in three time-series models that have different variance-covariance matrix assumption, separately. We show that the expected values and variances of...

Iterated one-step Huber-skip M-estimators are considered for regression problems. Each one-step estimator is a re-weighted least squares estimators with zero/one weights determined by the initial estimator and the data. The asymptotic theory is given for iteration of such estimators using a...

In this paper we investigate the properties of the Lagrange Multiplier (LM) test for autoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) in the presence of additive outliers (AO's). We show analytically that both the asymptotic size and power are adversely affected...

This paper describes how the frequency domain analysis provides an alternative approach to time domain analysis for a given time series. Spectral and periodogram analysis for a given time series are performed to detect trends and seasonalities in the data. A cross-spectral analysis is used to...