The sample skewness and kurtosis of macroeconomic and financial time series are routinely scrutinized in the early stages of model-building and are often the central topic of studies in economics and finance. Notwithstanding the availability of several robust estimators, most scholars in...

The Beveridge-Nelson decomposition defines the trend component in terms of the eventual forecast function, as the value the series would take if it were on its long-run path. The paper in-troduces the multistep Beveridge-Nelson decomposition, which arises when the forecast function is obtained...

Im Zentrum dieser Dissertation steht das Beschreiben und Erklären von Konjunkturdynamiken. Motiviert durch den außerordentlich starken wirtschaftlichen Einbruch in 2008/2009 betont die Arbeit dabei die Wichtigkeit der Nutzung von nichtlinearen Modellansätzen. Die Dissertation kann als Beitrag...

The paper analyses reasons for departures from strong rationality of growth and inflation forecasts based on annual observations from 1963 to 2004. We rely on forecasts from the joint forecast of the so-called "six leading" forecasting institutions in Germany and argue that violations of the...

This paper discusses identification, specification, estimation and forecasting for a general class of periodic unobserved components time series models with stochastic trend, seasonal and cycle components. Convenient state space formulations are introduced for exact maximum likelihood...

The chapter deals with parametric models for the measurement of the business cycle in economic time series. It presents univariate methods based on parametric trend - cycle decompositions and multivariate models featuring a Phillips type relationship between the output gap and inflation and the...

We define and forecast classical business cycle turning points for the Norwegian economy. When defining reference business cycles, we compare a univariate and a multivariate Bry-Boschan approach with univariate Markov-switching models and Markov-switching factor models. On the basis of a...

This paper aims to assess the usefulness of leading indicators in business cycle research and forecast. Initially we test the predictive power of the ESI within a static probit model as a leading indicator, commonly perceived to be able to provide a reliable summary of the current economic...

Structural time series models are formulated in terms of components, such as trends, seasonals and cycles, that have a direct interpretation. As well as providing a framework for time series decomposition by signal extraction, they can be used for forecasting and for ‘nowcasting’. The...

Measuring economic activity in real-time is a crucial issue in applied research and in the decision-making process of policy makers; however, it also poses intricate challenges to statistical filtering methods that are built to operate optimally under the auspices of an infinite number of...