To match the NBER business cycle features it is necessary to employ Generalised dynamic categorical (GDC) models that impose certain phase restrictions and permit multiple indexes. Theory suggests additional shape restrictions in the form of monotonicity and boundedness of certain transition...

This paper introduces a new regression model - Markov-switching mixed data sampling (MS-MIDAS) - that incorporates regime changes in the parameters of the mixed data sampling (MIDAS) models and allows for the use of mixed-frequency data in Markov-switching models. After a discussion of...

In this paper, we aim at assessing Markov-switching and threshold models in their ability to identify turning points of economic cycles. By using vintage data that are updated on a monthly basis, we compare their ability to detect ex-post the occurrence of turning points of the classical...

The R word has begun to appear in the media again bringing with it three technical questions viz, How will we know we are in recession? How will we know when it has ended? And How can we forecast its onset and ending? This paper does not provide answers to these questions rather it focuses on...

To match the NBER business cycle features it is necessary to employ Generalised dynamic categorical (GDC) models that impose certain phase restrictions and permit multiple indexes. Theory suggests additional shape restrictions in the form of monotonicity and boundedness of certain transition...

For modelling mixed-frequency data with business cycle pattern we introduce the Markovswitching Mixed Data Sampling model with unrestricted lag polynomial (MS-U-MIDAS). Usually models of the MIDAS-class use lag polynomials of a specific function, which impose some structure on the weights of...

This paper investigates the volatility of the rates of output growth for the U.S., Canada and the UK. We empirically characterize the volatility of the growth rate of real GDP and, at the same time, we hope we can successfully identify business cycle turning points. The empirical results show...

The aim of this paper is the identification of structural shocks which affect the dynamics of sectoral inventories, through an analysis of the forecasting error variance decomposition. This identification is achieved using the American and French time series of aggregate production, sectoral...

We provide a signal modality analysis to characterize and detect nonlinearity schemes in the US Industrial Production Index time series. The analysis is achieved by using the recently proposed ‘delay vector variance’ (DVV) method, which examines local predictability of a signal in the phase...

In this paper we investigate whether exchange rate pass-through (ERPT) responds nonlinearly to economic activity along the business cycle. Using quarterly data spanning the period 1975:1 to 2011:1, we explore the existence of nonlinearities in ERPT to CPI inflation for the Finnish economy....