This paper studies the behavior of corporate bond spreads during different market regimes between 2004 and 2016. Applying a Markov-switching vector autoregressive (MS-VAR) model, we document that the dynamic impact of spread determinants varies substantially with market conditions. In periods of...

To simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural changes, we introduce a time-varying parameter mixed-frequency VAR. To keep our approach from becoming too complex, we implement time variation parsimoniously: only the intercepts and a common...

There has been increased interest in the use of "big data" when it comes to forecasting macroeconomic time series such as private consumption or unemployment. However, applications on forecasting GDP are rather rare. In this paper we incorporate Google search data into a Bridge Equation Model, a...

Nonresponse in surveys may result in a distortion of the distribution of interest. In a panel survey the participation behavior in later waves is different from the participation behavior at the start. With register data that cover also the information for non-respondents one can observe a fade...

This paper studies the life-cycle dynamics of exporters and multinational enterprises (MNEs). We present a dynamic model of trade and MNE activity in which the mode of serving a market depends on the well-known proximity-concentration tradeoff. We show that the option of performing MNE...

This paper analyzes the sustainability of fiscal debt contingent on fiscal policy operating in two fiscal regimes. The first regime is characterized by active policy (not reacting to debt) and the other by passive fiscal policy (reacting to debt). The average duration for which either regime can...

Space-varying regression models are generalizations of standard linear models where the regression coefficients are allowed to change in space. The spatial structure is specified by a multivariate extension of pairwise difference priors thus enabling incorporation of neighboring structures and...

This paper is concerned with the study of Bayesian inference procedures to commonly used time series models. In particular, the dynamic or state-space models, the time-varying vector autoregressive model and the structural vector autoregressive model are considered in detail. Inference...