Do inflation expectations and the associated pass-through of oil price shocks depend on demand and supply conditions underlying the global market for crude oil? We answer this question with a novel structural vector autoregressive model of the global oil market that jointly identifies...

This paper demonstrates that inflation expectations have acted as significant amplifiers of recent global demand and supply shocks, thereby playing a crucial role in maintaining inflation at relatively high levels. This finding is established by applying a structural vector autoregression model...

We use Norwegian tax data and a life-cycle model with housing to study how wealth transmits across generations through the housing market. After controlling for a rich set of attributes, households with richer parents are nearly 15% more likely to be homeowners at age 30. Moreover, when...

The Fed's policy rule switches during the different phases of the business cycle. This finding is established using a dynamic mixture model to estimate regime-dependent Taylor-type rules on US quarterly data from 1960 to 2021. Instead of exogenously partitioning the data based on tenures of the...

We study scar formation and persistence after a house price bubble has burst using data on 3,089 US counties and county equivalents over the period 1980q1-2019q4. We date house price booms and busts for each county, and identify periods with explosive house price developments. Applying a sharp...

The Fed's policy rule shifts during different phases of the business cycle, particularly in relation to monetary easing and tightening phases. This finding is established through a dynamic mixture model, which estimates regime-dependent Taylor-type rules using US quarterly data from 1960 to...

The Fed's policy rule switches during the different phases of the business cycle. This finding is established using a dynamic mixture model to estimate regime-dependent Taylor-type rules on US quarterly data from 1960 to 2021. Instead of exogenously partitioning the data based on tenures of the...

We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...

This paper finds that asset prices on Oslo Stock Exchange is the single most important block of data to improve estimates of current quarter GDP in Norway. Other important blocks of data are labor market data and industrial production indicators. We use an approximate dynamic factor model that...

An approximate dynamic factor model can substantially improve the reliability of real time output gap estimates. The model extracts a common component from macroeconomic indicators, which reduces errors in the gap due to data revisions. The model's ability to handle the unbalanced arrival of...