We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a...

We propose a new Bayesian VAR model for forecasting household loan stocks in Finland. The model is designed to work as a satellite model of a larger DSGE model for the Finnish economy, the Aino 2.0 model. The forecasts produced with the BVAR model can be conditioned on projections of several...

We develop a tractable model of Bitcoin adoption with network effects and social learning, which we then connect to unique data from the Bank of Canada's Bitcoin Omnibus Survey for the years 2017 and 2018. The model determines how the probability of Bitcoin adoption depends on (1) network...