We search for the presence of hysteresis, which we define as aggregate demand shocks that have a permanent impact on real GDP, in the U.S., the Euro Area, and the U.K. Working with cointegrated structural VARs, we find essentially no evidence of such effects. Within a Classical statistical...

In this paper, I examine the forecasting performance of a Bayesian Vector Autoregression (BVAR) model with steady-state prior and compare the accuracy of the forecasts against the forecasts of QPM model and official NBU forecasts over the period 2016q1-2020q1. My findings suggest that inflation...

We study the dynamic impact of Covid-19, economic mobility, and containment policy shocks. We use Bayesian panel structural vector autoregressions with daily data for 44 countries, identified through sign and zero restrictions. Incidence and mobility shocks raise cases and deaths significantly...

This paper studies how to combine real-time forecasts from a broad range of Bayesian vector autoregression (BVAR) specifications and survey forecasts by optimally exploiting their properties. To do that, it compares the forecasting performance of optimal pooling and tilting techniques, including...

This note provides the details of the estimation procedure in Br¨unner (2019). In Section 2 we derive the posterior distribution. Section 3 describes the MCMC algorithm used to obtain draws from the posterior distribution and in Section 4 we present the method for our model check. We conclude...

This article describes the techniques employed in the production of a synthetic dataset of driver telematics emulated from a similar real insurance dataset. The synthetic dataset generated has 100,000 policies that included observations regarding driver's claims experience, together with...

Reliable local demographic schedules are in high demand, but small area problems pose a challenge to estimation. The literature has directed little attention to the opportunities created by increased availability of high-quality geo-coded data. We propose the use of empirical Bayes methods based...

Although a large number of mortality projection models have been proposed in the literature, relatively little attention has been paid to a formal assessment of the effect of model uncertainty. In this paper, we construct a Bayesian framework for embedding more than one mortality projection...

During the past decades, seasonal autoregressive integrated moving average (SARIMA) had become one of a prevalent linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear models can be an encouraging alternative to traditional linear models....