The COVID‐19 recession that started in March 2020 led to an unprecedented decline in
economic activity across the globe. To fight this recession, policy makers in central banks …

This paper focuses on tail risk nowcasts of economic activity, measured by GDP growth, with
a potentially wide array of monthly and weekly information. We consider different models …

Mixed-frequency data prediction tasks are pertinent in various application domains, in which
one leverages progressively available high-frequency data to forecast/nowcast the low …

State-space models (SSMs) offer a powerful framework for dynamical system analysis,
wherein the temporal dynamics of the system are assumed to be captured through the …

Interest in regional economic issues coupled with advances in administrative data is driving
the creation of new regional economic data. Many of these data series could be useful for …

Entropy | Free Full-Text | Approximate Bayesian Inference Next Article in Journal Minimum
Spanning vs. Principal Trees for Structured Approximations of Multi-Dimensional Datasets …

To date, only annual information on economic activity is published for the 16 German states.
In this paper, we calculate quarterly regional GDP estimates for the period between 1995 to …

The empirical investigation of the macroeconomic consequences of fiscal or monetary policy
changes has typically relied on the conventional vector autoregressive framework, which …

This paper develops a simple two-stage variational Bayesian algorithm to estimate panel
spatial autoregressive models, where N, the number of cross-sectional units, is much larger …

Timely information about the state of regional economies can be essential for planning,
implementing and evaluating locally targeted economic policies. However, European …