In this paper we present and describe a large quarterly frequency, macroeconomic
database. The data provided are closely modeled to that used in Stock and Watson (2012a) …

We construct robust empirical Bayes confidence intervals (EBCIs) in a normal means
problem. The intervals are centered at the usual linear empirical Bayes estimator, but use a …

We introduce a dynamic network model with probabilistic link functions that depend on
stochastically time-varying parameters. We adopt a blockmodel framework and allow the …

Air pollution is a serious issue that currently affects many industrial cities in the world and
can cause severe illness to the population. In particular, it has been proven that extreme …

Unlike the central banks of most developed economies, the People's Bank of China (PBC)
does not release its macroeconomic forecasts to the public but instead carries out narrative …

We introduce a dynamic network model with probabilistic link functions that depend on
stochastically time-varying parameters. We adopt the widely used blockmodel framework …

Air pollution is a serious issue that currently affects many industrial cities in the world and
can cause severe illness to the population. In particular, it has been proven that extreme …

Deep Learning (DL) has gained momentum in recent years due to its incredible
generalisation performance achieved across many learning tasks. Nevertheless …

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In this thesis we empirically investigate to what extent such a detrimental start to “adult” life,
as sketched above, has lasting impacts on socioeconomic adult outcomes, and whether life …