In economics, many quantities are related to each other. Such
economic relations are often much more complex than relations in
science and engineering, where some quantities are independence,
and the relation between others can be well approximated by linear
functions. As a result of this complexity, when we apply
traditional statistical techniques -- developed for science and
engineering -- to process economic data, the inadequate treatment
of dependence leads to misleading models and erroneous predictions.
Some economists even blamed such inadequate treatment of dependence
for the 2008 financial crisis.
To make economic models more adequate, we need more accurate
techniques for describing dependence. Such techniques are currently
being developed. This book contains description of state-of-the-art
techniques for modeling dependence, and economic applications of
these techniques. Most of these research developments are centered
around the notion of a copula -- a general way of describing
dependence in probability theory and statistics. To be even more
adequate, many papers go beyond traditional copula techniques and
take into account, e.g., the dynamical (changing) character of the
dependence in economics.