atRisk:At-Risk
The at-Risk (aR) approach is based on a two-step parametric estimation procedure that allows to forecast the
full conditional distribution of an economic variable at a
given horizon, as a function of a set of factors. These density
forecasts are then be used to produce coherent forecasts for
any downside risk measure, e.g., value-at-risk, expected
shortfall, downside entropy. Initially introduced by Adrian et
al. (2019) <doi:10.1257/aer.20161923> to reveal the
vulnerability of economic growth to financial conditions, the
aR approach is currently extensively used by international
financial institutions to provide Value-at-Risk (VaR) type
forecasts for GDP growth (Growth-at-Risk) or inflation
(Inflation-at-Risk). This package provides methods for
estimating these models. Datasets for the US and the Eurozone
are available to allow testing of the Adrian et al. (2019)
model. This package constitutes a useful toolbox (data and
functions) for private practitioners, scholars as well as
policymakers.
