  On September 15th 2020, Arctic sea ice extent (SIE) ranked second-to-lowest
in history and keeps trending downward. The understanding of how feedback loops
amplify the effects of external CO2 forcing is still limited. We propose the
VARCTIC, which is a Vector Autoregression (VAR) designed to capture and
extrapolate Arctic feedback loops. VARs are dynamic simultaneous systems of
equations, routinely estimated to predict and understand the interactions of
multiple macroeconomic time series. The VARCTIC is a parsimonious compromise
between full-blown climate models and purely statistical approaches that
usually offer little explanation of the underlying mechanism. Our completely
unconditional forecast has SIE hitting 0 in September by the 2060's. Impulse
response functions reveal that anthropogenic CO2 emission shocks have an
unusually durable effect on SIE -- a property shared by no other shock. We find
Albedo- and Thickness-based feedbacks to be the main amplification channels
through which CO2 anomalies impact SIE in the short/medium run. Further,
conditional forecast analyses reveal that the future path of SIE crucially
depends on the evolution of CO2 emissions, with outcomes ranging from
recovering SIE to it reaching 0 in the 2050's. Finally, Albedo and Thickness
feedbacks are shown to play an important role in accelerating the speed at
which predicted SIE is heading towards 0.
