"Politically speaking, austerity is a challenge. While we would expect that
governments imposing spending cuts on their voting public may face electability
issues, in fact, a recent paper from the Center for Economic Policy Research
finds that there is no empirical evidence to confirm this - i.e. a
budget-cutting government is no less likely to be re-relected than a spend-heavy
government. However, what the CEPR paper does find as a factor in
delaying austerity is much more worrisome - a fear of instability and unrest.
The authors found a very clear relationship between CHAOS
(their variable name for demonstrations, riots, strikes and worse) and
expenditure cuts. As JPMorgan notes, austerity sounds
straightforward as a policy, until the consequences bite. It remains
unclear that the road Europe is taking is less costly in the long run, in
economic, political and social terms. The history of Europe over the
last 100 years shows that austerity can have severe consequences and
outcomes and perhaps most notably, the independent variable that did
result in more unrest: higher levels of government debt in the first
place.
The passage through time of the author's CHAOS factor shows that since 1994 we have had relative stability but given the ongoing austerity that is being forced (rightfully) upon the most indebted nations in Europe, it is perhaps no longer an issue of electability as technocrats roam freely and much more one of central stability and fear of the empirical link between austerity and anarchy..."
at http://www.zerohedge.com/news/austerity-unrest-and-quantifying-chaos
The passage through time of the author's CHAOS factor shows that since 1994 we have had relative stability but given the ongoing austerity that is being forced (rightfully) upon the most indebted nations in Europe, it is perhaps no longer an issue of electability as technocrats roam freely and much more one of central stability and fear of the empirical link between austerity and anarchy..."
at http://www.zerohedge.com/news/austerity-unrest-and-quantifying-chaos