Clearly, you’ll lose $1 about five times out of six,
and you’ll win $10 about one time out of six. Over many gambles, this averages
out to about 83 cents per try. Hence, the gamble has a positive “expected”
payoff and is worth it, even if the gain is trifling. Play a million times and
you’re sure to win big.
But here’s something odd. Suppose I offer precisely
the same gamble, only scaled up. Roll a six and you now win not $10, but 10
times your total current wealth; if you roll anything else, you lose your
entire wealth (including property, pensions and all possessions). Your expected
profit is now far bigger -- equal to 83 percent of your total current wealth.
Still want to play? It turns out that most people won’t take the latter
bet, even though it will, on average, pay off handsomely. Why not? For most of
us, putting everything on the line seems too risky. Intuitively, we understand
that getting wiped out carries a brutal finality, curtailing future options and
possibilities.
‘Risk Averse’
Economic theories generally ascribe such cautious
behavior to psychology. Humans are “risk averse,” some of us more than others.
But there’s a fundamental error in this way of thinking that still remains
largely unappreciated -- even though it casts a long and distorting shadow over
everything from portfolio theory to macroeconomics and financial regulation.
Economics, in following Pascal, still hasn’t faced up honestly to the problem
of time.
Anyone who faces risky situations over time -- and
that’s essentially everyone -- needs to handle those risks well, on average,
over time, with one thing happening after the next. The seductive genius of the
concept of probability is that it removes this history aspect, and estimates
the average payoff by thinking of a single gamble alone, with two outcomes. It
imagines the world splitting with specific probabilities into parallel
universes, one thing happening in each. The expected value doesn’t reflect an
average over time, but over possible outcomes considered outside of time.
This is so familiar that most of us take it as the
obvious method of reasoning. That’s a mistake. As the physicist Ole Peters of
the London Mathematical Laboratory has shown in several recent papers, averages
through time and over probable outcomes aren’t the same, and the latter
calculation offers a dangerously misleading guide to risky choices. Especially
whenever downside risks get large, real outcomes averaged through time are much
worse than the expected value would predict. Even in the absence of risk
aversion, there can be sound mathematical reasons for being unwilling to take
on gambles (or projects), despite wildly positive expected payoffs. (To learn
more, see my blog).
So what? Well, the assumption of the equality of
these different averages -- technically known as the assumption of “ergodicity”
-- is considered a given by most of contemporary economics. It makes the
mathematics easier in the financial portfolio theory that influences countless
investors and in frameworks for designing regulations to keep financial risks
at acceptable levels. Unfortunately, this error systematically underestimates
prevailing risks.
Confidence Brake
It also may encourage overly optimistic ideas about
the ability of an economy to recover from a crisis. For example, those who
support policies of fiscal austerity believe that companies, in seeking to
maximize their profits, will naturally drive an economy back to steady growth.
The economy will spring back if companies and individuals have confidence that
their investments will pay off. If that’s the case, why aren’t businesses
investing globally when interest rates are at historic lows. What’s holding
them back?
The fairly obvious answer is serious downside risk,
which makes the reticence entirely sensible -- if you live in the real world
where time matters. Such behavior is in fact sensible in this
“balance-sheet recession” -- the term coined by Nomura Research Institute Chief
Economist Richard Koo to describe what happens after big asset bubbles burst,
leaving companies mired in debt, their assets worth less than their
liabilities. Low interest rates won’t encourage borrowing -- even to finance
positive-return investments -- because companies need to pay down their debts,
and fear going bust altogether.
Unfortunately, errors of analysis embedded within
core theories can ultimately become errors of intuition for the millions of
people educated in those theories. It’s ironic -- and a little alarming -- that
so much of our thinking remains founded on aspects of Pascal’s ideas that are
still largely unexplored.