1.
Behavioral Economics, Day 1
1. Section added a couple of years ago at behest of economics majors, who encountered some behavioral economics
and were frustrated that their department did not offer them the chance to study it.
a. It’s tempting to suppose that disciplines have always been as they are now. But every discipline goes through
changes of approach, sometimes revolutionary ones. Mathematical economics, as you study it now, is of
relatively recent provenance. It emerged after World War II and is largely due to Paul Samuelson.
b. Behavioral economics does not reject the mathematicization of economics, not really an alternative to neoclassical economics – or so its practitioners insist. Rather it attempts to base economics on more realistic
psychological assumptions than had been used in classical or neo-classical economics
c. emerged in the 1980’s as a reaction to two features of neo-classical economics:
(1) its methodology, which was resolutely non-experimental
(2) its assumptions about human decision-making
d. my impression is that it is maturing, with:
(1) an experimental agenda
(2) implications for policy-making, as we’ll see on Thursday and as you can read about in this NYT piece.
(3) Impact on disciplines related to economics. Mendoza now offers a course in behavioral finance.
2. Rabin – Today, focus on challenges to traditional assumptions of economics and why they matter
a. Rabin lists at p. 660:
(1) Bayesian information processors
(2) Well-defined and stable preferences
(3) Maximize expected utility
(4) Exponentially discount future well-being
(5) Are self-interested, narrowly defined
(6) Have preferences over final outcomes, not changes
(7) Have only instrumental/functional tastes for beliefs and information
b. to see the challenges to (1)-(7), consider that people are said to seek Max x € X ∑ s€S π(s) U(x/s)
(1) X is person A’s choice set, S is state-of-the-world space, U is A’s stable, well-defined preferences
(2) π(s) – A’s subjective beliefs about s, the state of the world, updated according to Bayes’ Rule
The probability of H conditional on E is defined as PE(H) = P(H & E)/PI, provided that both terms of this
ratio exist and PI > 0
To illustrate, suppose J. Doe is a randomly chosen American who was alive on January 1, 2000. According
to the United States Center for Disease Control, roughly 2.4 million of the 275 million Americans alive on
that date died during the 2000 calendar year. Among the approximately 16.6 million senior citizens (age 75
or greater) about 1.36 million died. The unconditional probability of the hypothesis that our J. Doe died
during 2000, H, is just the population-wide mortality rate P(H) = 2.4M/275M = 0.00873. To find the
probability of J. Doe’s death conditional on the information, E, that he or she was a senior citizen, we
divide the probability that he or she was a senior who died, P(H & E) = 1.36M/275M = 0.00495, by the
probability that he or she was a senior citizen, PI = 16.6M/275M = 0.06036. Thus, the probability of J.
Doe’s death given that he or she was a senior is PE(H) = P(H & E)/PI = 0.00495/0.06036 = 0.082.
-- from The Stanford Encyclopedia of Philosophy
2.
c. Three challenges treated briefly (pp. 661-62):
i. What do utility functions really look like? – Reference-based utility, non-expected utility = utility which is
not a linear function of what A thinks will happen, Social preferences
ii. How do people really form p(s) ≠ π(s)? – they use heuristics to arrive at perceived state-of-the-world
iii. Do people really maximize utility – i.e. do they really maximize the satisfaction of stable preferences? –
mis-remembering, framing and context
d. Three challenges treated at greater length (not all different from those enumerated above, as the phrase “more
types of departures” on p. 662 misleadingly suggests):
i. Reference-based utility – sense of well-being, utility depends not just on consumption but upon what we
are used to: “endowment effect”  loss aversion  risk aversion – pp. 662-63 (also Kahneman, p. 164)
Explain the “endowment effect”
(1) Will increases in consumption bring increase in sense of well-being?
(2) Attitudes toward changes not interpretable “fully in utility maximization terms” –by which I take it he
means or implies that people avoid risks that are expected to increase utility because
(a) People exaggerate how long the sensation of loss will last
(b) People fail to contextualize losses in the course of a life which includes long-term gains
Someone walk through argument on p. 664, implications for predictions of insurance purchase.
Remember we always want to know what difference the new assumptions make!
ii. Caring about others and what they do – pp. 665-68
(1) Altruism – care about how others are faring, and incorporate that into one’s own utility function
(2) Experimental evidence shows we care about the fairness of outcomes
(3) Experimental evidence also shows that we care about motivations
Someone walk us through the movie argument on pp. 667-68.
iii. “Caring about now” = present-bias – pp. 668ff.
(1) Exponential discounting  time-consistent preferences
It is common in economic models that involve decision-making over time to assume that decisionmakers are exponential discounters; this is generally what students are taught. Exponential
discounting yields time-consistent preferences. Exponential discounting and, more generally,
time-consistent preferences are often assumed in rational choice theory, since they imply that all
of a decision-maker’s selves will agree with the choices made by each self.1
(2) Hyperbolic discounting – helps us understand a wide range of phenomena
Someone walk us through
3. Themes and Perspectives
1
http://en.wikipedia.org/wiki/Dynamically_inconsistent
3.
Appendix: Exponential vs. Hyperbolic Discounting
1. Exponential discounting
a. Start with problem of computing compound interest = problem of how a given amount of money A increases
in value to value V over time t when interest rate r is compounded.
i. Interest can be compounded discretely but, in theory, also continuously. When compounded continuously,
the formula for computing the value of A at time t is:
V = Aert
Where e = 2.71828 = base of a number’s natural logarithm = lim m  ∞ (1 + 1/m)m
(1) Won’t go through where this comes from
(2) Gives exponential growth of money
b. A natural way of thinking about discounting, about something’s decline or decay in value over time, is as
reverse-interest. If we think of it that way, we get the formula:
A = Ve-rt
Where e is as before, r = discount rate, V is the nominal value of the asset
i. This is just instantaneous case of the equation Rabin gave us for exponential discounting:
Uτ = ute-r(t-τ)
(1) Note that this formula gives exponential decay of money
(2) The decay-rate is constant/ utility function has a constant slope 
(a) the amount people discount a future reward depends only on the length of the wait = (t-τ) and
your utility at t
(b) not on its proximity to some arbitrarily point – the present
ii. motivations:
(1) seems natural to treat decay, discount – as the opposite of interest
(2) seems irrational to pick out one arbitrary point in time as special reference point – present
(3) seems irrational to pick out one arbitrary point in your life as special – present
2. BUT this is not what people do – they do pick out the present as special, and discount less sharply or severely
with respect to it –
a. losses that are more distant matter less to people
b. one day’s decay or decline in utility means less to people if the day is a year from now than if it is tomorrow
c. This is reflected in the equation of people’s utility function, which is hyperbolic and does not have constant
slope