Behavioural Welfare Economics
Johannes Abeler
[email protected]
CES 2016
Outline
How should we do welfare economics when agents aren’t rational and
selfish?
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Positive models of behaviour
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Bernheim/Rangel (2009) and Chetty/Looney/Kroft 2009: bounds
on welfare
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Libertarian paternalism
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Happiness
Thanks to Clare Leaver, Guy Mayraz, Raj Chetty, and Jim Andreoni on whose slides
parts of the lectures are based.
How do we do welfare economics in the standard model?
The main two welfare criteria are
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Pareto efficiency
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Social welfare functions
Underlying both of these are revealed preferences: we can infer
preferences from choices. If option a is chosen over option b, then
a % b or U (a ) ≥ U (b )
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How do we do welfare economics in the standard model?
Focusing on Pareto efficiency...
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First Welfare Theorem: Any Walrasian equilibrium is
Pareto-efficient.
If there is a complete set of perfectly competitive markets (and
local non-satiation), the resulting allocation will be Pareto
efficient.
Assumptions that behavioural economics focuses on (and casts
doubts on): rationality, no social preferences
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Bounded rationality, inconsistency, inability to predict experienced
utility: agents will not choose the individually optimal option
Social preferences: individually optimal option could have
externalities
Inconsistency: optimal option for current self might not be optimal
for future selves, i.e., could have “internalities”
Second Welfare Theorem: If all agents have convex preferences,
each Pareto efficient allocation is a Walrasian equilibrium for an
appropriate assignment of endowments.
Many people are not rational or not selfish or neither.
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106 documented distinct departures from standard economic
model
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What are the empirically most important deviations?
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Social preferences
Bounded willpower, impatience
Reference-dependent preferences
Bounded rationality
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What should the government do if people are boundedly
rational or present-biased?
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Potential chance for paternalism
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E.g., regulate behaviour, encourage healthy life-style, make saving
for retirement compulsory
Potential danger of paternalism
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Are politicians rational and not present-biased?
Even boundedly rational people might know more about their own
preferences than rational politicians
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Positive models for bounded willpower, impatience or
procrastination
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Many people are impatient, valuing the now much more than the
future
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That is no problem for standard exponential discounting: just
decrease δ
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But many people are also inconsistent: they plan to read all papers
on the reading list next week but once next week has arrived, they
change their mind and decide to go to the Englische Garten
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Important for: investment in human capital, saving for retirement,
investment in health capital (dieting), ...
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Several ways to model this intuition
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Hyperbolic discounting (“β − δ model”)
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Usually linked to Laibson (1997) who builds on older papers, e.g.,
Phelps/Pollak (1968)
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People always overweight the present period.
∞
Ut = u (xt ) + β
∑ δτ u (xt +τ )
τ =1
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Discount factor between two future periods: δ
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Discount factor between now and the future: βδ
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Naive individuals think their future selves will discount
exponentially; sophisticated individuals know the true utility
function of future selves (cf. birds and worms)
Which discount factor should we use for welfare
calculation?
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O’Donoghue and Rabin (1999), Bernheim (2009), etc. argue that
long-run preferences should be used for welfare evaluation: β = 1
(δ < 1 is ok)
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Imagine each period-τ self as a different person and all selves vote
on the discount rate from t to t + 1. Period-t self votes for βδ; all
other selves vote for δ
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Similarly, for any t at almost all periods the discounting from t to
t + 1 is δ, so unless we put special weight on the t period we
should use the value of β = 1 .
Which discount factor should we use for welfare
calculation?
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Sugden (AER 2004) argues that the short-run preferences βδ
should be used for welfare evaluation
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He suggests to identify a person with responsibility, rather than
preferences (as usual)
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“To treat a future action as one’s own is to take ex ante
responsibility for it, rather than conceiving of oneself as the
principal in a principal-agent interaction with an alien future self.”
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Libertarian argument: free choice is valuable per se
Bernheim also makes a (perhaps hypothetical) case for this because of
“intellectualization bias”: only the choice between now and later
reflects true preferences
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Experienced vs. decision utility
Another way to think about the correct discount factor is to compare
experienced vs. decision utility (Kahneman et al. 1997)
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Experienced utility, often linked to Bentham, is a measure of
pleasure and pain
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Decision utility is the weight of an outcome in a decision (cf.
revealed preferences)
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Rational agents will maximize their experienced utility, so the two
concepts are identical for these agents
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In hyperbolic discounting models the current self maximizes
according to a discount factor of βδ while the experienced utility
of the future selves is better described by δ
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Experienced vs. decision utility
Looking at other models, which type of utility seems more relevant for
welfare calculations?
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Agents overweight small probabilities: agents still care only about
the final outcomes, so their decisions will be ex-post judged (by
them) to be mistaken; experienced utility seems more relevant
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Agents dislike losses: agents care about the final outcome but still
suffer from loss aversion in that final outcome; they don’t regret
their decisions, decision and experienced utility coincide
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What does that mean for hyperbolic discounting?
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An application (Pollak AER 1998): Inhabitants of a village think
their water supply is contaminated which increases the risk of
cancer and ask the mayor to buy an expensive filter system. A
water expert from the University of Oxford investigates the water
supply and finds that it is not contaminated. Should the mayor
buy the filter system?
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Welfare for inconsistent decision makers
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Most economists would argue that the preferences of the long-run
self (β = 1) should be important for welfare concerns, putting no
(or very little weight) on the short-run self
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But consider this story (Schelling 1984):
Some anesthetics block transmission of the nervous impulses that constitute pain; others have the characteristic
that the patient responds to the pain as if feeling it fully but has utterly no recollection afterwards. Imagine you
volunteer as a subject for a medical experiment. For a handsome fee you will be knocked out for an hour or two,
allowed to sleep it off. You do this regularly, and one afternoon you walk into the lab a little early and find the
experimenters viewing some videotape. On the screen is an experimental subject writhing, and though the audio is
turned down the shrieks are unmistakably those of a person in pain. When the pain stops the victim pleads,
“Don’t ever do that again. Please.” The person is you. Do you care? Do you walk into your booth, lie on the
couch, and hold out your arm for today’s injection? Should I let you?
Multiple selves
There are several other ways to model bounded
will-power/present-biasedness.
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E.g., Fudenberg/Levine 2006
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Long-run self with discount factor δ: the “planner”
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Sequence of short-run selves that only live for one period each
with discount factor γ = 0: the “doers”
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Long-run self can only set incentives for short-run selves;
deviations from exogenously faced incentives come at a cost
(self-control actions reduce budget set)
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Short-run selves choose the action given the incentives set by the
long-run self
Multiple selves
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Short-run selves get utility from action
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Utility of long-run self is the discounted sum of utilities of all
short-run selves
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Surprisingly tractable model as short-run self is mechanically
reacting to self-control actions; hyperbolic discounting probably
still more tractable
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Predictions often similar to hyperbolic discounting models: value
illiquid assets, etc.
What is the welfare implication?
Temptation and Self-Control
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Temptation à la Gul and Pesendorfer (2001)
When one chooses x ∈ X one may suffer utility loss because of
the presence of a tempting alternative y ∈ X
Modelled as a preference over choice sets:
{salad } {salad, steak } % {steak }
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Can continue to use revealed preferences
Often qualitatively similar predictions to hyperbolic discounting:
there is value in restricting choices, but no inconsistent choices or
preference changes
Welfare implication of choice restriction can be derived without
choosing between selves
(Paper can be a daunting read; but “only” an application of
Dekel/Lipman/Rusticchini 2001)
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How to choose between different positive models?
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Test models against each other with data: take the one that fits
data best
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If similar predictions: take the one which is easier to handle
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Example from social preferences: Bolton/Ockenfels (2000) vs.
Fehr/Schmidt (1999)
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Not that simple: they might differ in their welfare implications
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Masatioglu/Raymond (2015)
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Study the choice-acclimating personal equilibrium (CPE) of
Koszegi-Rabin. CPE is their most-widely used equilibrium concept
(e.g., Abeler et al. 2011) and is becoming the most-widely used
loss aversion model in general
Can thus compare CPE to other non-expected utility models
Outcome lottery F and reference lottery F 0 ; CPE posits that
expectations are consistent with choice: F = F 0
U (F |F ) =
∑ u (x )F (x ) + ∑ ∑ g (u (x ) − u (y ))F (x )F (y )
x
x
y
What does that mean?
I The reference point is recent expectations, people dislike having
outcomes fall short of their expectations, i.e., they dislike
disappointment
I g () is assumed to be piece-wise linear (linear gain-loss utility),
with λ ≤ 2 to rule out stochastically-dominated choices
Masatioglu/Raymond (2015)
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Very similar idea modeled by Bell (1985), Loomes/Sugden (1986),
and Gul (1991) in slightly different ways
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All of these models assume that agents are otherwise rational and,
in particular, use probabilities correctly
Should we take gain-loss utility into account when calculating welfare?
Probably yes. This is not a mistake, people do suffer from the loss;
taking away the loss sensation would make them better off.
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Masatioglu/Raymond (2015)
Let’s study a totally different model for a moment: rank-dependent
utility (Quiggin 1982)
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Agents rank outcomes x from worse to best
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They then distort objective probabilities p (x ) to weights π (x ),
depending on rank
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Value of lottery: ∑x u (x )π (x )
Pessimism: overweight bad outcomes
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Should we take pessimism into account when calculating welfare?
Probably not. This is a mistake and moreover agents ex-post only care
about final outcome and not the probabilities
Masatioglu/Raymond (2015)
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Masatioglu/Raymond (2015)
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Show that choice data cannot distinguish between CPE (with
λ ≤ 2) and rank-dependent utility (pessimism)
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Any given choice data that is in line with Koszegi-Rabin could
thus also be explained by pessimism with very different welfare
implications
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Additional results: Bell and Loomes-Sugden and Gul predict
differently even though the intuition of the models is very similar
Does this mean that behavioural welfare economics using
positive models is doomed?
No.
But this shows that standard welfare economics can deliver such sharp
results (First Welfare Theorem, etc.) only because of its strong
assumptions.
Looking at the data, the assumptions are wrong, so this is an example
of “searching the key under the street light”.
Behavioural welfare economics won’t deliver such sharp predictions
(yet) but at least it is looking in the right place. So we shouldn’t
expect behavioural (welfare) economics to replace standard economics
soon. There is a place for both.
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There might be too many positive behavioural models.
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Difficult to account for all 106+ deviations, in particular if
normative implications are unclear
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We could rather not specify a positive model at all
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Instead, map observed choices to statements about welfare directly
and derive bounds on welfare (Bernheim/Rangel, QJE 2009)
Deriving bounds
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Take three different car insurance plans with different excesses:
L, M, H
We have data from two environments:
1. On red paper, H > M > L
2. On blue paper, M > H > L
Difficult to build a model of paper colour; but we can bound the
effect
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L is never optimal given available data regardless of positive theory;
optimum is bounded between M and H
Don’t need to understand why/how colour affects choice to make
statements about welfare
Bernheim and Rangel 2009: Setup
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Theory that delivers bounds on welfare based purely on choice data
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In standard model, agents choose from a choice set x ∈ X
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Goal of policy is to identify optimal x
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In behavioural models, agents choose from “generalized choice
sets” G = (X , d )
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d is an “ancillary condition”: something that affects choice
behaviour but (by assumption) does not affect experienced utility
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Example: colour of paper, salience, framing, default option
Bernheim and Rangel 2009: Choice Sets
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Let C (X , d ) denote choice made in a given GCS
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Choice inconsistency if C (X , d ) 6= C (X , d 0 )
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Define revealed preference relation P as xPy if x always chosen
over y for any d
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Using P, can identify choice set that maximizes welfare instead of
single point
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With continuous choices, effectively obtain bounds on welfare
Bernheim and Rangel 2009: Compensating Variation
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Consider a change in choice set from X to X 0 ⊂ X
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Compute compensating variation (CV) as amount needed to make
agent indifferent to restriction of choice set for each d
Lower bound on CV is minimum over all d’s
Upper bound on CV is maximum over all d’s
Bernheim and Rangel 2009: Compensating Variation
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Example: suppose insurance plans are restricted to drop M option
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Under red paper condition, CV is 0 – no loss in welfare
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Under blue paper condition, calculate price cut $z on H needed to
make agent indifferent between M and H.
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Bounds on CV: (0, z )
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If L option is dropped, bounds collapse to a singleton: CV = 0.
Bernheim and Rangel 2009: Refinements
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Problem:looseness of bounds
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Bounds tight when ancillary conditions do not lead to vast
changes in choices
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That is, bounds tight when behavioural problems are small
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In cases where behavioural issues are important, this is not going
to be a very informative approach
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Bernheim and Rangel 2009: Refinements
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Solution: “refinements” – discard certain d’s as being
“contaminated” for welfare analysis
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E.g. a neuroscience experiment shows that decisions made under
red paper condition are more rational
Or compare across different people: Currie (2011) finds that only
white, educated women react to news about hazardous waste sites
nearby and move away
Or assume that choice rational when incentives are more salient
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With fewer d’s, get tighter bounds on welfare and policy
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Brings us partly back to square 1, as refinements require some
positive theory of behaviour
Tax Incidence with Salience Effects
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Central assumption of neoclassical model: taxes are equivalent to
dx
prices ( dx
dt = dp )
In practice, are people fully aware of marginal tax rates?
More generally, do people take “hidden” charges fully into
account? E.g., ebay shipping costs, cost of toner replacement,
Ryanair add-on charges, wifi in hotels, optional service charge in
restaurants, ...
Chetty, Looney, and Kroft (2009) test this assumption and
generalize theory to allow for salience effects
Part 1: Test whether “salience” (visibility of tax-inclusive price)
affects behavioural responses to commodity taxation
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Does effect of a tax on demand depend on whether it is included in
posted price?
Part 2: Develop formulas for incidence and efficiency costs of
taxation that permit salience effects and other optimization errors
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Chetty et al.: Empirical Framework
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Economy with two goods, x and y
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Prices: Normalize the price of y to 1 and let p denote the (fixed)
pretax price of x .
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Taxes: y untaxed, x subject to an ad valorem sales tax τ (not
included in posted price)
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Tax-inclusive price of x is q = p (1 + τ ).
Let demand for good x be denoted by x (p, τ )
Chetty et al.: Empirical Framework
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If agents optimize fully, demand should only depend on the total
tax-inclusive price: x (p, τ ) = x ((1 + τ )p, 0)
Full optimization implies price elasticity equals gross-of-tax
elasticity:
ε x ,p ≡ −
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∂ log x
∂ log x
= ε x ,1+τ ≡ −
∂ log p
∂ log(1 + τ )
To test this hypothesis, log-linearize demand function x (p, τ ) to
obtain estimating equation:
log x (p, τ ) = α + β log p + θβ log(1 + τ )
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θ measures degree to which agents under-react to the tax:
θ=
∂ log x
ε x ,1+τ
∂ log x
/
=
∂ log(1 + τ ) ∂ log p
ε x ,p
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Chetty et al.: Two Empirical Strategies
Two strategies to estimate θ:
1. Manipulate tax salience: make sales tax as visible as pre-tax
price
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Effect of intervention on demand:
v = log x ((1 + τ )p, 0) − log x (p, τ )
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Compare to effect of equivalent price increase to estimate θ:
(1 − θ ) = −
v
ε x ,p log(1 + τ )
2. Manipulate tax rate: compare ε x ,p and ε x ,1+τ
θ = ε x ,1+τ /ε x ,p
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Chetty et al.: Strategy 1
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Experiment manipulating salience of sales tax implemented at a
supermarket
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30% of products sold in store are subject to sales tax
Posted tax-inclusive prices on shelf for subset of products subject to
sales tax (7.375% in this city)
Data: Scanner data on price and weekly quantity sold by product
Chetty et al.: Strategy 1
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Chetty et al.: Research Design
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Quasi-experimental difference-in-differences
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Treatment group:
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Products: Cosmetics, Deodorants, and Hair Care Accessories
Store: One large store in Northern California
Time period: 3 weeks (February 22, 2006 – March 15, 2006)
Control groups:
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Products: Other prods. in same aisle (toothpaste, skin care, shave)
Stores: Two nearby stores similar in demographic characteristics
Time period: Calendar year 2005 and first 6 weeks of 2006
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Chetty et al.: Results
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Chetty et al.: Strategy 2
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Compare effects of price changes and tax changes
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Alcohol subject to two state-level taxes in the U.S.:
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Excise tax: included in price
Sales tax: added at register, not shown in posted price
Exploiting state-level changes in these two taxes, estimate θ
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Addresses concern that supermarket experiment may have induced
a “Hawthorne effect” or that prices ending on .99 are perceived
differently or that other things might have affected the experiment
Chetty et al.: Results
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Chetty et al.: Results
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Chetty et al.: Results
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Applied Welfare Analysis with Salience Effects
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Derive partial-equilibrium formulas for incidence and efficiency
costs
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Focus here on efficiency cost analysis
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Formulas do not rely on a specific positive theory, in the spirit of
Bernheim and Rangel (2009)
Welfare Analysis with Salience Effects: Setup
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Two goods, x and y ; price of y is 1, pretax price of x is p.
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Taxes: y untaxed. Unit sales tax on x at rate t S , which is not
included in the posted price
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Tax-inclusive price of x : q = p + t S
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Welfare Analysis with Salience Effects: Setup
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Representative consumer has wealth Z and utility u (x ) + v (y )
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Let{x ∗ (p, t S , Z ), y ∗ (p, t S , Z )} denote bundle chosen by a
fully-optimizing agent
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Let {x (p, t S , Z ), y (p, t S , Z )} denote empirically observed
demands
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Place no structure on these demand functions except for feasibility:
(p + t S )x (p, t S , Z ) + y (p, t S , Z ) = Z
Welfare Analysis with Salience Effects: Setup
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Price-taking firms use y to produce x with cost function c
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Firms optimize perfectly (why are they not behavioural?). Supply
function S (p ) defined by:
p = c 0 (S (p ))
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Let ε S =
∂S
∂p
×
p
S (p )
denote the price elasticity of supply
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Efficiency Cost with Salience Effects
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Excess burden (EB) of introducing a revenue-generating sales tax
t is (equivalent variation: same ex-post utility):
EB (t S ) = Z − e (p, 0, V (p, t S , Z )) − R (p, t S , Z )
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Can think of EB as the extra amount of money that could be
collected when replacing the distortionary tax by a lump-sum tax,
keeping consumers’ utility constant; it is basically a measure of
deadweight loss
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V : indirect utility function
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e (p, 0, V (p, t S , Z )): expenditure to get without tax to same level
of utility as with tax
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R: tax revenue
Preference Recovery Assumptions
A1 Taxes affect utility only through their effects on the chosen
consumption bundle. Agent’s indirect utility given taxes of (t E , t S ) is
V (p, t S , Z ) = u (x (p, t S , Z )) + v (y (p, t S , Z ))
A2 When tax inclusive prices are fully salient, the agent chooses the
same allocation as a fully-optimizing agent:
x (p, 0, Z ) = x ∗ (p, 0, Z ) = arg max u (x ) + v (Z − px )
x
How do these two assumptions relate to Bernheim/Rangel?
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A1 analogous to specification of ancillary condition: tax rate and
salience do not enter utility directly
A2 analogous to refinement: fully salient taxes reveal “true”
preferences
Efficiency Cost with Salience Effects
Two demand curves: price-demand curve x (p, 0, Z ) (i.e., p varies) and
tax-demand curve x (p, t S , Z ) (i.e., t S varies):
1. Use tax-demand x (p, t S , Z ) to calculate behaviour, V (p, t S , Z )
and EB
2. Use price-demand x (p, 0, Z ) to recover utility as in standard model
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Excess Burden with No Income Effect for Good
∂x
= 0)
x ( ∂Z
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Efficiency Cost: No Income Effects
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∂x
In the case without income effects ( ∂Z
= 0), which implies utility
is quasilinear, excess burden of introducing a small tax t S is
1
∂x /∂t S
EB (t S ) ' − (t S )2
∂x /∂t S
2
∂x /∂p
1 S 2 εD
(θt )
=
2
p + tS
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Is inattention a good or a bad thing for welfare when dx /dZ = 0?
Inattention reduces excess burden.
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Intuition: tax t S induces behavioural response equivalent to a fully
perceived tax of θt S .
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What is the optimal θ?
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If θ = 0, tax is equivalent to a lump sum tax and EB = 0 because
agent continues to choose first-best allocation.
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Efficiency Cost with Income Effects
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With income effects: same formula, but all elasticities are now
compensated:
∂x c /∂t S c
1
∂x /∂t S
EB (t S ) ' − (t S )2 c
2
∂x /∂p
1 c S 2 εcD
=
(θ t )
2
p + tS
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Compensated price demand: dx c /dp = dx /dp + xdx /dZ
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Compensated tax demand: dx c /dt S := dx /dt S + xdx /dZ
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Compensated tax demand does not necessarily satisfy Slutsky
condition dx c /dt S < 0 because it is not generated by utility
maximization
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Efficiency Cost with Income Effects
∂x c /∂t S c
1
∂x /∂t S
EB (t S ) ' − (t S )2 c
2
∂x /∂p
1 c S 2 εcD
(θ t )
=
2
p + tS
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With income effects (dx /dZ > 0), making a tax less salient can
raise deadweight loss.
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Tax can generate EB > 0 even if dx /dt S = 0
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Example: consumption of food and cars; agent who ignores
complex tax on cars underconsumes food and has lower welfare.
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Intuition: agent does not adjust consumption of x despite change
in net-of-tax income, leading to a positive compensated elasticity.
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Why did I choose this paper?
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Important question in its own right
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First application of Bernheim/Rangel
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Two empirical studies, with different sources of identification;
robust to either identification failing (though no experimental
variation)
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Nice link to Economics 101, showing the fundamental point of
salience very clearly
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Combination of theory and empirics
Libertarian Paternalism
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Mainly linked to Thaler/Sunstein (“Nudge”) but also
Camerer/Issacharoff/Loewenstein/O’Donoghue/Rabin
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Basic insight: Some people are rational, some are behavioural
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Main question: How can we help behavioural individuals without
restricting the choice of rational people?
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Rely on self selection and use tricks that only influence behavioural
people but are ignored by rational people: framing, defaults, loss
aversion, ...
Defaults: Organ donation
Johnson/Goldstein 2003
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Defaults: Asset allocation/saving
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Madrian/Shea (2001) first to study defaults in 401(k) plans: huge
effect on savings rate
Choi/Laibson/Madrian (2009) on 401(k) contributions: employer’s
amount first allocated only to employer’s stock (but could be
reallocated); from May 2003, active decision
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It is not clear why defaults work
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Procrastination?
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Endorsement effect?
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Transaction costs? (probably not)
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Anchor?
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Disutility of thinking about the topic?
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Still, very popular with politicians: cheap and effective
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Model-freeness is similar to Bernheim/Rangel
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Not that simple: are there nudges for everything?
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Perhaps more importantly, nudge reasoning relies on perfect
correlation between tendency to follow nudges and inability to
make good decisions, i.e., perfect self-selection
Happiness/Subjective well-being/Life satisfaction
All things considered, how satisfied are you with your life as a whole
nowadays? Please answer using this card, where 0 means extremely
dissatisfied and 10 means extremely satisfied.
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Happiness/Subjective well-being/Life satisfaction
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Happiness/Subjective well-being/Life satisfaction
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Here is a picture of a ladder. The top of the ladder “10” is the
best possible life for you and the bottom “0” is the worst possible
life for you. In general, where on the ladder do you feel you stand
at the moment? (Cantril 1965)
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Taking all things together, would you say you are: ‘very happy,’
‘quite happy,’ ‘not very happy,’ or ‘not at all happy’?
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Experience Sampling Method (Stone and Shiffman, 1994):
Beeper, “What do you do now? How do you feel now?”; overall
feeling is the sum of feeling for each individual activity weighted
by time spent on this activity
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Day Reconstruction Method (Kahneman et al., 2004): Questions
about each individual time period the day before; less intrusive
than ESM
Promises of happiness research
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Measure (cardinal!) utility directly
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Old idea: Edgeworth’s hedonimeter
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Interpersonal comparison of utility
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Objective welfare criterion
Answer big questions
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Does money make you happier?
What priority should we put on GDP growth?
What is the effect of inequality?
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Application of happiness research: Optimal contracts in
insurance markets
Rothschild & Stiglitz (1976): Two states: s = sick, h = healthy; π =
probability of state s. Y = gross income; L = cost of treatment; yj =
net income in state j. Expected utility is:
EU = πus (ys ) + (1 − π )uh (yh )
With premium P and benefits B in the event of illness:
yh = Y − P
and ys = Y − P − L + B
Assume competitive insurance market with full information
Optimal contracts in insurance markets
The optimal contract satisfies: us0 (ys ) = uh0 (yh )
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If only costs of illness are financial, us (y ) = uh (y ) = u (y )
⇒ ys = yh ⇒ B = L. Full insurance.
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If marginal utility of income is higher when healthy, uh0 (y ) > us0 (y )
⇒ yh > ys and less than full insurance
Is Marginal Utility Higher When Healthy?
Finkelstein, Luttmer, Notowidigdo (JEEA 2013) use happiness data to
proxy for utility:
Use non-parametric tests to ensure that wrong mapping from happiness
answer to utility cannot affect results. Calibration results suggest that
B should be 20–45 percentage points lower and retirement saving 3–5
percentage points lower.
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Doubts about happiness research
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Non-incentivized survey question, people might lie or not pay
attention
People don’t know how happy they are, haven’t thought about the
question, make up the answer on the spot
Scale is bounded: if you said 8 last time and you got richer, at
some point everyone has to be at 10 (think probit function); this
leads to thick indifference curves
Interperson comparison impossible, some people are just always
“very” everything
If you say 10 now, how sad is that: it won’t get better
Looking back to your life: when was your life satisfaction highest?
Would you have given 10 at that point in time?
Effect on life satisfaction of many policies may be too small to
measure
No need to measure happiness: if they’d maximize it, we could
just use revealed preferences
More doubts about happiness research
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Simple interventions, e.g., finding a dime at the photocopier
(Schwarz 1987), move answers strongly
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Strong seasonal and day-of-the week effects
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Focusing illusion: asking dating questions before life-satisfaction
question increases correlation of dating status and life satisfaction
(Strack et al. 1988);
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More fundamentally: asking about life satisfaction in general
focuses on the big things: money etc., might prompt normative
answer (“I am rich, I should be happy.”)
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This will lead to violations of transitivity
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Anyway, is this a causal relationship, e.g., if income were
correlated with happiness? Happier people get good jobs and
become richer; focusing illusion; omitted variables: democracy,
rule of law, favourable weather, etc.
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Does happiness equal utility?
How can we tell?
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Things that we know should increase utility should also make
people happier (cf. preference relation leading to utility function)
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Marriage increases happiness
Divorce decreases happiness
Disability decreases happiness
Unemployment decreases happiness
Income increases happiness
Not that simple
Unemployment-life satisfaction correlation
Should unemployed people be more or less happy than employed
people?
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With a complete labour market unemployment is voluntary:
should have no effect
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Involuntary unemployment should reduce happiness
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Clark/Oswald (1994): unemployment reduces happiness
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Must control for income (they didn’t) to disentangle
unemployment from income; later studies do and result is robust
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Income-life satisfaction correlation: across country
(absolute income)
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Income-life satisfaction correlation: over time within
country (Japan)
Dubbed the “Easterlin paradox” (Easterlin 1974)
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Easterlin paradox
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Developed countries seem to reach a satiation point; no
improvement over time
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Points to importance of relative income (with a national peer
group)
Policy implications
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Progressive taxation: income has a direct externality
Stop trying to increase GDP at all cost
Focus on things that make people really happy (Gross National
Happiness)
Not that simple
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Easterlin paradox seemingly not in line with migration
patterns.
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Migration patterns reveal a preference for relative rich people from
poor countries to become relatively poor people in rich countries
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Exactly contradicts Easterlin paradox
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But perhaps migration is just about remittances?
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Or the reference group stays the same and I am now even richer
compared to my old country?
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Or I plan to save and then go back even richer?
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Time dimension of happiness data is difficult to interpret.
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For the scale to work, people have to be able to imagine the
unimaginable (e.g., invention of new products; especially
important for GDP-happiness correlation over time)
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Maybe the judgement of my current situation changes as soon as
the new iPhone is out
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Better example: as soon as I meet my future wife: I didn’t know
what I was missing; I suddenly become much less happy until I
have married her, then I am as happy as before; in the time series,
this appears as if the marriage didn’t have an effect while in fact it
did
Income-life satisfaction correlation: across country (log
income)
Stevenson/Wolfers (2008) use log income as independent variable:
within-country evidence points very much towards log income instead
of absolute income
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Income-life satisfaction correlation: cross-section within
country (log income)
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Income-life satisfaction correlation: within and across
country
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Easterlin paradox revisited
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Adaptation of life satisfaction: Men (Clark et al. 2008)
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Adaptation of life satisfaction: Women
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Adaptation to disability
Oswald/Powdthavee 2008: “sufficiently disabled that they are unable
to work” (N=61)
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How is instantaneous utility/happiness translated into
overall utility of an episode?
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How is instantaneous utility/happiness translated into
overall utility of an episode?
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Normatively: integral of instantaneous utility over time (“total
utility”)
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In fact “peak-end rule”: U = (max inst. utility + last utility)/2
(“remembered utility”)
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Total utility 6= remembered utility ≈ decision utility
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What is a dominated choice?
What can we learn from this?
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Hard to judge what happiness really measures or means
Apparently, we don’t know what makes people happy or increases
utility; e.g., absolute income or log income? Thus difficult to test
or calibrate happiness question. Do economists need to know?
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Still, happiness question works surprisingly well given conceptual
problems
Peak-end rule opens new interesting questions
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Not really: whatever people choose makes them happy; take
individual preferences as given
“Just” need complete markets
How could/should utility maximization calculations be done over
time?
Effect of goal setting: feel bad while trying to reach it, then reap
reward
Is happiness an input into utility (like health)?
Is happiness the biological incentive to steer behaviour
(Becker/Rayo 2007)?
What can we learn from this?
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Perhaps happiness research’s ambition goes too far
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Underlying problem: revealed preferences are very uninformative
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Imagine someone prefers strawberry jam to peanut butter at
relative price p
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Would she still prefer jam at another price p 0 ?
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Perhaps we could ask her for her reasons: if she is allergic to
peanuts, she will prefer jam for any price p 0 ; if jam just happens to
be cheap, she will switch preferences depending on p 0
Broader theme: use non-choice data to complement, not
substitute, choice data
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Ask for reasons, ask for hypothetical choices
Neuro-economic evidence
Process data: decision time, search behaviour, ...
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