Behavioral Economics and Environmental Policy

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Behavioral Economics and Environmental Policy

• William Schulze
• Cornell University

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BEHAVIORAL ECONOMICS AND ENVIRONMENTAL POLICY
This talk will first review some early history
and summarize some of the most important
discoveries in behavioral economics. The Nobel
Prize in economics was awarded to Daniel Kahneman
of Princeton and Vernon Smith of George Mason in
2002 for introducing a behavioral approach to
economics. Kahneman, along with Amos Tversky
(Stanford, deceased) published their tests of
expected utility in a now famous paper in 1979 in
the journal Econometrica, and called their
alternative theory Prospect Theory (Daniel
Kahnemanand Amos Tversky, Prospect Theory An
Analysis of Decision under Risk, Econometrica,
1979, vol. 47, issue 2, pages 263-91). Richard
Thaler, formerly of Cornell, popularized and
applied behavioral economics to business
decisions.
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Environmental Economists

• What do we believe?
• Policy should be efficient
• Policies should be subjected to benefit-cost
  analysis
• Benefits are best measured by revealed
  preferences
• We should get our hands dirty

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But, when digging in the dirt, environmental
economists found anomalies!

• Gardner Brown did an early CV study of salmon
  fisheries and found WTAgtgtWTP. Other CV studies
  showed WTA infinity! Early evidence of the
  value function.
• Property value studies near hazardous waste sites
  found enormous losses and perceived risks. Early
  evidence of the overweighting of low
  probabilities.
• Future risks appear to be discounted in peculiar
  ways. Early evidence of hyperbolic discounting.

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Why? An answer from evolutionary psychology.

• The social sciences (business, economics,
  sociology, and psychology) traditionally have
  viewed the mind as a blank slate.
• This empty hard drive was filled with an
  operating system, software, and memories by
  parents, schools, and culture.
• Human behavior was the product of this
  programming and data entry.
• Homo economicus
• In contrast, biologists and evolutionary
  psychologists believe that the mind was evolved
  to solve very specific problems encountered by
  our ancestors.
• The mind consists of a number of evolved problem
  solving modules.
• These modules may or may not be adequate to solve
  the problems that culture, technology, economy
  and business world now present. Intuition often
  fails.
• Behavioral Economics focuses on systematic errors
  that occur when intuition fails. An analytical
  approach is then required.

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Two Thought Experiments
EXPERIMENT 1 Imagine that your are faced with
the following decision A) You can have 100
or B) You can have a coin toss for 200 or
0. How many of you would choose A? ________ How
many of you would choose B? ________
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Two Thought Experiments
EXPERIMENT 2 Imagine that you are faced with the
following decision A) You must pay 100 or B)
You can have a coin toss for paying 200 or
0. How many of you would choose A? ________ How
many of you would choose B? ________
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Prospect Theory allows you to be risk averse in
gains and risk seeking in losses

• WE HAVE AN ANOMALY!
• PROSPECT THEORY ATTEMPTS TO EXPLAIN THIS ANOMALY
  BY POSITING
• THAT THE UTILITY FUNCTION IS FUNDAMENTALLY WRONG
  FROM
• BIOLOGICAL PRINCIPLES AS FOLLOWS
• The nervous system is set up to primarily to
  detect differences,
• not absolute levels.
• A gain is perceived as a pleasurable change from
  the status quo
• (reference point) and the nervous system shows a
  decreasing response both
• to the intensity and duration of pleasurable
  stimuli.
• A loss is perceived as a painful change from the
  status quo (reference point)
• and the nervous system shows a decreasing
  response both to the intensity and
• duration of painful stimuli.

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Prospect Theory (Cont.)

• 4) The reference point is usually where you are
  (the status quo), but can be
• where you would like to be, or think you should
  be.
• 5) We do not yet fully understand how reference
  points are determined, but
• they are subject to phenomena such as adaptation
  and social pressure
• (social norms), etc.

These observations add up to the VALUE FUNCTION
as a replacement for the utility function.
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The value function may provide survival value by
making humans risk seeking and loss averse when
they fall below a reference point of subsistence!

• DOMAINS
• Pleasure
• Neutral Reference Point (Slope above to the right
  is half the slope below to the left)
• Pain

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There are many examples of phenomena that can be
explained by the Value Function of Prospect Theory
These include RISK SEEKING. Behavior motivated
by an attempt to make up for perceived losses.
Examples The Watts Riots of 1965,
Employees who become belligerent because they
feel they have been wronged in salary
adjustments (especially if a colleague got
more!), Customers who argue and ask for
unreasonable compensation because their
expectations were not fulfilled.
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There are many examples of phenomena that can be
explained by the Value Function of Prospect
Theory (Cont.)
STATUS QUO BIAS. The tendency of people to remain
at the status quo even when it is in their
interest to change what they are doing.
Examples Failure to sell stocks when the market
tanks because people do not want to admit to
losses. Failure to adopt new technology and
accept changes in production methods because the
existing skills and knowledge become
worthless. Staying in a bad relationship too
long (see below). The failure to react to price
changes.
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There are many examples of phenomena that can be
explained by the Value Function of Prospect
Theory (Cont.)
THE SUNK COST FALLACY. Most people, if they have
put a lot of effort or money into something, are
unwilling to give up. Students stay with a bad
research topic way to long before switching to
another one. Continued investment into
engineering a new product that has become a
black hole for money with no production in
sight. Continued marketing expenditures on a
product that consumers hate.
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There are many examples of phenomena that can be
explained by the Value Function of Prospect
Theory (Cont.)

• Finally, losses are often valued about twice as
  much as gains, a
• phenomenon known as LOSS AVERSION.
• TWO EXAMPLES APPLYING THE
• VALUE FUNCTION
• WTA/WTP DISPARITY
• EXISTENCE VALUES

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WTA/WTP DISPARITYCoursey, Hovis, Schulze (1987)

• Study motivated by early difficulties with
  valuation including
• Reluctance to give up environmental amenities
• Peculiar survey values for WTA
• Subjects either were paid to avoid or were
  compensated to taste sucrose octa acetate, a
  bitter tasting liquid in a competitive auction.

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WTA/WTP for EXISTENCE VALUES
Boyce, Brown, McClelland, Peterson, Schulze (1992)

• The forest service was interested in the question
  do existence values exist?
• Staff employees at the university of Colorado
  were given the opportunity in different
  treatments to buy (WTP) or sell (WTA) a Norfolk
  island pine tree which would either be killed or
  not killed if they ended up in the hands of the
  experimenters rather than the subjects.
• Existence values were present but in an amplified
  form in WTA.
• Apparently moral responsibility is associated
  with initial ownership. If the subjects owned the
  tree, they felt responsible to protect it (WTA).
  If the experimenters owned the tree (WTP), the
  subjects felt less responsible.

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Weighting Function

• Edwards, a psychologist at USC in the 1960s,
  showed overweighting of low probabilities. His
  weighting function is incorporated in Prospect
  Theory.
• The distortion is exaggerated in the figure to
  the left.
• In terms of WTP little distortion at high
  probabilities but large over-bidding can be shown
  at low probabilities.
• However, this low probability response is made up
  of zero bids (risk dismissal) and very high bids
  which cannot be explained by risk aversion.
• Superfund sites show a bimodal perceived risk
  among nearby residents.

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Bids for insurance in the lab are bimodal for low
probabilities.

• Pooled frequency distribution of bids over 50
  rounds.
• Subjects received 1 cash on each round and 8
  subjects bid for 4 insurance policies in a
  competitive auction.
• Subjects had an initial balance of 100 and faced
  1 odds of a 40 loss.
• Subjects switched from overbidding to
  underbidding as experiment proceeded.

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Representative Agents in Lottery Choice
Experiments One Wedding and A Decent Funeral by
Glenn W. Harrison and E. Elisabet Rutström July
2005

• Bimodality often observed in economics
  experiments testing EUT or PT. Usually one mode
  looks like PT and the other mode is consistent
  with EUT. For example in the previous slide,
  individuals bidding 0 could be risk neutral for
  the 40 loss (consistent with estimates of the
  coefficient of relative risk aversion that
  suggest risk aversion should not be observable in
  the lab) and indifferent between having insurance
  for EV.40 and just taking the risk (bid 0).
  Insurance prices are about 1 in repeated rounds
  so a zero bid is consistent with EUT.
• Harrison and Rutstrom use lottery choices to
  estimate the frequency of these behaviors and fit
  a mixture model predicting the probability of
  each theory predicting participant behavior.

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Screen Display in Gain Frame
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Classifying Subjects

• Subjects are either clearly EUT or probably
  PT, not two distinct modes

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Classifying Subjects

• Males, and non-minorities favor EUT.

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Classifying Subjects

• Business majors and young people favor EUT!

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Tests of Time Preference
One of the first challenges to discounted utility
theory was Jerry A. Hausman, 1979. "Individual
Discount Rates and the Purchase and Utilization
of Energy-Using Durables," Bell Journal of
Economics, RAND, vol. 10(1), pages 33-54. The
voluminous literature on anomalies in time
preferences is surveyed in Shane
Frederick,George Loewenstein, and Ted
O'Donoghue, 2002. Time Discounting and Time
Preference A Critical Review, Journal of
Economic Literature, vol. 40, issue 2, pages
351-401(FLO)
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Many CV studies of the value of statistical life
for future risks have shown peculiar results

• Maureen L. Cropper, Sema K. Aydede, and Paul R.
  Portney, Discounting Human Lives, 1991 Am. J.
  Agric. Econ. 1410, 1412. This study shows both
  infinite and negative discount rates.
• John K. Horowitz and Richard T. Carson,
  Discounting Statistical Lives, 3 J. Risk
  Uncertainty 403, 410 (1990). One-third of the
  respondents used zero or negative discount rates.
  This implies that the weight those respondents
  assign to future lives equals or exceeds the
  weight they accord present lives.
• These studies also show that the opportunity cost
  of money over time seems to be ignored by
  consumers.

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Just how bad is it? Cornell undergrad experiment
over 2 months (Oct 10-Dec10), randomly pick one
decision to implement.

• Decision 1. Offer to sell 10 asset, payable to
  you on Dec. 10th for cash paid to you
  today________.
• Decision 2. Offer to accept 10 liability due on
  Dec 10th for cash paid to you today____________.
• Decision 3. Bid to buy 10 asset payable to you
  on Dec 10th for cash paid by you today________.
• Decision 4. Bid to pay off 10 liability due on
  Dec 10th for cash paid by you today____________.

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Analysis

• Decision 1. Offer to sell 10 asset, payable to
  you on Dec. 10th for cash today (6). Status quo
  bias helps here to insure rationality. People are
  reluctant to to take cash out of mandatory
  retirement programs lime TIAA CREF (Madrian, B.
  C., and Shea, D. The Power of Suggestion
  Inertia in 401(k) Participation and Saving
  Behavior. Quarterly Journal of Economics,
  November 2001, 116(4), pp. 11491187).
• Decision 2. Offer to accept 10 liability due on
  Dec 10th for cash paid to you today
• (-99). Subjects require 11.80 today to avoid a
  10 debt later! Theories abound but focus on the
  preference for improving sequences and wanting to
  get pain over with rather suffering anxiety.
• Decision 3. Bid to buy 10 asset payable to you
  on Dec 10th for cash paid to buyer today (173).
  Hyperbolic discounting implies a high discount
  rate over the near term followed by lower
  discount rates over the long term. Thus, the
  longer the period, the lower the discount rate
  observed.
• Decision 4. Bid to pay off 10 liability due on
  Dec 10th for cash paid by you today (59). The
  sign effect implies that gains are discounted
  more than losses (compare Decisions 3 and 4). So
  the asset is discounted more than the liability.

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More temporal choice anomalies

• When the size of the money outcome is varied,
  larger outcomes are discounted less than smaller
  outcomes, the magnitude effect.
• The delay/speedup asymmetry is illustrated by the
  following example On average, subjects who
  expected a VCR in a year would pay 54 to get it
  today but subjects who expected it today demanded
  126 to delay it a year.
• The preference for spread occurs when the best
  meal out is placed in the middle of the week if
  it is the only fancy meal in a week but placed
  first if there are two fancy meals in a week. Not
  irrational but a violation of the assumption
  utility independence over time.

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The psychology of choice is described in

• Bettman, James R, Mary Frances Luce and John W.
  Payne, 1998. Constructive Consumer Choice
  Processes, Journal of Consumer Research An
  Interdisciplinary Quarterly, University of
  Chicago Press, 25(3), 187-217

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Studies ask subjects which car would you
choose? They then study the process used.
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Psychologists, by examining the consumer decision
task, have found several processes

• The weighted adding strategy (linear utility)
  examines alternatives and is compensatory.
  Consumers pick the alternative which has the
  greatest sum of attributes times weights
  (values). It is accurate but high in cognitive
  effort--the standard. Less accurate and less
  effort strategies include
• The lexicographic strategy implies the consumer
  uses the most important single attribute and
  chooses based on that alone.
• Satisficing implies the consumer evaluates
  alternatives sequentially in order and rejects
  any that fail to meet minimum thresholds for any
  attribute and then go on to the next alternative,
  choosing the first that meets the minimum
  threshold for all attributes.
• Elimination-by-aspects combines the lexicographic
  and satisficing strategies by eliminating any
  alternatives that fail to make a cutoff for the
  most important attribute, repeated for second
  most important, etc., until only one alternative
  is left.

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Psychologists, by examining the consumer decision
task, have found that people employ several
processes under different circumstances

• Equal weighting is the same as the weighted
  adding strategy but with equal weights.
• Majority of confirming dimensions compares two
  alternatives at a time on each attribute and the
  one with the most wins survives for further
  comparison until only one is left.
• Frequency of good/bad features counts good votes
  (based on a cutoff) for each attribute for each
  alternative. Alternative with the most good votes
  is chosen.
• Componential context model is the weighted adding
  criterion plus a weight on relative advantage
  between alternatives based on their attributes.
  It thus combines approaches.

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How do consumers pick their strategy? If there is
little emotion, they trade off accuracy versus
cognitive effort

• Accuracy is measured by the weighted adding
  criterion (utility).
• Cognitive effort is measured by elementary
  information processes (EIPs).
• EIPs are reading an item of information,
  comparing items of information, multiplying or
  adding information, eliminating information, etc.
• These steps can be counted and added up for any
  choice task and give a measure of EIPs for each
  strategy.

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Example

• What strategy would you use to pick a husband
  (wife) if
• You had as long as you liked to search?
• You are on TV and have just met three candidates,
  and have one minute to choose a husband (wife) or
  you lose 10 million dollars (you can only ask one
  question in the remaining time)?
• Obviously you would use different strategies.
• Factors that effect choice strategy include
  problem size, time pressure, attribute
  correlation, information completeness and format,
  and comparable versus non-comparable choice.

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What have we learned?

• People have difficulty making tradeoffs.
• People have difficulty with probability.
• People have difficulty with time.
• People have difficulty if they dont have
  sufficient cognitive resources.
• All people are irrational some of the time, some
  people are irrational all of the time, but not
  all of the people are irrational all of the time.