Experimental & Behavioral Economics
Defaults, paternalism, and nudges
Prof. Dr. Dorothea Kübler Taught by Dr. Hande Erkut Summer term 2019
Memos Nudging: Pros
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Nudging targets behavior rather than beliefs
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Nudging: Robustness?
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Nudging: Egalitarian?
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Nudging: Egalitarian?
• Economics deals with choices that people make, how the choices of decision makers interact etc.
• Revealed preference theory (Samuelson, 1948) shows how to construct utility functions (that are not observable) from (observable) choices.
• Experiments investigate real choices in contrast to surveys with attitudinal questions, measurement of physiological reactions etc.
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Revealed preferences (Positive):
– The choices that people make
Normative preferences: – The choices that they should make
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Positive (revealed) preferences
• Positive preferences are preferences that predict my choices
• Economists usually assume that revealed preferences are normative preferences (policy recommendation are often based upon revealed preferences, thus implicitly assuming revealed preferences = normative preferences)
• Example: choosing dark chocolate over milk chocolate reveals preference for one kind of chocolate over another…
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Normative preferences
• Normative preferences are preferences that society (or you) should optimize
• Normative preferences are philosophical constructs • Normative debates are settled with empirical evidence and
philosophical (ethical) arguments
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The limits to “revealed preferences”
Behavioral economists are particularly skeptical of the claim that positive and normative preferences are identical. Why? Cognitive mistakes
– Complexity of choice (e.g., financial products) -> delay or avoid decision
– Limited personal experience -> some decisions are made only once in a lifetime (…)
– Passive choice, i.e., people often accept default options (made by others) -> preferences may be unstable because variation in defaults can generate variation in outcomes
– Self control problems
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Choosing Today Eating Next Week Time
If you were deciding today, would you choose fruit or chocolate for next week? Read and van Leeuwen (1998)
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Self-control problem
Choosing Today Eating Next Week Time
Today subjects typically choose fruit for next week. -> 74 % choose fruit
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Time
If you were deciding today, would you choose fruit or chocolate for today?
Choosing and eating simultaneously
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Time Choosing and eating simultaneously
70% choose chocolate
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Desire for instant gratification (Read, Loewenstein & Kalyanaraman, 1999) Choose among 24 movie videos • Some are “low brow”: Four Weddings and a Funeral • Some are “high brow”: Schindler’s List
• Picking for tonight: 56% of subjects choose “low brow.” • Picking for night two weeks away: 29% choose “low brow.”
->Tonight I want to have fun…, next week I want things that are good
for me.
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Present-Bias and Consumption
Generally, intertemporal decisions can be classified according to when costs and benefits of a decision occur. Simple theoretical framework: • Consumption activity A with benefits u(x1) in t=1 and u(x2) in t=2 • Activity A can be
– An investment good: immediate costs, long-run benefits (e.g., exercising, doing homework, “high brow” movie): u(x1)0
– A leisure good: immediate benefit, long-run costs (e.g., spend on credit card, smoke cigarette): u(x1)>0 , u(x2)
How is consumption decision impacted by present-bias? • Desired consumption at t=0:
ex ante agent wants to consume at t=1 if
• Actual consumption at t=1:
agent consumes if
• Self-control problem (if β u(x2)>0 – Agent over-consumes leisure goods -> u(x2)
Naiveté and consumption How is consumption decision impacted by naiveté? • Forecasted consumption: at t=0 agent expects to consume A if with estimate of β in future periods (from t=0‘s perspective) • At t=1 agent consumes A if
• Naiveté (if ): – Agent over-estimates consumption of investment goods -> u(x2)>0 – Agent under-estimates consumption of leisure goods -> u(x2)
Self-control & 401(k) savings plans
• Voluntary, private retirement saving plan & one of the most important pillars of the US retirement system
• “Employer-sponsored” plan, i.e., employer offers the plan to employees • Employees are free to choose
– whether or not to enroll – contribution level (saving rate) – portfolio composition
• Penalty for early withdrawal of funds • Strong incentives for employees to participate in 401(k) plans
– tax deferral (defined contribution framework) – often: contributions up to certain threshold matched by employer
nevertheless, people seem to save “too little” for retirement
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Madrian and Shea (QJE,2001)
• Study the impact of change in default rule on 401(k) savings behavior at a large US firm.
– Health Care company – Paper-and-pencil 401(k) choice
Default rule:
employees have to enroll actively if they want to participate in the plan
“Opt In”
Default rule:
employees have to notify employer if they do not want to participate
“Opt Out”
April 1, 1998
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Active Enrollment
Before April 1, 1998: Opt in regime
– Only employees with at least one year of employment are eligible to participate.
– Choose contribution rate between 1% and 15%, with 50% employer match for first 6%.
– In order to participate, employees have to • authorize payroll to deduce contribution • choose contribution rate • choose investment allocation.
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Automatic Enrollment
After April 1, 1998: Opt out regime
– All employees can participate immediately. – Employer match only for employees with at least one
year of employment. – New employees are automatically enrolled in 401(k)
plan with possibility to opt out. – Default contribution rate = 3%. – Default allocation = 100% money market fund. – Possibility to change contribution rate and allocation at
any time • identical constraints as before April 1 23
Measuring the Effects of Automatic Enrollment
How to exploit the discontinuity in 401(k) design? Compare three groups of employees:
– OLD (hired before 03/31/97)*: employed, eligible before 04/01/98, no automatic enrollment
– WINDOW (hired between 04/01/97 and 03/31/98): employed, not eligible before 04/01/98, no automatic enrollment
– NEW (hired after 04/01/98): eligible, automatic enrollment with less than 2 years of tenure
– 3+, three and more years of tenure
Compare participation, contribution, and asset allocation Data from June 1997 – June 1999
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Participation on June 30, 1999
• Tenure matters • WINDOW has higher average tenure on June 30, 99 than NEW Compare group behavior for similar level of tenure.
Madrian/Shea (2000)
Participation rates
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Contribution rates, conditional on participating (default = 3%)
• Difference remains when controlling for employer-match eligibility, tenure and individual differences.
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Contribution rates
Explaining the default effect
• Status quo bias (driven by procrastination) Why procrastinate? -> procrastination happens if cost exceeds short run benefits
– Direct transaction costs: implementing a decision – Indirect transaction costs: making a decision
• Complexity (contribution rate, allocation of portfolio)
– Self-control problem
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In general, defaults can influence outcomes without restricting choices of decision makers -> makes it interesting for policy makers • Caveat:
– The very inertia that increases 401(k) participation also lowers employees’ contribution rate.
– Overall, this may lead to lower total savings in the long run compared to alternative plans that require active savings decisions.
• Alternatives: – Choose higher contribution rate as default (might not
be possible for all employees) -> SMarT (Thaler, Benarzi, JPE 2004)
– Implement active decisions
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Active decision mechanisms require employees to make an active choice about 401(k) participation.
– Welcome to the company – You are required to submit this form within 30 days of
hire, regardless of your 401(k) participation choice – If you don’t want to participate, indicate that decision – If you want to participate, indicate your contribution
rate and asset allocation – Being passive is not an option
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Carroll, Choi, Laibson, Madrian and Metrick (QJE, 2009)
Natural experiment Natural ≠ controlled experiment: -> subjects are assigned to treatment by nature
Policy change in a large financial service firm in the US: Switch from paper-based enrollment to phone-based enrollment in November 1997 Paper-based enrollment
– within 30 day after hire decision necessary – non-enrollment default (not publicized ) – Discontinuity in enrollment if initially declined (only
with beginning of succeeding calendar year enrollment possible)
Phone-based enrollment – No active decision enrollment form when hired – Daily enrollment possible 30
Data Two data sets:
– Cross-sections: end of 1998, 1999, 2000, 2001 with socio-economics characteristics and 401(k) participation information
– Panel data from 9/1997 – 4/2002 consisting of individual transactions in the 401(k) plan
Comparison of two groups – Actives: employees hired between 1/1997 and 7/1997
under the “active regime” – Standards: Employees hired between 1/1998 and
7/1998 under the “standard enrollment regime” -> Different tenure when they first show up in data for 1998 -> Actives: 17-24 months of tenure
-> Standards 5-12 months of tenure 31
Hire Date and 401(k) Participation
0%10%20%30%40%50%60%70%80%
Janu
ary
Febru
aryMa
rch April
May
June Ju
ly
Month of Hire
Parti
cipa
tion
Rat
e in
3rd
M
onth
of T
enur
e
Active decision Standard enrollment
-> Treatment effect stems from active decision and the non-ability to delay decision indefinitely
Average enrollment rate for - Actives 69% - Standards 41%
Compare this to (Madrian & Shea)
NEW Cohort: 86%
OLD Cohort: 56%
Actives are not more likely to stop contribution to 401(k) than Standards
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Participation rates
Chart2
JanuaryJanuary
FebruaryFebruary
MarchMarch
AprilApril
MayMay
JuneJune
JulyJuly
Active decision
Standard enrollment
Month of Hire
Participation Rate in 3rd Month of Tenure
Hire Date and 401(k) Participation
0.6984615385
0.4507575758
0.7518796992
0.4245283019
0.7138810198
0.4219178082
0.712
0.4121212121
0.6426116838
0.3602693603
0.6875
0.4030612245
0.7258883249
0.4151436031
fig3
Jan-970.6984615385
Feb-970.7518796992
Mar-970.7138810198
Apr-970.712
May-970.6426116838
Jun-970.6875
Jul-970.7258883249
Jan-980.4507575758
Feb-980.4245283019
Mar-980.4219178082
Apr-980.4121212121
May-980.3602693603
Jun-980.4030612245
Jul-980.4151436031
monthActive decisionStandard enrollment
January0.69846153850.4507575758
February0.75187969920.4245283019
March0.71388101980.4219178082
April0.7120.4121212121
May0.64261168380.3602693603
June0.68750.4030612245
July0.72588832490.4151436031
Jan-970.6984615385
Feb-970.7518796992
Mar-970.7138810198
Apr-970.712
May-970.6426116838
Jun-970.6875
Jul-970.7258883249
1-Aug-970.6655405405
1-Sep-970.4210526316
1-Oct-970.4
1-Nov-970.4267100977
1-Dec-970.4474474474
Jan-980.4507575758
Feb-980.4245283019
Mar-980.4219178082
Apr-980.4121212121
May-980.3602693603
Jun-980.4030612245
Jul-980.4151436031
fig3
Month of Hire
401(k) Participation rate in the Third Month of Tenure
FIGURE 5: Time Until Next Enrollment Opportunity and 401(k) Participation
Active decision
Standard enrollment
Month of Hire
401(k) Participation Rate in Third Month of Tenure
FIGURE 5: Time Until Next Enrollment Opportunity and 401(k) Participation
month
share
Rate of Participation in the 401(k) plan by month of hire
• Active enrollment: – On average 4.8 % of income at month nine – Increases to 5.5% by 48 months
• Standard enrollment: – On average 3.6 % of income at month nine – Takes 33 month to reach 4.8% (= average level of
Actives) • Little difference between the savings rate chosen
immediately after hiring under active decision and the rate in effect after 30 months under Standard enrollment
-> Active decision leads immediately to a relative high contribution rate
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Contribution rates
Participation rates under different regimes (different studies)
Laibson (2010)
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Policy interventions
• The presence of agents who might act against their long-run interests (and the absence of market forces to eliminate such behavior) opens the door for paternalistic policy interventions to “help” the agents.
• To judge whether certain deviations from standard model justify policy interventions, we need a sound understanding WHY these deviations occur
• Non-standard behavior might require non-standard policies – agents do not only react to monetary incentives and
constraints – policies that should not affect decisions from a
traditional perspective might have strong behavioral consequences 35
Libertarian paternalism • Many different names for similar concepts
– “soft”, “asymmetric” paternalism, “nudges”, … – Nudge – “any aspect of the choice architecture that alters people’s
behavior in a predictable way without forbidding any options or significantly changing their economic incentives” (Thaler and Sunstein 2008)
– currently one of the most intensely discussed ideas in the social sciences
• Main idea: – Take limitations of rationality, self-control, and
attention into account – Design policies or “choice architectures” such that…
• biased decision makers avoid making mistakes… • while at the same time decisions of perfectly rational people are
not distorted -> “No one is hurt, but most people gain” 36
Instruments Libertarian paternalistic policies a.k.a. “nudges”:
– Defaults – Information disclosure, framing and labels – Reminders – Cooling-off periods – Self-commitment devices (Constraining choice sets)
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Do defaults save lives?
Source: Johnson & Goldstein, 2003
Countries with explicit consent
(“opt-in” regulation)
Countries with presumed consent (“opt-out” regulation)
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Source: Johnson & Goldstein, 2003
UK implemented “prompted choice”: when applying for new driver’s license one must register to donate, or say that one has already signed up or state: “I do not want to answer this now.”
Germany: health insurers regularly ask members about their willingness to donate organs (yes/no/do not want to answer)
Netherlands: failed to increase donors with large campaign 39
Do defaults save lives?
The $144 Million Default Rule
• New York City introduced credit card readers in 2007 in taxis • Before that cab drivers used to accept cash only and tipping was
governed by informal rule with an average of 10%
With introduction of card readers and 3 “default” buttons (15% / 20% / 25%) tipping more than doubled -> On average tips around 22% In 2014 they changed the default buttons to 20% / 25% / 30%
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Libertarian paternalism in action
Reduces spillage by 80% 41
Information disclosure/framing
Cigarettes in Australia
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Libertarian paternalism: + / –
• Encourages passiveness. Better force people to make a decision.
• Who is best willing and able to take good decisions
– the individual or public institutions? – Do bureaucrats have proper incentives and the relevant
information to define and set up the optimal decision-making environment?
– Best default maybe easy to find if most people have a shared optimum. But what if people choices are heterogeneous?
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• Adopting libertarian paternalistic policies is a slippery slope into more restrictive regulations – Often, libertarian paternalistic policies can be an
alternative to more invasive regulations • In many situations it is inevitable to specify
certain rules. Policies always implement a certain frame. Why not implement the best? – There is often an implicit default (e.g., organ donations)
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Libertarian paternalism: + / –
Paternalism (Nudges) are widespread
• People in “rich” countries are surrounded with invisible nudges – Health insurance (most options are default) – Automatic contribution to pension plan – Licensing for professionals (physician) or activities
(driving) – Immunization – Helmet requirement for (motor) cyclists – Online transactions (right to rescind transaction within
certain time frame) – Age limits for certain behavior (drinking, driving, …) – ….
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Experimental & Behavioral Economics��Defaults, paternalism, and nudges�Memos�Nudging: ProsFoliennummer 3Foliennummer 4Foliennummer 5Foliennummer 6Foliennummer 7Foliennummer 8Positive (revealed) preferencesNormative preferencesThe limits to “revealed preferences”Foliennummer 12Foliennummer 13Foliennummer 14Foliennummer 15Foliennummer 16Present-Bias and ConsumptionFoliennummer 18Naiveté and consumptionSelf-control & 401(k) savings plansMadrian and Shea (QJE,2001)Active EnrollmentAutomatic EnrollmentMeasuring the Effects of Automatic EnrollmentParticipation ratesFoliennummer 26Explaining the default effectFoliennummer 28Carroll, Choi, Laibson, Madrian and Metrick (QJE, 2009)�Natural experimentDataParticipation ratesFoliennummer 33Participation rates under different regimes (different studies)Policy interventionsLibertarian paternalismInstrumentsDo defaults save lives?Do defaults save lives?The $144 Million Default RuleLibertarian paternalism in actionInformation disclosure/framingLibertarian paternalism: + / – Foliennummer 44Paternalism (Nudges) are widespread