A Study of Preferences Under Constraint

1. A Study of Preferences Under Constraint Jayson Shi Jia Kunal Patel

2. Research Question • Will the existence of a consumption constraint result in higher consumption at some point? • How does the modification of a consumption constraint change an agent’s consumption pattern? • Inspired by the “Yale College Law School Run” - of yore • Expect loss aversion and information effect with budget constraints

3. Why use an experiment? • Can try to solve different FOC’s and Lagrangians for different constraints • Hard to conjecture what people will do because we are interested in a behavioral effect • Needed at least a survey instrument • Used the experiment and Excel to try some other things, like looking at information effects • Harder for subjects to ‘screw up’ when we design things on excel as opposed to pencil and paper

4. Value V(x) -x x Losses Gains Reference Point V(-x) Loss Aversion in Riskless Choice: A Reference Dependence Model (1991) • Reference Dependence • Gains and losses relative to reference level • Loss Aversion • Losses loom larger than gains • Diminishing Sensitivity • The marginal value of both gains and losses decreases with their size

5. Mental Accounting (Thaler 1985, 1990, 1999) • Framing: How a person subjectively frames a transaction in their mind will determine the utility they receive/expect • Expenditures grouped into a number of non-fungible accounts • Frequency with which accounts are evaluated and ‘choice bracketing’

6. What we initially wanted… • Scenario 0: buffet – tell people to ‘eat’ as much as they would normally like– don’t tell people how much they paid – see how much they would like to consume – use this to calculate x • Scenario 1: buffet where people are told they paid $x • Scenario 2: impose a constraint on consumption at $x, for which you pay $x • Scenario 3: pay $x for a constraint y, where y<x • Scenario 4: pay $x for a constraint z, where z>x Try to capture effects of loss aversion: scenario 0 is reference point, scenario 3 is loss, scenario 4 is gain

7. Menu Experiment (1) • Choose Items on a Menu (too easy?) • In each question, you have essentially solved a maximization problem and told us what amount of food maximizes your utility

8. Menu Experiment (2) • Gain and Loss treatments • Control: all you can eat with no price - measure natural reference point • Give new reference points with new budget constraints: • Buffet, Buffet with market value price tags, +$2 budget, +$4 budget, -10% budget, -20% budget

9. Menu Experiment (3) • Information treatment • Reveal Percentage spending of others – people see how efficient others are • Reveal Absolute spending – people realize base values are very different

13. Results – Part 1

14. Results – Part 2

15. Criticism • Small sample size (trading games didn’t have this problem because bids were individual data points) – not much we can say now • Experiment design: diversity seeking bias with a big menu • Overly involved sample population – sabotage, trying to open hidden pages, too much talking, context and group effects

16. Future Improvements • Larger sample size to allow for statistical analysis • Focus on one commodity, e.g. cell phone minutes, emission credits • Ask people to rate satisfaction for different gains and losses – this is to measure the value function • No PhD students in sample

17. Thanks for listening!