Boosts and Nudges under GARP

In this research, we aim at assessing how decision support tools might impacts individual choice relevancy. More precisely, we want to compare the impact of nudges and boosts on individuals’ errors. Nudges had been considered since Thaler and Sunstein 2008’s book as cost-effective mechanisms to reduce the consequence of decision biases for individuals. More recently, some debate had risen about the persistence of nudges’ effects over time (Brandon et al 2022, DellaVigna and Linos 2022). Some authors have suggested that boost interventions (Hertwig and Grune-Yanoof 2017 ; Caballero and Ploner 2022, Banerjee and John 2020), -- ie, processes where elements of reflection and understanding for the mechanism are acquired by participants for « boosting » competence – might be more efficient and more persistent.
Our intervention consists in a laboratory economic experiment where participants should make repeated allocation choices along a budget line by using the Choi et al 2007 interface and method. This method is based on the consistency of successive bundle consumption choices by an individual to GARP (Generalized Axioms of Revealed Preferences) These allocation choices are incentivized and participants get a monetary payoff at the end of the experimental session that depends upon their personal choices during this task.
These participants are randomized in 6 experimental treatments (described below) consisting in 2 control treatments, 2 nudge treatments and 2 boosts treatments. Each experimental session is organized in 8 steps for an expected duration of 1h45mn.

In our experimental design, 6 treatments are to be implemented. The basic task consists for a participant to choose a consumption bundle along a given budgetary line that changes at each round of choice. There will be 50 rounds of choices under the Choi et al 2007 method. Answers to these tasks enable us to assess various rationality scores that are widely used in the GARP literature.
For the nudge treatments, we implement 2 treatments. In the first one -- Nudge 1 --, during the allocation choices task that evaluates the consistency with GARP axioms, the computer uses previous allocation choices made under various budget lines to indicate to the participant for the current choice which segment line is consistent with their past choices and which segment line is inconsistent. The participant should therefore make an allocation choice either in the 'good' line segment but remains totally free to make a choice that belong to the 'bad' line segment. The second one -- Nudge 2 -- is a variant of Nudge 1; Instead of indicating a 'good' and a 'bad' line segment to each participant, the computer randomly selects a choice bundle that is consistent with their previous bundle choices. That is, the random bundle lies within the 'good' line segment but without materializing the segment in the computer graphical interface.
For the boosts treatments, we also implement 2 treatments. The first one --- Boost 1 -- consists in a 30' duration teaching course about GARP. This course is divided in 2 phases, a 10' video teaching course that explains the basic principles of GARP theory + numerical illustrations about bundle choices and a 20' practice task where each participant should learn to identify choice inconsistencies in numerical exercices. Answers are collected through the computer interface and the participant will have the opportunity to assess her level of understanding by obtaining active feedback regarding her answers to the numerical applications. The second one -- Boost 2 -- uses the Money Pump Argument by Echenique et al 2011. The ideal is that a consumer that violates GARP is subject to being exploited as a "money pump". This money pump will be stronger if the severity of violation of GARP is higher and a Money Pump Index could be meased by the amount of money that could be extracted from the consumer. In our boost 2, each participant directly confronts to a computer AI that tries to extract money from her depending on his previous allocation choices during a sequence of 30'. The participant makes a choice and has the opportunity to consider which amount could be extracted by the computer from choosing this particular bundle given her previous sequence of choices, which incites her to change her current choice. Contradingly to the GARP choice sequence that occurs after, boosts are non monetary-incentivized.
In order to compare cleanly our experimental treatments, we will implement two control treatments: The first one -- Control 1 -- is the basic 50 rounds sequence of allocation choices to be completed by each participant, and that was implement in past economic experiments that are reported in the literature. The second control -- Control 2 --- consists in putting randomly a bundle choice on the budgetary line for each participant at each round. This control enables us to compare more properly the choice outcomes to the ones under the Nudge 2 treatment, where a random bundle choice occurs in the 'good' line segment.
Moreover, an important characteristic of our experiment is that we implement in all treatments but boost ones a 'fake' boost before the GARP choice sequence. The implementation of it is explained by the fact that participants that are in the boost treatments will be confronted with tasks that are cognitively highly-demanding, which is not the case in the other treatments. In this 'fake' boost that lasts 30' (like in the other boosts), participants are exposed to a 10' duration teaching course about macroeconomic theory of growth and then should complete tasks with numerical applications aiming at computing growth rates and the contributions of production factors to it. In order to check the comparability of this fake boost to the GARP boosts, we will also use a psychometric score for measuring fatigue level before and after the boost sequence (Multidimensional Fatigue Inventory measure, see Smets et al 1995).
We use also the Cognitive Reflection Test to measure cognitive abilities for each participant.

2023-05-23

2023-06-28

1) percentage of GARP-consistent participants
2) money-pump index.

1) GARP-consistency means the participant never violates the Generalized Axiom of Revealed Preferences, which is that whenever he chooses a bundle of goods A when a bundle of goods B is available, then he cannot choose the bundle B if A is available (Varian, 1982, Econometrica). 2) Average of maximum and minimum money pump index (a rationality index introduced by Echenique, Lee and Shum, 2011, Journal of Political Economy), as computed following the algorithm described in Smeulders et al, 2013 (Journal of Political Economy).

in our laboratory economic experiment, the main stage consists for participants to make repeated allocation choices along a budget line by using the Choi et al 2007 interface and method. This method is based on the consistency of successive bundle consumption choices by an individual to GARP (Generalized Axioms of Revealed Preferences). These allocation choices are incentivized and participants get a monetary payoff at the end of the experimental session that depends upon their personal choices during this task.
In the control treatments, partcipants did not get any help during the GARP sequence (information nudges) or before the GARP sequence (
In our nudge treatments, participants get some help by the computer during a given allocation choice. The computer uses previous choices made by each participant to indicate where lies the consistent choice for the current round.
In our boost treatments participants have the opportunity to learn during a 30' sequence about GARP principles and its implementation through choices along a budget line. This boost sequence occurs naturally before the GARP sequence where they repeatedly choose consumption bundles.
These participants are randomized in 6 experimental treatments (described below) consisting in 2 control treatments, 2 nudge treatments and 2 boosts treatments. Each experimental session is organized in 8 steps for an expected duration of 1h45mn.

In our experimental design, 6 treatments are to be implemented. The basic task consists for a participant to choose a consumption bundle along a given budgetary line that changes at each round of choice. There will be 50 rounds of choices under the Choi et al 2007 method. Answers to these tasks enable us to assess various rationality scores that are widely used in the GARP literature.
For the nudge treatments, we implement 2 treatments. In the first one -- Nudge 1 --, during the allocation choices task that evaluates the consistency with GARP axioms, the computer uses previous allocation choices made under various budget lines to indicate to the participant for the current choice which segment line is consistent with their past choices and which segment line is inconsistent. The participant should therefore make an allocation choice either in the 'good' line segment but remains totally free to make a choice that belong to the 'bad' line segment. The second one -- Nudge 2 -- is a variant of Nudge 1; Instead of indicating a 'good' and a 'bad' line segment to each participant, the computer randomly selects a choice bundle that is consistent with their previous bundle choices. That is, the random bundle lies within the 'good' line segment but without materializing the segment in the computer graphical interface.
For the boosts treatments, we also implement 2 treatments. The first one --- Boost 1 -- consists in a 30' duration teaching course about GARP. This course is divided in 2 phases, a 10' video teaching course that explains the basic principles of GARP theory + numerical illustrations about bundle choices and a 20' practice task where each participant should learn to identify choice inconsistencies in numerical exercices. Answers are collected through the computer interface and the participant will have the opportunity to assess her level of understanding by obtaining active feedback regarding her answers to the numerical applications. The second one -- Boost 2 -- uses the Money Pump Argument by Echenique et al 2011. The ideal is that a consumer that violates GARP is subject to being exploited as a "money pump". This money pump will be stronger if the severity of violation of GARP is higher and a Money Pump Index could be meased by the amount of money that could be extracted from the consumer. In our boost 2, each participant directly confronts to a computer AI that tries to extract money from her depending on his previous allocation choices during a sequence of 30'. The participant makes a choice and has the opportunity to consider which amount could be extracted by the computer from choosing this particular bundgle given her previous sequence of choices, which incites her to change her current choice.
In order to compare cleanly our experimental treatments, we will implement two control treatments: The first one -- Control 1 -- is the basic 50 rounds sequence of allocation choices to be completed by each participant, and that was implement in past economic experiments that are reported in the literature. The second control -- Control 2 --- consists in putting randomly a bundle choice on the budgetary line for each participant at each round. This control enables us to compare more properly the choice outcomes to the ones under the Nudge 2 treatment, where a random bundle choice occurs in the 'good' line segment.
Moreover, an important characteristic of our experiment is that we implement in all treatments but boost ones a 'fake' boost before the GARP choice sequence. The implementation of it is explained by the fact that participants that are in the boost treatments will be confronted with tasks that are cognitively highly-demanding, which is not the case in the other treatments. In this 'fake' boost that lasts 30' (like in the other boosts), participants are exposed to a 10' duration teaching course about macroeconomic theory of growth and then should complete tasks with numerical applications aiming at computing growth rates and the contributions of production factors to it. In order to check the comparability of this fake boost to the GARP boosts, we will also use a psychometric score for measuring fatigue level before and after the boost sequence (Multidimensional Fatigue Inventory measure, see Smets et al 1995).
We use also the Cognitive Reflection Test to measure cognitive abilities for each participant.

Randomization is made within the experimental platform: Participants register for particular time slots for which they are available and treatments are randomized at the session level. Participants can only participate once to the experiment, which is ensured with the experirmental platform registration system based on ORSEE (See Greiner 2017).

Session-level randomization: Participants register to participate on time slots and they are randomized in our various treatments. individuals are randomly assigned to the treatment and comparison groups

Yes

330 participants for individual choices, experimental sessions of 20 participants as a whole for all treatments but Control 2, that will have only 15 participants. The total number of experimental sessions to complete is 17.

330 participants will make 50 allocation choices during the GARP sequence after having 5 trials. Moreover they will answer to 2 fatigue questionnaires (2 scores per participant, before and after the boost sequence), a Cognitive Reflection Test. We also observe their answers during the boost sequence. Last, they should complete the Big5 personality test (Goldberg 1992) before the usual post experimental questionnaire.

- in Control 1 (Basic GARP sequence based on Choi et al 2007) we will have 60 subjects and therefore 60 independent observations for GARP indexes
- in Control 2, 30 participants
- In Nudge 1: 60 participants
- In Nudge 2: 60 participants
- In Boost 1 : 60 participants
- In Boost 2 : 60 participants