We show that delaying acceptance decisions in the Ultimatum Game drastically increases acceptance rates of low offers. While in standard treatments without delay less than 20% of low offers are accepted, these numbers increase to around 65-75% as we delay the acceptance decisions by around 10 minutes. Our findings provide precise evidence for familiar notions such as ''sleeping on it'' and show that there may be a good reason why public administrations often communicate bad news on Friday afternoons. They shed new light on recent evidence in Neuroscience on brain activation after receiving bad news and raise questions about the extent to which decisions reveal the preferences of a decision-maker.microeconomics ;

Grimm Veronika

Mengel Friederike

English

Research Papers in Economics

Veronika Grimm, Friederike Mengel 
 
Let me sleep on it: Delay reduces 
rejection rates in Ultimatum Games 
 
RM/10/017 
 
 
 Let me sleep on it: Delay reduces rejection rates in Ultimatum Games
Veronika Grimm∗ Friederike Mengel†
March 5, 2010
Abstract
We show that delaying acceptance decisions in the Ultimatum Game drastically increases acceptance
rates of low oﬀers. While in standard treatments without delay less than 20% of low oﬀers are accepted,
these numbers increase to around 65-75% as we delay the acceptance decisions by around 10 minutes.
Our ﬁndings provide precise evidence for familiar notions such as ’sleeping on it’ and show that there may
be a good reason why public administrations often communicate bad news on Friday afternoons. They
shed new light on recent evidence in Neuroscience on brain activation after receiving bad news and raise
questions about the extent to which decisions reveal the preferences of a decision-maker.
There is a common implicit understanding that delaying a reaction to bad news may lead to more
moderate reactions and hence more prudent economic decisions. This is often alluded to when people say
”Let me sleep on it before I make a decision”. Public administrations sometimes try to make use of this by
communicating bad news on Friday afternoons such that people cannot react until Monday morning. In this
study we show that ”having a break” can be enough. Delaying decisions by only 10 minutes after receiving
bad news drastically changes human behavior in a controlled laboratory environment.
We study the eﬀect of delaying decisions in the context of the so called Ultimatum Game. In this game
a proposer proposes a division of say 10 Euros to a responder. If the responder accepts the proposal, both
parties receive the suggested amounts. If he rejects both receive nothing. This game has been widely studied
to investigate economic decision making and one of the most robust ﬁndings in experimental economics is
that low oﬀers (of say 1 or 2 Euros) are almost always rejected. Those empirical observations have triggered
the development of a literature questioning the standard model of economic decision making which predicts
that responders should accept any amount oﬀered and consequently, proposers should never oﬀer more than
the minimal amount possible. By now a large body of work exists that incorporates social motives into the
description of preferences in order to accommodate the observed behavior (see [3], or [2] for a survey).
In this study we show that the mere fact of delaying the acceptance decision by approximately 10 minutes
drastically and signiﬁcantly changes human behavior in the Ultimatum Game. Acceptance rates for low
oﬀers increase from 0–15% without delay to around 65–75% with delay.
We report the ﬁndings from an experiment held with 168 undergraduate students from Maastricht
University (84 per treatment). In each experimental session participants were randomly matched in pairs
and given either the role of proposer or responder. The proposer then decided how to split 10 Euros between
∗University of Erlangen–Nuremberg, Department of Economics, Lange Gasse 20, D–90403 N¨ urnberg, Germany, Tel: +49-
911-5302 224; Fax: +49-911-5302 168; E-mail: veronika.grimm@wiso.uni-erlangen.de
†Department of Economics (AE1), Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands; Tel:+31-43-38
83891; Fax:+31-43-38 84878; E-mail: f.mengel@maastrichtuniversity.nl
1herself and the responder. This proposal was immediately presented to the responder on her computer screen.
In the treatments without delay the responder could decide on the proposal immediately after receiving it.
Afterwards all participants ﬁlled in a questionnaire which lasted for approximately 10 minutes. In the
treatments with delay this order was reversed. All responders ﬁrst observed the proposal, then ﬁlled in the
questionnaire, and only thereafter they could decide on the proposal. Hence, their acceptance decision was
delayed in a natural way by approximately 10 minutes. The average (minimal, maximal) waiting time was
10:14 (8:40, 11:57) minutes. We used three very diﬀerent questionnaires and do not ﬁnd any eﬀect of the
questions themselves on responder behavior.
Figure 1: Acceptance Rates and Distributions of Oﬀers. The blue (left) bars indicate the acceptance rates in
the treatments with delay and the red (right) bars those in the treatments without delay. 66% of oﬀers of 1 Euro are
accepted with delay and no such oﬀers are accepted without delay. Oﬀers of 2 Euros are accepted by 75% with delay
but only by 16% without delay. The acceptance rates are signiﬁcantly diﬀerent across treatments for oﬀers of 1 and
2, but not for higher oﬀers (Mann-Whitney, p =0 .0068,p=0 .0483,p>0.1205). Also the probability that any ’low’
oﬀer is rejected (of 0,1 or 2) diﬀers signiﬁcantly across treatments (Mann-Whitney, p =0 .0008). The distributions
of oﬀers in the two treatments are shown by the green and purple lines. The share of extremely low oﬀers of 0 or 1
(those predicted by rationality) diﬀers somewhat between the two treatments (Mann-Whitney, p =0 .0595).
The eﬀect of the delay, though, is drastic, as Figure 1 illustrates. While almost no low oﬀers are accepted
without delay, a large share (65–75%) of these oﬀers gets accepted after a 10 minutes delay only. The fact
that oﬀers are somewhat lower with delay could indicate that proposers do anticipate higher acceptance
rates to some extent if they know that the acceptance decision will be delayed. In fact, given the acceptance
rates we observe proposers maximize their expected payoﬀ by oﬀering 1 in the treatments with delay and
5 in the treatments without delay. Responders in the treatments with delay also earn higher payoﬀs on
average than those in treatments without delay, albeit not signiﬁcantly so.
Our ﬁndings raise fundamental questions about the relation of decisions and underlying preferences. If
(more reﬂected) decisions after delay reveal true preferences, the question arises why (without facing any
time pressure) people choose to make diﬀerent short run decisions and what these decisions reﬂect. If we
want to think of both decisions (with and without delay) as revealing preferences, our results suggest that we
2have to rethink our model of preferences to understand how preferences are formed and why one motivation
may come to dominate others to trigger fundamentally diﬀerent behavior.
Neuroeconomic studies can potentially shed some light on these issues. In fact our results can be useful to
distinguish between two hypotheses recently advanced in this literature. In some studies it has been shown
that rejections of low oﬀers in the Ultimatum Game are strongly correlated with activation of brain regions
such as anterior insula, often associated with feelings such as disgust or anger. These studies also show
diﬀerential activation of the bilateral DLPFC (dorsolateral prefrontal cortex). A common interpretation
is that DLPFC activation might represent cognitive control of the emotional impulse to reject low oﬀers.
Other studies, however, have argued the opposite, namely that the DLPFC may be involved in controlling
the impulse to accept low oﬀers, i.e. in controlling economic self-interest (see [4], or [1] for a survey). Our
results are in line with the former hypothesis, since rejections become much less frequent as the decision
maker is forced to delay her reaction.
References
[1] Camerer, C. and E. Fehr (2007), Social Neuroeconomics: the neural circuitry of social preferences,
TRENDS in Cognitive Sciences 11, 419-426.
[2] Cooper, D.J. and J.H. Kagel (2009), Other Regarding Preferences: A Selective Survey of Experimental
Results, prepared for the Handbook of Experimental Economics.
[3] Nowak, M., K.M. Page and K. Sigmund (2000), Fairness vs Reason in the Ultimatum Game, Science
289, 1773-1775.
[4] Sanfey, A., J.K. Rilling, J.A. Aronson, L.E. Nystrom and J.D. Cohen (2003), The Neural Basis of
Economic Decision-Making in the Ultimatum Game, Science 300, 1755-1758.
3A Supplementary Material
A.1 Experimental Instructions
Welcome and thanks for participating in this experiment. Please read these instructions carefully. They are
identical for all the participants with whom you will interact during this experiment.
If you have any questions please raise your hand. One of the experimenters will come to you and answer
your questions. From now on communication with other participants is not allowed. If you do not conform
to these rules we have to exclude you from the experiment. Please do also switch oﬀ your mobile phone at
this moment.
For your participation you will receive 6 Euros. During the experiment you can earn more. How much
depends on your behavior and the behavior of the other participants. All your decisions will be treated
conﬁdentially.
THE EXPERIMENT
At the beginning of the experiment you will be randomly matched with another participant, who we will
call your interaction partner.
There are two types of players in the experiment, Player 1 and Player 2. Your role and the role of your
interaction partner will be determined by a random draw. In particular, this means that both, you and your
interaction partner, will be Player 1 with probability 1
2.
The experiment has three stages
Stage 1: Player 1 makes an oﬀer how to split 10 Euros among the two of you and Player 2 observes the
oﬀer that player 1 has made.
Stage 2: All participants answer a questionnaire which lasts for approximately 10 minutes.
Stage 3: Player 2 can decide whether to accept or reject the oﬀer made by Player 1. If Player 2 accepts,
then the money is divided as proposed by player 1. If Player 2 rejects both Players receive 0 Euros.
After Stage 3 the experiment ends.
[In the treatment without delay stage 2 and stage 3 were reversed. Otherwise the instructions were
identical.]
A.2 Additional Results and Procedures
We used three diﬀerent questionnaires to control for possible eﬀects of the questions themselves on responder
behavior. Our ﬁrst questionnaire (Q1) was ’neutral’ asking questions such as ”What is your favorite colour?”.
Our second questionnaire (Q2) was ’cognitive’. Questions in this questionnaire are similar to those that can
typically be found in intelligence tests. The third questionnaire (Q3) was ’social’ asking participants their
opinion about social justice.
4In each session 1/3 of all participants were randomly allocated a questionnaire and the waiting time
was the longest time any participant needed to ﬁll in the questionnaire. Hence we ruled out by design that
waiting time is correlated with the type of questionnaire the participants ﬁlled in.
The following ﬁgure shows the acceptance rates as well as the distributions of oﬀers separately for each
questionnaire in the treatment with delay. As expected there are no statistically signiﬁcant diﬀerences in
the distribution of oﬀers (at the time of making an oﬀer the proposers did not know which questionnaire
they, or the responders, had to ﬁll in). Also the distribution of acceptance rates does not diﬀer signiﬁcantly.
Note that in order to calculate overall acceptance rates (Figure 1 in the paper) one needs to take a weighted
average over the three bars in the graph, since oﬀers were not distributed equally across treatments.
Figure 2: Acceptance Rates and Distributions of Oﬀers per Questionnaire (Q1,Q2 and Q3) with Delay
5

Other Regarding Preferences: A Selective Survey of Experimental Results, prepared for the Handbook of Experimental Economics.

Social Neuroeconomics: the neural circuitry of social preferences,

Let me sleep on it: Delay reduces rejection rates in Ultimatum Games

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Let me sleep on it: Delay reduces rejection rates in Ultimatum Games

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