Experimental economics

PhD STUDENT:
BOCCARDO SERENA

EXPERIMENTAL ECONOMICS
6th
June 2014
Experimental Design:
THE ROLE OF FRAMING EFFECT IN AFFECTING
INDIVIDUAL TAX COMPLIANCE

Aim of the experiment

This experiment aims at investigating the role of communication in tax compliance. In particular, it
is an attempt to shed light on the role of different linguistics register and different informative
contents in framing communication for tax payers.
We use a “threating” and a “neutral” messages on tax duties as a treatment and an endogenous
labour supply task modification build on a traditional ASY framework. Deviations of declared
income from earned income measure the individual degrees of tax avoidance.
Overall, the results would contribute to shed lights on the discussed utility of the Prospect Theory
versus EUT in explaining the Yitzhaki puzzle.

Introduction and Motivation
Experimental research into tax compliance and taxpayers’ behaviour can be perceived, according
to Guala and Mittone1
(2013), as “(…) a link between models and the ‘real world’”. The economic
analysis of the tax compliance decision began in 1972, with the research conducted by Allingham
and Sandmo2
, who modelled the taxpayer as choosing the level of evasion to maximize expected
utility where risk arose from the possibility that an audit might be conducted by the tax authority.
Yitzhaki (1974) modified the model to reflect the fact that the punishment for evasion is typically a
fine levied on unpaid tax. Yitzhaki (1974) showed that when the penalty surcharge is proportional
to evaded taxes, as it is indeed most often case in many countries, the effect is unambiguously
negative. However, when confronted with values of the audit probability and the fine rate close to
those observed in practice, the model predicts that all taxpayers should engage in evasion. This has
been named the “Yitzhaki puzzle”.
Subsequent developments of his model have been in the years conducted in various directions.
Among them, there have been studies which have: endogenized pre-tax income by adding labour
supply; extended the basic framework to account for considerations of public expenditure, moral
sentiments, public goods; introduced various sources of imperfect information; modelled different
forms of strategic interaction, etc. These developments have indeed documented that evaded
income depends to an increasing degree on the relative size of the various parameters at play.
Surprisingly, deterrence is not the most important factor3
: i) the fear of feelings of guilt and the risk
of social stigmatisation, have a considerably greater effect on the decision to pay tax than pure
economic self-interest4
; ii) procedural justice is of particular importance5
iii) external incentives in
general can either increase or decrease the internal motivation6
. In particular, Hite (1987)7
found
that if respondents were asked about their own tax behaviour, they tend to attribute evasion to
external factors whereas they attribute evasion to internal factors if they assume the role of others
taxpayers.
Remarkably, Bernasconi and Zanardi (2002) suggested the importance of the “reference dependent
point” in tax evasion decisions, which is part of Prospect Theory literature. According to these
authors, the results of Prospect Theory seem to hold also in the field of tax compliance.
Nevertheless, the attempts to explain the Yitzakhi puzzle with Prospect Theory produced
controversial results: on the one hand, Trotin (2012) found not robust results under the EUT and PT
as a consistent general framework under her assumptions8
; on the other hand, Piolatto et al.(2013)

1
Guala
F.,
Mittone
L.,
2013.
"A
Political
Justification
of
Nudging,"
CEEL
Working
Papers
1307,
Cognitive
and

Experimental
Economics
Laboratory,
Department
of
Economics,
University
of
Trento,
Italia.

2
Allingham,
M.,
G.,
Sandmo,
A.
1972,
Income
Tax
Evasion:
A
Theoretical
Analysis.
University
of

Pennsylvania,
Philadelphia,
USA
and
The
Norwegian
School
of
Economics
and
Business
Administration,
Bergen,

Norway.

3
Taylor,
N.
2001,
Understanding
Taxpayer
Attitudes
Through
Understanding
Taxpayer
Identities.
Centre
for

Tax
System
Integrity,
The
Australian
National
University.
Working
Paper
N.
14.

4
OECD
Report
on
Tax
Administration,
Understanding and Influencing Taxpayers’ Compliance
Behaviour
2010.
Retrieved
from
www.oecd.org/tax/administration/46274793.pdf

5
Kirchler,
E.
(2007).
The
economic
psychology
of
tax
behaviour
.
Cambridge
University
Press.

6
Dwenger
N.,
Kleven
H.,
Rasul
I.,
Rincke
J,
2014,

Extrinsic
and
Intrinsic
Motivations
for
Tax
Compliance:
Evidence

from
a
Field
Experiment
in
Germany,
working
paper,
retrieved
from
www.
tax.mpg.de.

7
In
Hasseldine,
J.,
Hite,
P.,
James,
S.,
and
Toumi,
M.
(2007).
Persuasive
communications:Tax
compliance

enforcement
strategies
for
sole
proprietors.
Contemporary
Accounting
Research
,
24(1):171–194.

8
Trotin,
G.(2012)
Solving
the
Yitzhaki
Paradox:
Income
Tax
evasion
and
Reference
Dependence
under
Prospect

Theory,
AMSE
Working
Paper
N.38

showed that, with the most common specifications for the reference level, PT fails to reverse the
puzzle9
.
Five aspects appear to be crucial considering compliance after publicity according to a recent study
from the Tax and Customs Administration in the Netherland,: a) Targeted coverage; b) arguments
for and against: where strong arguments are put forward in favour, or weak arguments against, this
will tend to increase the number of taxpayers falling into line (albeit reluctantly); c) Risk of
detection: (or at least, the taxpayer’s perception of it) and its consequences (or at least the
impressions of them); d) Standards of behaviour: prescribed standards, what other people expect
from the tax administration (both the implicit and explicit rules) and observed standards, what the
people in society do; e) Legitimacy: justness of procedures, the way in which taxes are levied and
the way the tax administration performs its enforcement duties.
Literature in tax law, moreover, admits that one of the most significant determinants of tax non-
compliance has been detected to be inherent in its complexity. But complexity has also a lot to do
with framing: wording and framing effects, then, contribute to affect the rate of tax compliance
because of their role in increasing/decreasing the level of complexity.
Here it were behavioural economics comes: studies on the framing effect of communication in tax
compliance are indeed quite recent. The oldest one relates to Green, Kahneman and Kunreuther
(1994) who asked visitors to a science museum about funding two projects either by donations or
by means of a tax increase: they found that subtle changes in question order and wording can affect
the nature of the responses. After it, there have been a lot of field experiments (Sausgruber 2009,
2013; Dwenger et al. 2014). In order to build upon existing experiments, Fonseca’s survey was
extremely helpful10
.
i. Experimental design
1.Overview
We designd the experiment by making use of a modification of the standard ASY approach to
income tax evasion: participants ought to engage in some activities in order to gain a personal
endowment (IE) on which to pay taxes. IE is known to the government's tax collector but subjects
do not know that. They only know that the authority can run some detection checks randomly.
Taxpayers decide how much income to report, knowing that: i) taxes on the reported income are a
flat rate t=15%; ii) that, with probability p, his declaration will be audited; iii) that, in case of
auditing and misreported income, his fine will be s (%) where s is a strictly positive penalty
surcharge (look at the equation below).
Random controls occur. Tax payments are withdrawn and subjects are informed of their net income
for the round. The phases are explained in more detail below. Gains (positive values) and discounts
(on the amount to be paid) are not possible and in order to avoid the interaction between risk
aversion and ambiguity risk, we assume the latter to be zero: when tax control occurs, the fine is
applied for sure. The fine is proportional to the extent of evasion (so total evaders and partial
evaders will be charged differently).
By making use of the traditional maximization of EU approach, the taxpayer's problem is to choose
D so as to maximise:

9
Piolatto
A.
&
Rablen,
M.
(2014).
Prospect
theory
and
tax
evasion:
a
reconsideration
of
the
Yitzhaki
puzzle,

Working
Papers
2014/3,
Institut
d'Economia
de
Barcelona
(IEB)
and
Brunel
University
London.

10
Fonseca
M.,
Myles

G.
D.,
A
Survey
of
Experiments
on
Tax
Compliance,
Institute
For
Fiscal
Studies,
Report.

+ RD% (redistr.factor)
where:
- I-D= evaded income = degree of non compliance (dependent variable)
- RD = an equal fraction of the total amount collected during the round. This mechanism well
replicate both the need for a motive for tax payment and the free-rider problem occurring in real
world. On one hand, thus, evasion is the dominant strategy, on the other hand, compliance is
economically rewarded by a redistributive factor.
- p and q are “calibrating” factors: since 0<p<1 and 0<q<1, with q = t (1+s), they can be
manipulated in order to assess individual patterns in response to a higher(lower) fine extent and
audit probability.
The baseline model (second session, explained in the next paragraph) will serve the purpose of
identifying individual baseline behaviours to no message at all and no informative contents in the
neutral and threating messages.
2.Rounds
Each round had two stages both for the treatment and for the control group: a labor task and a
reporting decision. In the labor task stage, subjects undertook a real-effort task and earned money
depending on their performance on the task.
In the reporting decision stage, all subjects have to report an income amount between zero and their
true earned gross income; the reported amount is taxed at the known tax rate.
3. Timeline
Phase 1 : Participants work in order to gain their endowment (labour task).
Phase 2 : Every player receives her communication (randomly distributed), in the second session
one of the control groups receive no communication at all, other two groups receive messages with
no informative contents, only different linguistics registers.
Phase 3 : Subjects are given the 2 min. to declare. They can decide how much to declare and write
down the amount (in figures).
Phase 4 : Taxes are collected + random controls occur.
Phase 5 : Tax evaders are fined. All subjects can see their personal final income with all
components of it (see instructions). The round period ends.
This process will occur in 3 sessions, repeatedly for 20 rounds, so participants face the declaration
task 20 times during each session. Each session included 30 subjects.
4. Treatments
Our treatment is a message given after the labour task (see instructions). In each treatment we vary:
i) the contents of the message, such that p and q can be known or unknown; ii) the linguistics
register used: neutral (N) or (T) threating (table below).
5. Sessions
In order to allow subjects to familiarize with the labour task, the message and the round timeline,
we run a first not paied session. Then, to get rid of “honest” taxpayers, we run a second session with
three treatments as follows:
MESSAGE LINGUISTIC
REGISTER USED
BASELINE
NO

YES NEUTRAL “It is the task of the authority to ensure that all individuals pay their
taxes”.
THREATING “It is the task of the authority to ensure that all individuals pay their
taxes. Please, keep in mind that in case of non-compliance you may
face financial consequences and considerable costs”
The other two sessions are the real game and are run according to the table below.
6. Labour task (see instructions below)
ii. Behavioural expectations
• We expect the threating message to be an incentive for tax compliance with respect to the
neutral case (Sausgruber); moreover, we expect that an increased informative content (on p,
q or both) makes the communication more transparent, so the informative set (auditing
probability+fine amount) delivered into the message should increase tax compliance,
assuming risk neutral individuals. Nevertheless, since individuals have internal
expectations on p and q (reference points) , which operates also in case no information is
given, it might be the case that the levels of p and q communicated “clash” with these
expectations such that:
i) a given p “external” (given in the message) > p “internal” (of the individual) might
possibly produce opposite results on compliance : either a “compliant” result (if the
individual is risk averse) or a “angry” approach (i.e. the fine is considered too high so I
don’t pay). Viceversa if p external is inferior to p internal.
The same can apply to q and to p+q. These results are crucial because by working on the
behavioural reactions to an internal reference point they might shed lights on the Yitzachi
puzzle under Prospect Theory. Of course, in order to do so, the experiment has to be
INFORMATIVE CONTENTS LINGUISTIC
REGISTER USED
MESSAGE DELIVERED
NONE
“ THREATING “It is the task of the authority to ensure that all individuals pay their
taxes. Please, keep in mind that in case of non-compliance you may
face financial consequences and considerable costs”
NEUTRAL “It is the task of the authority to ensure that all individuals pay their
taxes”.
AUDITING PROBABILITY
0<p<1
p%
taxes. Please, keep in mind that in case of non-compliance you may face
“ consequences and considerable costs. Each year, 30% of taxpayers
are audited.”
taxes. Each year, 30% of taxpayers are audited.”.
FINE EXTENT
0<q<1
q%
financial consequences and considerable costs. The fine rate applied to
non-compliant taxpayers is 15% of their real income plus the
difference between their real income and the declared one”
taxes. The fine rate applied to non-compliant taxpayers is 15% of
their real income plus the difference between their real income and
the declared one”.
AUDITING PROBABILITY+
FINE EXTENT
p%+q%
THREATING “It is the task of the authority to ensure that all individuals pay their
financial consequences and considerable costs. Each year, 30% of
taxpayers are audited. The fine rate applied to non-compliant
taxpayers is 15% of their real income plus the difference between
their real income and the declared one”
taxes. Each year, 30% of taxpayers are audited. The fine rate
applied to non-compliant taxpayers is 15% of their real income plus
the difference between their real income and the declared one”.

repeated for different levels of p and q, in order to establish which are the “threshold”
levels of p and q which can be considered the reference points.
Based on the above two predictions, we can establish the following inequalities:
BEHAVIORAL PREDICTIONS
ZERO CONTENTS THREATING0>NEUTRAL0
AUDITING PROB. ONLY THREATING p> NEUTRAL p ?
THREATING0>NEUTRAL0
FINE EXTENT ONLY THREATING q> NEUTRAL q ?
THREATING0>NEUTRAL0
AUDITING+FINE THREATING q+p> NEUTRAL q+p >
THREATINGi>NEUTRALi>
THREATING0>NEUTRAL0 i=p,q
Moreover:
• We expect the probability of evading taxes in one period increases if the player has been
audited in the previous period and, generally, increases as the experiment goes on (Mittone
2014) and we expect the likelihood of cheating reduces as the number of audits increases
(Mittone 2006).
iii. Experimental Manipulations
1. Framing the information given in terms of percentages, times, or scale (i.e. 1 out of 10) can
considerable modify the results. It has been suggested to frame it in terms of scale rather than
percentages given the small number of participants comparing to a natural field experiment.
2. The tax % applied is arbitrary. Modifying this rate can also produce significant changes in
results. The tax rate can be modified in each round. Moreover, as above, its framing counts (i.e. 10
$ tax each 1000 $, 1/10 or 10%). Moreover, the taxation system could be proportional, progressive
or regressive: we kept it proportional and in % dimension for simplicity. What is relevant, it has a
close range of possible value between 0% and 100% which can be applied (values exceeding these
extremes wouldn’t make sense in a tax compliance framework).
3. Individual income can be modified to be based not only on earnings gained during the
preliminary phase, but also on some exogenous source of wealth randomly allocated across
individuals regardless of their ability (i.e. in the real world: corresponding to inheritances, transfers,
benefits, etc.) Their gross-income in each round could have consisted of their labor income plus a
fixed amount of non-labor income. This would frame a more realistic environment where
individuals are aware that some people pay taxes on earned and some on inherited wealth (It might
be interesting to compare these two scenarios).
4. Peer-effect and information cascade can occur when modifying the information available to
individuals: i.e. do individuals ignore their past experience (“private information”) when public
information about other people’s behaviour is available?... All else equal, do public information
induce towards more or less tax compliance?
By assuming Bayesian rationality and common knowledge, do taxpayers adapt their pattern
according to the collective behaviour occurred in previous rounds?
5. Duration of the “decisional period” can be randomly assigned to each person instead of being
fixed. This would help finding evidences pro or against consistent behaviour (i.e. regardless of the
duration of the period at disposal, tax evaders can decide to not to pay or, conversely, they decide to

pay only proportionally to the length of the decisional period, as they perceive an increase in the
risk of tax checking). Moreover, this random distribution of “time available” might or might not be
perceived as iniquitous and unfair: does it matter for tax compliance? And how to disentangle these
two effects?
5. Duration might also be modified with regard to the amount to be given by imposing a fine for
belated payments (i.e. fine=0 if payments occur before the deadline, fine=10% of the due if
payment is made within 1 minute after the deadline, fine=50% of the due if payment is made within
5 minutes after the deadline and so on). This would provide evidence for assessing individual risk-
aversion. (See below)
iv.Methodological issues
The deviations of declared incomes from earned incomes is our variable of interest. It is our
measure of the degree of non-compliance. We can estimate it through a difference-in-difference
analysis of each group. Thanks to the first session, we can be sure participants understood the
mechanism of the game. Thanks to the second session, where we could identify the control groups,
which received no information about p and q. Thanks to the second and third sessions, we can run
several difference-in-difference estimations (considering the dependent variable as the deviation of
the declared income from the earned income):
- threating vs no message; neutral vs no message; no message at all; (Control groups)
- threatingp vs threating0 ; threatingq vs threating0; threatingq+p vs threating0; threatingq+p vs threatingi
with i=p,q;
- neutralp vs neutral0 ; neutralq vs neutral0; neutralq+p vs neutral0; neutralq+p vs neutrali with i=p,q;
Since participants are the same and they are an homogeneous population in terms of age, education,
etc. and that no individual characteristics can affect the y, except for their risk preferences, the D-in-
D technique seems the most reliable technique to applied in this case. Thanks to the 20 repeated
declarations and thanks to the fact that participants can see whether or not they have been detected
during the round (each information about their net income contains all the components for the net
income, see instructions for more details) we can control for potential path dependence and for
fixed effect in every session.
The dependent variable is necessarily positive and can vary over a wide scale, so ordinary linear
regression is unlikely to generalize well over both small income and large misreported declarations.
We could make use of is GLMM, which takes into account also the random effects in addition to
the usual fixed effects.
For what concerns the independent variables, in addition to the dimensions of treatment, we can add
some control variables (age, sex, Econ, which takes into account whether the subject is a student of
Economics or not) and the variables concerning the experiment: R=round (from 1 to 20),
RE=repeated evasor (dummy yes/no), AC=number of audits already experienced by the subject).
v. Observations
1. It seems that people’s behavior at the end of a series of stationary repetitions is more
representative of their behavior in economic settings than their behaviour at the beginning
and this would justify the use of a repeated game of 20 rounds each.
2. Stationary repetition is a useful tool for studying learning, not a technique to increase
external validity 11
. As Ledyard (1995) noticed12
, stationary repetition helps us in separating

11
Cit.
supra

12
Cit.supra

the noise from the data, in the sense of being sure that the data re not simply the result of
confusion and inexperience of subjects about the mechanics of the experiment.
vi. Instructions
Introduction
Welcome and thank you for participating in our experiment. From now on until the end of the experiment, please
refrain from communicating with other participants. If you do not abide by this rule, we will have to exclude you from
the experiment. We kindly ask you to read the instructions thoroughly. If you have any questions after reading the
instructions or during the experiment, please raise your hand and one of the instructors will come to you and answer
your question in person. Your payment and your decisions throughout the experiment will be treated conﬁdentially.
None of the other participants is informed (possible extention of the experiment is to modify this rule), neither
during nor after the experiment, about your decisions in the experiment or your payment. You can earn money in this
experiment. How much you earn depends on your decisions. During the experiment, your payments will be calculated
in a virtual currency: Experimental Currency Units (ETU). 1 ECU corresponds to 0.10 Euro. After the experiment, your
pay-off will be converted to Euro and given to you in cash. Additionally, you will receive a show-up fee of 2.50 Euro.
The experiment
Overview The experiment consists of 3 sessions of 20 rounds each. In each round, you will complete a labor task and,
depending on your performance, earn money from this labor task. After that, a message will be shown to you, informing
that you have to pay taxes on your earned income and that authorities will check your behaviour.
Payment The first session serves as a practice session, in which you cannot earn money. The subsequent 2 sessions are
paying sessions. In each session, all rounds are independent of each other and at the end of each of them you will know
your payoff for that round only. What is more, your payoff does not at all depend on the decisions of other participants.
Flow of each round In each round, you will phase a first step (the labour task) and a second step (the declaration phase).
In the middle, we will show you a message informing you about the fixed tax rate of 15% which is applied to your
income and some more details on the detection phase (no details on the probability of detection and on the extent of
the fine should be added now in the instructions because the first session will contain every kind of message,
being it a trial, while the second session will serve the purpose of building the control groups so messages
delivered in the second session will not be informative of any p and q, whereas the third session will again have p
and q in the message). In the second step, you have 2 minutes to declare your income for that round. After the
declaration phase, a random detection phase will occur. Eventually, you will be informed of your net income for that
round. This is the same for every round.
The Labor Task You will have 5 minutes to complete the labour task. During the task a screen with 48 so-called sliders
appears on the screen. Each slider is initially positioned at "0" (Zero) and can be moved by you. You can move the
slider to every whole number between "0" and "100" by clicking on the slider and moving the computer mouse. The
current position of each slider is displayed to the right of this slider. You can readjust the position of each slider as
many times as you wish. For each slider that you position exactly at "50" during the five minutes, you earn 6 ECU.
During the 5 minutes of the labor task, on the upper right of the screen you are shown how many sliders are currently
positioned at "50".
The Tax Return You are now asked to report income for tax purposes. You choose an amount which shall be taxed at
the tax rate of 15%. This chosen amount can be between zero and your gross income.
Calculation of Net Income After the completion of the tax reporting decision, we will make random detection controls
and after that you will be shown your net income for that round. The net income is based on the number of correctly
positioned sliders. Moreover, all tax revenues collected will be shared equally and this will be part of your net income
(“RF”).
Its amount depends on the contributions of all participants, but all of you will receive an equal amount of it. This sum
might be decreased by a fine to be paid in case you misreport your income and you are detected. The fine will be
proportional to what you misreported, meaning to the difference between your declared and your earned income.

The net income will be shown to you at the end of the round in the form:
ROUND INCOME= NET+ RF – FINE (IF ANY)
so you will be informed exactly of how it has been calculated.
Final Remarks After the completion of all 3 sessions - one practice session plus 2 paying sessions of 20 rounds each -
the experiment is finished. One of the experimental investigators will come and pay you. Your payment consists of the
total net income that you earned in all the 40 rounds (two sessions).
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London.
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California – Berkeley.
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Centre for Tax System Integrity, The Australian National University. Working Paper N. 14
Trotin, G.(2012) Solving the Yitzhaki Paradox: Income Tax evasion and Reference Dependence
under Prospect Theory, AMSE Working Paper N.38

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