overweight the low probability of audit. although such overweighting is not universal. The ... reasons behind individual tax compliance behavior remains limited.
Journal
of Public Economics
48 (1992)
21-38.
North-Holland
Why do people pay taxes? James Aim, Gary H. McClelland
Received February
and William D. Schulze*
1990. revised version received January
1991
Why do people pay taxes when they have an opportunity. even an incentive. IO evade? The experimental results in this paper suggest that tax compliance occurs because some individuals overweight the low probability of audit. although such overweighting is not universal. The results also indicate that compliance does not occur simply because individuals believe that evasion is wrong. since subject behavior is unchanged by the use of either neutral or loaded terms. Finally. there is evidence that individuals pay taxes because they value the public goods that their taxes linance. In short. individuals exhibit much diversity in their behavior.
I. Introduction In rcccnt years economists have dcvotcd incrcasinp attention to the study of individual tax evasion. Despite these efforts. our understanding of the reasons behind individual tax compliance behavior remains limited. In fitct, the puzzle of tax compliance is that most pcoplc continue to pay their taxes. This papa uses cxpcrimcntid methods factors play in the compliance dccision. One explanation punishment
is
to examine the role
that
various
for compliance strcsscs that the threat of dctcction and
responsible
for
complinnce.
This
theory
stems
from
the
economics-of-crime itpproach, based upon traditional expcctcd utility theory and first applied to titx evasion by Allingham and Sandmo (1972).’ Here a rational from
individual
is viewed as weighing the expected utility
successful tax evasion
with
the uncertain
of the benefits
prospect of detection and
punishment. and an individual pays taxes because he or she is afraid of getting caught. Although it is clear that detection and punishment affect compliance to ii dcgrec,* it is equally clear that these factors cannot explain all. or even most, tax compliance behavior. The percentage of individual Correspondmce ro: J.
Aim. University of Colorado. Boulder, CO 80309-0256. USA. ‘We wish Lo thank Charlie PIott, Mark Isaac. and Jorge Martinez for helpful comments on an earlier version of this paper. Mark Evrrs. Steve Elliot, and Julie Irwin provided excellent research assistance. ‘The basic model of Allingham and Sandmo (1972) has been extended in a variety of dimensions. See. for example. Yitzhaki (1974). Pencavel (19791. Sandmo (1981). Cowell (1985). and Alm (19X8). Cowell (1990) provides a comprehensive survey of the literalurr. ‘For empirical evidence on the deterrent &ccl of government audit and penalty policies. see Dubin and Wilde (19XX). 0057-2727.92,SOS.oO
3’) l992-Elsrvicr
Science Publishers B.V. All rights reserved
1.
22
A/m
er al.. Why do peoplepay mres.?
income tax returns that are subject to a thorough tax audit is quite small in the United States, less than I percent in recent years. In addition. the penalty on fraudulent
evasion in the United
States is only 75 percent of unpaid taxes,
and the penalties on non-fraudulent evasion are even less. A purely economic analysis of the evasion gamble implies that most individuals would evade if they are ‘rational’, because it is unlikely that cheaters will be caught and penalized.’ Yet compliance with the individual income tax remains relatively high; that is. individuals
pay far more in taxes than suggested by the
standard expected utility theory of compliance. It seems implausible that the low penalties and the low probability of detection that prevail in the United States. indeed in most countries, can by themselves act as an effective deterrent to evasion, unless individuals’ aversions to risk far exceed conventional assumptions. In fact, the Internal Revenue Service (1978) has found that there are numerous factors other than detection and punishment that affect the decision to pay taxes. It therefore appears that there is some discrepancy between the way in which people actually decide to pay their taxes and the models based on expcctcd utility theory that have been used by economists to explain this behavior. Such anomalous behavior has frcqucntly been found in other arcas of choice under uncertainty, particularly in those arcas that involve low probability-high
loss cvcnts, such as natural
or man-made
disasters, or in
those arcas whcrc the decisions of individuals arc intcrdcpcndcnt repcatcd. such as the voluntary provision of public goods. Scvcral explanations One argument
for this behavior
stems from thcorctical
and
have been suggcstcd in rcccnt years.
work of Machina
(1983) and Kahncman
%rartr and Wilde (19X5)and Skinner and Slemrod (19X5)make a simihlr nryumcnt. To illustrutc more prcciscly. consider the stand;ud cvas~on modrl of Allinyh;un and Sandmo (1972). Hcrc an individual receives a fixed cndowmant of income. I, and must choose how much of this income to declare IO the lax authorities and how much to under-report. The individual must pay taxes 31 thr rate I on every dolhlr D of income that is declared. while no 13xcs are paid on evaded income. tiowcvcr. the individual may be audited with probability p; if audited. then all unreported income is discovrrcd. and the individual must pay :I penalty a~ the rate 1’ on each dollar that he or she was supposed to pay in taxrs but did not pay, The individual’s incomr. I,. if caught under-reporting equ~ds I,=f -rD-l[r(l-01). while income. I,. if not caught is I, = I -rl). Expec~cd utility theory then assumes that the individual will choose D in order to maximize expected utility EU =pU(/,) +( I +p)U(/,). where U(,) is the utility function. Now suppose that this optimization is solved for specilic. realistic values of the various parameters and ti,r the spccitic utility runction. I,! -‘!‘I I -e). where the subscript i rcfcrs to the sta~c of the world (i =C.N) and c is 3 measure of the individual’s constant relative risk aversion. For ex;lmple, il r = 0.4. /’ = 2, p = 0.0 2. and e = I. then the individual will optimally declare no income. Very large valucx for rrlativrs risk aversion are rcquirrd IO generate compliance consistent with aclual U.S. experience. When e= 3. declared income is only I4 percent of true income: when e= 5. it is still only 44 percent; when c= IO. it is only 71 percent. Risk aversion must ctceed 30 for compliance to exceed 90 percent. However. existing ticld evidence suggests that c rangrs between one and two [Cohn et al. (1975). Friend and Blume (1975). Morin and Suarcz (19X3)]. Consequently. cxpeclcd utility theory predicts that the optimal strategy for most individuals is IO report littlr or no income. Tar Ices than is actu;dly observed.
J. Alm et al.. Why do
and Tversky either
(1979).
can
show
Using
great
different
sensitivity
pu.vta.re.~.7
peopie
approaches. to
or
can
they
23
argue
overweight
that low
individuals
probabilities.
Suppose. for example. that the true probability of an event is 0.02. In making their decisions, however, many individuals will systematically behave as if they
think
the likelihood
of the event
exceeds 0.02, when
viewed from an expected utility perspective. ties may therefore provide an additional taxpayers
give more
weight
to the probability
relative to an expected utility the level suggested by expected Another
factor
Overweighting explanation of an audit
model, then compliance utility theory.’
arises from
theoretical
and
their
behavior
is
of low probabilifor compliance. If than they ought will
experimental
be greater work
to
than
on public
good provision. Samuelson (19%) argued that the private provision of public goods will be inefficiently low because each individual will have an incentive to ‘free ride’
on the private
purchases
of others.
The
Samuelson
result
has
received some support from the experimental work of Kim and Walker (1984). Isaac, Walker and Thomas (1984). and Isaac, McCue and Plott (1985). However, other work argues that voluntary provision may not always play as a prisoners’ dilemma game; that is. an individual’s optimal decision may depend upon the actions that hc or she cxpccts others to follow, both now and in the future.’
Under
some circumstances.
full voluntary
tions (or cooperation) may be the dominant individual thcrcforc suggests that individuals pay taxes voluntarily
contribu-
strategy. This because they
work value
the goods
provided by govcrnmcnt and they rccognizc that their payment Howcvcr. the role of public may bc necessary to get others to contributc.h good provision in tax compliance has largely been ncglcctcd.’ The purpose of this paper is to use cxpcrimcntal methods to examine the ‘Studies of flood and carrhqudc insurance [Kunreuthcr cl aI (lY7X)j and of the vduc’ of avoiding cxp~urc IO hazardous suhst;mccs [f~urncss CI al. ( IYX.3). Smith and C~csvousgcs (1956)J alI suggestextraordinary lcvcls of risk aversion. Laboratory experiments by McClelland. Schulrr and Coursry ( IYX6) also confirm that individds oftsn overweight low probabilities when they have the opportunily IO purchase insurance IO protect against an uncertain loss of income. Marc generally. there is growing evidrnce from numerous areas tha[ indicarcs that individuals do not always behave in a manner consistent with cxpectrd utility theory. SW Machina (19X7) for a &tailed discussion of this li(erraturr. ‘For rxamplc, the theoretical work of Taylor (lY76). Axelrod (IYXJJ, Palfrey and Rocrnthnl (lW4). and Bagnoli and Lipman (1986) shows thar voluntary provision can lead to Ihe efiicirnl level of public good provision, despite the usual prrsumplion that individuals will attempt to frcr ride. The rxperimen[al litrralurr has mixed resulks. but there are numerous instances in which these theorrlicnl results hove hccn verified [Brubaker (19X2). Rapoporr (19X5).rrrd Uagnoli and McKee (IYYI)]. ‘There are. of course. other factors that may explain compliance. For example. psychologias and Other social scirntids argue that so&d norms and perceptions of fairness nlkcr compliancr; thar is, individuds pay taxes because they furl thal it is a social obligarion IO do so. although they comply less if they perceive th;ll they are tread less fairly than others. ‘Ser. however. Becker. Buchncr and Sleeking (19X7). who examine cxperimendly the role of transfer paymrnls on compliance. and Cowcll and Gordon (19xX). who analyze theoretically the dTcc[ of governmenl rxpcnditurcs on lax compliance and show Ihal a higher I;IX rale can Id IO less compliance.
J. Alm et
2‘4
roles that overweighting services
play
in
the
of..Why
do
people
of low probabilities individual’s
tax
pay taxes.? and recognition
compliance
of government
decision.
Experimental
methods have been applied to some issues in tax compliance by Friedland, Maital and Rutenberg (1978). Spicer and Becker (1980), Friedland (1982). Spicer and Hero (1985). and Becker. Buchner and Sleeking (1987). among others. In the experimental design used here, subjects are faced with a typical tax compliance decision: they receive income. they must decide how much income to report as taxable income, knowing that there is some probability that they will be caught and penalized if they do not report all of their income. and they receive a return
for
their
taxes (or a public good) that
depends upon the level of group tax payments. The parameters relevant to their decision - the tax rate, the probability of detection, and the like - are based upon values that individuals actually face. In particular, several levels for the probability of detection are used in separate treatments, with the values set at low levels, and several levels for the public good are also used in separate treatments. The experimental results provide strong evidence that some individuals overweight low probability events; that is, when the probability is non-zero but is low enough that evasion is the optimal strategy, the compliance far cxcccds the level predicted by expected utility
level of theory.
However, behavior is somewhat more complicated. For example, there is cvidcncc that individuals do not always exhibit ovcrwcighting or extreme risk aversion.
since
thcrc
is
still
some
compliuncc
when
the
probability
of
detection is zero and thcrc is still some evasion when individuals face a high enough probability to make full compliance the optimal strategy. The results also indicate that compliance behavior does not stem from a bclicf by subjects that evasion is wrong. Some cxpcrimcnts arc run twice. once with neutral terminology that makes no mention of taxes or evasion and instcnd treats the cxpcrimcnt simply as a risky decision, and once with instructions that clearly place the experiment in the context of tax evasion. Both treatments yield identical results. Finally, the results suggest that some individuals pay taxes bccausc they recognize that payment is necessary to receive government goods. An increase in the payoff that individuals rcccive from a given tax payment increases compliance, and compliance is positive and stable over time cvcn when the probability of detection is zero. Section 2 discusses the design of the expcrimcnts that examine the roles of overweighting and public goods in the compliance decision, and section 3 reports the results from the experiments. Summary and conclusions arc in section 4.
2. Experimental The
design
subjects used in the experiments
arc volunteers
drawn
from
undcr-
J. Alm et al.. Why do people pay taxes.7
graduate
classes at the University
to participate
of Colorado
only once in the experiment.’
3
at Boulder.
and are allowed
At the beginning
of a round.
each of the eight subjects is given one of eight incomes between SO.25 and 52.00 in SO.25 increments,
randomly
chosen by computer.
The subject must
decide how much income to report, and must pay taxes on all reported income at the rate of 40 percent. The subject pays no taxes on unreported income: however, the subject is told that there is some probability that his or her underreporting will be detected by an audit, at which point he or she must pay a penalty equal to 15 times all unpaid taxes.’ An audit is determined by the draw of a chip from a bag that contains a total of 100 red and white chips. If a red chip is drawn, an audit of all subjects occurs; if a white chip is drawn, no audit occurs. Three different levels of red and white chips are used in the experiments. After taxes arc paid and penalties if any are assessed, the total taxes paid by all subjects arc summed to give the ‘group tax fund’, increased by some multiple (or the ‘group surplus multiplier’) to reflect the consumers’ surplus that individuals
dcrivc from povcrnmcnt
provision of a public good. and then
divided equally among the subjects. Three different group surplus multipliers on the group tax fund arc used. The net balance for each subject is calculated (original income less taxes less pcnaltics plus share of the multiplied
group
tax fund).
A new round
then begins, with
the subject’s
balance carried over from the previous round. Subjects arc not allowed to communicate with one another during the cxpcrimcnt. At the completion of the cxpcrimcnt, the subject keeps all the money that hc or she has accumulated; each is guaranteed earnings arc typically botwccn conducted University
a minimum of $5.00 for participating, $ I5.00 and $25.00. The cxpcrimcnts
and arc
in the Laboratory for Economics and Psychology (LEAP) at the of Colorado. AII cntrics arc made and rccordcd on computer
terminals.
and
computer.
The cxpcrimcnt
all
calculations
arc
typically
pcrformcd
by
the
LEAP
MicroVAX
lasts less than one hour.
Thcrc arc six basic trcatmcnts, with ;I different set of subjects each time. Three sets of eight subjects face each of three different probabilities of audit during the experiment: 0 percent, 2 pcrccnt. and IO percent. The order in
“The instructions given IO subjects arc awil;~hlc upon rcquert. ‘A penalty multiphrr of IS times unpaid taxes may seem quite large. since actwl pcnaltics for incoms 1x1 fraud arc currently 75 percent of unpaid I~XL’S plus the unpaid taxes. However, it is important IO rccognirc that the di>covcry of fraud in one yrar Icclds IO Internal Rcvenuc Service (IRS) invcstigafion of potential fraud in previous years. The lncomc Tax Code (Section 6501 (C)) specilics that taxes 2nd penalties may he asscssrd al any time for fraud; that is, the IRS csn cxtcnd its investigation any numhcr of years in the ptls~ when it disrovcrs fraud. If. for example. the IRS cxtendcd its investigation for six years into the pss~.then the cfkctivr penalty multiplier is 10.5 (or 6x 1.75). When intcrcst penalties and. more significantly. legal costs arc also conridcrrd. a pentllty multiplwr of I5 does MI scum unreasonable. It also capture the type of catastrophtc loss that dctectwn of evasion okn brings.
‘6
3. Aim er al.. Why do Table Experimental
peoplepay taxrs? I design.’
Rounds Session
l-15
16-30
3135
lb
p=o
p = 0.02 p=O.lO
p=O.lO
m=O m=6 m=?
m=6 m=?
?b
p =
0.01
5
p=O.lO
‘4 5
m=2
6 -
m=O m=6
p=o
m=2 p=o p = 0.02 > p = 0.02
m=O >
‘In all sessions. the tax rate is 0.40. the penally rate is IS. and the individual’s share of the group fund is 1 R. %zssions 1. ? and 3 are run twice. once with and with loaded neutral once inslructions mstructions.
which the subjects fact those probabilities
is varied across sessions.
In the
first session the order is 0, 7, and IO pcrccnt; in the second session the order is 2. IO, and 0 pcrccnt; the order is IO, 0. and 2 pcrccnt in the third session. All subjects fact each probability for I5 rounds; they arc not told the number of rounds, although they arc told that the number of rounds is prcdctcrmined. The group surplus multiplier equals ?. in all of thcsc trcatmcnts. Three sets of tight
subjects also fact each of thrco diffcrcnt
lcvcls of the group
surplus multiplier. The lcvcls arc 0, 3, and 6. As with the probability, the order in which the subjects fact thcsc multipliers is varied across ssssions, and all subjects fact each multiplier for 15 rounds. The probability of dctcction equals 2 pcrccnt in itll of thcsc latter cxpcriments. The cxpcrimcntal design is summarized in table I. This cxpcrimcntal design is diffcrcnt in several rcspccts from previous cxpcrimcnts in tax compliance. “I Previous work has not always used values for the various policy parameters that approximate actual real-world values. In addition, some acccptcd proccduros of the cxpcrimcntal paradigm have not always been followed. Many of the results have not been verified by rcpcatcd rxpcrimcnts. Of perhaps more importance, previous work may have inadequately induced subject preferences because the instructions given to the subjects have placed the experiment squarely in the context of tax evasion; that is. the terminology used in all previous work may have provided an undcsirablc context to the experiments, and so the decision of the subjects may have reflected the values that they associate with such terms as ‘tax compliance’ or ‘tax evasion’, rather than the rewards or pcnaltics that ‘%e. for example. l.‘rlcdland (lYlc2). Spwx
Fricdland. Mailal and Rulenherg (lY7X). Spicer and Becker and ticro (lYN5). and Becker. Buchner and Sleeking (19X7).
(1980.
J. Alm er al.. l4’h.v do people pay tares?
they faced in the experiment in
the
compliance
per se. To explore
decision,
two
treatments
27
the role of such terminology are
examined,
one
that
uses
neutral Finally,
terminology and one that uses tax. or ‘loaded’. terminology.” most previous experimental work on tax evasion has not considered
the role
that
government
provision
of public
goods
plays
in tax compliance;
that is, individuals may voluntarily pay taxes to provide for public goods, even if there is no penalty on the failure to pay. because they recognize that they will recognize
receive something for their tax payments.” The experiments here that tax compliance may be affected by this exchange relationship
between the taxpayer and the government. Note that the optimal single-period strategy
for each subject
determined
maximize
implied
when by
the
expected
individual’s utility
goal
theory
in
is to the
special
can be easily
expected
case of
value,
as
a risk-neutral
individual who takes the actions of others as given (Cournot-Nash behavior). The expected value, Er! from the choice of how much income to report is
EV=f-tD+,ns(G+tD)-pJ‘[t(f-D)],
(1)
whcrc I is the individual’s tixcd income, D is dcclarcd income, G is taxes paid by all other group members. t is the tax rate on declared income, /’ is the tine rate on unpaid
taxes, p is the probability
of detection,
111is the group
surplus multiplier. and s is the individual’s share of the group tax fund. Maximization of cq. (I) by the choice of dcclarcd income f1 indicates that the individual will optimally report all income if
pj’ +
while When
the
IfIS
>
I,
individual
the group
(2
will surplus
report multiplier
zero
income equals
if the inequality
2 (and
the share
is reversed. of the public
good is 0.125), inequality (2) suggests that the dominant strategy for riskneutral individuals is to report zero income for the experiments in which the probability of detection is 0 and 2 percent, and to report all income when the probability is IO percent. More generally, the critical (or ‘cutoff’) level of the probability is 0.05 (=[ I-2 x O.lZS]/lS). However, if overweighting of low probabilities occurs, or if individuals bccomc extraordinarily risk averse at low probabilities, then there will be some compliance at 9 percent prob“The issue of loaded versus neu~rA instructions is discussed in more d&l b&w. “An exception is Rcckrr. Ruchner and !&eking (19X7). who examine the role of tmnsfer payments on compliancr.
Table 2 Average
groupcompliance
rate.
Probabihty
of audit (m = 2)
Treatment
p=o
p = 0.02
p=O.lO
XIesn, sessions I. 2. 3 Neutral instructions Loaded instructlons
0.200 0.189
0.503 0.522
0.675 0.672
Group
surplus
multiplier
Ip = 0.02) Mean. sessions 4. 5. 6
ability.
m=O
m=Z
m=6
0.435
0.537
0.592
even though it is less than the critical
probability.
Similarly.
probability of detection is 2 percent (and s = 0. IX), risk-neutral who behave according to the expected utility model should income for the treatments
when the individuals report zero
in which VI equals 0 and 3, and should
income when IPI equals 6.” relationship, then there will
report all
However, if subjects recognize the exchange bc some compliance at the lower multiplier
values.
3. Expcrirnental 3.1.
I’rohhility
The results
results
fj’mtfif for the variations
in the probability
of audit arc summarized
in
table 3. which gives the avcragc of the group compliance rates at each of the probnbilitics for the three groups. The average group compliance rate is calculated by dividing total reported income of all group members by total group income. Consider each of the three theory, the single-period
probabilities.
dominant
According
to expected utility
strategy for a risk-neutral
individual
is to
report zero income when the probability of detection is less than 5 percent. However, there is clearly substantial compliance at 2 percent probability. Compliance at p=O.O2 is on average 50.3 percent; the amount of compliance by group varies little, from 45.3 percent for group 3 to 48.1 percent for group I to 57.5 percent for group 2. Although expected utility theory is unable to explain this result, it is consistent with the overweighting of low probabilities that is suggested by Kahneman and Tversky (1979) or the extreme aversion to risk at low probabilities that is suggested by ivlachina (1983). As discussed below, compliance may also be motivated by the presence of the public good. “The
CUIOIT vaiuc for m is S.h( = [ I -0.02
x ISJO. 125).
J. Ah
er al.. Why do people
pay taxes?
In particular, coupling an enforcement mechanism may help overcome the free-rider problem. Even at p=O expected although Expected when the
there
is substantially
with
compliance
voluntary than
provision
is predicted
by
utility theory. The average group compliance is 20.0 percent. there is some variation across the three groups (5.3 to 35.8 percent). utility theory predicts that there will be zero reporting of income probability of detection is zero. This prediction is not observed,
due to the presence of the public be explained by overweighting detection
more
29
good. It is also clear that this result cannot or risk aversion, since the probability of
is zero.
Note, however, that compliance is actually less than that predicted by inequality (2) when p=O.l. When the probability is 0.1. the expected return to evasion
becomes
negative.
and
fully comply. However, the avcragc As with p=O. this behavior cannot
inequality
(2) predicts
that
subjects
will
group compliance is only 67.5 percent. be explained by overweighting or risk
aversion. Instead, subjects now appear to be risk-seeking, perhaps because of the guaranteed payment of $5.00. Also, some subjects may dismiss the likelihood of an audit bccausc of the relatively low level of the probability, even though it exceeds the critical level, and some subjects ride due to the prcscncc of the public good. The
rate
of compliance
rises in a non-linear
way
as the
may
try
to free
probability
of
detection increases; that efforts, but this payoff
is. tax rcvenucs increase with grcatcr enforcement dcclincs as the probability incrcascs. At p=O, compliance is 20.0 pcrccnt; the compliance rate incrcascs significantly to 50.2 Thcsc pcrccnt at p = 0.02, and then rises but only to 67.5 percent at p=O.l. differcnccs arc highly statistically significant.14
‘*Statistical ;mdysis of the diffcrencc in mc;ms rcquircs that the observations be normal and independent. Scvcral alkrnativc approxhcs arc followed to gener:lle average complisncc rates that satisfy thcsc requircmcnts. In the lirst approxh. Ihc round is trc:lted as the unit of observation. The average compliance raft for a given round is cdcula~cd by averaging for each round the compliance rats across all right subjects in all three replications of a given probability; this procedure generates 45 IOI~I obscrvdtons. or one for each of the fifteen rounds fur each ol the three probabilities. The sample I~SI st;ltistic for the difTercnce between the average compliance rates JI p=O and p=O.O2 is 16.56. and is 8.60 for rhc di!Tcrcncc bctwecn the average compliance rdcs ;II p =0.02 and p = 0. I; the critical value of the r-statistic is 2.47 for a one-&led ICSI 31 the 0.01 significance level with 28 degrees of freedom. In the second and more conservative approach, the group is treated as the unit of analysis. Here the average compliance rate IS calcula~cd by averaging across all right subjects und all liken rounds in a given group for each probabdity level; this approach generates 9 total observations, or one fur each of the three groups at each of the three problrbiliries. Bccausc there may be non-independence induced by having the same subjects a~ each of the three probabilities. difkrencc scores arc then calcula~cd, so that there is only one dirercncr for each group. For example, the sample test slarisuc for the dillcrcncc between the average compliance rates 31 p =O and p =0.02 is computed by first calculaling for each group the difTercncc between rhc compliance rates DI p=O and p =O.OZ. and then using these three differences IO form the sample test statistic; the resulting I~SI statistic is 5.69. The ICSI statistic for p=O.O2 versus p=O.l equals 4.1 I. Both difkrenccs arc highly significant.
J. Ah
30
Fig.
er al.. Why do
peoplepay tars”
I gives a more dctailcd picture of the avcragc amount of compliance
by round for the three probnbilitics.
When
the probability
of dctcction is 0,
thcrc is substantial compliance and the amount of compliance dots not decay as the cxpcrimcnt proceeds. I5 This . trcntment corresponds to the voluntary
provision
of public good cxpcrimcnts - there is no penalty on non-
payment of taxcs - so that the results hcrc may bc compared with those from the public good literature. In particular, the results contrast with those of Isaac, McCuc and Plott
(19X5). in which they find funding
lcvcls for the
public good that arc near zero and that decay with rcpcatcd rounds. Here there is substantial compliance that dots not on avcragc fall in later rounds. Fig.
I also shows compliance by round when the probability
of dctcction
is 0.02. Although the dominant stratcpy from cxpcctcd utility theory is to evade. the average group compliance rate is 50.3 percent, and this does not vary much by round. On the other hand, compliance is lower than that predicted by cxpcctcd utility theory when p=O.l. Fig. L clearly shows that the level of compliance increases with the probability of dctcction. It also demonstrates that the predictions of a riskneutral version of cxpectcd utility theory arc not vorificd: thcrc is grcatcr compliance at low probabilities (p=O and p=O.O2) and less compliance at Hidden within fig. 2 is some individual variation in compliance across “Thcrc is. howcvcr. romc variation xross groups. In groups widely. Appurcntly some suhjccts cqxrimcnkd with tar payments follow: when others dd not follow. maws Ml IO zero.
I
and 3. compliance tluc~ua~cs in the hop Ihal others would
1.
Aim
et al.. Why
do people pay taxes?
31
60
50
40
30
20
10
0 0
0.1
0.2
0.3
Fraction
0.4
0.5
of
0.6
Income
0.7
0.6
0.9
1
Declared
Fig. 2
high probabilities (p=O.I) way in which individuals
than is predicted by cxpcctcd utility theory. The actually weight the probability of an uncertain
event is apparently not the way that is assumed under expected utility t hcory. It is also of some intcrcst to cxamine the individual data. Fig. 3 presents the frcqucncy distribution of the individual compliance rates for the three probability trcatmcnts.“’ Thcrc is much cvidcncc of all-or-none behavior, as would result from any linear (or risk-neutral) individual. Overall, 67 percent of the individual Howcvcr, this varies with the probability
payoff function for the decisions arc all-or-none.
of detection. When p=O. 7X pcrccnt
arc all-or-none; for p=O.O2 this drops to 64 pcrccnt. and it drops still further to 61 pcrccnt for p=O.l. Recall, however, that (risk-neutral)
cxpcctcd utility
theory predicts that the
cut-off lcvcl for the probability of detection is 0.05: when ~~0.05, compliance should be 0, while compliance should be complete when p>O.O5. These predictions are complctcly rejcctcd by the results. It therefore appears that individuals are largely risk neutral and rationally select and follow a cutoff rule. However, many do not use expcctcd utility theory in the selection of that cutoff value. rounds. A subject apparently may try different strategies in the compliance game in nn attempt. for example, to induce others in the group to comply. Recall that the subjects know the size of the group fund at the end of each lbFor each Irwtment lhcrr arc 360 observations. or three replications timcs right subjects times IS rounds. The individual compliance rate for any round equals declared income divided by true income.
J. Ah et al., Why do people
32
pay tares.”
“OI
0.9 J
06-
(4
0.1 -
mr6
1
0.0 1 0
2
4
6
6
10
12
14
5
Round Fig. 3
round, so they can dctcrmins decision
to report
more
whcthcr other group mcmbcrs respond to their
income (and they ciln
infer
whcthcr
others
arc
complying or cheating). Thcrc is in fact a positive and significant correlation bctwccn each individual’s compliance rate in ;I given round and the amount of the public good rcccivcd in the previous round.” Eventually. howcvcr, nearly all subjects scttlc into ;I stable strategy. and their compliance dots not fluctuate. Subjects also gcncrally bchavc consistently
across the three diffcr-
cnt levels of probability. Thcrc arc virtually no instances in which ;I subject complies at p = 0 or p = 0.03 and cvadcs at p = 0. I, or vice versa.
The results for the group surplus multiplier arc summarized in table 2 and in figs. 3 and 4. Recall that under expected utility theory the sin&period dominant strategy for ;L risk-neutral individual is to cvadc fully when the multiplier equals 0 and 2 and to comply fully when IPI = 6. These predictions “This rcsuh c‘onfr;rsfs somewhat with that of Spicer and Hero (I9XSj. who found in their experiments Ihat an individual’s compliance did not depend upon his or her pcrcep(ion of the comphancc behavior of others. However. in their experiments subjects dtd not know how other mcmhcrs of rhcir group actually hchaved. since (heir perceptions were had upon drcuptivr informntion provided by the experimenters ahoul average group compliance rates In cxpcrimcnrs that were not m &I run. Also. suhjccls in their cxpcrimcnts were not ahlc IO AXI the behavior of other group members by their own compliance decisions, since there was no group tax fund and (hew was no interaction among the group mcmhers.
J. Aim et (11..Why do people
0
0.2
0.I
0.3
Fraction
0.4
of
0.5
pay taxes?
0.6
Income
0.7
33
0.6
0.9
1
Declared
Fig. 4
arc not supported
by the results.
Compliance
fitlls is 0 and 2, ,md .
the multiplier
below
signiticantly
full
cxcceds zero
compliance
when
when
the multiplier
is 6. The
trcatmont
cxpcrimcnts, substantial rate
in
since
compliance
cqual
to 43.5
dctcction
;md
dctcction
(p=O.O2).
cxpcctcd
utility
higher is
avcragc
grcatcr.
riding. various
further.
possibly
The
of 53.7
under
;Lrc identical. but
only
of
provision
carlicr
tax
is motivated
ovcrwcight which pcrccnt),
enforccmcnt, mechanism
percent
the earlier
low
to 59.2
percent.
dismissal
m=2
level
Thcrc by fear
probability
by
an
cvcn
to taxes
overweighting
of
low
to overcome
treatment
of of
predicted
gcncratcs
helps
is
compliance
since the payoff
is not statistically
probability
increase
group solely
the
cxcccd the zero in
compliance
payments.
hcrc
An
due to risk-seeking.
most
the avcragc
rate (53.7
combination
their
with
will
trcatmcnt
to
for
individuals
compliance
compliance percent’
nothing
Compliance If
compliance
the
that (50.3
corresponds
trc:ttmcnt,
3 voluntary
paramctcrs
compliance rr1=6,
then
theory.
and
Note
in this
psrccnt.
group
m=O rcccivc
punishment.
Again.
probabilities, complinncc
which
subjects
different
frccfrom
in which
the
in the multiplier
to 6 incrcascs
There
compliance
is not
of the (low)
full
probability
;Lt
of audit,
or free-riding.“’ ‘“As with the probaility sessions. IWO alternative approaches are used to analyze the average compliance ralrs (see footnote 14). When the round is the unit of andysis. so that there are 45 IOI:I~ observations. rhere arc signilicanl dillcrencrs between the average compliance rates ~1 m =O and m = 2 (I-slalistic = 5.74). and al m = 2 dnd m = 6 (f-ctaGstic = 2.79). When the group is kated
These
results
demonstrate
that
compliance
increases
with
the
group
surplus multiplier. and suggest that government can increase compliance by providing goods that their citizens prefer more. by providing these goods in a more efficient
manner,
or by more effectively
emphasizing
that
taxes are
necessary for receipt of government services. However, although compliance increases with m, the increase is non-linear. As with the probability of detection, there appear to be limits
on how much governments
can affect
compliance by increasing the individual payoff to tax payments. Compliance by round for the three levels of the multiplier is shown in fig. 2. There is substantial variation in the average group compliance rate, especially for m = 0 and VI = 6. However. this variability does not exhibit any trend: that is, there is no systematic tendency for compliance to rise or to fall as the experiment
proceeds. More importantly.
fig. 3 demonstrates
again that
with few exceptions compliance is greater when the group surplus multiplier is greater. Individuals pay more in taxes when they receive more for their tax payments. The frcquoncy distribution of individual compliance rates is shown in fig. 4. As with fig. 2. the compliance behavior tends to be all-or-none. with 60 pcrccnt
of
all
decisions
in
these
categories.
somcwhat wcakcr than in the probability
although
trcatmcnts.
this
tendency
is
Fig. 4 also shows that a
risk-neutral version of expected utility theory is not supported by the results. Again, most individuals follow a cutofT rule in their compliance behavior, but their behavior suggests that they do not use cxpcctcd utility theory in the dctcrmination of the cutoff value. Individual subjects also bchavc consistently across the throc group surplus multipliers, cvmpliancc when the multiplier incroascs.
increasing (or not dccrcasing) their
As discussed
carlicr. all previous cxpcrimcntal work on tax evasion has instructions that make it clear to subjects that they are participating in a tax compliance game. Unfortunately, use of such loaded instructions may used
lead to unpredictable results. since subjects may respond to the values they associate with the loaded terms rather than to the incentives in the experiment itsclc that is, loaded instructions may lead to context effects that can inllucncc the results in unpredictable ways [Kahneman and Tvcrsky (1979). Machina (1987)]. Concern with framing cfTects has led most expcrimcntalists to USC it neutral terminology, one that masks the context of the experiment and that gives the experimenter more control over the laboratory setting. However. thcrc are few studies in experimental economics that have
J.
Aim
et ul.. W’hy do people
directly examined whether results instructions: This
pup faxes.?
35
are affected by the use of loaded or neutral
there are no evasion experiments
that have examined this issue.
section looks at this issue by comparing two treatments (see table I). In
the additional treatment described here. the instructions
include loaded terms
like taxes. audit, reported income. and penalty; in the base treatment. a neutral terminology was used (payment. check, disclosed money. shortfall). In experimental instructions, context effects might occur because the use of
loaded
words and the inclusion
invoke different ‘mental scripts’.
of irrelevant material may lead subjects to which enable the subject to till in missing
information in the instructions but which also may unpredictably influence subject choices. Of course. the more explicit and complete the instructions. even in the presence of loaded terms, the less will subjects have to rely on scripts to fill in missing information. In this case it seems likely that there should be little difference between loaded and neutral instructions. This
reasoning
information
suggests
on the situation
that if subjects
are given complete and precise
they face in the laboratory
- as they are in the
experiments here - then scripts should not bc needed to help subjects till in missing context. Since the context is already complete, the USC of potentially loaded words such as tax. audit, or penalty should
have no impact on the
behavior of subjects relative to a treatment that does not WC such words. Note, howcvcr. that if true uncertainty is present in an experiment (say, prohahilities arc unknown), loaded words may call up scripts that suggcsl the probability Icvcl and so affect choices. The results arc summarized in table 2, which gives the average group compliance
rate across
trcatmcnts.
for
each of the three
probabilities.“’
Trcatmcnts using loaded and neutral instructions give results virtually identical. Dcbricfing of subjccls in the neutral terminology
that arc treatment
also suggcstcd. somewhat surprisingly, that Ihey did not realize that they had participated in a ‘tax’ cxpcrimcnt. Thus, although the conlcxt apparently dill&s
for subjects in the two trcatmcnts, subjects arc not forced to rely upon
their own scripts (i.e. real-world knowlcdgc of the tax system) to complete the context because in both trcalmcnts they are given identical and full information on the parameters relevant to their choices, including probabilitics of audit. Consequently, their behavior is unaffcctod by the nature of the instructions. This result implies that previous compliance experiments may not have been substantially affected by their use of loaded terms. at Ieast if they provided complctc information on the situation facing subjects.
4. Conclusions Why
do people pay taxes
when they
have an opportunity,
even an
incentive.
to evade?
compliance weight with their taxes
occurs
the low
The experimental because
probability
some
results
of audit
that
than
a simple there
overweighting
application
they
or
to extreme
risk
does not behavior Finally,
occur
from
a belief
suggest
oversensitive
that
to
in fact face. When
or
combined
that
utility
theory
compliance
aversion,
since
is not
there
would
suggest.
always
is some
due to
compliance
and there is some evasion when the is negative. Furthermore, compliance
by subjects
that
evasion
is wrong,
since their
is unchanged by the use of either loaded or neutral instructions. the results suggest that compliance occurs because some individuals
the public
goods
that
their
amount that individuals receive compliance rate, and individuals
tax
payments
from a given pay something
finance.
An increase
in the
tax payment increases their in taxes to receive govern-
mcnt services even when there is no chance of detection and punishment. In short. individuals exhibit a remarkable diversity in behavior. somctimcs appear to ovcrwcight low probabilities. bc risk-seeking, they arc on occasion coopcrativc, free-riders. Whcthcr any theory of compliance such behavior is unknown at present. However, theory
tax over-
individuals do not behave as if Rather, they often pay more in
of expected
is also some evidence
when there is no chance of detection expected value of the evasion gamble
value
are
the high penalty on detected evasion, preferences are linear in probabilities.
However.
in this paper
individuals
is nccdod. one can then dual with
or arc dealt
with
unsatisfactorily
can bc dcvclopcd to explain it is apparent that some new
those factors
by cxpcctcd
They
they sometimes appear to and at other times they are
utility
that arc either
ignored
lhcory.
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people
pay taxes?
37
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38
J.
Aim
et
al..
U’hy
do
people
puy
roes?
Spicer. Michael W. and Lee Becker. 19X0. Fiscal inequity and tax evasion: approach. Nntlonul Trir Journal 33. no. 2. 171-175. Spicer, Mwhuel W. and Rodney E. Hero. IYL(S. Tax evwon and heuristics. Economics 26. 263-267. Taylor. 51.. 1976. Anarchy and Cooperation (John Wdey and Sons. Fl;ew York. Yitzhahi. Sholomo. 1974. A note on income tax evasion: A theoretical analysis. Econamlcs 3._‘01 -‘O’. __
An experimental Journal NY). Journal
of Public
of Public
