48(1) 23–40, January 2011 0042-0980 Print1360-063X Online.docx

48(1) 23–40, January 2011
0042-0980 Print/1360-063X Online
© 2011 Urban Studies Journal Limited
DOI: 10.1177/0042098009360688
Stef Adriaenssens and Jef Hendrickx are in the HUB—
University College Brussels, Stormstraat 2,
Brussels, 1000, Belgium. E-mail: [email protected] and
[email protected]
Street-level Informal Economic
Activities: Estimating the Yield of
Begging in Brussels
Stef Adriaenssens and Jef Hendrickx
[Paper first received, September 2008; in final form, October
2009]
Abstract
This article develops and applies a method to estimate the
revenues of beggars in
Brussels. This is relevant for three reasons. First, in the
literature on the informal
economy, we lack reliable empirical knowledge of informal
street-level activities like
begging, substantiating the expectation that beggars’ income
will be low. Secondly,
popular representation of beggars often depicts them as criminal
and wealthy.
Finally, recent legislation builds on the idea of criminal

organisations behind beggars.
Building on an analysis of existing attempts to measure
beggars’ income, we aim for
a triangulation with data from three different sources:
observation, self-reports and
quasi-experimental observations. This triangulation allows for
more reliable and valid
conclusions. Hypotheses based upon popular images and the
criminalisation of begging
are dismissed. The evidence does support the hypothesis based
upon the literature on
informal activities.
aspects of their lives that appeal to the public’s
imagination.
Our starting-point is that a theory of action
is valid if it is able to reconstruct the reasons of
the actor. That’s where most popular theories
of begging fail. Many everyday judgements
about begging build upon assumptions
referring to the ‘traditions’ of certain ethnic
groups, detrimental effects on the safety feel-
ings of the public and so forth. Nevertheless,
both the public and policy-makers seem to be
1. Problem and Hypotheses
In many western European cities, begging is
receiving growing attention from the public,
policy-makers and social scientists (case stud-
ies in Donovan, 2008; Fitzpatrick and Jones,
2005; Mitchell, 2005). Thereby, the wildest
claims about the nature, the motivations and
the income of beggars are made. This paper
attempts to elucidate the earnings of people

who beg. If one bears in mind that there is a
huge gap between the definite assertions and
the lack of reliable evidence, this is one of the
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24 STEF ADRIAENSSENS AND JEF HENDRICKX
attached to this point of view, as expressed in
everyday discourse as much as in discussions
in political bodies. Related with this, a large
proportion of the public seems to be con-
vinced that begging is connected with deceit,
fraud and organised crime.
What then are the reasons why people beg?
A consistent starting-point for this question
is that begging serves the same manifest
function working in general has: to yield an
income. To be clear: this starting-point does
not preclude the existence of deceit, fraud or
organised crime in begging; it just situates
begging among the meaningful and purposive
actions of real people. Whether begging as
an income-generating activity is chosen or
imposed, is part of the problem investigated
in this contribution. The basic starting-point,
however, is that the dominant motivation of
begging is acquiring means.
We define begging as informal work in a
public space, consisting of a receiver asking for
a non-reciprocated gift. Begging is informal
work in the sense that it is part of

those economic activities that circumvent the
costs and are excluded from the benefits and
rights ... of formal society (Feige, 1990, p. 992).
In the case of begging, this implies that it
takes place within the public space. Like many
other street-level informal activities (Dean
and Gale, 1999), it has a discordant relation-
ship to the formal and mainstream users of
this space (other examples in Donovan, 2008;
Venkatesh, 2006). The informal character of
begging mainly refers to the second part of
Feige’s definition: the work of begging nor-
mally does not entitle people to formal rights
and benefits. Their work does not benefit
beggars with legal protection or access to, for
example, health insurance, as normally results
from formal jobs.
In some countries, regions or cities, beg-
ging is explicitly prohibited—for example,
in England and Wales (Fitzpatrick and Jones,
2005). In other places, begging is allowed and
sometimes the right to beg is even warranted,
as is the case in Belgium and in the US
(Hershkoff and Cohen, 1991). In Belgium,
the legislator abolished the penalisation of
begging and vagrancy in 1994 (Jamar and
Herbots, 2006) and since then courts have
acknowledged the right to beg (Fierens, 2004).
Even so, begging continues to be an informal
activity because of its insecure and unregu-
lated nature. In fiscal and social security
matters, for example, beggars find themselves

in a legal no-man’s-land. They derive no
rights in terms of social benefits from their
activities. Furthermore, security forces often
actively suppress begging activities in reality.
This has a lot to do with the fact that beggars
are users of a fiercely competed public space.
Within the informal economy, begging is part
of the sub-type of so-called survival activities,
denoting that people are immersed in off-the-
books transactions because of the destitute
economic position they find themselves in
(Portes and Haller, 2005).
In this article, we present and apply a method
in order to estimate the revenues of people
begging. There are three good grounds legiti-
mating such an endeavour
(1) Uncovering the earnings from begging
improves our understanding of the
underground economy and, more specifi-
cally, of survival activities.
(2) Common sense about begging is caught in
a web of unsubstantiated presuppositions.
(3) Recent legislation in Western countries is
based on strong assumptions about the
nature of begging. Some of them relate to
the income of beggars and can be tested
with the help of these estimates.
It is important to stress that the first ground
leads to expectations and hypotheses contra-
dictory to grounds 2 and 3. We elaborate on
all three grounds consecutively.

The first inspiration for this research lies
in a general interest in the income from
informal activities. It is important to measure
THE YIELD OF BEGGING IN BRUSSELS 25
the living standard of people thrown back
on the underground economy for their
survival. ‘Underground economy’ is the
broader concept, denoting all off-the-books
transactions and institutions, including both
the informal and the illegal economy (Feige,
1990). The former refers to licit activities that
take place off the books; ‘illegal’ activities
are explicitly forbidden by law. Begging may
both be informal as well as illegal, depend-
ing on a country’s legislation. In Belgium, it
is informal because the legislator has stated
that begging cannot be prohibited.
Under the surface of the huge diversity in
approaches of the underground economy,
a consensus seems to exist that informal
economies are strongly segmented (Pahl,
1987). Informal activities therefore take place
within two distinct markets: a top end of
relatively affluent workers, often simultane-
ously employed in formal jobs, and a bot-
tom end with informal work performed by
marginalised groups (Slack, 2007; Williams,
2004). For the latter, the main determinant of
informal activity is that their access to formal
activities is blocked and they lack alternative

income-generating opportunities (van Eck
and Kazemier, 1988; Williams and Windebank,
2002). This subsistence motive is conceptu-
alised as an informal economy of survival (for
example, Portes et al., 1989) and correlates
with low-quality occupations, low produc-
tivity and income (Rosser et al., 2000; Trejos
Solorzano and Del Cid, 2003). The statement
that poverty and the corresponding lack of
opportunities lead to a higher supply of infor-
mal work is corroborated by data at a national
level—for example, in eastern Europe, where
the decline of national income in the 1990’s
went hand-in-hand with the growth of infor-
mal activities (Renooy et al., 2004). Although
most economists studying the informal sector
with macroeconomic comparative material
hardly pay attention to the subsistence motive
(for example, Friedman et al., 2000; Schneider,
2007), they generally do acknowledge the
relevance of national income and the preva-
lence of poverty as a determinant.
In short, the literature on informal work
and begging tends to classify begging as a
survival activity. The overall conclusion
would be that the income from begging is
considerably lower than the income from
formal work. Given the unattractive and
harsh nature of begging (Smith, 2005), one
can assume that it will even be lower than
most other informal activities.
The second ground for estimating the
income from begging has to do with ubiqui-

tous and recurrent everyday judgements of
begging. The representation of people who
beg throughout the centuries is consistently
built upon three associated images (Erskine
and McIntosh, 1999): fraudulent beggars—
for example, using children or shamming dis-
abilities to evoke pity; ‘professional’ impostors
working in an organised criminal network;
and beggars acquiring great wealth. These
three images reappear from the 16th century
on (Geremek, 1980; Woodbridge, 2002). This
second ground gives rise to expectations
contrary to the first inspiration: the income
from begging is comparable with profits from
criminal activities and will be higher if more
indicators of fraud are observable.
Thirdly, there exists a policy rationale for
this research. The second ground refers to
collective mentalities that inspire collective
behaviour, such as state regulation. This has
recently happened in quite a few Western
countries, both in North America (Ellickson,
1996; Hopkins Burke, 2000; Mitchell, 2005)
and in Europe. Similar penal laws were
recently adopted in France1 and Belgium2
criminalising so-called organised begging.
Thereby the explicit parallel is drawn with
organised criminal activities such as pros-
titution and human trafficking. The argu-
mentation for the law assumes that begging
is as rewarding as these criminal activities.
Criminal organisations are also assumed
to employ profit-maximising strategies, for

example, forcing children to accompany adult
beggars, as children supposedly increase gifts
substantially. The explanatory memorandum
of the Belgian enactment3 arguing for the
necessity of the law provides illustrations
This (act) does not have as a goal to criminalize
the offence of begging again, but to punish those
who exploit the begging of others, analogous
to the legislation existing in prostitution (p. 4).
After the example of the exploitation of
prostitution, the exploitation of mendicancy
can be looked upon from the angle of human
trafficking (p. 16).
The law decrees that begging with a minor
is an aggravating circumstance of organised
begging (article 433quater of the penal code).
Article 433ter assumes that the assistance of
children is inspired by the intention to “evoke
pity of the passer-by” thus increasing the
income of the beggar. The close resemblance
between the legislative logic and popular
images should be clear.
Summarising, the motivation to research
the income of beggars is grounded in the
social-scientific line of research on informal
economic activities and in the popular images
concerning begging and beggars, also leading
to formal rule-making. The basic hypothesis
refers to the income of beggars. Literature

on informal work leads to expectations con-
tradicting the popular judgements and law-
making. The former hypothesises that begging
generates a low income. From the latter, we
infer that beggars yield a higher income from
their activities, similar to, for example, human
trafficking or the exploitation of prostitution.
The criminalisation of (the exploitation of )
begging is based on strong assumptions with
little empirical foundation. Therefore, we
build hypotheses that allow us to falsify these
assumptions. As a direct measure of ‘exploita-
tion’ and ‘criminal organisation of begging’
is impossible, we use a detour to falsify the
assumptions underlying recent legislation.
We therefore hypothesise that: begging yields
profits comparable with human trafficking
and prostitution; and, yields are higher if
begging is linked to human trafficking and if
there are indications of fraudulent strategies.
Four hypotheses will be tested with respect
to the exploitation of begging: two referring
to the overall profitability of begging activi-
ties; one referring to the difference between
the profitability of begging for indigenous
persons relative to migrant east European
beggars; and finally one referring to the sur-
plus income by the assumed properties of
exploitation, in particular by begging with
children. The hypotheses are stated as follows
(1) Begging generates an income under or
around the poverty line.

(2) The profitability of begging is comparable
with other criminal activities.
(3) Beggars who have migrated yield a higher
return.
(4) Begging with children yields a higher
return.
The first and the second hypotheses refer to
the discussion as to whether begging is able
to generate high profits. There is a contradic-
tion here between the expectation based on
the social-scientific literature (hypothesis 1)
and the second hypothesis inspired by the
prevailing collective images (as a motivator
for contemporary law-making). Provided
the yields of begging are so low that it hardly
allows beggars to earn an income above the
poverty line, the informal-sector research is
confirmed. If the yields are higher, this may
lay an empirical foundation for the image
about the high profitability of begging. The
confirmation of the second hypothesis would
be consistent with the existence of criminal
organisations behind begging.
The third hypothesis refers to the assump-
tions of recent legislation that there exists a
close connection between human traffick-
ing and ‘organised’ begging. Therefore, one
expects that the yields of beggars who have

migrated are higher in comparison with those
of indigenous beggars. The final hypothesis
tests the assumption in recent Belgian and
French penal laws that children are brought
in with the intent to increase revenues.
Before we build our estimates that allow
us to test these hypotheses, we first give an
overview of previous attempts to measure
earnings from begging, sketch the context and
features of begging in Brussels, and describe
the different sources of data for our estimates.
2. Previous Attempts to Measure
the Income of Beggars
The serious studies of the life of beggars are
often based on qualitative data (for example,
Danczuk, 2000; Fitzpatrick and Kennedy,
2000; Lankenau, 1999; Wardhaugh and Jones,
1999). These studies were helpful to reveal the
experiences and perceptions of people who
beg, but they cannot provide reliable estimates
of their income. Therefore, we concentrate
ourselves on a quantitative research strategy.
Reports of systematised attempts to estimate
the beggars’ income are scarce. Moreover,
the existing approaches have fundamental
weaknesses. Given the concealed nature of the
activities and the hard-to-reach population of
beggars, these shortfalls are partly inevitable.
Notwithstanding, an overview of the existing
methods will be a useful start in order to list
feasible approaches and the shortcomings

to avoid. Roughly speaking, data are either
based on standardised questionnaires or on
observations. Although observations and
self-reports have serious biases, most studies
only use one source of data. We will argue that
a mixed-method approach is to be recom-
mended. An overview of the reviewed studies
is presented in Table 1.
There is one peculiar older illustration of
questionnaire-based self-reports: in 1932–33,
two sociology students conducted a survey
of people who beg in Shanghai (cited in Lu,
1999). Respondents were asked to list their
families’ monthly income at the time of the
interview and from their previous occupa-
tion. Lu’s discussion does not mention the
sampling strategy used. Some contemporary
Table 1. Studies with estimates of beggars’ income
Study Method Sample Yield measured
Jiang and Wu; in Lu Questionnaire Sampling unclear Self-
reported
(1999) Unit: people who beg n = 700 monthly income
in Shangai
(Murdoch (1994) Questionnaire Sampling unclear Self-reported
daily
Unit: people who beg n = 145 income from begging
in central London
Bose and Hwang (2002) Questionnaire Sampling: systematic
Self-reported
Unit: people who beg search of public places income

in Toronto n = 54 Lowest payment for
interview with high
response rate
O’Flaherty (1996) Questionnaire Sampling: systematic Self-
reported
Unit: ‘daytime search at well-known maximum and
streetpeople’ in locations minimum daily
Manhattan n = 209 earnings
Butovskaya et al. (2004) Observation of people Observations of
Number of gifts in
who beg during beggars in Moscow trains 2 minutes.
2 minutes n = 178
studies also provide little information about
the crucial issue of sampling. For instance,
Alison Murdoch’s research report (1994)
only mentions where respondents were inter-
viewed, but remains unclear about the criteria
for their selection.
Others do document the sampling strategy.
Bose and Hwang (2002) researched begging
with the help of a standardised questionnaire
in Toronto. The researchers “located panhan-
dlers by systematically searching major streets
and subway stations” (p. 477). They estimated
the income of beggars through self-reported
hourly, daily and monthly yields. The general
conclusion of this research was that begging is
the main source of the respondents’ income,

but that it brings in rather meagre revenues.
The Toronto study attempted to test the reli-
ability of self-reported income of people who
beg through offering different amounts of
compensation for co-operation in the inter-
view. According to the researchers, the estab-
lishment of the lowest amount with a high
response rate would serve as an indication
of their income. This interesting approach
could hardly be tested because the number of
respondents was rather low (n = 54).
In the same vein, O’Flaherty (1996, p. 82)
systematically interviewed the “daytime street-
people” in New York’s Manhattan by cruising
the well-known locations during several week-
ends. The author does not communicate the
proportion of beggars within the sample, but
he did question the survival strategies, with
begging as one of seven categories. The general
conclusion is consistent with the study by Bose
and Hwang: low earnings for long and hard
work (O’Flaherty, 1996, pp. 84–85).
The basic disadvantage of self-reported
measures obviously has to do with mem-
ory effects and socially desirable answer-
ing. Many studies on people who beg (for
example, Melrose, 1999) and other excluded
groups or hidden populations (Sifaneck and
Neaigus, 2001) report the distrust towards
outsiders. Beggars often confuse interviewers
with officials, fearing that telling the truth
about their income may lead to sanctions. In
our fieldwork, we also noticed that respon-

dents had problems with questions about
their average income, probably due to the
lack of registering of their income; usually
the yields are immediately consumed. These
drawbacks made us decide only to use self-
reported measures for information that can-
not be attained otherwise.
From the observational method, we found
one example: Butovskaya et al. (2004) used it
to compare the amount of gifts received in a
fixed time-span by people who beg in Moscow.
Basically this is an interesting approach that
may be able to overcome some of the weak-
nesses of self-reported income measures.
However, the linear relation between the num-
ber of gifts observed in a fixed time-interval,
on the one hand, and the income of a beggar,
rests on two strong assumptions.
First, it assumes that the alms received have
the same mean value for each (type of) beggar.
The researchers have no data supporting this
assumption and neither do they propound
convincing arguments for this a priori (in fact,
the problem is not addressed). Other research
does indicate that most of the alms received
are rather small, mainly consisting of coins,
literally ‘spare money’ (Adler et al., 2000;
McIntosh and Erskine, 1999). This does not
exclude the possibility that the mean gift var-
ies considerably between beggars. Alms-givers
may give different sums to different types of
beggars, or a certain specialisation of alms-
givers may exist, related to their perceptions
of ‘deserving poor’.

Secondly, one should be aware that the
frequency of observed gifts in a given time-
period is an indicator of productivity, not
of income. The use of productivity as an
indicator of income passes over the probable
differences of working time between beggars.
Summarising, data based on observations
avoid some of the drawbacks of self-reported
data. Observing beggars and their alms gives
access to reliable data on the frequency of gifts,
but information on the working time is lacking.
3. The Context: Poverty and
Begging in Brussels
The Brussels Capital Region is the part of
Belgium with a high concentration of extreme
poverty. The most recent study available esti-
mates the number of homeless people in the
region at 1200 (Réa, 2001).
One important background regulatory fea-
ture is the legal status of begging in Belgium.
Since the start of begging regulation, different
measures have been used: periods of penali-
sation, assistance and institutionalisation
alternated and sometimes even occurred in
the same period (Depreeuw, 1988). In 1891,
the most recent law (until further notice),
prohibiting vagrancy and begging, was pro-

mulgated. It lasted until 1993. By that time,
there was an overall political consensus on the
inhumanity of criminalising people who beg,
leading to the abolition of this criminal law.
What does the begging population look
like in Brussels? The survey we conducted
taught us that the great majority (85.4 per
cent) of Brussels beggars fall into three types:
male indigenous beggars and female Roma
beggars alone or accompanied by children.4
Indigenous beggars are those born in Belgium
or with an official language of the Brussels
capital region as a mother tongue (French
or Dutch). Members of this group are often
homeless and have a history of drug or alco-
hol addiction. This is similar to the profile
of people who beg in Britain, according to
Danczuk’s study (2000).
The background and issues of Roma beg-
gars are fundamentally different. The Roma
in Brussels originate from Romania, the larg-
est Roma population in central and eastern
Europe (Ringold et al., 2003, p. 89). They pre-
dominantly migrated recently, definitely after
the fall of the Iron Curtain and the implosion
of the communist regimes there. Important
push factors are the economic backwardness
of the region in comparison with western
Europe, high unemployment and poverty, in
particular for Roma (UNDP, 2003). Around
three-quarters of the interviewed Roma
indicated that they were unemployed (UNDP,
2003). They also suffer from discrimination

and racial violence, exacerbating the hopeless-
ness of their situation (OSCE, 2000).
4. Methods and Ethical Aspects
In order to estimate the beggars’ income
as precisely as possible, we constructed a
design based on the conclusion that self-
reports and observations have distinct limi-
tations. Therefore, we used both methods,
complemented with a quasi-experimental
version of participant observation. These
three distinct sources correspond to the
different data we need in order to estimate
the income of beggars.
The begging time is assessed through stan-
dardised interviews with beggars in the Brussels
capital region, conducted in the autumn of
2005 and the spring of 2006 (n = 268). Three
typical problems in questioning beggars arose:
the absence of a register, the volatility of beg-
ging and the difficulties of questioning beggars.
First, no register of beggars exists. As earn-
ings are dependent upon traffic, access to the
population of beggars was constructed with
the help of a detour through the places where
people beg. A register of 255 possible begging
locations was constructed with the help of
volunteer reports, police reports and a list
of public marketplaces, subway stations and
supermarkets of the major chains.
A second potential problem was the assumed
short-term variation in the begging popula-

tion. The precarious judicial status of many
people who beg, the possible transience of
migratory beggars and the irregular approach
by the police force all support the assumption
that begging is a volatile phenomenon. The
choice for a register of begging places also
bears the risk that respondents were not beg-
ging at the time the location was observed.
Therefore, each location was visited three
times at different moments of the day and in
the week. Furthermore, the researchers chose
to conduct two waves of interviews: one in the
autumn of 2005, one in the spring of 2006,
preventing our data from being overinflu-
enced by seasonal coincidences. Finally, we
took measures to overcome the inaccessibility
of people who beg. This group is hard to reach
due to general distrust and the linguistic and
ethnic diversity. There was an expectation
of a significant proportion of analphabetic
respondents (afterwards confirmed by the
data). Face-to-face interviews guaranteed
the participation of illiterate respondents.
Linguistic diversity was overcome by a ques-
tionnaire in four languages (French, Dutch,
English and Romanian) and interviewers
mastering these languages. In general, this
proved to be an effective method: 85.8 per cent
of the respondents agreed to be interviewed.
In order to estimate the mean frequency of

gifts, data were collected through observa-
tions of the three types of beggar.5 People
begging were randomly selected in an area
in central Brussels. The observations were
made in crowded places such as the central
station or the Rue Neuve. Observers posi-
tioned themselves at a fair distance from the
beggars, preventing interaction. Because of
the crowded nature of the spaces, this hardly
received attention. The researchers recorded
the exact time of alms collected by beggars
during 60 sessions of 36 hours in total. The
duration of the observed period was quite
uneven, as the researchers had no control over
the beggars or their context. During these ses-
sions, 225 gifts were recorded. The duration of
the observations was divided evenly for each
type of beggar.
The data from this second source were meant
to estimate the mean begging time beggars
of all three types needed to get a gift in kind
or a gift in coins. However, it proved possible
to determine the value of the gifts in kind or
notes through these observations. Therefore,
the income in a given period of begging time
from gifts in kind and notes was estimable on
this source of data alone. As the observation
of real beggars is a more reliable and therefore
superior source of information than data of
test subjects simulating begging, we preferred
to rely on the former as much as possible. The
reason why gifts in kind and in notes are taken
together thus is based on a methodological
rather than an intrinsic communality: both

were measured by observations of beggars.
The third source of data was necessary
in order to estimate the mean value of the
gifts in coins. For the estimate of the value
of gifts in coins, a quasi-experimental use of
observation was set up.6 We are well aware
that the denotation of ‘quasi-experimental use
of observation’ is a rather inelegant formula-
tion. The reference to observation was added
because the design has no causal ambitions
whatsoever. On the other hand, as one element
is actively manipulated—the exposure of the
public to a certain kind of beggar –legitimises
the reference to quasi-experimentation.
Begging activities were simulated in and in
the vicinity of the Rue Neuve, an important
commercial area in central Brussels with
frequent begging activities. Six experimental
subjects engaged in begging activities during
sessions of two hours. Thereby, Roma female
and indigenous male beggars were simulated.
The third type of beggar, female Roma accom-
panied by a child or children, has not been
included in the design for ethical reasons. The
six test subjects consisted of four male and
two female test subjects. They begged during
three sessions of two hours each. For every gift
in coins, the test subjects recorded the value,
the time and some background variables of
the alms-giver with the help of a small hidden
microphone. The test subjects were watched
by an observer, for support and to have a
backup record of the timing of the gift and the
characteristics of the alms-giver. Because they

were mainly a backup for security reasons and
in order not to arouse suspicion, the observers
posted themselves at quite a distance. In total,
149 gifts in coins were recorded during these
sessions, allowing us to estimate mean and
the distribution of the value of alms in coins
for the main types of beggar.
The combination of the data of the second
and the third sources allows us to estimate
the return of begging activities in a given
time-period. This provided us with the
necessary information to measure the mean
and distribution of the frequency and values
of the distinct types of gifts (coins, notes,
in kind), itemised per type of beggar. The
data obtained from the questionnaire are
used to estimate the mean working time our
respondents ‘work’. This allows us to make
the inference from productivity of begging to
estimated income.
Research into informal and underground
phenomena poses difficulties with regard to
measuring and method, but it is also cause
for obvious ethical concerns. This is all the
more the case for a vulnerable group such as
homeless people or people who beg (Melrose,
1999; Williams and Cheal, 2002). Our main
ethical concerns were twofold: to prevent
adverse effects on people who beg and to

avoid insecure situations for the researchers.
The aim not to divert earnings from people
who beg was achieved through two interven-
tions. When interviewing the begging popu-
lation, respondents were offered a payment
of 5 € in exchange for their collaboration
because the interview took working time.
Secondly, the alms received during the quasi-
experimental observations obviously were
diverted from earnings of people begging in
the vicinity of our researchers. Therefore, the
takings were redistributed to people begging
in the direct vicinity of the places where we
begged.
The second ethical concern affects the safety
of the researchers and in particular those imi-
tating beggars. During the sessions, the test sub-
jects were watched all the time by an observer.
This allowed for support in case of problems.
Although the police were informed in advance
of the research, the test subjects behaved like
other people who beg when chased of by the
police or private security companies. In case
someone was arrested, the observers did carry
a letter from the chief of police clarifying the
aim of the begging activities.
5. Estimates
The calculation of the income of begging
in a given time-period is possible with data
measuring the value of the alms and their
frequency. In order to estimate the income

from begging, one also needs information
about the begging time. Evidence for the first
is mainly collected through observation, the
second by the quasi-experimental observation
and, for the final information, we made use
of the results of the survey.
The calculation was complicated because of
the variety of alms beggars receive. Basically
they receive gifts in money, mainly coins and
sometimes notes and in kind. The latter type
consists of a wide variety: cigarettes, food,
soft drinks, and sometimes even utensils. The
income of beggars in a given time-period
t (Y(t)) thus equals the sum of the value of
gifts in coins (YC(t)), in notes (YN(t)) and in
kind (YK(t))
Y(t) = YC(t) + YN(t) + YK(t)
The mean income for every term is the mean
value of the respective gifts multiplied by the
mean frequency of gifts in a time-period t
mY(t) = mC . mNC(t) + mN . mNN(t) + mK . mNK(t)
where, mC, mN and mK denote the mean value of
gifts in coins, in notes and in kind; and mNC(t),
mNN(t) and mNK(t) denote the mean number
of gifts in coins, in notes and in kind in a
time-period t.
These estimates build on observations and
quasi-experimental participant observation.
The income of begging equals the value of
the alms received in a fixed time-period

(for example, per hour) multiplied by the
begging time.
The most recurrent type of gifts consists
of coins (81.8 per cent). We calculated con-
fidence intervals for the mean gift in coins
respectively in kind and in notes (Table 2).
This way it is possible to control for whether
there is a significant difference in the mean
value of gifts between the groups. First, we
check whether the mean value of gifts dif-
fers significantly between the three groups
(Roma alone, Roma with children and indig-
enous beggars). This is done with the help of
ANOVA tests and two sample t-tests. This
is not the case for coin gifts between Roma
alone and indigenous beggars (two sample
t-test p-value = 0.84) or for the mean value in
kind or notes between the three types of beg-
gar (ANOVA-test f = 0.073, p-value = 0.93).
The normal distribution cannot be rejected
on the basis of a Kolmogorov–Smirnov test.
Combining these results, a 95 per cent confi-
dence interval for the mean value of the gift
in coins is estimated [0.66, 0.89]; for the gifts
in kind or notes it is [0.95, 2.03].
Next, we estimate the frequency of gifts,
analysing the interval times between the gifts
(Table 3), modelled by an exponential dis-
tribution.7 A 95 per cent confidence interval
for the mean of an exponential distribution

is calculated (Festinger, 1943)
,
nX nX2 2
, . , .n n
2
2 0 975
2
2 0 025| |
; E
where, X
−
is the sample mean (in minutes) and
c22n,0.025 (respectively c22n,0.975) denotes the 2.5
per cent (respectively 97.5 per cent) percentile
of a chi-squared distribution with 2n degrees
of freedom. The results of these estimates are
shown in Table 3.
To compare the mean interval time of Roma
with child(ren) with Roma alone, we use the
following test-statistic for two independent
exponential distributions
F
X
X
2

1
=
Under the null-hypothesis that the population
mean of the two distributions are equal, F has
an F-distribution with degrees of freedom
2n1 and 2n2. X
−
1 and X
−
2 denote the sample
mean of the first and second sample; n1 and
n2 represent the sample size of the first and
second sample.
There is no significant difference in the
average value of the interval times between
Roma with child(ren) and Roma alone.8 From
the F-test comparing the mean interval time,
we infer a significant difference between the
Roma beggars and the indigenous beggars.
Table 2. Confidence intervals for the value of gifts (in €)
95 per cent confidence interval
for mean
N Mean S.D. Lower bound Upper bound
Gifts in coins
Roma alone 55 0.76 0.69 0.58 0.95
Indigenous 94 0.79 0.72 0.64 0.93

Gifts in kind or notes
Roma with child(ren) 12 1.55 0.35 0.78 2.33
Roma alone 8 1.58 0.61 0.14 3.01
Indigenous 9 1.34 0.51 0.16 2.51
Gifts overall
Gift in coins 194 0.78 0.71 0.66 0.89
Gifts in kind or notes 29 1.49 1.41 0.95 2.03
Sources: quasi-experimental observation (gifts in coins) and
observation of beggars (gifts in kind
and notes).
The p-value is 1.2 × 10−11 for gifts in coins
and 0.034 for gifts in kind or notes. This
allows us to start from confidence intervals
for Roma begging alone or with children on
the one hand and for the indigenous on the
other hand.
The mean income per hour (Table 4)
is a result of the average inter val time
between gifts and the average value of a
gift combined. The confidence interval of
the ratio of two means is calculated with
the help of the method of Fieller (Fieller,
1940; Motulsky, 1995). The confidence
interval for the total income per hour is
measured through a combined estimation
for the income in coins and the income
in kind or notes. The method to calculate

a confidence interval for the sum of two
population means is similar to the formula
for the confidence interval for a difference
between two population means.
Finally, the income per day is estimated
with the help of the survey data of the mean
begging time per day (Table 5). In order to
combine this self-reported working time with
the other data, we start from the assumption
that 90 per cent of the reported begging time
is productive working time; the remaining
Table 3. Interval times (in minutes) for the gifts
for mean
Gifts in coins
Roma alone 38 17.53 16.65 13.06 24.77
Roma overall 76 17.92 18.91 14.49 22.75
Indigenous 109 6.56 7.72 5.49 7.99
Roma alone 8 88.00 61.42 48.81 203.83
Roma overall 21 66.67 62.03 46.70 116.49
Indigenous beggars 21 34.36 31.27 23.36 55.50
Source: observation of beggars.
Table 4. Income (in €) per hour

for mean
Mean S.E. df Lower Bound Upper Bound
Gifts in coins
Roma 2.60 0.356 223 2.01 3.47
Indigenous 7.10 0.863 256 5.61 9.11
Roma 1.34 0.377 48 0.76 2.57
Indigenous 2.61 0.731 48 1.48 4.98
Total income
Roma 3.94 0.583 2.77 5.12
Indigenous 9.71 1.243 7.21 12.21
10 per cent is invested in organisation and
preparation. To find a confidence interval
for the income per day, we use a confidence
interval for a product of two population
means (Wold, 1974).
In order to be able to compare the daily
income of beggars with the poverty line in
Belgium, we estimated the necessary income
per working day in order to avoid poverty.
According to research by the OECD (2004), a
‘typical’ employee in Belgium works 200 days
a year. Therefore, a daily income of 49.32 € is
necessary in order to evade poverty. As beg-
ging is often hampered by rain, the cold or

police actions, there is no proof that the beg-
gars in fact work the same amount of days.
The estimates in Table 5 provide us with
the basis to test the four hypotheses we for-
mulated earlier.
Hypothesis 1: Begging generates an income
under or around the poverty line.
On the basis of the informal work literature,
we expected that begging is a survival activity.
Therefore, the yields should not exceed the
lower revenues of formal work, or even stay
below them. We chose as a basis of compari-
son the poverty line that refers to the overall
income distribution, often applied in the
European Union. A person is poor whenever
his income is lower than 60 per cent of the
median income (Boarini and d’Ercole, 2006;
Ruggeri Laderchi et al., 2003).9 Table 6 indi-
cates that Roma beggars stay far below the
poverty line. The depth of their poverty is
even more serious than illustrated here, as we
based our comparison on the poverty line of
a single-person household. This is a realistic
Table 5. Self-reported average begging time and income per
day
for mean
Self-reported average begging time (in hours)a

Roma alone 40 4.76 2.31 4.02 5.50
Indigenous 45 5.99 3.57 4.92 7.06
Estimated income per day (in €)
Roma 16.26 2.523 11.18 21.33
Indigenous 52.35 8.183 35.90 68.81
a Source: survey.
Table 6. Estimated income of beggars as percentage of income
of prostitution and of the
poverty line
for mean
Mean Lower Bound Upper Bound
Percentage of the minimum income of prostitution
Roma 4.09 2.82 5.37
Indigenous 13.18 9.04 17.33
Percentage of the 60 per cent poverty line
Roma 32.97 22.67 43.25
Indigenous 106.14 72.79 139.52
option for the indigenous beggars. The Roma,
on the other hand, often have young children
to take care of (65.5 per cent of the female
Roma respondents in our survey) and they
usually depend on the begging revenues as

their only income.
The situation of the indigenous beggars
looks somehow different. It is impossible
to rule out that indigenous people who beg
might avoid poverty due to their income
from begging. In addition, a majority of
this latter group (72.3 per cent) enjoys some
welfare benefit in addition to their income
from begging.
Hypothesis 2: The profitability of begging
is comparable with that of other criminal
activities.
A direct verification of this assumption
would require considerable police resources.
An indirect test is possible, however. From
the assumption that criminal entrepreneurs
seek to maximise profit, we expect that the
exploitation of people who beg will yield
considerable gross revenues in order to be
an attractive activity. Therefore, we attempt
to compare the gross revenues of begging
with those of illegal or semi-illegal activities.
After an analysis of the available literature,
it was clear that only few reliable estimates
exist of the revenues of illegal or semi-legal
activities. Moffat and Peters (2004) published
a detailed, recent and reliable estimate of the
gross revenues of prostitution in the UK.
The mean price of an encounter was £55 in
1999 (£60.38 or 87.61 € in 2006 prices); the
mean time was 30 minutes. Prostitutes have
an average of 21 (window prostitution) to
25 (streetwalkers) encounters a week. The

comparison with begging shows a massive
difference, lending no support whatsoever for
the assertion that begging is a serious candi-
date for a criminal entrepreneurial strategy.
On the basis of the Brussels data, there is a
rather strong support for the opposite asser-
tion: gross earnings from begging are so low
that they probably attract little attention from
criminal organisations.
Hypothesis 3: Beggars who are migrants yield
a higher return.
This hypothesis is inspired by the legislator’s
vision that ‘organised begging’ is closely linked
to human trafficking. This assumption is not
supported either. The migrants who beg, pre-
dominantly female Roma, have a consistently
lower productivity than indigenous beggars.
Both in frequency and in mean value of the
alms they receive, Roma come off worse. In
general, they also seem to invest less time in
their begging activity than indigenous beggars.
Hypothesis 4: Begging with children yields a
higher return.
Our estimates do not seem to indicate a sur-
plus value of begging with children. Because
begging with children was not simulated in
our quasi-experimental observations, this
statement is based on begging time and
frequency of gifts. There is no significant
difference in the frequency of gifts between
female Roma beggars with children and Roma

women begging alone; the value of gifts in
kind and in notes is not higher. Finally, the
working time of people who beg with children
is not longer than those working alone.
6. Conclusions and Discussion
First and foremost, it is important to stress
the limited possibilities to generalise this
research. Due to the impressive variety of beg-
ging contexts, and because of the general lack
of knowledge, it is not possible to generalise
the findings of this study straightforwardly
to other places and times. Applying these
conclusions to other cities and contexts there-
fore cannot be done without the necessary
reservations. The relevance of this research
rather is inductive: it provides a consistent and
empirically based starting-point for research
elsewhere.
This paper primarily develops a method to
measure the yields of begging. Basically, the
strategy is built upon a careful assessment of
the available methods in the literature. Two
strategies were found: observation and self-
reports. Self-reports lack reliability because of
their sensitivity to sampling errors, memory
effects, socially desirable answering and non-
response. Observation may overcome these
weaknesses. However, because only the fre-
quency of gifts can be observed, this approach

is limited in the scope of data that one can
collect. Therefore, we used a combination of
observations, self-reports and a third source
of data: quasi-experimental observation,
simulating a person who begs in order to
reconstruct the value of gifts. Triangulating
these data, we estimated the income of three
groups in the population of beggars: indig-
enous male beggars, Roma migrant women
alone and with children. These three groups
constitute the large majority of beggars in
Brussels.
The question is whether the applied
method leads to valid and useful results. In
addition to the consistency of the method,
the conclusion that the results are consistent
with the social-scientific theories and that
the estimates lead to significant differences
between the groups, do seem to support the
supposition of validity and usefulness. The
development of a multimethod approach
to tackle the problem seems to survive the
empirical confrontation well. As expected
in the design, the combination of data from
different sources in a careful design allows for
more insight. In general, this approach is an
extension of recent pleas to measure infor-
mal economic activity with approaches that
are close to the problem at hand (Alderslade
et al., 2006) and arguing against an approach
that builds upon macro-economic or macro-
sociological heroic assumptions (for exam-
ple, Thomas, 1990).
The hypotheses are based on three sources:

the literature on informal work as a survival
activity, the popular social myths about
the nature of begging and the assumptions
underpinning recent legislation that crimi-
nalises some forms of begging. The informal
economy literature expects that the yields of
begging will be rather low, probably under
or around the poverty line. These hypotheses
based upon the social-scientific literature are
antithetical to the popular images and the
discourse legitimating legislation. The latter
assume that begging often is a fraudulent
activity, organised by criminal groups, with
high profits. Recent legislation in France
and Belgium builds upon the assumptions
that some criminal groups coerce people
into begging, often trafficked migrants, and
that these criminal groups also make use
of children accompanying the beggars in
order to evoke pity. Based on these popular
beliefs and the rationale for legislation, we
hypothesised that beggars generate returns
comparable with those of other criminal
activities, and that migrant and child beggars
yield higher returns.
Our data do not support the hypotheses
inspired by popular beliefs and legislation.
The estimates seem to indicate that they can
be categorised as myths. On the other hand,
our findings are consistent with the hypoth-
esis based on social-scientific literature on
informal work, at least for what concerns
the Roma who beg. For the indigenous
people who beg, the results are inconclusive:

their earnings from begging surpass those
of Roma and it is not certain whether it is
impossible for them to evade the poverty
line by begging.
The most striking element for policy issues
probably is the conclusion that the produc-
tivity of Roma with children is comparable
with those who beg without children. The
question is how this can be explained.
Observations and public discussions indicate
that the presence of children arouses intense
feelings. We argue that these intense feelings
lead to two types of behaviour with more or
less compensating effects. Some passers-by
may give more frequently to begging people
who beg with children, while others may
refrain from giving because of the presence
of children.
The second question is what determines the
significant gap in income between Roma and
indigenous beggars. At first sight, this seems to
indicate a negative view of the public towards
Roma. There are indeed plenty of case reports
and observations of negative feelings towards
this group. Passers-by may have an unfavour-
able image of Roma beggars, due to the per-
sistent stories about ‘organised begging’ and
exploitation, or even to a general xenophobic
distrust (as argued in Butovskaya et al., 2004).

However, the difference may also be caused
by the mere difference in quantity. The fact
that there are more Roma than indigenous
beggars may lead to a lower income, assuming
that more or less equal parts of the public are
willing to give alms to indigenous people and
to Roma people begging.
The final paragraphs of this discussion are
reserved for the policy conclusions that can
be drawn from this research. It is a return-
ing theme to discuss the recent tendency to
criminalise begging and other activities of
the poor. Although one should point to the
continuity of legislation penalising begging
(Baker, 2009), legitimating criminalisation
is built upon a different logic in different
times and places. In the US and in Canada,
for example, the dominant logic is planning
and structuring public space, thus effectively
circumventing campaigns that defend the
rights of the urban poor (Blomley, 2007).
In continental Europe, the new forms of
legislation build their discourse upon the
protection against exploitation of people who
beg. The latter logic is built upon a number
of heroic assumptions about the nature and
motivations behind begging, linking up
almost perfectly with the older myths about
beggars and fraud. The paradox is that,
despite the difference in logic, both types of
resulting regulations turn their weapons on
the people who beg.
Assessments of these different types of

regulations can be and should be based
upon different logics also. While an appraisal
of the internal (in)consistency or the hid-
den logic behind the legislation often is an
effective strategy (Fitzpatrick and Jones,
2005; Mitchell, 2005), this paper follows an
alternative logic, confronting the empirical
assumptions with the real life of people who
beg (compare Fitzpatrick and Kennedy, 2000;
Kennedy and Fitzpatrick, 2001). The overall
policy conclusion is that the recent legislation
tackles a problem that does not exist, or that
is trifling and ephemeral at best. The evidence
suggests that the most pressing problem of the
begging population, and in particular of the
Roma, is their astoundingly low standard of
living. If the estimates of their earnings prove
anything, it is that Roma people who beg are
primarily in need of social support instead of
criminal disciplining.
Notes
1. Article 706-55 of the French Code of Penal
Procedure, adopted 12 February 2003.
2. Article 433ter and 433quater of the Belgian
Penal Code, adopted 10 August 2005.
3. Chambre des Représentants de Belgique
(14 January 2005), Projet de Loi modifiant
diverses dispositions en vue de renforcer la lutte
contre la traite et le trafic des êtres humains,
Document parlementaire de la 51e législature,
no. 1560/001.

4. The design of this survey and other data
collected are explained in the methods section.
5. Data collected 9 November 2005 to 10 February
2006.
6. Data collected 17 October 2005 to 31 January
2006.
7. Confirmed by a Kolmogorov–Smirnov test.
8. P-value = 0.85 for gifts in coins and p-value =
0.25 for gifts in kind or notes.
9. At the time of our data collection, the 60 per
cent poverty line for an individual in Belgium
equalled 822 € per month, or 9.864 € per year.
Acknowledgements
The authors would like to thank Ann Clé, Koen
De Borgher, Tim Matthees, Rob Nijs and Annuska
Rodrigues Bento for their excellent support in the
fieldwork. There are also grateful for the comments
of the anonymous referees.
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