Post on 16-Aug-2020
All You Need Is a Dollar and a Dream.
Explaining the Inverse Relationship
Between Socio-economic Position and
Lottery Play
JENS BECKERT
MARK LUTTER
Max Planck Institute for the Study of Societies
Paulstr. 3, 50676 Cologne, Germany
beckert@mpifg.de
lutter@mpifg.de
Paper presented at the conference
“Random Riches. Gambling and Speculation in Perspective”
Vienna, May 23-24, 2013
1
Sociologists generally agree that there is an inverse relationship between socioeconomic
position and lottery play.1 Low-income individuals spend a larger part of their incomes on
lottery tickets than those with higher incomes (Beckert and Lutter 2009; Clotfelter and Cook
1991; Livernois 1987), and they benefit less from lottery proceeds (Beckert and Lutter 2008;
Borg et al. 1991; Borg and Mason 1988; Rubenstein and Scafidi 2002). However, the question
remains open as to what factors explain this pattern. Why do the poor spend proportionally
more of their income on lottery tickets than their wealthier and better educated peers?
Much of the research on motivating factors in lottery participation stems from
cognitive psychology (e.g. Ariyabuddhiphongs 2011; Griffiths 1990; Rogers 1998; Rogers
and Webley 2001) and economics (e.g. Albers and Hübl 1997; Brenner and Brenner 1990;
Friedman and Savage 1948; McCaffery 1994; Ng 1965). In sociology, research provides
insightful historical or qualitative in-depth studies (Casey 2008; Garvía 2007; Garvía 2008;
Light 1977; Reith 1999; Rosecrance 1986; Zola 1967) on gambling motivations, but
quantitative accounts that test theories explaining lottery play are almost nonexistent. In this
study, we use survey data to test structural, cultural, and network approaches to explain why
the poor play the lottery. First, deprivation or strain theory explains lottery gambling through
structural factors of disadvantaged social position, and assumes that lottery participation
serves as compensation for and release of tensions arising from social inequalities and
feelings of deprivation (Bloch 1951; Devereux 1980; Frey 1984). Second, cultural
explanations view lottery participation as an expression of prevailing pro-gambling value
orientations such as superstitious beliefs; as a reliance on fate and luck for upward mobility;
and as a denial of the protestant work ethic (Binde 2007; Ellison and Nybroten 1999; Lutter
2011; Murell 1979; Thorner 1956). Third, network-analytical explanations emphasize the
1 This paper is an early version of Beckert and Lutter (2013). It presents previously unpublished additional findings and results.
2
influence of social network structures on the demand for lottery tickets (Adams 1996; Garvía
2007; Guillén, Garvía, and Santana 2012).
Using survey data from a nationwide probability sample, we test these three
approaches, and perform controls for alternative explanations (cognitive bias theory). We find
that all three accounts play a role in explaining the stratified patterns of lottery expenditure.
Factors such as educational attainment and self-perceived social deprivation both have major
effects, whereas cultural factors play a much lesser role. While lottery players show fatalistic
value orientations, it is not a lack of a Protestant work ethic that makes the poor spend
relatively more on lottery tickets. Among the strongest predictors are network factors. The
gambling behavior of an actor’s close social network clearly corresponds to intensified
spending patterns, measured both in terms of monthly lottery expenditure as well as
expenditure as a proportion of income. Interaction effects with income level show that all
factors are able to explain lottery expenditure among the poor. In particular, social
deprivation, peer group influences and fatalistic beliefs are relevant to explaining lottery
consumption among lower income households.
The first section briefly presents the main approaches to explaining gambling
behavior. We then develop arguments to explain the popularity of lotteries among the poor,
and discuss sociological accounts on lottery gambling. We derive several testable hypotheses
from this section. The article’s empirical section describes the data, variable definitions, and
the analytic strategy to test the hypotheses, followed by a presentation and discussion of the
results. The article concludes with a summary of its main findings and reflections on its
implications.
SOCIAL STRATIFICATION AND THE DEMAND FOR LOTTERY TICKETS
Why are members of the lower classes more likely to play the lottery? An answer to this
question must be based on those factors that motivate people to spend money on lotteries. It 3
must also show that people of a lower social status face situations which result in lottery
gambling having greater attractivity to them than to people of a higher social status.
There are two general approaches to explaining socially stratified demand in lottery markets,
individualistic and contextual theories. Individualistic theories reconstruct lottery participation
either as a rational investment decision or as a cognitively biased decision arrived at by an
incorrect understanding of the statistics of the game. Economists view lottery participation as
a rational wealth maximizing strategy for the middle and lower-middle classes (Friedman and
Savage 1948). Once basic needs are fulfilled and the opportunity costs for lottery tickets are
low, playing the lottery can be reconstructed as a rational choice for those who otherwise lack
the means to accumulate substantial wealth (McCaffery 1994). In contrast, cognitive
psychologists and behavioral economists view lottery participation as a function of incorrect
probability assessments, cognitive biases and heuristics (Griffiths 1990). Lottery players
systematically overestimate the very low probability of the game and have overly optimistic
assessments of the chance to win. It is assumed that biased knowledge on the statistical
properties of games of chance and limited cognitive abilities are more prevalent among lower
social classes.
From the contextual viewpoint, purchasing decisions are socially anchored. They are
either structurally explained, arising from tensions and frustrations caused by disadvantaged
socio-economic positions, or culturally explained from beliefs in fate, luck and magic, or
perceived as a result of social contagion through peer group influences. All three contextual
theories maintain that actors of lower social position are at a higher risk of exposure to factors
that bring about lottery gambling. In the following part, we discuss these approaches and
derive testable hypotheses.
Structural factors: Lottery playing as tension management
4
The first approach to explaining socially stratified demand in lottery markets assumes factors
such as low levels of education and disadvantaged socio-economic positions are associated
with higher states of tension, leading to compensatory patterns of behavior. Gambling is such
a pattern. According to functionalist and deprivation theories (Bloch 1951; Devereux 1980;
Frey 1984), gambling is a socially accepted way of channeling frustrations and tensions
resulting from contradictory or unattainable demands imposed on the individual in modern
societies. Gambling, especially for the lower and lower middle classes, is a social practice in
which these tensions can be released without having a disruptive impact on the social order.
Lotteries provide a form of catharsis, giving an outlet for feelings of disadvantage and
dissatisfaction about one’s own status.
Lottery players “indulge in fantasies about what could be done with the prize money”
(Clotfelter and Cook 1991: 9). This makes lottery tickets not a monetary investment but rather
a trigger for daydreams, a vehicle for the momentary escape from reality (Binde 2012; Lutter
2010). Lottery players are motivated by the imaginative value of this consumer good (Beckert
2011; Beckert 2013; Campbell 1987; Lutter 2012). Fantasy worlds stemming from the
purchase of lottery tickets are comparatively cheap. Lower social strata are excluded from
most other “evocative” consumer goods that also create dream worlds, for example status
goods such as fine clothing, wines or luxury cars. Because of this relative exclusion from
alternative opportunities for imaginative goods consumption, individuals from lower social
strata are more likely to be drawn to lottery tickets than members of higher social strata
(Cohen 2001: 730ff.). The likelihood of players projecting unattainable desires onto lottery
tickets is higher for those from lower social status groups.
Two hypotheses follow from this. First, we assume that low socio-economic status
leads to higher personal states of tension and therefore more frequent lottery participation.
Education provides the main resource for material success in modern societies. Aspirations
for upward mobility are highly constrained by lower levels of education. At the same time, 5
lottery participation gives hope for social elevation that is independent of education. A second
hypothesis takes subjective indicators of deprivation into account. Gambling is a method of
sensation seeking to compensate for feelings of boredom and monotony in daily life.
Therefore, people who experience monotony and meaninglessness in their personal and
working lives devote higher expenditure to playing the lottery.
H 1.1: People with low levels of education spend more money on lottery tickets.
H1.2: People who feel their work and everyday lives to be boring and monotonous
spend more money on lottery tickets than those experiencing interesting and
eventful lives.
Cultural factors: Lottery as an expression of beliefs
A second approach to explaining socially stratified demand in lottery markets sees the lower
strata’s increased fascination with lotteries as a function of a culture that both emphasizes
beliefs in fate and luck instead of personal achievement, and lacks orientation towards the
values of a Protestant work ethic (Binde 2007; Ellison and Nybroten 1999; Murell 1979;
Thorner 1956). The Protestant work ethic proclaims virtues of diligence, thriftiness, efficiency
and profitability as well as productivity. From such a perspective, gambling is a waste of time
and money. Betting on random outcomes undermines the Protestant values of self-discipline,
prudence and sober rationality. The reliance on chance moves gambling close to fatalism,
superstition and magic.
The lottery is a game of pure chance in which individual skill, intelligence or habitual
difference have no influence on the opportunities for winning. It is not personal achievement,
talent, creativity or social and cultural capital that determines success in gambling. At the
same time randomness, as a distributive mechanism, stands in opposition to the achievement-
based justification of economic success in modern societies. The fact that the chances of 6
winning are completely equal is a central attraction of lotteries (McCaffery 1994: 88). This
attraction, however, varies with social position: Members of the lower social strata find the
egalitarian distribution of chance more attractive because their opportunities for success are
then greater than when meritocratic or ascriptive mechanisms prevail.
Participation in the lottery can be regarded as a flight from the all-embracing merit
principle of modern societies: “The element of chance also provides an escape from the
rationality of the culture, since gambling permits one to rely on fate and superstition” (Murell
1979: 92). This withdrawal from a Protestant work ethic is especially attractive to people from
lower social classes. While Protestant values of merit and achievement oppose the temptation
to play the lottery, a belief in fate and luck promotes playing games of chance. Two
hypotheses follow from this:
H2.1: People who deny the Protestant work ethic spend significantly more money on
the lottery.
H 2.2: People who express beliefs in fate and luck as a basis for personal success
spend more money on the lottery.
Network Factors: Lottery as a peer influence
A further explanation for the socially stratified demand in lottery markets focuses on the
causal effect of social network position. In the literature on gambling, the network perspective
has been explored in qualitative studies mainly on other games of chance and rarely in studies
on the lottery. Exceptions include the works of Light (1977) and Adams (1996) and especially
Roberto Garvía (2007; 2008). According to Garvía (2007), the exceptionally high demand for
lottery tickets in Spain can be traced back to the widespread tradition of sharing lottery tickets
by playing in syndicates among friends, relatives or colleagues. In a recent study, Guillén, 7
Garvía, and Santana (2012) analyze the motives for playing in syndicates. The authors show
that syndicate players share tickets not primarily out of economic reasons of maximizing their
chances, but mostly to establish cohesive social groups and to maintain friendships (see also
Humphreys and Perez 2013).
Therefore, we assume that syndicates positively affect demand by making lottery
participation part of social interaction and group life. Shared tickets and the activity around
playing the lottery constitute a group identity. As a group activity, the utility of a shared
lottery ticket is not defined primarily by the expected monetary return from a ticket—although
in the minds of the players winning remains a possibility—but by the secondary social effects
which evolve from membership in the informal group. The lottery ticket generates shared
experiences and emotions and forms a basis for communication. Affirmative attitudes toward
gambling are promoted in the group. Losses are less likely to stop future participation, since
quitting would threaten the continuity of the group or one’s own group membership. In
addition to the effects from these voluntary syndicates, we can also assume effects from social
contagion from a players’ social surroundings. The gambling habits of those in social
networks close to an individual should influence his or her own gambling behavior.
H 3.1: Playing in a syndicate positively correlates with intensified demand for lottery
tickets.
H 3.2: The more members of a respondent’s close network (friends, partner and
parents) play the lottery, the higher the probability that the respondent plays
the lottery more intensively.
DATA AND METHODS
8
The data used to test the hypotheses come from a CATI survey on the demand structure of
Lotto players in Germany (for details on the sample, see Beckert and Lutter 2013). Table 1
presents basic descriptive statistics of all variables used in this study. Our central dependent
variable is the amount of monthly expenditure for lottery tickets. We take the natural log of
this variable to account for skewness and to improve model fit. In addition, we construct this
variable as a percentage share of monthly income. In doing this, we capture lottery playing as
a measure of wasteful consumption.
We use the following set of indicators as independent variables. Following H1.1,
educational level is measured by the number of years spent in school and higher learning
institutions. H1.2 indicates an association between lottery gambling and work or life
dissatisfaction. We measure work/life dissatisfaction with a simple additive index of three
seven-point Likert items. The items are (a) “I often feel that I am doing something meaningful
in my work (in my everyday life)”, (b) “My work (everyday life) often bores me” and (c) “I
think my work (everyday life) is much more interesting than those of others.”2
Hypothesis H2.1 proposes a negative relation between gambling habits and the
Protestant work ethic. We use a simple additive index of the following seven-point Likert
items: (a) “If one works hard enough one is likely to make a good life for oneself.”, (b)
“There are few satisfactions equal to the realization that one has done his best at a job”, (c)
“The self-made person is likely to be more ethical than the person born to wealth.”3 As for
hypothesis H2.2, which assumes an association between the intensity of play and fatalistic
value orientations, we use a scale that consists of an additive index of the following three
seven-point Likert items: (a) “In order to get along in life, it is good to have luck on your
side”, (b) “Most people are not aware of how much of their life depends on chance and luck”
2 The items are taken from a scale by Firestone et al. (2005). 3 Items are taken from a scale by Mirels and Garrett (1971).
9
and (c) “Life is mostly controlled by fate.”4 All items were recoded in such a way that higher
values represent greater beliefs.
With regard to social network effects, we use two indicators. First, we use a dummy
variable that counts the number of respondents playing in a syndicate with friends, colleagues
or acquaintances (1 = player usually plays in a syndicate; 0 = player usually plays alone). In
order to assess the influence of the players’ social networks on the demand for lottery tickets
(H3.2), we generate ego-centric network data from our survey data. Respondents were asked
to consider two very close friends and how often each had played the lottery, if at all, within
the past year (coded as 0 = never, 8 = a few times a year, 18 = once or twice a month, 52 = at
least once a week). We also asked how often the respondent’s life partner and parents played
the lottery. We then matched the data of the four variables into a single additive index which
measures the intensity of lottery play in the respondent’s close social network.
In all statistical models, we use the following set of control variables: a dummy for
gender (1 = female), monthly available net income (transformed into logged values), age
(logged years), level of employment (where 1 = full time, 0 = otherwise), status of
employment (1 = blue-collar worker, 0 = otherwise), unemployed (1 = yes, 0 = no), retired (1
= yes, 0 = no), cohabitation (1 = living together with a partner, 0 = otherwise), urbanity
(1=living in region with more than 200.000 inhabitants, 0 = otherwise), Catholic (1 = yes, 0 =
no), Protestant (1 = yes, 0 = no), minority (1 = citizenship other than German, 0 = otherwise).
To control for possible cognitive biases, as suggested, we use a variable that measures
biased or overly optimistic assessments of the game’s winning probabilities. Survey
respondents were asked if they believe that winning the jackpot is either “likely” (coded as 1),
“unlikely” or “very unlikely” (both coded as 0). We assume that players who think they are
“likely” to win the lottery have an overly optimistic perception of the true winning chances of
the game.
4 The items are taken from a scale used by Pearlin (1981) and Darke and Freedman (1997). 10
INSERT TABLE 1 ABOUT HERE
RESULTS
Table 2 presents the results of our regressions on the log of the amount of lottery expenditure.
The first model estimates the socioeconomic determinants of lottery play. A number of
statistically significant differences can be observed, revealing insights into the
sociodemographic composition of lottery players. Income, age, employment status, and
cohabitation are significant factors. Monthly income varies positively with lottery
expenditure, but with a disproportionate growth rate. Because of the double log-linear model
specification (Gujarati 2003: 175f.), we can interpret the coefficient as an estimator of income
elasticity. The result reveals that for a 10 percent increase in monthly income, we can expect
an increase of roughly 3 percent in expenditure. This means that low income households
spend a relatively higher proportion of their income on lottery tickets than higher income
households.
Age is another nonlinear predictor of lottery play. Lottery players tend to be older but in a
disproportionate relation to spending. We can expect an approximate 8 percent increase in
expenditure when age increases by 10 percent. Furthermore, lottery players are significantly
more likely to work full-time and tend to cohabitate.
In line with our first hypothesis, education proves to be a significant factor in
explaining the demand for lottery tickets. Since the dependent variable was transformed into
logged values, the coefficients can be interpreted in terms of percentage change. With every
additional year of education, the average expenditure drops by roughly six percent. People
with low educational levels spend significantly more on lottery tickets than the better
educated.
11
Hypothesis H1.2 concerns the subjective assessment of strain arising from socially
disadvantaged positions, and proposes an association between lottery gambling and work or
life dissatisfaction. As the model results show, dissatisfaction with one’s work is significantly
related to lottery expenditure. Those who lack autonomy and express feelings of senselessness
in their everyday routines spend significantly more money on lottery tickets. These findings
underline the assumption that lottery gambling functions as an outlet for strain by offering an
easy dream of escape from daily drudgery.
The cultural factors proposed by hypotheses H2.1 and 2.2 cannot sufficiently explain
lottery expenditure. While fatalistic value orientations have a clear impact on expenditure,
spending patterns do not correspond to work-ethic value orientations. Although lottery players
maintain a culture of beliefs in fate and luck, they do not play because they lack or deny a
Protestant work ethic.
By far the strongest predictors of lottery expenditure are the network-related factors,
peer play and syndicate play. This is shown by the substantial increase in model fit when
including network variables in Model 4. Adjusted R-square doubles from .117 to .232. Both
coefficients are highly significant. The effect of education diminishes to some extent when
these predictors are included. Therefore, controlling for social network variables affects the
social composition of lottery playing with regard to educational attainment.
INSERT TABLE 3 ABOUT HERE
Table 3 displays the results of OLS regressions on expenditure as a proportion of income.
Measuring the variable in this way allows us to examine the degree of “wastefulness” of this
form of demand behavior. Findings are in line with the proposed hypotheses. Spending a high
proportion of income on lottery tickets is primarily a function of disadvantaged social
positions, self-perceived work and life dissatisfaction, beliefs in fate and luck and network 12
influences from close peers. The Protestant work ethic as a cultural explanation again shows
no significant effect. Furthermore, the finding that class differences are moderated mostly by
network variables emerges more clearly in these models. Adding network variables in the
fourth model diminishes the negative effect of education, which becomes insignificant.
Overall, one can speak of a curvilinear relation of lottery expenditure and
socioeconomic position. Lottery players are most likely to come not from the poorest, but
from upper segments of the lower classes. It is not the unemployed or those in insecure work
that are most likely to spend money on lottery tickets. It is rather middle aged full-time
employees with lower educational backgrounds but with mid-range incomes. In line with Tec
(1964), this can be interpreted in line with the deprivation approach to gambling (also see
Beckert and Lutter 2007). Those in the higher segments of the lower classes are to a greater
extent than others situated in a tension-filled status arrangement: Compared to the poorest
layer of social strata, they are integrated more deeply into the meritocratic value system of a
capitalist society and have greater personal contact to people of higher statuses. This exposes
them to social comparison. They perceive the success of others and develop aspirations for
upward mobility which remain unfulfilled because they lack educational credentials.
Participation in the lottery gives hope for social elevation independently of society’s
constraints.
INSERT TABLE 3 ABOUT HERE
We now analyze how the effects of predictors alter over different levels of income. For
this we estimate regressions with interaction effects for income and all substantial predictors
used in this study.5 Figure 1 shows the conditional effects of the variables on the absolute
expenditure. Figure 2 shows the conditional effects of the variables on relative expenditure
5 Detailed regression results can be made available upon request. 13
measured as a share of income. In these figures, each panel plots the estimated regression
coefficients of the respective predictor for the whole range of values of the income variable.
This approach reveals how effects change with income, both in their direction and in their
statistical significance. The outer lines indicate the lower and upper limits of the 95-percent
confidence interval of the respective coefficient at a specific value of income. If the interval is
beyond the zero line, then the coefficient is significant at the 95-percent level. If the zero line
intersects the confidence interval, the coefficients are insignificant.
INSERT FIGURE 1 ABOUT HERE
Firstly, the outcomes reveal interesting results with regard to strain/deprivation theory.
In Figure 1, the negative effect of education and the influence of work and life dissatisfaction
are particularly strong at higher income levels. Subjective feelings of work/life dissatisfaction
only moderately increase the (already quite high) level of lottery expenditure among the lower
income classes but lead to drastic changes among the higher classes. People from higher
income levels who feel socially disadvantaged probably experience more acute subjective
feelings of status inconsistency. This produces a higher level of strain and tension which in
turn results in more intensive gaming behavior. The same pattern can be observed in the
negative education effect. When income levels increase, lower levels of education play a
stronger role in determining lottery expenditure. Therefore, frustration or status discrepancy
has a greater effect on playing behavior and leads to higher amounts of expenditure among
those classes who are able to afford it. This result vividly portrays strain theory: Lottery
playing seems to serve as an outlet for the strain that people experience from status
inconsistencies.
On the other hand, peer play imposes increased lottery involvement on people from
lower classes. While the composition of organized syndicates only moderately varies with 14
income, peer influence is a strong explanatory factor among lower income households.
Network factors seem to have a strong clustering effect with regard to class.
Figure 2 displays interaction effects of regressions on expenditure as a percentage of
monthly income. Here, contrary to absolute amounts of expenditure, all predictors except for
the work-ethic factor reveal their strongest effects among the lower income classes. Again,
peer play proves to be the most significant factor. Socioeconomic position has an effect on the
constitution of an actor’s network, and the characteristics of the network affect the individual
behavior of its members. A lower position in the social strata of a society clearly bonds
networks of lottery players, which in turn affects the playing behavior of the respondent.
Therefore, network-ties play an important role in the formation of this market by creating and
maintaining demand, and moreover, in affecting socially skewed patterns of wasteful
consumption through lottery play.
INSERT FIGURE 2 ABOUT HERE
CONCLUSION
Each of the discussed approaches partially contributes to an explanation of the demand for
lottery tickets. We were able to show that the explanatory mechanisms identified by the
theories are related to income positions. The explanatory relevance of each approach does,
nevertheless, differ as does their relationship to income status.
Structural factors of educational disadvantage and self-perceived deprivation prove to
be relevant in explaining lottery expenditure. People who feel alienated at work spend more
on the lottery than those who are satisfied with their everyday life. Moreover, the conditional
relationship between levels of income and gambling expenditure also corroborates the theory.
Interestingly, feelings of dissatisfaction have greater effects on absolute lottery expenditure 15
from higher income classes. This is probably due to status inconsistencies being felt more
intensely. In contrast, dissatisfaction is highly relevant among lower income classes when
expenditure is measured as a share of income.
Cultural factors, on the other hand, play only a minor role in explaining why the poor
play the lottery. While beliefs in fate and luck can explain spending patterns both for lower
and higher income classes, the Protestant work ethic is a relevant cultural factor only for
higher income classes in deterring gambling. The lack or denial of this ethic is not a
characteristic of the poor. Therefore, a central finding of this study is that a lack of the “right”
values is not a reason why the poor play the lottery.
Compared with all other factors, the network approach makes the best fit to the data.
Network variables can explain approximately half of the variance and are therefore the
strongest predictors of lottery expenditure. Expenditure is significantly increased when there
is an increase in the number and frequency of close peers playing the lottery, with the effect
being most pronounced among lower income individuals. Hence, the poor play more because
network factors impart influences on spending patterns, both measured absolutely and relative
to income.
The intention of this article was to provide a more comprehensive examination for the causes
of socially stratified demand behavior in lottery markets. The results show that in addition to
networks, factors of social position and deprivation as well as beliefs on fate and luck are
relevant. The relationship between the intensity of lottery play and objective criteria such as
sociodemographic status has been known from previous research (Brown, Kaldenberg, and
Browne 1992; Clotfelter and Cook 1991). However, the associations between lottery play and
subjective indicators of status frustration and their respective mediation effects have not been
detected in this form before. Some of the findings from previous empirical studies by Tec
(1964), Downes et al. (1976), Smith et al. (1976) and King (1985) do point in a similar
16
direction, but their results are either statistically insignificant or refer to other forms of
gambling.
Explaining spending patterns for lottery tickets among different income groups
provides insights into the social stratification of market demand. Our findings point to the
importance of social context – in contrast to individual player characteristics as stressed in
economic and psychological approaches – in explaining demand patterns within the lottery
market, and hence reveal the social influences that explain the stratification of certain patterns
of consumption.
17
TABLES
TABLE 1: Descriptive statistics
of all dependent and independent variables
Variable Mean Std. Dev. Min. Max.
Expenditure (euros) 10.66 20.33 0 216 Expenditure (ln) 1.49 1.38 0 5.39 Expenditure (% of income) 0.83 2.25 0 35.29 Female .48 .50 0 1 Income (ln) 6.96 .59 4.42 9.43 Age (ln) 3.77 .37 2.89 4.47 Employment full-time .46 .50 0 1 Blue-collar worker .24 .43 0 1 Unemployed .05 .21 0 1 Retired .21 .41 0 1 Cohabitation .63 .48 0 1 Urbanity .25 .43 0 1 Catholic .32 .47 0 1 Protestant .38 .49 0 1 Minority .02 .14 0 1 Education 12.10 3.23 8 17 Work dissatisfaction 6.97 3.42 3 21 Work ethic 7.19 2.95 3 21 Belief in fate & luck 12.86 4.03 3 21 Syndicate play .17 .37 0 1 Peer play 37.66 39.97 0 208 Optimism .05 .22 0 1
18
TABLE 2: Results of OLS regressions
on log of lottery expenditure
(1) (2) (3) (4) (5) Expen-
ditures, ln Expen-
ditures, ln Expen-
ditures, ln Expen-
ditures, ln Expen-
ditures, ln Female 0.084 0.069 0.085 0.129 0.110 (0.976) (0.799) (0.986) (1.597) (1.372) Income (ln) 0.304*** 0.311*** 0.360*** 0.315*** 0.320*** (3.589) (3.664) (4.246) (3.979) (4.091) Age (ln) 0.787*** 0.809*** 0.692*** 0.661*** 0.656*** (4.933) (5.081) (4.311) (4.413) (4.427) Employment full-time 0.234* 0.253* 0.213* 0.141 0.136 (2.137) (2.318) (1.971) (1.394) (1.358) Blue-collar worker 0.170 0.140 0.083 0.052 0.047 (1.711) (1.391) (0.818) (0.554) (0.503) Unemployed 0.081 0.010 -0.086 0.005 0.017 (0.387) (0.047) (-0.403) (0.026) (0.086) Retired 0.030 0.008 -0.021 0.083 0.080 (0.189) (0.052) (-0.133) (0.561) (0.541) Cohabitation 0.215* 0.216* 0.252** 0.112 0.108 (2.452) (2.454) (2.865) (1.349) (1.311) Urbanity -0.142 -0.132 -0.091 -0.091 -0.093 (-1.515) (-1.407) (-0.972) (-1.046) (-1.072) Catholic -0.133 -0.104 -0.148 -0.154 -0.168 (-1.266) (-0.992) (-1.417) (-1.578) (-1.741) Protestant 0.017 0.031 0.006 -0.045 -0.053 (0.174) (0.315) (0.059) (-0.495) (-0.586) Minority 0.393 0.341 0.260 0.362 0.305 (1.288) (1.121) (0.827) (1.236) (1.052) Education -0.060*** -0.060*** -0.053*** -0.033* -0.029* (-4.199) (-4.214) (-3.727) (-2.438) (-2.163) Work dissatisfaction 0.028* 0.032* 0.027* 0.026* (2.255) (2.569) (2.331) (2.232) Work ethic -0.027 -0.022 -0.018 (-1.855) (-1.619) (-1.322) Belief in fate & luck 0.046*** 0.035*** 0.031** (4.392) (3.577) (3.191) Syndicate play 0.865*** 0.829*** (8.230) (7.955) Peer play 0.008*** 0.008*** (8.094) (8.069) Optimism 0.852*** (4.883) Constant -3.106*** -3.441*** -3.826*** -3.842*** -3.883*** (-4.426) (-4.825) (-5.260) (-5.664) (-5.787) R2 0.096 0.102 0.131 0.245 0.262 Adjusted R2 0.086 0.090 0.117 0.232 0.249 Observations 1090 1080 1043 1043 1043
Notes: t statistics in parentheses; * p < 0.05, ** p < 0.01, *** p < 0.001 (two-sided tests).
19
TABLE 3: Results of OLS regressions
on lottery expenditure as a percentage of income
(1) (2) (3) (4) (5) Expen-
ditures, % of income
Expen- ditures, % of
income
Expen- ditures, %
income
Expen- ditures, % of
income
Expen- ditures, % of
income Female 0.004* 0.003* 0.003* 0.003* 0.003* (2.305) (2.010) (2.000) (2.326) (2.122) Income (ln) -0.009*** -0.008*** -0.005*** -0.006*** -0.006*** (-5.536) (-5.131) (-3.841) (-4.252) (-4.229) Age (ln) 0.015*** 0.015*** 0.012*** 0.012*** 0.012*** (5.066) (5.317) (4.413) (4.412) (4.422) Employment full-time 0.001 0.001 -0.000 -0.001 -0.001 (0.453) (0.498) (-0.118) (-0.486) (-0.538) Blue-collar worker 0.001 0.001 0.001 0.001 0.001 (0.362) (0.355) (0.759) (0.545) (0.497) Unemployed -0.003 -0.004 -0.007 -0.006 -0.006 (-0.744) (-0.987) (-1.937) (-1.748) (-1.709) Retired -0.002 -0.003 -0.002 -0.001 -0.001 (-0.557) (-0.962) (-0.706) (-0.286) (-0.313) Cohabitation 0.002 0.001 0.003* 0.002 0.002 (0.968) (0.900) (2.248) (1.243) (1.206) Urbanity -0.003 -0.003 -0.002 -0.002 -0.002 (-1.626) (-1.565) (-1.131) (-1.157) (-1.182) Catholic -0.001 -0.001 -0.000 -0.000 -0.000 (-0.479) (-0.276) (-0.150) (-0.151) (-0.288) Protestant -0.000 -0.001 -0.000 -0.001 -0.001 (-0.239) (-0.363) (-0.290) (-0.620) (-0.704) Minority 0.008 0.007 0.007 0.007 0.006 (1.427) (1.272) (1.252) (1.439) (1.269) Education -0.001* -0.001* -0.001* -0.000 -0.000 (-2.545) (-2.507) (-2.326) (-1.515) (-1.252) Work dissatisfaction 0.000* 0.001* 0.000* 0.000* (2.033) (2.398) (2.168) (2.072) Work ethic -0.000 -0.000 -0.000 (-1.021) (-0.821) (-0.539) Belief in fate & luck 0.000* 0.000 0.000 (2.465) (1.861) (1.490) Syndicate play 0.007*** 0.006*** (3.645) (3.350) Peer play 0.000*** 0.000*** (5.169) (5.112) Optimism 0.014*** (4.515) Constant 0.021 0.012 0.001 0.001 -0.000 (1.630) (0.902) (0.065) (0.050) (-0.006) R2 0.083 0.083 0.094 0.134 0.150 Adjusted R2 0.072 0.071 0.080 0.118 0.135 Observations 1090 1080 1043 1043 1043
Notes: t statistics in parentheses; * p < 0.05, ** p < 0.01, *** p < 0.001 (two-sided tests).
20
FIGURES
FIGURE 1: Conditional effects of the predictors on the log of
lottery expenditure at different levels of income,
with 95-% confidence intervals
-.2-.1
0.1
-.10
.1.2
-.20
.2
0.0
5.1
.15
0.5
11.
52
0.0
05.0
1.0
15.0
2
-2 0 2 -2 0 2 -2 0 2
Education Work dissatisfaction Work ethic
Belief in fate & luck Syndicate play Peer play
effect on lottery expenditures95%-confidence interval
Income
21
FIGURE 2: Conditional effects of the predictors on
expenditure as % of income, at different levels of income,
with 95-% confidence intervals
-.4-.2
0.2
-.20
.2.4
-.2-.1
0.1
.2
-.20
.2.4
-20
24
-.02
0.0
2.0
4
-2 0 2 -2 0 2 -2 0 2
Education Work dissatisfaction Work ethic
Belief in fate & luck Syndicate play Peer play
effect on expenditures (as % of income)95%-confidence interval
Income
22
REFERENCES Adams, Douglas James. 1996. Playing the Lottery. Social Action, Social Networks and
Accounts of Motive. Ph.D. Dissertation, Department of Sociology, University of Arizona.
Albers, Norman and Lothar Hübl. 1997. "Gambling Market and Individual Patterns of Gambling in Germany." Journal of Gambling Studies 13:125-144.
Ariyabuddhiphongs, V. 2011. "Lottery Gambling: A Review." Journal of Gambling Studies 27:15-33.
Beckert, Jens. 2011. "The Transcending Power of Goods: Imaginative Value in the Economy." Pp. 106-128 in The Worth of Goods. Valuation and Pricing in the Economy, edited by J. Beckert and P. Aspers. Oxford: Oxford University Press.
Beckert, Jens. 2013. "Imagined Futures: Fictional Expectations in the Economy." Theory and Society 42:219-240.
Beckert, Jens and Mark Lutter. 2007. "Wer spielt, hat schon verloren? Zur Erklärung des Nachfrageverhaltens auf dem Lottomarkt." Kölner Zeitschrift für Soziologie und Sozialpsychologie 59:240-270.
Beckert, Jens and Mark Lutter. 2008. "Wer spielt Lotto? Umverteilungswirkungen und sozialstrukturelle Inzidenz staatlicher Lotteriemärkte." Kölner Zeitschrift für Soziologie und Sozialpsychologie 60:233-264.
Beckert, Jens and Mark Lutter. 2009. "The Inequality of Fair Play. Lottery Gambling and Social Stratification in Germany." European Sociological Review 25:475-488.
Beckert, Jens and Mark Lutter. 2013. "Why the Poor Play the Lottery: Sociological Approaches to Explaining Class-based Lottery Play." Sociology 47:1152-1170.
Binde, Per. 2007. "Gambling and Religion: Histories of Concord and Conflict." Journal of Gambling Issues 20:145-165.
Binde, Per. 2012. "Why people gamble: a model with five motivational dimensions." International Gambling Studies 13:81-97.
Bloch, Herbert A. 1951. "The Sociology of Gambling." The American Journal of Sociology 57:215-221.
Borg, Mary O. and Paul M. Mason. 1988. "The Budgetary Incidence of a Lottery to Support Education." National Tax Journal 41:75-85.
Borg, Mary O., Paul M. Mason, and Stephen L. Shapiro. 1991. The Economic Consequences of State Lotteries. New York: Praeger.
Brenner, Reuven and Gabrielle A. Brenner. 1990. Gambling and Speculation. A Theory, a History, and a Future of Some Human Decisions. New York: Cambridge University Press.
Brown, Daniel J., Dennis O. Kaldenberg, and Beverly A. Browne. 1992. "Socioeconomic-Status and Playing the Lotteries." Sociology and Social Research 76:161-167.
Campbell, Colin. 1987. The Romantic Ethic and the Spirit of Modern Consumerism. Oxford, New York: B. Blackwell.
Casey, Emma. 2008. Women, pleasure and the gambling experience. Aldershot, U.K.: Ashgate.
Clotfelter, Charles T. and Philip J. Cook. 1991. Selling Hope. State Lotteries in America. Cambridge, MA: Harvard University Press.
Cohen, Lloyd R. 2001. "The Lure of the Lottery." Wake Forest Law Review 36:705-745. Darke, Peter R. and Jonathan L. Freedman. 1997. "The Belief in Good Luck Scale." Journal
Of Research In Personality 31:486-511.
23
Devereux, Edward C. Jr. 1980. Gambling and the Social Structure. A Sociological Study of Lotteries and Horse Racing in Contemporary America, vol. I & II. New York: Arno Press.
Downes, David M., B.P. Davies, M.E. David, and P. Stone. 1976. Gambling, Work and Leisure. London: Routledge and Kegan Paul Ltd.
Ellison, Christopher G. and Kathleen A. Nybroten. 1999. "Conservative Protestantism and Opposition to State-sponsored Lotteries: Evidence from the 1997 Texas Poll." Social Science Quarterly 80:356-369.
Firestone, Juanita M., Raymond T. Garza, and Richard J. Harris. 2005. "Protestant Work Ethic and Worker Productivity in a Mexican Brewery." International Sociology 20:27-44.
Frey, James H. 1984. "Gambling: A Sociological Review." Annals of the American Academy of Political and Social Science 474:107-121.
Friedman, Milton and L. J. Savage. 1948. "The Utility Analysis of Choices Involving Risk." The Journal of Political Economy 56:279-304.
Garvía, Roberto. 2007. "Syndication, Institutionalization, and Lottery Play." American Journal of Sociology 113:603-652.
Garvía, Roberto. 2008. Loterías. Un Estudio Desde La Nueva Sociología Económica, vol. 254. Madrid: CIS.
Griffiths, Mark D. 1990. "The Cognitive Psychology of Gambling." Journal of Gambling Studies 6:31-42.
Guillén, Mauro F., Roberto Garvía, and Andrés Santana. 2012. "Embedded Play: Economic and Social Motivations for Sharing Lottery Tickets." European Sociological Review 28:344-354.
Gujarati, Damodar N. 2003. Basic Econometrics. Boston: McGraw Hill. Humphreys, Brad R. and Levi Perez. 2013. "Syndicated Play in Lottery Games." The Journal
of Socio-Economics 45:124-131. King, Kim M. 1985. "Gambling: Three Forms and Three Explanations." Sociological Focus
18:235-248. Light, Ivan. 1977. "Numbers Gambling Among Blacks: A Financial Institution." American
Sociological Review 42:892-904. Livernois, J. R. 1987. "The Redistributive Effects Of Lotteries - Evidence From Canada."
Public Finance Quarterly 15:339-351. Lutter, Mark. 2010. Märkte für Träume. Die Soziologie des Lottospiels. Frankfurt/Main, New
York: Campus. Lutter, Mark. 2011. "Konkurrenten auf dem Markt für Hoffnung: Religiöse Wurzeln der
gesellschaftlichen Problematisierung von Glücksspielen." Soziale Probleme 22:28-55. Lutter, Mark. 2012. "Tagträume und Konsum: Die imaginative Qualität von Gütern am
Beispiel der Nachfrage für Lotterien." Soziale Welt 63:233-251. McCaffery, Edward J. 1994. "Why People Play Lotteries and Why It Matters." Wisconsin
Law Review 71:71-122. Mirels, Herbert L. and James B. Garrett. 1971. "Protestant Ethic as a Personality Variable."
Journal of Consulting and Clinical Psychology 36:40-44. Murell, May E. 1979. "Why People Gamble: A Sociological Perspective." Pp. 84-105 in
Gambling Today, edited by D. Lester. Springfield, Ill.: Thomas. Ng, Yew Kwang 1965. "Why do People Buy Lottery Tickets? Choices Involving Risk and the
Indivisibility of Expenditure." The Journal of Political Economy 73:530-535. . Pearlin, Leonard I., Elizabeth G. Menaghan, Morton A. Lieberman, and Joseph T. Mullan.
1981. "The Stress Process." Journal of Health and Social Behavior 22:337-356. Reith, Gerda. 1999. The Age of Chance. Gambling in Western Culture. London: Routledge.
24
Rogers, Paul. 1998. "The Cognitive Psychology of Lottery Gambling. A Theoretical Review." Journal of Gambling Studies 14:111-134.
Rogers, Paul and Paul Webley. 2001. ""It could be us!": Cognitive and Social Psychological Factors in UK National Lottery Play." Applied Psychology 50:181-199.
Rosecrance, John. 1986. "Why Regular Gamblers Don't Quit: A Sociological Perspective." Sociological Perspectives 29:pp. 357-378. .
Rubenstein, Ross and Benjamin Scafidi. 2002. "Who Pays and Who Benefits? Examining the Distributional Consequences of the Georgia Lottery for Education." National Tax Journal 55:223-238.
Smith, Ronald W., Frederick W. Preston, and Harry L. Humphries. 1976. "Alienation from Work. A Study of Casino Card Dealers." Pp. 229-246 in Gambling and Society, edited by W. R. Eadington. Springfield, Ill.: Thomas.
Tec, Nechama. 1964. Gambling in Sweden. Totowa: Bedminster Press. Thorner, Isidor. 1956. "Ascetic Protestantism, Gambling And The One-Price System."
American Journal Of Economics And Sociology 15:161-172. Zola, Irving Kenneth. 1967. "Observations on Gambling in a Lower-Class Setting." Pp. 19-32
in Gambling, edited by R. D. Herman. New York: Harper & Row.
25