gambling households in canada

Gambling Households in Canada

Martha MacDonald

John L. McMullan

David C. Perrier

Saint Mary’s University

This paper examines the distribution of gambling dollars in Nova Scotia, Saskatche-wan and Canada and studies the impact of this spending on households. We focusfirst on how gambling expenditures are related to the level and source of householdincome as well as to other demographic characteristics such as age, education, house-hold composition, geographical area, and sources of income. Next we analyze howgambling expenditures are distributed among those households that gamble. Weshow how expenditure patterns differ in the intensity of gambling as measured bythe proportion of household income or total amount of dollars spent on gambling.Then we study the affects that gambling has on spending on household necessities,changes in net worth, retirement savings and household debt. Finally we determinewhether gambling expenditures act as a substitute or a complement to other recrea-tional spending on entertainment products and services. Throughout the paper weoffer a comparative analysis of provincial and national data.

KEY WORDS: gambling expenditures; gambling intensity; economic costs; consumerspending; survey Research.

INTRODUCTION

Gambling is organized differently in Canadian provinces than inplaces like Las Vegas and Atlantic City (MPM, 2000). In the case ofthe latter, gambling operators attract a high proportion of their

Please Address correspondence to Martha MacDonald, John L. McMullan, David C. PerrierSaint Mary’s University, Halifax, Nova Scotia, Canada B3H 3C3.

Journal of Gambling Studies, Vol. 20, No. 3, Fall 2004 (� 2004)

187

1050-5350/04/0900-0187/0 � 2004 Human Sciences Press, Inc.

customers from outside the areas in which they do business. They, ineffect, export gambling services to residents of other regions andcountries. These destination-driven gambling sites create jobs in bothresort complexes and in related areas such as restaurants, amuse-ments, recreation, retail shopping, construction and supplies. Muchlike a factory, they bring in new money that is spent locally on pay-rolls and the purchase of inputs. Owners’ profits, in turn, are rein-vested back into the local community. This pattern of economicdevelopment occurs either because gambling is prohibited in adja-cent regions or because the destination locales have a large enoughtourist infrastructure to attract a broad base of customers beyondwhat the gambling facilities themselves command. In effect, gam-bling in Las Vegas, Reno and Atlantic City is segregated from thepopulation centres they depend on, and this geographic patternaffords these cities a relative protection from long lasting negativesocial impacts (Apt, Smith, & Christiansen, 1985; Eadington, 1995b;Goodman, 1995a, 1995b; Grinols and Omorov, 1996:3). AsEadington (1995a:52) observes of Las Vegas ‘‘it is difficult to attri-bute social problems in the community to any or all of the possiblecausal factors [of gambling]’’.

Gambling in most Canadian provinces, however, emphasizes localconsumers rather than tourists as customers. It is organized as a regularurban and rural leisure activity in its own right. Almost every commu-nity has corner stores selling lottery commodities. Many churches andservice organizations provide bingos, raffles, and charitable casino stylegambling. Video lottery terminals are available in local taverns,lounges, bars, restaurants, and other licensed community sites in mostprovinces. Casino gambling is also based on expedience. It draws mostof its customers from local regions and not from outside the country.Casinos in Canada are closer to their customer markets and are moreaccessible than casinos at destination sites. Ultimately, their raisond’etre is to encourage people to gamble, not to have a holiday experi-ence (Eadington, 1995a: 53–54; Henrikssen, 1996; LaFramboise, 1998).

The market structure of convenience gambling in Canada is alsodifferent from the traditional, open and competitive model that char-acterizes the development of commercial gambling in the U.S. Pro-vincial governments in Canada now directly own and manage mostgambling products. They authorize monopolies (i.e., lottery gam-bling), multiple licensing arrangements with operators (i.e., video

188 JOURNAL OF GAMBLING STUDIES

lottery gambling and bingo) and exclusive franchise arrangementswith private companies to run gambling as joint ventures (i.e., casi-nos). These governments have also established numerous regulationsand controls over the marketplace. They include financial guaranteesto the public, constraints which protect gamblers from their own mis-fortunes, restrictions which limit access or which restrain the organi-zation of the gambling activity proper, rules which ensure theintegrity of the games, regulations which guarantee the process ofrevenue collection and sharing, and procedures which watch againstthe involvement of unwanted people in the ownership, managementand play of the games (Campbell & Smith, 1998; Eadington,1995b:174; Smith & Azmier, 1997).

The economic and social benefits of convenience gambling inmost of Canada are not as obvious; nor are the social impacts asdistant or dispersed (Seelig & Seelig, 1998:98; Smith & Hinch,1996:41–43; Smith & Wynne, 1999). Indeed, gambling that catersprimarily to local residents may not have a sizable, stimulating eco-nomic effect. Instead, it may reshuffle available expenditures awayfrom other goods and services, and revenues and jobs gained maybe offset by jobs lost and declining revenues elsewhere in theregion (Goodman, 1995a, 1995b; Grinols, 1995; Grinols &Omorov, 1996). Similarly, social impacts that are hidden orexported in tourist destination gambling economies remain visibleand enduring in gambling economies shaped by the spread of theconvenience marketplace. These impacts may rejuvenate or enricha region, or they may add to social and economic costs (Abt,1996; Cyrenne, 1995; Eadington, 1994:6; Goodman, 1995a, 1995b;Lesieur, 1996; Stokowski, 1996; Thompson, 1997; Thompson andGazel, 1997:183–205, 1998).

Much of the growth of gambling over the past decade in Canadahas been fueled by government tolerance, promotion and policy andby the general increase in discretionary consumer spending. In 1996,the consumption of goods and services totaled $338.2 billion, a realincrease of 16% from 1986. Household consumption of goodsincreased by 6% but the consumption of services soared by 34%. Inparticular, household expenditures for services were galvanized bythe demand for: (a) financial and real estate products; (b) communi-cation products; and (c) amusement and recreation services. In thelatter category, total household spending was 47% higher than in

189MARTHA MACDONALD, JOHN L. MCMULLAN, AND DAVID C. PERRIER

1986 while Canada’s population rose by only 14% (Little and Beland,1998:18,21,25,27). The amusement and recreational services sectorgrew at twice the rate of the overall economy and of the $8.5 billionspent on these services in 1996, the largest amount was spent ongames of chance ($3.8 billion). By 1996, spending on games ofchance was $334 per household, or 44% of the average householdexpenditure of $780 on amusement and recreational services (Littleand Beland, 1998:27–28).

The objectives of this study are to offer new evidence con-cerning the distribution of gambling dollars across households andthe impacts of this spending. Key questions explored include:(a) how are gambling expenditures related to the level and sourceof household income, as well as other demographic characteristics?(b) how are gambling expenditures distributed across the gam-bling population? (c) to what extent is household spending onnecessities affected by gambling? (d) to what extent are changesin household debt levels, and net worth, affected by gambling?(e) is gambling a substitute or a complement to other recrea-tional/entertainment products and services? (f) how do expendi-ture patterns differ by intensity of gambling, as measured by theproportion of household income, or total amount, spent on gam-bling? (g) what are the variations in these expenditure patterns byprovince?

This study does not pretend to offer a precise definition of agambler versus a non-gambler, since the data do not distinguishbetween frequent and infrequent gambling activities. Nor do weclaim to be able to discover the ‘‘threshold level’’ of the socioeco-nomic and demographic variables that transforms a non-gambler toa gambler or to assess the probability that a household will become agambling household. This study does, however, analyze householdswho gamble compared to non-gambling households. Most impor-tantly, it provides a detailed discussion of the relationship betweengambling households and other socioeconomic and demographicvariables such as income, age, education, household composition,sources of income, geographical location and so on.

This article is organized as follows. First, we discuss the datasources and methodology. Second, we analyze gambling expenditurepatterns in all jurisdictions, examining determinants of householdgambling, and the amount spent on gambling by households. Next,


we study the impact of gambling expenditures on the financial wellbeing of households. Then, we examine the relationship betweenexpenditures on gambling and other discretionary and recreational/entertainment spending. Finally, we conclude by looking at what ourfindings mean for the spread of commercial gambling.

METHODOLOGY

We use data from Statistics Canada’s 1996 Family ExpenditureSurvey (FAMEX) and from the 1997 Survey of Household Spending[SHS] (Marshall, 1996a, 1996b, 1998). These surveys introducedquestions about winnings from games of chance and expenditureson: government run lotteries; casinos and slot machines; bingos; andnon-government lotteries and raffle tickets. They provide us withquantitative information about both the positive effects of gamblingas entertainment/recreation and the costs in terms of income dis-placement from other discretionary spending or from basic necessi-ties.

The FAMEX survey is a stratified multi-stage sample selectedfrom the Labour Force Survey sampling frame (Statistics Canada,1991). Data is collected using a detailed questionnaire for eachhousehold. Household is defined as a person or a group of personsoccupying one dwelling unit, and thus in some cases householdsinclude unrelated individuals. Basic demographic information is col-lected in face-to-face interviews with a reference person and a spouse,if applicable. The data includes: total household income (before andafter taxes) and income from each of wages/salaries, self-employ-ment, investments, government transfers and other sources; maritalstatus, age, sex, education, occupation, weeks worked full time, weeksworked part time, and country of birth of reference person andspouse. Other variables provide a description of the household, suchas number of children, youths and adults, household type (one per-son, married couple, lone parent, etc.), and indicators related toemployment income (EI), social assistance and the low-income cut-off (LICO).

Information is also collected on household expenditures ofgoods and services, including financial items and charitable contri-butions. Large expenditures such as automobiles, furniture, and


electronic equipment, and food and transportation expenditures,that are known percentages of a typical budget, can be estimatedfairly readily and accurately. But expenses on smaller consumeritems or on entertainment/recreational products are less easilyrecalled by respondents because they are not predictable financialtransactions with canceled checks, receipts or contracts. Informa-tion about gambling is also not easily recalled. Gamblers are oftenreluctant to diverge reliable information about their gambling infront of family members or strangers (Dickerson, 1993; Thompson,Gazel, & Rickman, 1996; Walker, 1992). As Marshall (1996b:30)notes of lotteries ‘‘households [in the FAMEX survey] consistentlyunderreport the amount of money they spend on government lot-tery tickets per year.’’ Underreporting also applies to casinos andbingos, and we caution that our results are on the conservativeside.

We study a sample of 821 households in Nova Scotia, 898 in Sas-katchewan and 10,406 in Canada. These jurisdictions have similardemographics (i.e., age, income, education, rural–urban populationdistributions), gambling products (i.e., bingos, video lottery termi-nals, lotteries and casinos), gross gambling revenues, per capita adultwagering rates, rates of problem gamblers, percentages of provincialgovernment revenues derived from gambling and they allow for use-ful provincial and national comparisons (Azmier & Smith, 1998;Campbell & Smith, 1998; Smith & Azmier, 1997). While we do nothave comparative data over several survey periods to track spendingon gambling activities versus other recreational activities, our analysisis unique and important in that it compiles information on thereported gambling expenditure habits of Canadian households atone point in time.

The basic data we use is ‘‘expenses on games of chance’’, whichwe refer to as expenditures on games of chance, or gambling. Wecategorize households as engaging in gambling if this variable isgreater than zero. Non-gambling households have zero ‘‘expenses ongames of chance’’. We caution that the data set does not differenti-ate between occasional, frequent or problem gamblers. Someonewho purchases an occasional lottery ticket or participates in a charita-ble bingo game is classified as a gambler as are those who regularlyfrequent casinos or play video lottery terminals. We use several mea-sures of gambling in our analysis. We examine games of chance


expenses ($), for those households for whom this is positive. Theaverage expenditures on games of chance reported in our study arenet of winnings (unless winnings exceed wagers, in which case netwinnings are added to other money receipts, so that positive expen-ditures are recorded for all who gamble).1 We also construct a vari-able for games of chance expenditures as a proportion of totalhousehold before tax income and we study the quintile expendituredistribution for games of chance. To examine the most intensivegambling households, by which we mean the quantity of moneyspent on gambling, we use the top spending quintile as one measure,and the top quartile of gambling expenses as a proportion of house-hold income as the other measure.

Our research deploys a mixture of descriptive and multivariatetechniques to relate household gambling to other variables. We usethe sample weights in our analysis, so it will represent the popula-tion. Because the household is the unit of analysis, the basic demo-graphic characteristics of the respondent are adopted. We always usetotal household income before taxes. Descriptive techniques includecalculating frequencies, means, quintile distributions and cross-tabsto show differences in gambling expenditures in relation to oneother factor (i.e., household income). We report descriptive findingsfor each question first. For findings based on cross-tabs, we indicatewhether differences are statistically significant. In the case of meanvalues the standard errors are reported. We also estimate regressionsfor each aspect of gambling and for each regression we include thevariables examined separately in our descriptive tables. This enablesus to control for the impact of other variables, when focusing on onerelationship of interest. In instances where the dependent variablecan take only two values (i.e., does a household have gamblingexpenditures or not), we estimate a probit regression. When thedependent variable is continuous (i.e., the amount spent on gamesof chance by households who gamble), then ordinary least squares(OLS) regressions are estimated. In interpreting the regressionresults, we focus on variables whose coefficients are statistically signif-icant.2

Space limitations prevent us from presenting all of our results intabular form. Of 27 available tables, we include 9 in this paper. Moredetailed accounts of descriptive data and probit and OLS regressionsare available to interested readers upon request.


GAMBLING HOUSEHOLDS AND GAMBLING EXPENDITURES

Income, Age and Education

The vast majority of households (83%) in Nova Scotia, (82%)Saskatchewan and (81%) the rest of Canada spend money on gamesof chance (Table 1). Higher levels of income are associated withhigher frequency of gambling. In Nova Scotia 70% of householdswith incomes under $20,000 gamble, compared to 92% of those withincomes of at least $80,000 or more. The gambling rates for theseincome groups are virtually identical in Saskatchewan, but are lowerin Canada. In the probit regression analysis (Table 2), ‘‘total house-hold before tax income’’ is positively associated with the rate of gam-bling. Thus, as income increases, households are more likely toparticipate in games of chance.

We also find significant differences by age of respondent, withrates of gambling first rising and then declining (Table 1). Youngerhouseholds (respondent age under 25) and older households(respondent age 65 and over) have the lowest incidence of gamblingin each jurisdiction. However, the percentage of households in theyoungest age group who report gambling expenditures is higher inSaskatchewan (80%) than in Nova Scotia or Canada (71%). Highergambling rates tend to be found in the middle age groups in alljurisdictions, but ‘‘Young’’ and ‘‘Senior’’ gamblers are more evidentin Saskatchewan than elsewhere. In the probit analysis, (Table 2) thehigher gambling rates associated with middle age groups and thelower rates for seniors and youth are clearly confirmed in the Cana-dian regression. The results for Nova Scotia and Saskatchewan, how-ever, are not as strongly confirmed. In Nova Scotia only the lowerrate for ‘‘respondent age 65+’’ is significant.

Differences in percentage of households reporting gamblingexpenditures by educational level are also evident. Lower rates arefound in each jurisdiction for those with less than 9 years of educa-tion and those with university degrees. But the differences by educa-tion are not significant for Nova Scotia (Table 1). If you control forincome as well as other variables (Table 2), however, the likelihoodof gambling is significantly lower in Saskatchewan and Canada forhouseholds where the respondent has university education andwhere the respondent has less than 9 years education, compared to


Table 1Percentage of Households Reporting Expenditures on Games

of Chance—Nova Scotia, Saskatchewan and Canada*

Nova Scotia(%)

Saskatchewan(%)

Canada(%)

All households 83 82 81

Before tax income$0–$20,000 70 70 66$20,000–$39,999 83 82 82$40,000–$59,999 87 85 87$60,000–$79,999 86 93 87$80,000 and over 92 93 87

Age of reference person<25 69 80 7125–34 87 81 8335–44 87 86 8345–54 86 87 8755–64 84 87 8565 and over 71 73 72

Education ofreference person

Notsignificant

Less than 9 years 76 71 76Some/complete

high school83 86 84

Post secondarycertificate or degree

85 84 84

University certificateor diploma

81 77 75

Not stated 100 100 89

Household typeOne person 65 72 71Married couple only 86 87 84Married couple with

single children89 88 86


Table 1 (Continued)

Nov Scotia(%)

Saskatchewan(%)

Canada(%)

Married couple withrelatives/others

88 93 90

Lone parent families 83 79 74Other households withrelatives only

83 74 84

Other households unrelatedpeople

87 84 87

Presence of children Notsignificant

No children 81 80 81One child 88 83 82Two or more children 83 89 84

Presence of spouseNo spouse 73 75 74Spouse 88 88 86

Work patterns, couples only Notsignificant

Notsignificant

Both work FTFY 92 90 88One full time-full year,one PTFY

86 91 85

Other 86 86 84

Main source of incomeWages and salaries 88 87 86Self-employment 79

(Notsignificant)

84(Not

significant)

78

Investments 50 66 66Government transfers 73 72 71Other sources 86

(Notsignificant)

84 82(Not

significant)


high school graduates. In the Nova Scotia regression, only the lowerrate of gambling amongst university-educated respondent householdsis significant.

Household Composition, Sources of Income and Geographical Areas

Gambling rates also differ by type of household. In Nova Scotia,one-person households have the lowest rate (65%), while householdsof married couples with single children have the highest rate (89%).

Table 1 (Continued)

Nova Scotia(%)

Saskatchewan(%)

Canada(%)

Employment insurance income Notsignificant

Recipient households 90 86 88Non-recipient households 80 82 80

Social assistance income Significantat 90%


Low-income cut-off

Households below low-incomecut-off

71 70 67

Households above low-incomecut-off

85 85 85

Size of area of residence Significantat 90%

30,000 and over 84 84Less than 30,000 75 77Rural 84 77n= 821 898 6,458

*Unless otherwise indicated, differences in percentages are significant with at least a 95% level ofconfidence.


Tab

le2

ProbitRegressions—

Probab

ilityofRep

ortingGam

blingExpen

ditures

Var

iabl

eN

ova

Scot

iaSa

skat

chew

anC

anad

a1C

anad

a2

Intercep

t.517

(.34

1).763

**(.32

5).776

*(.08

5).776

*(.08

6)TotalHH

inco

mebefore

tax

8.16

2E-6*

(3.115

E-6)

.7.629

E-6*

(2.874

E-6)

3.38

8E-6*

(6.512

E-7)

3.40

6E-6*

(6.497

E-7)

Responden

tage15

–24

).355

(.31

5).101

(.27

4)).292

*(.08

3)).299

*(.08

3)Responden

tage25

–34

.116

(.19

1)).118

(.16

6).930

(.04

7).089

***(.04

7)Responden

tage45

–54

).266

(.18

5).254

(.18

2).123

**(.05

1).119

**(.05

1)Responden

tage55

–64

).300

(.22

3).389

***(.21

5).141

**(.06

2).133

**(.06

2)Responden

tage65

+).501

**(.23

1).111

(.22

8)).139

**(.06

4)).153

**(.06

4)Responden

t<9yrsed

ucation

).142

(.17

2)).280

***(.16

5)).133

*(.04

9)).127

*(.04

9)Responden

tcert

ordiploma

).114

(.14

5)).150

(.13

2)).132

*(.04

0)).131

*(.040

)Responden

tuniversity

education

).515

*(.192

)).727

*(.17

4)).555

*(.04

6)).554

*(.04

6)Nospouse

inHH

).100

(.16

1)).200

(.15

7)).158

*(.04

4)).163

*(.04

4)Responden

tan

dspouse

work

FTFY

.567

**(.24

8)).062

(.21

1).099

(.06

1).100

(.06

1)

Responden

tan

dspouse

work

combinationFTFY–

PTFY

).362

(.22

6).080

(.20

7)).092

(.06

0)).096

(.06

0)

#Adults15

+.188

**(.09

5)).051

(.08

5).091

*(.02

5).083

*(.02

4)EIrecipient

.293

***(.16

3).014

(.17

3).132

*(.04

8).133

*(.04

8)So

cial

assistan

cerecipient

.010

(.21

3)).228

(.18

9)).177

*(.05

4)).169

*(.05

4)Most

inco

mefrom

self-employm

ent

).458

**(.20

6)).126

(.19

9)).305

*(.06

3)).308

*(.06

3)Most

inco

mefrom

investmen

ts).729

(.44

8)).635

**(.30

0)).437

*(.098

)).431

*(.098

)


Tab

le2

(Con

tin

ued

)

Var

iabl

eN

ova

Scot

iaSa

skat

chew

anC

anad

a1C

anad

a2

Most

inco

mefrom

governmen

ttran

sfers

.024

(.20

3)).186

(.19

7)).257

*(.05

6)).254

*(.05

6)

Most

inco

mefrom

other

sources

.290

(.24

3)).057

(.25

3)).013

(.07

0)).010

(.06

9)

Onech

ildin

house

).087

(.19

9).025

(.17

1)).095

**(.04

9)).102

(.04

9)Twoormore

childrenin

house

).444

**(.19

0).397

**(.17

6)).079

(.04

9)).089

(.04

9)Resides

inurban

area

>30,00

0.097

(.15

7).266

***(.15

6)Resides

inruralarea

.239

(.17

3)).033

(.19

7)Resides

NFLD

.102

(.11

7)Resides

PEI

).094

(.21

2)Resides

NS

.165

**(.09

0)Resides

NB

).087

(.09

4)Resides

QUE

.339

*(.04

0)Resides

MAN

.099

(.07

9)Resides

SASK

.198

**(.08

7)Resides

ALB

.127

**(.05

7)Resides

BC

.078

(.04

8)Governmen

tcasinospresent

.060

***(.03

4)VLT’spresent

.203

*(.03

1)

Not

e.Allvariab

lesex

cepthousehold

inco

mebefore

taxan

d#ad

ultsaredummyvariab

les.Stan

darderrors

arein

brackets.Sign

ificance

levels:*significant

with99

%co

nfiden

ce,**Sign

ificantwith95

%co

nfiden

ce,***S

ignificantwith90

%co

nfiden

ce.


In Saskatchewan, married couple households that include otheradults are most likely to have gambling expenditures (93%), whileone-person households are least likely (72%). In both provinces, ahigher percentage of married couple households with children gam-ble than do lone parent households. Similarly, households with nospouse are less likely to have gambling expenditures than householdsthat include couples. This difference persists in the regression analy-sis (Table 2), where the probability of gambling is lower for house-holds with no spouse. However, the impact of children on thelikelihood of households having gambling expenditures is less clear.The coefficient for two or more children in the household is positivefor Saskatchewan, but negative for Nova Scotia and Canada.

Family work patterns seem also to affect the likelihood of gam-bling. In Canada, 88% of households, where both spouses work full-time full-year (FTFY), have gambling expenditures, compared to85% of households, where one person works FTFY, and one personworks part time full-year (PTFY), and to 84% of households with atmost only one full-year worker. In the probit regression analysis(Table 2), the coefficient for respondent and spouse work (FTFY) ispositive and significant for Nova Scotia when controlling for income.

Households in all jurisdictions whose main source of income iswages and salaries are also more likely to report gambling expendi-tures. In the probit regression (Table 2), the coefficients on thedummy variables for most income from self-employment, invest-ments, and government transfers are negative and significant forCanada. That is the likelihood of reporting gambling expendituresis lower than for wage and salary earners. In the Nova Scotia regres-sion, however, only the negative self-employment income coefficientis significant and in the Saskatchewan regression only the negativeinvestment income coefficient is significant.3 The coefficients for‘‘EI recipient’’ are also positive and significantly related to theprobability of gambling in the probit regressions for Nova Scotiaand Canada (Table 2). A lower percentage of households withsocial assistance income gamble in each jurisdiction (Table 1), butthe coefficient for ‘‘social assistance recipient’’ is negative and sig-nificant in the probit regression for Canada, yet not for Nova Scotiaor Saskatchewan (Table 2). Thus, EI recipient households are morelikely to spend on gambling, while social assistance recipient house-holds are less likely to gamble. Similarly, in each jurisdiction,


households below the LICO are significantly less likely to gamblethan households above it.

Differences in gambling rates vary by community type. In NovaScotia, gambling rates are higher in rural and larger urban areas, butlower in small (less than 30,000) urban towns (Table 1). In the pro-bit regression, however, the coefficients for area of residence are notsignificant (Table 2). In Saskatchewan, households in the largerurban areas have higher gambling rates compared to those in eithersmall towns or rural areas (Table 1). This difference is confirmed bythe probit regression for Saskatchewan, where the coefficient for‘resides in urban area >30,000’ is positive and significant (Table 2).

We also find that a higher percentage of households report gam-bling expenditures in provinces with VLTs (84%), but there is littledifference between provinces with and without casinos. However, inthe probit regression (Table 2), the coefficients for casinos and VLTsare both significant and positive. Living in a province that offersboth types of gambling increases the probability of householdsreporting gambling expenditures (Eadington, 1998; Henrikssen,1996; Smith & Azmier, 1997; Smith &Wynne, 1999).

GAMBLING HOUSEHOLDS AND THE INTENSITYOF GAMBLING

While the great majority of households report gambling expen-ditures, there are important differences in the intensity of gamblingby households. Prevalence studies typically focus on the gambler(Baseline Market Research, 1996; Shaffer, Hall, & Bilt, 1997; Walker,1996a, 1996b; Wynne, Smith, & Volberg, 1994; Wynne Resources,1998), but we emphasize the quantity of spending by household.These include actual dollars spent on games of chance, gamblingexpenditures as a percentage of before tax household income, andthe expenditure quintile distribution of gambling households. Wecategorize households into Low, Medium or High groups on thebasis of the proportion of household income spent on gambling.Households in the Low group are in the bottom quartile (bottom25%) of the distribution in terms of percent of income spent ongambling, while those in the High group are in the top quartile.Thus, while the top quintile group consists of the 20% of households


who spend the most money on gambling, the High group consists ofthe 25% of households who spend the highest share of their incomesgambling.4

The top 20% of gambling households accounts for 70% ofgambling expenditures. In Nova Scotia, the average expenditure perquintile ranges from $7 in the bottom to $932 in the top. Themean household income in Nova Scotia is $38,024 in the lowestgambling expenditure quintile, $46,437 in the second quintile, and$50,000 in each of the top three quintiles, while in Saskatchewanaverage income continues to increase in the top gambling expendi-ture quintiles to $56,429 and $60,948 respectively. Households inthe Low, Medium and High gambling groups in Nova Scotia spendan average .02%, .32%, and 2.98% of their household incomes ongambling and an average of $15, $141, and $773 on gambling. Thiscompares with $19, $171, and $791 in Saskatchewan and $23, $176,and $893 in Canada. Thus, lower income households are morelikely to be in the High intensity category, a point we elaborate onlater in the paper.

Income, Age and Education

Gambling expenditures increase with household income in Can-ada. In Nova Scotia, they first increase and then decrease, though onlythe lowest income group differs significantly from the overall mean(Table 3). In Saskatchewan, the difference between the lowest andhighest income groups is noticeably wider, with those under $20,000spending less on average and those over $80,000 spending consider-ably more than in Nova Scotia. Our regression analysis (Table 4) con-firms that the level of expenditures increases with income in Canadaand Saskatchewan but not in Nova Scotia, controlling for other vari-ables. The significant negative coefficient for the ‘‘total householdincome before taxes, squared’’ variable for Canada and Saskatchewanshows that gambling expenditures grow at a decreasing rate as incomerises. In Nova Scotia, however, income levels do not affect how muchthose who gamble actually spend as borne out by studying householdswho gamble most intensively. As Table 5 shows, there is a clearincrease by income group in the percentage of households who are inthe top expenditure quintile in Saskatchewan and Canada, but not inNova Scotia. Similarly in the probit regression (Table 6), income is not


Table 3Average Expenditures per Household on Games of Chance*

Nova Scotia Saskatchewan Canada

Mean SE** Mean SE Mean SE

Overall $267 $287 $317Before tax income

$0–$20,000 183 41.77 156 28.23 229 19.29$20,000–$39,999 290 44.98 289 40.41 280 13.70$40,000–$59,999 300 36.36 334 46.90 328 15.09$60,000–$79,999 264 45.91 318 37.86 377 22.39$80,000 and over 278 42.90 363 61.07 380 19.09

Age of reference person<25 273 135.94 109 22.05 191 36.2525–34 160 21.06 210 35.14 215 10.6335–44 236 29.01 247 22.65 292 15.0245–54 326 47.81 332 60.52 345 15.6155–64 374 85.15 426 69.01 431 28.4765 and over 260 38.68 317 55.53 371 21.83

Education of reference PersonLess than 9 years 441 69.35 342 78.95 425 34.65Some/complete high school 285 31.60 323 26.95 362 11.67Post secondary certificateor degree

209 26.15 259 41.88 242 10.53

University certificate ordiploma

178 38.83 151 21.82 201 12.34

Not stated 50 0 352 77.89 160 44.32

Household typeOne person 131 23.58 206 26.78 256 18.09Married couple only 352 51.26 310 34.37 360 14.23Married couple with singlechildren

270 29.29 286 36.00 306 11.90


538 129.77 665 183.27 494 43.81

Lone parent families 127 22.60 184 44.05 184 16.69Other HHs with relativesonly

315 101.42 466 132.26 362 38.26


Table 3 (Continued)



Other householdsunrelated people

176 66.52 124 24.24 402 76.76

Presence of childrenNo children 283 25.05 321 28.75 347 10.42One child 288 62.77 252 47.77 274 15.53Two or more children 190 21.57 215 22.00 239 13.49

Presence of spouseNo spouse 156 19.75 218 23.19 268 14.18Spouse 319 27.05 326 28.35 343 9.21

Work patterns, couples onlyBoth work FTFY 268 23.34 272 25.16 338 14.07One FTFY, one PTFY 408 33.43 273 55.55 374 36.24Other 255 129.81 294 28.15 302 9.58

Main source of incomeWages and salaries 273 25.90 289 25.07 313 9.00Self-employment 355 63.13 339 57.00 343 31.90Investments 91 48.19 159 51.26 445 135.95Government transfers 256 46.42 224 33.67 301 17.11Other sources 208 35.98 449 142.95 342 28.20

Employment insurance incomeRecipient households 265 33.63 320 51.78 325 15.65Non-recipient households 268 23.70 282 21.68 315 8.82

Social assistance incomeRecipient households 150 49.08 303 104.03 239 19.19Non-recipient households 280 21.11 285 19.00 326 8.39

Low-income cut-offHHs below low-incomecut-off

178 47.94 153 24.85 219 18.61

HHs above low-incomecut-off

283 21.53 314 23.38 335 8.53


a significant determinant of being in the top quintile in Nova Scotia,but it is in Saskatchewan and Canada.

Income levels are, however, related to the proportion of incomespent on gambling in Nova Scotia. In the regression analysis(Table 7), the coefficient on ‘‘total household income before tax’’ isnegative and significant in each jurisdiction, confirming that poorerhouseholds spend a higher proportion of their income on gambling.Gambling households in the lowest income group in Nova Scotiaspend 1.9% of their income on gambling, while those in the highestincome group spend only .3% (Table 8). In Saskatchewan, the per-centage of income spent by the lowest income group is lower(1.2%), while that spent by the highest income group is slightlyhigher (.4%). Gambling as a tax, then, is regressive and more so inNova Scotia than elsewhere.

The relationship of household income to Low, Medium andHigh intensity household gambling is revealing. The likelihood ofbeing in the High group declines as household income increases ineach jurisdiction (Table 9). In Nova Scotia and Saskatchewan, 35%of households with incomes less than $20,000 are in the High gam-bling group, compared to 11% and 10%, respectively, of householdswith incomes of at least $80,000. However, only 15% of householdsin the lowest income group are in the Low gambling group in NovaScotia compared to 28% in Saskatchewan, suggesting, once again,that lower income groups in Nova Scotia are gambling relativelymore of their incomes than their Saskatchewan counterparts.

In terms of age, those households with members 55 and overtend to spend higher amounts as well as a higher proportion of their

Table 3 (Continued)



Size of area of residence30,000 and over 307 25.84 296 23.64Less than 30,000 238 79.50 242 45.34Rural 210 27.98 275 56.93

*For households with gambling expenditures, ** SE: Standard error.


Tab

le4

OLSRegressions—

Level

ofGam

blingExpen

ditures

Var

iabl

eN

ova

Scot

iaSa

skat

chew

anC

anad

a1C

anad

a2

Intercep

t26

1.99

1**

(120

.118

))50

.192

(135

.883

)11

1.20

5**

(47.14

9)11

1.64

0**

(48.05

8)TotalHH

inco

me

before

tax

).001

(.00

2).006

**(.00

3).005

*(.00

1).005

*(.00

1)TotalHH

inco

me

before

tax(squared

)5.94

7E-9

(.00

0))2.01

7E-8

(.00

0))1.66

5E-8*

(.00

0))1.69

4E-8*

(.00

0)Responden

tage15

–24

115.91

5(131

.567

))78

.184

(109

.558

))46

.538

(50.26

3))41

.217

(50.24

5)Responden

tage25

–34

)51

.339

(61.90

5)15

.731

(61.49

1))31

.012

(23.67

7))27

.491

(23.66

3)Responden

tage45

–54

66.606

(59.58

3)61

.599

(65.09

0)10

.174

(24.68

6)11

.584

(24.68

4)Responden

tage55

–64

160.09

6**

(76.74

2)17

9.79

7**

(77.77

3)11

2.91

3*(30.79

8)11

6.41

5*(30.78

5)Responden

tage65

+61

.150

(83.30

8)25

6.37

2*(94.63

9)67

.773

***

(34.84

0)72

.102

**(34.79

3)Responden

t<9years

education

161.49

7**

(67.41

2))31

.231

(71.89

8)67

.166

**(27.06

2)64

.603

**(27.01

4)Responden

tcertificate

ordiploma

)94

.747

***

(48.49

1))66

.402

(47.91

3))14

0.96

6*(19.59

0))14

0.96

4*(19.59

0)


Tab

le4

(Con

tin

ued

)

Var

iabl

eN

ova

Scot

iaSa

skat

chew

anC

anad

a1C

anad

a2

Responden

tuniversity

education

)12

1.17

1***

(66.75

8))26

9.63

4*(69.00

8))22

5.24

8*(25.17

2))22

4.08

9*(25.17

1)Nospouse

inHH

)14

5.69

8*(55.92

8))43

.401

(60.72

8)16

.469

(22.80

5)18

.387

(22.80

3)Responden

tan

dspouse

work

FTFY

)13

0.84

1***

(74.08

0))82

.748

(70.06

5))27

.079

(28.22

9))29

.056

(28.22

8)Responden

tan

dspouse

work

combinationFTFY–

PTFY

86.851

(70.70

2))21

.351

(68.53

2)33

.327

(27.68

9)35

.002

(27.69

0)#Adults15

+63

.353

**(28.46

9)56

.290

***

(32.76

7)32

.140

*(11.63

3)34

.193

*(11.60

1)EIrecipient

)81

.720

(50.87

2)14

.774

(61.82

3)22

.444

(22.41

9)18

.659

(22.32

8)So

cial

assistan

cerecipient

)56

.037

(81.10

0)24

4.94

1*(85.28

2))33

.985

(30.31

4))35

.829

(30.30

9)Most

inco

mefrom

self-employm

ent

87.627

(74.69

2)65

.972

(75.82

3)23

.783

(34.33

6)23

.585

(34.31

9)Most

inco

mefrom

investmen

ts)16

2.81

4(232

.260

))26

2.36

9***

(137

.245

)10

0.82

3***

(60.80

8)99

.879

(60.81

5)Most

inco

mefrom

governmen

ttran

sfers

)55

.073

(76.81

4))16

2.98

5***

(86.15

0)10

.148

(31.73

6)7.69

5(31.67

5)


Tab

le4

(Con

tin

ued

)

Var

iabl

eN

ova

Scot

iaSa

skat

chew

anC

anad

a1C

anad

a2

Most

inco

mefrom

other

sources

)17

3.41

4**

(81.40

5)25

.889

(93.90

3))20

.807

(35.36

5))23

.414

(35.32

7)Onech

ildin

house

6.72

6(62.01

3))62

.108

(64.65

2))50

.408

**(24.50

7))8.72

9**

(24.50

7)Twoormore

childrenin

house

)36

.926

(63.52

2))76

.817

(61.93

4))79

.994

*(24.52

6))76

.708

*(24.49

9)Resides

inurban

area

>30,00

045

.780

(61.36

7)83

.454

(62.49

4)Resides

inruralarea

)89

.741

(65.68

4)25

.949

(81.83

6)Resides

NFLD

47.752

(60.51

4)Resides

PEI

6.05

0(122

.478

)Resides

NS

)44

.404

(45.91

1)Resides

NB

21.066

(52.99

2)Resides

QUE

)31

.193

(20.07

0)


Tab

le4

(Con

tin

ued

)

Var

iabl

eN

ova

Scot

iaSa

skat

chew

anC

anad

a1C

anad

a2

Resides

MAN

56.453

(41.73

8)Resides

SASK

)14

.581

(44.57

0)Resides

ALB

60.416

**(29.04

8)Resides

BC

)26

.494

(25.39

5)Governmen

tcasinos

present

)23

.901

(17.74

8)VLT’spresent

4.97

9(15.82

1)

Not

e:Forhouseholdswith

gamblingex

pen

ditures.

All

variab

lesex

ceptousehold

inco

mean

d#ad

ultsaredummyvariab

les.

Stan

dard

errors

arein

brackets.Sign

ificance

levels:*S

ignificantwith99

%co

nfiden

ce,**

Sign

ificantwith95

%co

nfiden

ce,***S

ignificantwith90

%co

nfiden

ce.


Table 5Percentage of Households Who are in the Top Gambling

Expenditure Quintile*

Nova Scotia(%)

Saskatchewan(%)

Canada(%)


Age of reference person Notsignificant

<25 18 3 725–34 12 13 1535–44 19 19 1845–54 26 24 2355–64 21 32 2665 and over 21 20 24

Education of reference personLess than 9 years 41 22 25Some/complete high school 20 25 23Post secondary certificateor degree

16 14 15


12 13 12

Not stated 0 27 5

Household typeOne person 11 14 14Married couple only 23 26 25Married couple with singlechildren

21 18 20


45 44 31

Lone parent families 11 12 11Other HHs with relatives only 25 39 23


Table 5 (Continued)

Nova Scotia(%)

Saskatchewan(%)

Canada(%)


15 5 20

Presence of children Notsignificant

No children 21 23 22One child 20 17 19Two or more children 16 15 14

Presence of spouseNo spouse 13 15 15Spouse 23 23 23

Work patterns, couples only Notsignificant

Notsignificant

Notsignificant

Both work FTFY 20 22 22One FTFY, one PTFY 26 23 22Other 25 25 23

Main source of income All notsignificant

All notsignificant

Wages and salaries 20 21 20(Not

significant)Self-employment 27 28 22

(Not significant)Investments 0 6 15

(significantat 90%)

Government transfers 18 13 20Other sources 19 29 22

(not significant)


Notsignificant

Notsignificant



income on gambling (Tables 3 and 8). The coefficient in the regres-sion analysis is also positive and significantly related to both the levelof gambling expenditure and the proportion of income spent ongambling (Tables 4 and 7). Indeed, in Saskatchewan, the positivecoefficients for ‘‘respondent age 65+’’ indicate that gambling expen-ditures and the proportion of income spent are especially high forsenior households.

The likelihood of being in the top quintile of gambling house-holds in Nova Scotia does not differ significantly by age group. Com-pared to Saskatchewan and Canada, a higher percentage of youngerhouseholds and a lower percentage of older households are in thetop quintile in Nova Scotia (Tables 5 and 9). The coefficients for both‘‘respondent age 55–64’’ and ‘‘respondent age 65+’’ are positive andsignificant in the Saskatchewan and Canada regressions (Table 6). InCanada, households in the lowest age group are significantly lesslikely to be in the top gambling quintile. But in Nova Scotia and

Table 5 (Continued)

Nova Scotia(%)

Saskatchewan(%)

Canada(%)

Social assistance incomeRecipient households 9 11 14Non-recipient households 21 21 21

Low-income cut-offHHs below low-incomecut-off

12 9 13


21 22 21

Size of area of residence Notsignificant

30,000 and over 25 20Less than 30,000 14 17Rural 14 21

Note. Unless otherwise indicated, differences in percentages are significant with at least a 95% levelof confidence.? *For households with gambling expenditures.


Tab

le6

ProbitRegressions—

Probab

ilityofBeingin

theTopGam

bling

Expen

ditureQuintile

Var

iabl

eN

ova

Scot

iaSa

skat

chew

anC

anad

a1C

anad

a2

Intercep

t)1.38

6*(.34

8))1.78

*(.352

))1.08

8*(.08

7))1.06

8*(.08

9)TotalHH

inco

mebefore

tax

)2.07

E)7

(2.525

E)6)

.1.0E)5*

(2.49E

)6)

4.58

9E)6*

(6.343

E)7)

4.57

2E)6*

(6.33E

)7)

Responden

tage15

–24

.276

(.41

1)).808

(.51

3)).493

*(.138

)).485

*(.138

)Responden

tage25

–34

).177

(.20

3)).017

(.18

7)).011

(.05

2)).010

(.05

2)Responden

tage45

–54

.143

(.17

6).108

(.18

5).063

(.05

2).065

(.05

2)Responden

tage55

–64

).013

(.23

4).467

**(.21

6).231

*(.063

).231

*(.063

)Responden

tage65

+.082

(.25

7).590

**(.27

5).287

*(.073

).284

*(.072

)Responden

t<9

yearsed

ucation

.716

*(.186

)).174

(.20

0).022

(.05

4).025

(.05

3)Responden

tcert

ordiploma

).287

***(.151

)).506

*(.144

)).351

*(.042

)).349

*(.042

)Responden

tuniversity

education

).501

**(.21

8)).907

*(.219

)).642

*(.059

)).640

*(.059

)Nospouse

inHH

).209

(.17

0).085

(.17

4)).129

*(.048

)).129

*(.048

)Responden

tan

dspouse

work

FTFY

).237

(.22

0)).242

(.19

9)).023

(.05

8)).023

(.05

8)

Responden

tan

dspouse

work

combinationFTFY)

PTFY

.169

(.20

8).225

(.19

4).049

(.05

8).050

(.05

7)

#Adults15

+.236

*(.082

).151

***(.091

).079

*(.023

).080

*(.023

)


Tab

le6

(Con

tin

ued

)

Var

iabl

eN

ova

Scot

iaSa

skat

chew

anC

anad

a1C

anad

a2

EIrecipient

).025

(.15

2).230

(.17

4).067

(.04

7).069

(.04

7)So

cial

assistan

cerecipient

).474

***(.281

).080

(.26

2)).155

**(.06

6)).156

**(.06

6)Most

inco

mefrom

self-employm

ent

.219

(.21

7).206

(.20

2).034

(.07

1).033

(.07

1)

Most

inco

mefrom

investmen

ts)8.79

1(7.20

9E9)

)1.02

6**(.499

)).348

*(.133

)).344

*(.133

)Most

inco

mefrom

governmen

ttran

sfers

).055

(.23

1)).429

***(.245

)).035

(.06

4)).029

(.06

4)

Most

inco

mefrom

other

sources

).068

(.24

8).034

(.25

5)).097

(.07

3)).096

(.07

3)

Onech

ildin

house

).040

(.18

7)).225

(.19

1)).089

***(.052

)).087

(.05

2)Twoormore

childrenin

house

).048

(.19

8)).224

(.18

5)).266

*(.054

)).266

*(.054

)Resides

inurban

area

>30,00

0.369

***(.197

).311

***(.186

)Resides

inruralarea

).218

(.21

7).232

(.24

0)Resides

NFLD

.287

**(.12

0)Resides

PEI

).186

(.27

7)Resides

NS

).146

(.10

1)Resides

NB

).003

(.11

1)Resides

QUE

).001

(.04

2)


Tab

le6

(Con

tin

ued

)

Var

iabl

eN

ova

Scot

iaSa

skat

chew

anC

anad

a1C

anad

a2

Resides

MAN

.013

(.08

7)Resides

SASK

.001

(.09

5)Resides

ALB

).006

(.06

2)Resides

BC

.012

(.05

3)Governmen

tcasinospresent

).028

(.03

7)VLT’spresent

).003

(.03

3)

Not

e:Forhouseholdswithgamblingex

pen

ditures.Allvariab

lesex

cepthousehold

inco

me,

#ad

ultsaredummyvariab

les.Stan

darderrors

arein

brackets.

Only

sign

ificantco

efficien

tsareshownin

full,iftherearemore

than

3zerosafterthedecim

alpoint.Thus,someco

efficien

tsap

pearas

.000

or).000

.Sign

ificance

levels:*S

ignificantwith99

%co

nfiden

ce,**Sign

ificantwith95

%co

nfiden

ce,***S

ignificantwith90

%co

nfiden

ce.


Tab

le7

OLSRegressions—

Gam

blingExpen

dituresas

aProportionofTotalHousehold

inco

me

Var

iabl

eN

ova

Scot

iaSa

skat

chew

asC

anad

a1C

anad

a2

Intercep

t.020

**(.00

9).012

*(.004

).014

*(.002

).015

*(.002

)TotalHH

inco

mebefore

tax

)3.90

E)7*

(1.4E)7)

)1.32

E)7*

**(8.0E)8)

)2.12

E)7*

(4.0E)8)

)2.11

E)7*

(4.0E)8)

TotalHH

inco

mebefore

tax

(squared

)1.43

0E)12

***

(.00

0)5.06

8E)13

(.00

0)7.82

3E)13

*(.00

0)7.80

2E)13

*(.00

0)Responden

tage15

)24

).002

(.00

9)).003

(.00

3)).004

(.00

3)).004

(.00

3)Responden

tage25

)34

).001

(.00

4)).000

(.00

2)).001

(.00

1)).001

(.00

1)Responden

tage45

)54

.010

**(.00

4).002

(.00

2).002

(.00

1).002

(.00

1)Responden

tage55

)64

.000

(.00

5).004

***(.002

).004

**(.00

2).004

**(.00

2)Responden

tage65

+).008

(.00

6).005

***(.003

)).002

(.00

2)).002

(.00

2)Responden

t<9

yearsed

ucation

.015

*(.005

)).000

(.00

2).006

*(.002

).006

*(.001

)Responden

tcert

ordiploma

).001

(.00

4)).002

(.00

1)).003

*(.001

)).003

*(.001

)Responden

tuniversity

education

.000

(.00

5)).005

**(.00

2)).002

(.00

1)).002

(.00

1)Nospouse

inHH

).003

(.00

4)).003

(.00

2).002

(.00

1).002

(.00

1)Responden

tan

dspouse

work

FTFY

).006

(.00

5)).002

(.00

2)).000

(.00

1)).000

(.00

1)

Responden

tan

dspouse

combinationFTFY)

PTFY

.005

(.00

5)).001

(.00

2).002

(.00

1).002

(.00

1)


Tab

le7

(Con

tin

ued

)

Var

iabl

eN

ova

Scot

iaSa

skat

chew

asC

anad

a1C

anad

a2

#Adults15

+.000

(.00

2).001

(.00

1).000

(.00

1).000

(.00

1)EIrecipient

).006

(.00

4)).001

(.00

2)).000

(.00

1)).000

(.00

1)So

cial

assistan

cerecipient

).015

**(.00

6).005

**(.00

3)).006

*(.002

)).006

*(.002

)Most

inco

mefrom

self-employm

ent

).001

(.00

5).001

(.00

2)).000

(.00

2)).000

(.00

2)

Most

inco

mefrom

investmen

ts.000

(.01

7)).005

(.00

4).022

*(.003

).022

*(.003

)

Most

inco

mefrom

governmen

ttran

sfers

.009

(.00

6)).002

(.00

3).006

*(.002

).006

*(.002

)

Most

inco

mefrom

other

sources

.001

(.00

6).001

(.00

3).001

(.00

2).001

(.00

2)

Onech

ildin

house

.001

(.00

5)).002

(.00

2)).000

(.00

1)).000

(.00

1)Twoormore

childrenin

house

.001

(.00

5)).002

(.00

2)).001

(.00

1)).001

(.00

1)Resides

inurban

area

>30,00

0.002

(.00

4).002

(.00

2)Resides

inruralarea

.002

(.00

5).000

(.00

3)Resides

NFLD

.002

(.00

3)Resides

PEI

.000

(.00

6)Resides

NS

.000

(.00

2)


Tab

le7

(Con

tin

ued

)

Var

iabl

eN

ova

Scot

iaSa

skat

chew

asC

anad

a1C

anad

a2

Resides

NB

.001

(.00

3)Resides

QUE

.000

(.00

1)Resides

MAN

.002

(.00

2)Resides

SASK

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Table 8Average Gambling Expenditures as a Percentage of Total Household

Income*


Mean% SE** Mean% SE Mean% SE

Overall .9 .8 .9Before tax income$0-$20,000 1.9 .68 1.2 .18 2.0 .21$20,000 – $39,999 1.0 .16 1.0 .14 1.0 .05$40,000 – $59,999 .6 .08 .7 .09 .7 .03$60,000 – $79,999 .4 .07 .5 .06 .6 .03$80,000 and over .3 .04 .4 .07 .4 .02

Age of reference person< 25 1.0 .32 .6 .14 .6 .0825–34 .4 .06 .5 .09 .6 .0335–44 .5 .07 .5 .06 .6 .0345–54 1.4 .59 .8 .16 .8 .0955–64 1.1 .29 1.2 .21 1.4 .2165 and over 1.2 .19 1.2 .20 1.5 .09

Education of reference personLess than 9 years 2.7 1.13 1.3 .25 1.9 .25Some/complete high

school.9 .13 .9 .09 1.0 .03

Post secondary certificateor degree

.5 .07 .6 .11 .5 .02


.3 .06 .3 .05 .5 .12

Not stated .1 0 1.8 .93 .6 .36Household type .One person 1.6 .76 1.1 .14 .2 .17Married couple only 1.1 .18 .9 .15 .9 .04Married couple with single

children.6 .13 .6 .10 .5 .03


1.1 .31 1.1 .29 .8 .07

Lone parent families .6 .10 .6 .10 .6 .05


Table 8 (Continued)



Other HHs with relativesonly

1.0 .37 1.1 .25 .9 .10

Other householdsunrelated people

.3 .10 .31 .07 .1.1 .27

Presence of childrenNo children 1.1 .19 1.0 .09 1.1 .06One child .8 .31 .5 .10 .6 .04Two or more children .4 .05 .5 .05 .5 .03

Presence of spouseNo spouse .8 .10 .9 .09 1.2 .10Spouse 1.1 .38 .7 .08 .7 .02

Work patterns, couples onlyBoth work FTFY .5 .08 .4 .04 .5 .02One FTFY, one PTFY 1.4 .78 .5 .13 .7 .07Other 1.0 .19 1.0 .09 1.1 .06

Main source of incomeWages and salaries .6 .09 .6 .06 .6 .02Self-employment .7 .14 .9 .18 .7 .06Investments .2 .11 .5 .23 2.9 1.35Government transfers 1.8 .51 1.2 .17 1.7 .12Other sources .6 .11 1.3 .40 .9 .07

Employment insurance incomeRecipient households .7 .08 .7 .12 .7 .04Non-recipient households 1.0 .18 .8 .07 .9 .05

Social assistance incomeRecipient households .7 .14 1.3 .30 1.1 .07Non-recipient households .9 .15 .7 .06 .9 .04

Low-income cut-offHHs below low-income

cut-off2.1 .84 1.1 .16 1.9 .21


Saskatchewan, households with the youngest and oldest age groupsare more likely (35% and 36% and 32% and 37%, respectively) to bein the High intensity group. In Canada, those in the youngest agegroup have only a 20% likelihood of being in the High intensitygroup compared to 40% for the senior age group (Table 9).

In terms of formal education the highest average gamblingexpenditures (Table 3) are by households where the respondent hasless than 9 years of education. In the regression analysis on this vari-able, education is significant and positively related to both the levelof gambling expenditures and gambling as a proportion of incomein Nova Scotia and in Canada. In Nova Scotia, those in the lowesteducational group are not more likely to gamble, but those from thisgroup who do gamble spend more than other educational groups.Conversely, households with university educated respondents spendsignificantly less on gambling in all jurisdictions (Tables 4 and 7).

Furthermore, in Nova Scotia fully 40% of households where therespondent has less than 9 years of education are in the top quintile,compared to rates of 22% and 25% in Saskatchewan and Canada(Table 5). The coefficient in the probit analysis is also significantand positively related to being in the top quintile, after controllingfor income and other variables (Table 6). Similarly, the percentageof those in the lowest educational group who proportionately spendmore of their income on gambling is much higher in Nova Scotiathan elsewhere (Table 9). University educated households, on the

Table 8 (Continued)




.7 .07 .7 .07 .7 .02

Size of area of residence30,000 and over .80 .10 .8 .07Less than 30,000 .90 .31 .7 .21Rural 1.1 .38 .9 .17

*For households with gambling expenditures, **SE: Standard error.


Table 9Percentage of Households Who are in the High Gambling Group(top 25%, Gambling Expenditures as a Proportion of Income)*



Age of reference person<25 35 32 2025–34 17 17 1735–44 19 18 1845–54 27 23 2355–64 27 34 3565 and over 36 37 40

Education of reference personLess than 9 years 59 41 44Some/complete high school 26 30 30Post secondary certificate or

degree18 17 16


7 8 9

Not stated 0 55 17

Household type Notsignificant

One person 24 32 32Married couple only 31 31 30Married couple with single

children21 14 17


34 40 26

Lone parent families 24 25 21Other households with

relatives only33 40 27


Table 9 (Continued)



11 10 25

Presence of children Significantat 90%

No children 28 30 29One child 23 22 19Two or more children 16 12 15Presence of spouse Not

significantNo spouse 26 30 29Spouse 24 22 23

Work patterns, couples onlyBoth work FTFY 17 17 18One FTFY, one PTFY 23 15 18Other 28 29 29

Main source of incomeWages and salaries 21 19 19Self-employment 25 (Not

significant)30 (Not

significant)24 (Not

significant)Investments 0 (Not

significant)18 (Not

significant)26 (Not

significant)Government transfers 36 39 42Other sources 24 (Not

significant)31 (Not

significant)27 (Not

significant)


Notsignificant

Notsignificant


Social assistance income Notsignificant



other hand, are less likely to be in the top quintile or in the Highgroup. So gambling expenditures are generally inversely related toeducation on all measures of intensity and this pattern is especiallyacute in Nova Scotia.

Household Composition, Sources of Income and Geographical Areas

Differences in spending levels by household type and per adult(Table 3) show that lone parent households who gamble have thelowest expenditure levels in both Nova Scotia and Canada. Marriedcouple households with single children spend less than householdswho have couples without children (also less per adult). Lone par-ent households and households with married couples with childrenare less likely to be in the top quintile. Similarly, the percentage ofhouseholds of married couples with single children who are in theHigh gambling group is also relatively low (Table 9). In the regres-sion analysis, the negative relationship between the presence of chil-dren in households and the level of expenditures is significant forCanada, but not for Nova Scotia or Saskatchewan (Table 4). Thepresence of children in households is also associated with a lowerprobability of being in the top spending quintile in Canada (Tables

Table 9 (Continued)


Low-income cut-offHouseholds below low-income

cut-off35 36 40

Households above low-incomecut-off

23 23 22

Size of area of residence30,000 and over 28 24Less than 30,000 23 24Rural 21 31

Note: Unless otherwise indicated, differences in percentages are significant with at least a 95% levelof confidence.*For households with gambling expenditures.


5 and 6). Moreover, the presence of children in households is notsignificantly related to the proportion of income spent on gam-bling. But the average percentage of income spent on gambling islower for households with children, as is the percentage of house-holds with children who are in the High gambling group in Sas-katchewan and Canada (Tables 7–9).

The absence of a spouse is associated with lower average spend-ing on gambling (Table 3), and this is significant in the Nova Scotiaregression (Table 4). Similarly, a lower percentage of householdswithout a spouse are in the top spending quintile compared to thosehouseholds with one (Table 5), although this relationship is only sig-nificant in the Canada regressions (Table 6). Average gamblingexpenditure as a percentage of income, on the other hand, is higherin households without a spouse (Table 8), but this relationship is notsignificant in any regression analysis (Table 7). Households with nospouses are also more likely to be in the High gambling group inSaskatchewan and Canada, but not in Nova Scotia.

Work patterns do not seem to affect the intensity of gambling byhousehold. In Nova Scotia and Canada, the highest average spendingand spending as a percentage of income, are in households whereone partner works FTFY and one works PTFY (Tables 3 and 8). Thispattern is supported by the regression result for Nova Scotia thatfinds that the coefficient for ‘‘respondent and spouse work full time’’is significant, and negatively related to the level of gambling expendi-tures (Table 7). Couples in households who work both FTFY aremore likely than other couples in households to gamble, but spend-ing is still relatively low.

We also find few significant differences in either the amount ofmoney or the proportion of income spent on gambling in relation tomain sources of income in households. In the Nova Scotia regres-sions (Tables 4 and 7), the only significant income variable is ‘‘mostincome from other sources’’ which has a significant negative coeffi-cient in the regression for level of gambling expenditures. In theCanadian regressions, both the amount and proportion of incomespent gambling are significantly higher for those households whosemain income source is from investments. However, in the Saskatche-wan regression the relationship is reversed and, in addition, gam-bling expenditures are significantly lower for households whose mainsource of income is government transfers (Table 4).


One such transfer payment is EI. Gambling spending levels donot vary significantly between EI recipient households and other typesof households. Nor does the proportion of income spent by thosehouseholds who gamble vary significantly (Tables 4 and 7). House-holds with social assistance recipients in Nova Scotia and Canada,however, spend a lower proportion of their income gambling whilethose households in Saskatchewan spend a higher proportion andhave a higher level of spending (Tables 4 and 7). Sources of house-hold income are not significant determinants of being in the topgambling expenditure quintile in Nova Scotia. But in the Saskatche-wan regression the coefficient for most income from governmenttransfers is actually negative and significant (Table 6) as is the coeffi-cient for most household income from investments. Interestingly,however, those households whose main source of income is govern-ment transfers are somewhat more likely to be in the High group inall jurisdictions (Table 9). While receipt of EI does not affect theprobability of being in either the top quintile or the High group, thesame cannot be said of social assistance. Social assistance recipienthouseholds have a lower probability of being in the top quintile inNova Scotia and Canada, but they have a higher probability of beingin the High intensity group in Canada and Saskatchewan (Table 9).

Gambling expenditure levels are higher for households in urbanareas in Nova Scotia and Saskatchewan compared to households intowns or rural areas. But the percentage of income spent gambling ishighest among households in rural areas in both provinces (Table8). These differences, however, are not significant in our regressionanalysis (Tables 4 and 7). Households in urban areas are more likelyto be in the top gambling expenditure quintile in Nova Scotia andSaskatchewan and in the high gambling group in Nova Scotia only(Tables 5 and 9).

GAMBLING AND FINANCIAL WELL BEING

Our analysis raises a number of important questions. Is thefinancial security of households affected by gambling expenditures?Is spending on necessities compromised by gambling? Are savingsbeing depleted? Are future financial plans affected by gamblingpractices?


Spending on Necessities

In comparing spending of households who gamble and thosewho do not,5 we find that gambling households spend more on foodfor home and principal accommodations. The coefficients on thegambling variables are not significant predictors of expenditures onfood for home. Where the coefficients are significant, however, theyare positively related to spending on food. Households who gambleactually spend more on food at home, after controlling for othervariables, including income. In the regression analysis using the Low,Medium, and High variables, the coefficients are also positive, indi-cating higher spending on food by these groups than bynon-gambling households.

No gambling variables have significant coefficients for expendi-tures for principal accommodation in Nova Scotia or Saskatche-wan. However, in the Canada sample gambling households spendmore than non-gambling households on their principal accommo-dation. Amongst gambling households, expenditures on principalaccommodation decrease as gambling expenditures increase. Fur-thermore, the proportion of income spent gambling is not a sig-nificant predictor of spending on principal accommodation.However, the intensity of household gambling variables (Low, Med-ium, High) has significant positive coefficients in the Canadaregression sample. This suggests that gambling expenditures inhouseholds do not negatively affect spending on the basic necessi-ties of food and shelter. Like spending on food and accommoda-tion, the probability of gambling is positively related to householdincome.

Changes in Net Worth

We find little difference between gambling and non-gamblinghouseholds with regard to debt.6 On average both types of house-holds increase their net worth. However, as a percentage of house-hold income, the average change for gambling households isslightly negative in Nova Scotia and Canada. In the regression anal-ysis, the level of household gambling expenditures is negativelyrelated to the net change in assets minus liabilities. This negativepattern holds as well for the proportion of income spent by house-


holds on gambling in Canada and Saskatchewan. The change innet worth, moreover, worsens as the amount of gambling increasesin either absolute or relative terms. In the Nova Scotia and Canadaregressions, there are significant negative coefficients for the Highgambling group. For these households gambling is negatively affect-ing their net worth.

Saving for Retirement

Another indicator of financial well being is the net change inRRSP balances.7 We find that changes are lower for non-gamblinghouseholds. The coefficient for the level of gambling expenditures issignificant and negatively related to the change in RRSP balances inhouseholds in each jurisdiction. Gambling as a proportion of incomeis less clearly related to the change in RRSP balances in households.The only significant and negative regressions are for the ‘‘gamblingexpenditures as a proportion of income’’ and the High gamblinggroup variables in Canada. This suggests that the amount spent ongambling reduces savings for retirement. But since gambling expen-ditures are positively related to spending on both food and shelter,the key distinction may be between spenders and savers, rather thangambling and non-gambling households.

Savings

We use total household income minus total expenditures as anindicator of the amount households saved (or dissaved) in a year(i.e. the change in savings, not total savings). Gambling households,on average, save more than non-gambling households. However,the regression results show a negative relationship between gam-bling and saving, after controlling for other determinants of saving.The significant negative coefficients on the gambling variables indi-cate that gambling households save less than non-gambling house-holds, and that annual household savings decrease as gamblingexpenditures increase. In regressions using other gambling vari-ables, the proportion of household income spent on gambling hasa significant negative impact on household savings in Canada andSaskatchewan, but not in Nova Scotia. However, in Nova Scotia andCanada, the coefficients for the Medium and High gambling vari-


ables are negative and significant. Thus, households who spend arelatively low proportion of their incomes gambling are not losingtheir savings. But those households who spend proportionatelymore of their income on gambling are saving less and thereforeare putting their financial futures at risk.

GAMBLING AND OTHER DISCRETIONARY AND LEISURESPENDING

Spending on games of chance may be either a substitute or acomplement to other discretionary consumer spending (Marfels,1995, 1997). Is gambling displacing money from other leisure activi-ties or is it part of an expanding package of recreational spending byconsumers? How are gambling expenditures related to other catego-ries of discretionary spending? Do the expenditures of gamblinghouseholds on other recreational/leisure goods and services differfrom non-gambling households?

When comparing gambling and non-gambling households onrecreation expenditures we find that the average spending is slightlylower for non-gambling households. The most obvious anomalies,however, are spending on alcohol from licensed establishments andfood from restaurants. For example, in Nova Scotia, households whogamble spend $1,361 on food from restaurants compared to $1,234for non-gambling households. There appears to be a complementbetween gambling and other leisure activities. Gambling householdsin Nova Scotia also spend a larger share of their incomes on recrea-tional items than do non-gambling households. But among gamblinghouseholds, Nova Scotians spend fewer dollars and a lower propor-tion of their income on gambling than on all other recreationalproducts except alcohol.

The regression analysis8 relating spending to demographicvariables generally shows spending on all items to be positivelyrelated to household income and negatively related to age inhouseholds, although not all age variables are significant in eachjurisdiction. Spending is also generally higher in households with-out a spouse and without children. In every regression where agambling variable has a significant coefficient, the sign is positive.In other words, spending on the other discretionary items is unaf-


fected by gambling, is higher for gambling households, orincreases with the amount of money spent on gambling. Thusgambling expenditures are complements not substitutes for spend-ing on recreation, alcohol, food from restaurants, and home enter-tainment.

In the Nova Scotia regressions gambling activity has no impacton the other types of household spending, after controlling forfactors such as age and income. However, the coefficient on thedummy variable for households reporting gambling expenditures issignificant and positive for total household recreation spendingand for household spending on food from restaurants. The coeffi-cients for the gambling intensity variables are significant in theNova Scotia regression for household expenditures on alcoholfrom licensed establishments. These households then have higherlevels of alcohol expenditure than non-gambling households.Indeed, it is the High gambling group of households who arespending the most on alcohol. Similarly, the significance of theHigh and Medium gambling dummy variables in the Nova Scotiaregression for household spending on food from restaurants indi-cates that those households who spend a relatively high proportionof their incomes gambling also spend more on restaurant meals.The findings for Saskatchewan are similar except for householdexpenditures on food from restaurants. In the regressions for Can-ada, gambling expenditures are positively related to all other lei-sure/entertainment spending categories. Higher spending levelsfor all items are also found for households in the High andMedium gambling groups.

The generally positive relationship between gambling expendi-tures and discretionary household spending is not found with respectto charitable donations. This relationship is negative in each jurisdic-tion. Average charitable donations are lower for households withgambling expenditures compared to those without. In the regres-sions the gambling variables do not have significant coefficients inNova Scotia or Saskatchewan. However, in Canada, the coefficient issignificant and negative, as are the coefficients for gambling house-hold groups (High, Medium, Low) compared to non-gamblinghouseholds. So there may be a ‘‘cost’’ that charitable organizationshave to absorb as a consequence of the growth of gambling house-holds.


CONCLUSION

There are, then, considerable differences in the likelihood andthe quantity of gambling as they relate to both consumer characteris-tics and the convenience gambling marketplace. The spread of gam-bling products and services is differentially impacting households.While household income is positively associated with the likelihoodof gambling, it is not a predictor of the amount spent on gambling.Low income households are over-represented in the top gamblingexpenditure quintiles and spend a larger percentage of their incomeon gambling products than do other household income groups. Theconvenience and new expedience of gambling in Canada has con-tributed to a regressive relationship whereby the economic costs ofgambling are increasingly borne by those who can least afford thefinancial costs and related social problems.

Gambling is also distributed across the age structure. Highergambling rates are generally found in middle age household groups.But another pattern seems to be forming: both the youngest and old-est age groups have a strong likelihood of being in the High intensitygroup, especially in Nova Scotia and Saskatchewan. This suggests thatthe spread of instant, readily available de-skilled gambling productsis creating what Cook and Yale (1994) call the elderly and the adoles-cent gambler. These age groups are gambling more intensely thanothers, and the former is now facing loss of savings, declining networth and loss of retirement income.

Gambling is diffuse and dispersed geographically, but gamblingrates are significantly higher in households in urban areas and prov-inces where casinos and VLTs are available. Households in urbancommunities are more likely to be in the top gambling quintile andin the High gambling group. Perhaps the ‘‘casino effect’’ capturesmore affluent gambling households in metropolitan areas, or urbanenvironments contain more instant, accessible and electronic gam-bling products (Dickerson, 1996; Eadington, 1996, 1998; Henrikssen,1996; McMillan, 1996; Walker, 1996a, 1996b).

Gambling is also distributed widely across the educational struc-ture. There is little correlation between educational levels and gam-bling rates, except that university-educated households gamble lessand are less likely to be in the top quintile or High intensity house-hold gambling group. However, gamblers in the lowest educational


household group gamble more intensely, especially in Nova Scotiaand Canada. In Nova Scotia, six out of ten households in the Highintensity gambling group are households where the education of thereference person is less than 9 years. Most new games of chancerequire little skill, planning or knowledge to play (Dickerson, 1996;McMillan, 1996; Stokowski, 1996). The de-skilled gambler is now acrucial consumer of gambling products in Canada and their popular-ity is potentially pernicious for less educated players. In this sense,gambling may be an unfortunate ‘‘tax on the uneducated’’, since rev-enues to governments and operators come disproportionately fromsociety’s have-nots and less educated (Clotfelter and Cook, 1989:215–234; Eadington, 1996: 250; Nova Scotia Department of Health, DrugDependency Services, 1998).

Gambling rates and expenditures vary by types of household.While there are different patterns of spending and intensity involvingcouples with or without children and some variation by jurisdiction,our data suggest that the spread of gambling is effectively rearrang-ing household entertainment and discretionary spending in order tocapture local consuming households as gamblers.

All types of sources of household income are used to gamble.Households whose mainstay is wages and salaries are more likely toreport gambling expenditures but not to gamble more money ormore intensely than households with other income sources. Interest-ingly, households with social assistance income sources are less likelyto gamble, except in Nova Scotia where households with employmentinsurance income have a higher probability of gambling. There is noevidence that households who depend on government transfer pay-ments gamble more intensely than other households. They actuallyspend a lower percentage of their income on gambling and are lesslikely to be in the top gambling quintile. This suggests that gamblingis not segmented in lone parent or one-person families or dispropor-tionately relies on sources of government assistance. The gamblingmarketplace is normalized and heavy gambling is more appropriatelydetermined by factors such as before tax income, education and agerather than household composition or income sources.

Gambling expenditures are affecting the financial well being ofhouseholds in Canada. While spending on basic necessities is notnegatively impacted to date, the ability of households to save andplan is being eroded. In every jurisdiction, the net change in assets


minus liabilities, in RRSPs and in savings in households decreases asgambling expenditures increase. The spread of commercial gamblingis especially pernicious for those households in the High gamblinggroup. Yet overall gambling is not a substitute for other discretionaryspending. So far discretionary spending by households is unaffectedby the spread of commercial gambling, either because discretionaryspending is also higher for gambling households or because it isincreasing along with the growth and intensity of gambling. Up untilnow gambling expenditures seem to be complements in an expand-ing package of recreational spending by consumers. The emergingsubstitute, however, appears to be donations to charities. Gamblingmay be starting to displace household money that might otherwisehave been earmarked for benevolent causes.

ACKNOWLEDGMENT

The authors wish to acknowledge the Alcohol and GamingAuthority of the Province of Nova Scotia for their financial assistancein conducting this research.

NOTES

1. Marshall’s (1998) expense figures, by comparison, are based on ‘‘before winnings’’, since shehad access to Statistics Canada unpublished data that included both wagers and winnings.

2. Given the smaller sample sizes in Nova Scotia and Saskatchewan, the regression results ofteninclude fewer significant coefficients than when the Canadian sample is used. This makes itdifficult to compare a province with the national findings. We expect that, with a larger sam-ple, some variables that are not significant at the provincial level might become significant.These cautions should be borne in mind in interpreting our results.

3. It should be borne in mind that sample size considerations are important in interpretingthese differences. The sample sizes in Nova Scotia and Saskatchewan are much smaller thanthe Canadian sample size and so the regression results often include fewer significant coeffi-cients. This sometimes makes it difficult to compare a province with the national findings.

4. It should be noted that our high intensity groups of 20% or 25% of gambling householdsinclude many people who gamble responsibly. Prevalence studies show that about 5% of allgamblers in society are problem gamblers (Baseline Market Research, 1996; Shaffer, Hall &Bilt, 1997; Wynne, Smith, & Volberg, 1994; Wynne Resources, 1998).

5. We also estimated a set of regressions to test whether differences in spending on these neces-sities are related to gambling behaviour, after controlling for income and demographic char-acteristics. For each type of expenditure we tried three different specifications of‘‘gambling’’: (a) using dummy variables for being in the Low, Medium, or High gamblinggroup (compared to non-gambling households); (b) using ‘‘expenditures on gambling’’ aswell as a dummy variable for whether the household reports any gambling expenditures; and


(c) using ‘‘gambling expenditures as a proportion of household income’’ as well as a dummyvariable for whether the household reports any gambling expenditures.

6. The FAMEX data set does not include a measure of the level of debt, or even changes indebt levels, but it does have a measure of the ‘‘net change in assets minus liabilities.’’ How-ever, interpretation of this variable is difficult, as it measures the change in net worth, not itslevel. Thus, a very wealthy household, for example, could have a negative change in networth and still be rich, while a household with negative net worth could show a positivechange, as debts are paid down. Nevertheless this measure does indicate whether the house-hold is accumulating or disaccumulating wealth, or, alternatively, whether it is moving from aworse to a better debt position.

7. The FAMEX data set is the net changes in RRSP balances. So it is the direction of change,not the level of change, which is captured in this measure, and this can be negative (even forthose with high RRSP balances).

8. Variables are included in these regressions to determine if gambling activity affects spending,after controlling for demographic variables. As in the regressions reported earlier, we triedthree different specifications of gambling behavior (see Note 5 for details).

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