Skip to main content
SpringerLink
Log in

Social Capital and Gambling: Evidence from Australia

  • Original Paper
  • Published:
Journal of Gambling Studies Aims and scope Submit manuscript

Abstract

The prevalence of problem gambling in many countries necessitates research that examines factors influencing excessive and addictive consumption. We consider how social capital impacts gambling participation for a large representative sample of the Australian population. Specifically, we examine the association between social capital and gambling addiction using data from the Household, Income and Labour Dynamics in Australia survey. We address the endogeneity of social capital by instrumenting for social capital using an urban/rural reversed measure of ethnic diversity. Our main findings suggest that higher levels of social capital are associated with lower gambling risks measured by the Problem Gambling Severity Index. This general finding is robust to alternative ways of measuring social capital and gambling, and alternative estimation approaches. We also find that the effect of social capital is stronger in the case of problem gamblers compared to gamblers in other risk categories.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. http://natcen.ac.uk/our-research/research/british-gambling-prevalence-survey/.

  2. Our focus on waves 6 to 14 for the second and third measures of social capital is to ensure that the first year of data corresponds with the first wave in which the social capital modules were introduced for the first measure of social capital. Further, it allows us to appropriately instrument for social capital, which we discuss in the next section.

  3. \(FRACTIONALIZATION_{J} = 1 - \sum\nolimits_{e = 1}^{N} {S_{eJ}^{2} }\), where \(s_{ej}\) is the share of ethnic group \(e\) in neighbourhood (postcode) \(j\).

  4. Using country of birth of respondents’ father rather than respondents’ country of birth allows us to capture ‘ethnicities’ of respondents who were born to first generation migrants in Australia.

  5. See Lewbel (2012) for details on how identification is achieved.

References

  • Ambrey, C., & Fleming, C. (2014). Public greenspace and life satisfaction in urban Australia. Urban Studies, 51(6), 1290–1321.

    Google Scholar 

  • Appau, S., Awaworyi Churchill, S., & Farrell, L. (2018). Social integration and subjective wellbeing. Applied Economics. https://doi.org/10.1080/00036846.2018.1528340.

    Article  Google Scholar 

  • Armstrong, A., & Carroll, M. (2017). Gambling activity in Australia: Findings from wave 15 of the Household, Income and Labour Dynamics in Australia (HILDA) Survey. Melbourne: Australian Institute of Family Studies.

    Google Scholar 

  • Awaworyi Churchill, S., & Farrell, L. (2018). The impact of gambling on depression: New evidence from England and Scotland. Economic Modelling, 68, 475–483.

    Google Scholar 

  • Awaworyi Churchill, S., & Mishra, V. (2017). Trust, social networks and subjective wellbeing in China. Social Indicators Research, 132(1), 313–339.

    Google Scholar 

  • Awaworyi Churchill, S., & Smyth, R. (2017). Ethnic diversity and poverty. World Development, 95, 285–302.

    Google Scholar 

  • Bell, R., & Boldero, J. (2011). Factors affecting youth gambling. Melbourne: Victorian Government, Office of Gaming and Racing.

    Google Scholar 

  • Breusch, T., & Pagan, A. (1979). A simple test for heteroscedasticity and random coefficient variation. Econometrica, 47(5), 1287–1294.

    Google Scholar 

  • Castrén, S., Basnet, S., Salonen, A. H., Pankakoski, M., Ronkainen, J.-E., Alho, H., et al. (2013). Factors associated with disordered gambling in Finland. Substance Abuse Treatment, Prevention, and Policy, 8(1), 24.

    PubMed  PubMed Central  Google Scholar 

  • Clark, W. A., & Lisowski, W. (2018). Wellbeing across individuals and places: How much does social capital matter? Journal of Population Research, 35(3), 217–236.

    Google Scholar 

  • Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, S95–S120.

    Google Scholar 

  • Cramm, J. M., Van Dijk, H. M., & Nieboer, A. P. (2012). The importance of neighborhood social cohesion and social capital for the well being of older adults in the community. The Gerontologist, 53(1), 142–152.

    PubMed  Google Scholar 

  • Delfabbro, P., & Thrupp, L. (2003). The social determinants of youth gambling in South Australian adolescents. Journal of Adolescence, 26(3), 313–330.

    PubMed  Google Scholar 

  • Dincer, O. C. (2011). Ethnic diversity and trust. Contemporary Economic Policy, 29(2), 284–293.

    Google Scholar 

  • Dinesen, P. T., & Sønderskov, K. M. (2015). Ethnic diversity and social trust: Evidence from the micro-context. American Sociological Review, 80(3), 550–573.

    Google Scholar 

  • Drukker, M., Buka, S. L., Kaplan, C., McKenzie, K., & Van Os, J. (2005). Social capital and young adolescents’ perceived health in different sociocultural settings. Social Science and Medicine, 61(1), 185–198.

    PubMed  Google Scholar 

  • Ferris, J. A., & Wynne, H. J. (2001). The Canadian problem gambling index. Ottawa, ON: Canadian Centre on Substance Abuse.

    Google Scholar 

  • Fisher, S. (1993). The pull of the fruit machine: A sociological typology of young players. The Sociological Review, 41(3), 446–474.

    Google Scholar 

  • Gainsbury, S. M., Russell, A., Hing, N., Wood, R., Lubman, D. I., & Blaszczynski, A. (2014). The prevalence and determinants of problem gambling in Australia: Assessing the impact of interactive gambling and new technologies. Psychology of Addictive Behaviors, 28(3), 769–779.

    PubMed  Google Scholar 

  • Greenberg, J. H. (1956). The measurement of linguistic diversity. Language, 32(1), 109–115.

    Google Scholar 

  • Griswold, M. T., & Nichols, M. W. (2006). Social capital and casino gambling in US communities. Social Indicators Research, 77(3), 369–394.

    Google Scholar 

  • Hewitt, B., Turrell, G., & Giskes, K. (2012). Marital loss, mental health and the role of perceived social support: Findings from six waves of an Australian population based panel study. Journal of Epidemiology and Community Health, 66(4), 308–314.

    PubMed  Google Scholar 

  • Holtgraves, T. (2008). Evaluating the problem gambling severity index. Journal of Gambling Studies, 25(1), 105–120.

    PubMed  Google Scholar 

  • Huxley, J., & Carroll, D. (1992). A survey of fruit machine gambling in adolescents. Journal of Gambling Studies, 8(2), 167–179.

    CAS  PubMed  Google Scholar 

  • Korman, L. M., Collins, J., Dutton, D., Dhayananthan, B., Littman-Sharp, N., & Skinner, W. (2008). Problem gambling and intimate partner violence. Journal of Gambling Studies, 24(1), 13–23.

    PubMed  Google Scholar 

  • Layton, A., & Worthington, A. (1999). The impact of socio-economic factors on gambling expenditure. International Journal of Social Economics, 26(1/2/3), 430–440.

    Google Scholar 

  • Leigh, A. (2006). Trust, inequality and ethnic heterogeneity. Economic Record, 82(258), 268–280.

    Google Scholar 

  • Lewbel, A. (2012). Using heteroscedasticity to identify and estimate mismeasured and endogenous regressor models. Journal of Business & Economic Statistics, 30(1), 67–80.

    Google Scholar 

  • McQuade, A., & Gill, P. (2012). The role of loneliness and self-control in predicting problem gambling behaviour. Gambling Research, 24(1), 18–30.

    Google Scholar 

  • Millimet, D. L., & Roy, J. (2016). Empirical tests of the pollution haven hypothesis when environmental regulation is endogenous. Journal of Applied Econometrics, 31(4), 652–677.

    Google Scholar 

  • Milner, A., Krnjacki, L., Butterworth, P., & LaMontagne, A. D. (2016). The role of social support in protecting mental health when employed and unemployed: A longitudinal fixed-effects analysis using 12 annual waves of the HILDA cohort. Social Science and Medicine, 153, 20–26.

    PubMed  Google Scholar 

  • Productivity Commission. (2010). Gambling, Report No. 50, Canberra.

  • Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. New York: Simon and Schuster.

    Google Scholar 

  • Putnam, R. D. (2007). E Pluribus Unum: Diversity and Community in the Twenty-first Century The 2006 Johan Skytte Prize Lecture. Scandinavian Political Studies, 30(2), 137–174.

    Google Scholar 

  • Queensland Government Statistician’s Office. (2016). Australian gambling statistics (32nd ed.). Brisbane: Queensland Treasury.

    Google Scholar 

  • Raisamo, S. U., Mäkelä, P., Salonen, A. H., & Lintonen, T. P. (2014). The extent and distribution of gambling harm in Finland as assessed by the problem gambling severity index. The European Journal of Public Health, 25(4), 716–722.

    PubMed  Google Scholar 

  • Raylu, N., & Oei, T. P. S. (2002). Pathological gambling: A comprehensive review. Clinical Psychology Review, 22(7), 1009–1061.

    PubMed  Google Scholar 

  • Reith, G., & Dobbie, F. (2011). Beginning gambling: The role of social networks and environment. Addiction Research & Theory, 19(6), 483–493.

    Google Scholar 

  • Stock, J. H., & Yogo, M. (2005). Testing for weak instruments in linear IV regression. In D. Andrews & J. Stock (Eds.), Identification and inference for econometric models: Essays in honor of Thomas Rothenberg (pp. 80–105). Cambridge: Cambridge University Press.

    Google Scholar 

  • Sturgis, P., Brunton-Smith, I., Kuha, J., & Jackson, J. (2014). Ethnic diversity, segregation and the social cohesion of neighbourhoods in London. Ethnic and Racial Studies, 37(8), 1286–1309.

    Google Scholar 

  • Sturgis, P., Brunton-Smith, I., Read, S., & Allum, N. (2011). Does ethnic diversity erode trust? Putnam’s ‘hunkering down’ thesis reconsidered. British Journal of Political Science, 41(01), 57–82.

    Google Scholar 

  • Subramaniam, M., Wang, P., Soh, P., Vaingankar, J. A., Chong, S. A., Browning, C. J., et al. (2015). Prevalence and determinants of gambling disorder among older adults: A systematic review. Addictive Behaviors, 41, 199–209.

    PubMed  Google Scholar 

  • Tan, A. K. G., Yen, S. T., Nayga, J., & Rodolfo, M. (2010). Socio-demographic determinants of gambling participation and expenditures: Evidence from Malaysia. International Journal of Consumer Studies, 34(3), 316–325.

    Google Scholar 

  • Thomas, A. C., Allen, F. C., & Phillips, J. (2009). Electronic gaming machine gambling: Measuring motivation. Journal of Gambling Studies, 25(3), 343–355.

    PubMed  Google Scholar 

  • Victorian Responsible Gambling Foundation. (2015). Risk factors for problem gambling: Environmental, geographic, social, cultural, demographic, socio-economic, family and household. Melbourne: Victorian Responsible Gambling Foundation.

    Google Scholar 

  • Volberg, R. A. (1996). Prevalence studies of problem gambling in the United States. Journal of Gambling Studies, 12, 111–128.

    CAS  PubMed  Google Scholar 

  • Watson, N., & Wooden, M. P. (2012). The HILDA survey: A case study in the design and development of a successful household panel survey. Longitudinal and Life Course Studies, 3(3), 369–381.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Economics, Finance and Marketing, RMIT University, Melbourne, VIC, 3000, Australia

    Sefa Awaworyi Churchill & Lisa Farrell

Authors
  1. Sefa Awaworyi Churchill
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lisa Farrell
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sefa Awaworyi Churchill.

Ethics declarations

Conflict of interest

Awaworyi Churchill declares that he has no conflict of interest. Farrell declares that she has no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This paper uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Social Services (DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this paper, however, are those of the authors and should not be attributed to either DSS or the Melbourne Institute. (Melbourne Institute). The findings and views reported in this paper, however, are those of the authors and should not be attributed to either DSS or the Melbourne Institute.

Appendix

Appendix

See Tables 7, 8, 9, 10 and 11.

Table 7 Items used in the Problem Gambling Severity Index
Full size table
Table 8 Items used in the Social Capital 1 Composite Scale
Full size table
Table 9 Items used in the Social Capital 2 Composite Scale
Full size table
Table 10 Items used in the Social Capital 3 Composite Scale
Full size table
Table 11 Description and summary statistics of variables
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Awaworyi Churchill, S., Farrell, L. Social Capital and Gambling: Evidence from Australia. J Gambl Stud 36, 1161–1181 (2020). https://doi.org/10.1007/s10899-019-09901-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10899-019-09901-9

Keywords

Search

Navigation