The Demand For Sports Lottery: Evidence from the City of Kumasi in Ghana
Keywords:sports lottery, demand, Ghana, National Lotteries Authority, binary logit
AbstractFormalised sports lottery is fast becoming a craze in Ghana, especially amongst the male populace. There is however no documented research on the demand for this product as well as its effects on the population and economy of Ghana as a whole. This study sought to investigate the factors that influence the demand for sports lottery in Ghana. Based on the expected utility hypothesis, a model was constructed using a binary logistic regression to analyse the characteristics that influence the demand for sports lottery in Ghana. Four hundred respondents were employed in this study where it was realized that 92% out of the about 96% males engaged in sports lottery in Ghana were within the age bracket of 21-40 years. Furthermore, 53.6% of those engaged in sports lottery were reported to be unemployed. Price, gender, age, employment status, monthly income and whether a person has won a bet before were discovered to be significant factors of the demand for sports lottery in Ghana. The study also realized that online lotteries were such as MyBet and Supabet were the most preferred to the offline lottery offered by the National Lottery Authority. Therefore the NLA must redesign their product to meet the demand preferences of the patrons.
Ariyabuddhiphongs, V. (2011). Lottery gambling: A review. Journal of Gambling Studies, 27(1). 15-33.
Asteriou D. and Hall, S.G. (2011). Applied Econometrics, 11th ed. Palgrave Macmillan.
Awunyo-Vitor,D., Ishak, S., and Seidu, J.S. (2013). Urban Households' Willingness to Pay for Improved Solid Waste Disposal Services in Kumasi Metropolis, Ghana, Urban Studies Research, Vol. 2013 (2013). doi:10.1155/2013/659425.
Beckert J. and Lutter, M. (2013). Why the Poor Play the Lottery. Sociololgical Approaches to Explaining Class-Based Lottery Play. Sociology 47:1152-1170.
CSLAC. (2012). Sales Report of China Sports Lotteries 2011. Retrieved June 7, 2012, from http://www.lottery.gov.cn/news/10018632.shtml .
Conlisk, John (1993). The Utility of Gambling, Journal of Risk and Uncertainty, 6(3), 255-275.
Daily Graphic News (2015). Gaming Commission gets New Board. Retrieved February 15 2016, from www.graphic.com.gh/news/general-news/4175-gaming-commission-gets-new-board.html.
Dutta, A., Bandopadhyay, B., and Sengupta, S. (2012). Prediction of Stock Performance in the Indian Stock Market Using Logistic Regression, International Journal of Business and Information 7(1).
Eisenhauer, Joseph G. (2005). How Prevalent are Friedman-Savage Utility Functions, Briefing Notes in Economics, 66.
Friedman, M. and Savage L. J. (1948). The Utility Analysis of Choices Involving Risk. Journal of Political Economy 56:279-304.
Ghanaweb (2015). IMF Conditionalities Create Rough Road for Government. Retrieved February 27 2016 from mobile.ghanaweb.com/GhanaHomePage/NewsArchive?IMF-conditionalities-creare-rough-road-for-gov-t-355826
Grote, K. R. and Matheson, V. A. (2011). The Economics of Lotteries: A Survey of the Literature, Working Paper.
Hawley, C. B. and Fujii, E.T., (1993-94). An Empirical Analysis of Preferences for Financial Risk: Further Evidence on the Friedman-Savage Model, Journal of Post-Keynesian Economics, 16(2): 197-204.
Horowitz, J.L., and Savin, N.E. (2001). Binary Response Models: Logits, Probits and Semiparametrics, Journal of Economic Perspectives, 15(4): 43-56
Humphreys, B. R. and Perez, L. (2010). A Microeconometric Analysis of Participation in Sports Betting Markets, Economic Discussion Papers.
Humphreys, B. R., and Matheson, V.A., (2012). Booms, Busts, and Gambling: Can Gaming Revenues Reduce Budget Volatility? In Boom and Bust Again, edited by R. Ascah and D. Ryan. Alberta, Canada: University of Alberta Press.
Ignatin, G. (1984). Sports Betting, The Annals of the American Academy of Political and Social Science, Vol. 474, Gambling: Views from the Social Sciences, 168-177.
Kaizeler, M. J., & Faustino, H. C. (2008a). Demand for lottery products: A cross-country analysis. Working Paper: WP 33/2008/DE/SOCIUS. Department of Economics. Technical University of Lisbon.
Li, H., Mao, L., Zhang, J., Wu, Y., Li, A., & Chen, J. (2012). Dimensions of Problem Gambling Behavior Associated with Purchasing Sports Lottery. Journal of Gambling Studies, 28(1), 47-68.
Mao, L. L. (2013). Sports Gambling as Consumption: An Econometric Analysis of Demand for Sports Lottery. PhD Thesis.
Mao, L. L., Zhang J. J., Connaughton, D. P., (2015). Determinants of Demand for Sports Lottery: Insights from a Multilevel Model, Asian Economic and Financial Review, 5(8), 973-987.
Mao, L. L., Zhang J. J., Connaughton D. P., Holland, S.,(2015). An examination of the Impact of Socio-Demographic Factors on the Demand for Sports Lotteries in China, Asia Pacific Journal of Sport and Social Science, 4 (1), 34-52.
Mikesell, J. L. and Pirog-Good, M. A., (1990). State Lotteries and Crime: The Regressive Revenue Producer Is Linked with a Crime Rate Higher by 3 Percent. American Journal of Economics and Sociology 49 (1):7-19.
National Lottery Authority (2006). National Lotto Act, 2006, Act 722.
National Lottery Authority (2015). History. Retrieved 1st November 2015 from http://nla.com.gh/about.php and http://nla.com.gh/soccer_cash_page.php.
Ogden, C.L., Carroll, M.D., Curtin, L.R., McDowell, M.A., Tabak, C.J., and
Flegal, K.M. (2006). Prevalence of Overweight and Obesity in the United States, 1999-2004. The Journal of the American Medical Association, 295(13):1549-1555.
Partin, A.W., Yoo, J., Carter, H.B., Pearson, J.D., Chan, D.W., Epstein, J.I. and Walsh, P.C. (1993). The Use of Prostate Specific Antigen, Clinical Stagge and Gleason Score to Predict Pathological Stage in Men with Localised Prostate Cancer, The Journal of Urology, 150(1): 110-114.
Perez, L., (2009). State of Empirical Research on Demand for lottery, Economic Discussion Papers, 01.
Perez, L.C., (2010). The Demand for Gambling: Empirical Evidence from State-Operated Lotteries and Football Pools in Spain. Thesis.
Rahmatullah Imon, A.H.M., Roy, M.C., Bhattacharjee, S.K. (2012). Prediction of Rainfall Using Logistic Regression, Pakistan Journal of Statistics and Operation Research, 8(3).
Rodriguez, G. (2007). Lecture Notes on Generalized Linear Models. URL: http://data.princeton.edu/wws509/notes/
Silberberg, E. and Suen, W. (2001). The Structure of Economics, A Mathematical Analysis, 3rd ed. (McGraw-Hill), p. 394-415.
Sloman, J. (2006). Economics, 6th ed. (Prentice Hall), p. 34-93.
Trading Economics (2016). Ghana Government Debt to GDP. Retrieved February 27 2016 from www.tradingeconomics.com/ghana/government-debt-to-gdp.
UNDP (2014). Inequality in Ghana: A Fundamental National Challenge, Ghana-UNICEF Inequality Briefing Paper, Final Draft.
Zhou, L. J. and Zhang, J. J. (2015). Variables Affecting the Market Demand of Sports Lottery Sales in China: The Case of Guandong Province. North American Society for Sport Management.