Literature DB >> 22258556

Work and non-pathological gambling.

John A Nyman1, Bryan E Dowd, Jahn K Hakes, Ken C Winters, Serena King.   

Abstract

Most economists believe that people would value an additional $1,000 in income more if they were poor than if rich, but if so, people should not gamble according to standard expected utility theory. Thus, economists have been challenged to explain the pervasiveness of gambling in human behavior. A recently proposed solution to this theoretical challenge (Nyman 2004; Nyman et al. in Journal of Socio-Economics 37:2492-2504, 2008) suggests that, because having to work for one's income is a fact of life in market economies, many individuals view the winnings from gambling not only as additional income, but as additional income for which one does not need to work. As a result, individuals, and especially those who are disadvantaged in the labor market, attach a utility premium to gambling winnings and gamble because of that. This utility premium would explain the pervasiveness of gambling in society, especially among the economically disadvantaged. This paper reviews the economic approaches to explaining non-pathological gambling, presents an overview of the new theory, and uses data from the National Epidemiological Survey of Alcohol and Related Conditions from 2001 to test it. The results indicate that the respondent's work characteristics explain the decision to gamble in a way that is consistent with theory.

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Year:  2013        PMID: 22258556     DOI: 10.1007/s10899-011-9290-9

Source DB:  PubMed          Journal:  J Gambl Stud        ISSN: 1050-5350


  7 in total

Review 1.  Gambling and related mental disorders: a public health analysis.

Authors:  Howard J Shaffer; David A Korn
Journal:  Annu Rev Public Health       Date:  2001-10-25       Impact factor: 21.981

2.  Measuring the prevalence of sector-specific problem gambling: a study of casino patrons.

Authors:  S Fisher
Journal:  J Gambl Stud       Date:  2000

3.  Risk of harm among gamblers in the general population as a function of level of participation in gambling activities.

Authors:  Shawn R Currie; David C Hodgins; JianLi Wang; Nady el-Guebaly; Harold Wynne; Sophie Chen
Journal:  Addiction       Date:  2006-04       Impact factor: 6.526

4.  Replication of low-risk gambling limits using canadian provincial gambling prevalence data.

Authors:  Shawn R Currie; David C Hodgins; JianLi Wang; Nady el-Guebaly; Harold Wynne; Natalie V Miller
Journal:  J Gambl Stud       Date:  2008-03-04

5.  A Measurement of the Certainty Effect.

Authors: 
Journal:  J Math Psychol       Date:  1998-03       Impact factor: 2.223

6.  Risk factors for pathological gambling.

Authors:  John W Welte; Grace M Barnes; William F Wieczorek; Marie-Cecile O Tidwell; John C Parker
Journal:  Addict Behav       Date:  2004-02       Impact factor: 3.913

7.  Gambling participation in the U.S.--results from a national survey.

Authors:  John W Welte; Grace M Barnes; William F Wieczorek; Marie-Cecile Tidwell; John Parker
Journal:  J Gambl Stud       Date:  2002
  7 in total
  4 in total

1.  Expanding the study of internet gambling behavior: trends within the Icelandic lottery and sportsbetting platform.

Authors:  Heather M Gray; Guðberg K Jónsson; Debi A LaPlante; Howard J Shaffer
Journal:  J Gambl Stud       Date:  2015-06

Review 2.  The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Waves 1 and 2: review and summary of findings.

Authors:  Deborah S Hasin; Bridget F Grant
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2015-07-26       Impact factor: 4.328

3.  Speculating on Precarious Income: Finance Cultures and the Risky Strategies of Healthy Volunteers in Clinical Drug Trials.

Authors:  Jill A Fisher; Megan M Wood; Torin Monahan
Journal:  J Cult Econ       Date:  2020-12-21

4.  Risk of problem gambling among occupational groups: A population and registry study.

Authors:  Per Binde; Ulla Romild
Journal:  Nordisk Alkohol Nark       Date:  2020-03-13
  4 in total

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