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Interdependency Among Addictive Behaviours and Time/Risk Preferences: Discrete Choice Model Analysis of Smoking, Drinking, and Gambling

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Book cover Behavioral Economics of Preferences, Choices, and Happiness

Abstract

This chapter simultaneously measures the rate of time preference and the coefficient of risk aversion, as well as investigates the interdependencies of four addictive behaviours: smoking, drinking, pachinko (a popular Japanese form of pinball gambling), and horse betting among a sample of the Japanese population. We reach two main conclusions. First, there are significant interdependencies among the four addictive behaviours, in particular between smoking and drinking and between gambling on pachinko and the horses. Second, we conclude that the higher the time preference rate and the lower the risk aversion coefficient becomes, the more likely individuals smoke, drink frequently, and gamble on pachinko and the horses.

The original article first appeared in Journal of Economic Psychology 30(4):608–621, 2009. A newly written addendum has been added to this book chapter.

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Notes

  1. 1.

    See DiClemente and Hantula (2003) as to a review of the applied behavioural literature in consumer choice.

  2. 2.

    It would be interesting to extend the analysis to ‘beneficial addiction’ (d[\( \partial \)U/\( \partial \)ci]/dS > 0) including jogging and swimming. There is some controversy as to whether jogging and swimming can be also considered addictions (Holden 2001); excessive exercise can cause unhealthy outcomes (McKenzie 1999) and can also be a harmful addiction in this case.

  3. 3.

    Some research found the opposite: smokers exhibited lower discount rates (Chesson and Viscusi 2000).

  4. 4.

    A few studies have tried to integrate the measurements of time and risk preferences. Examples include Rachlin et al. (1991), Keren and Roelofsma (1995), Anderhub et al. (2001), and Yi et al. (2006).

  5. 5.

    In health economics, obtaining reveal preference (RP) data is sometimes difficult, since the market is incomplete; it is advantageous to utilize stated preference (SP) data using experiments and questionnaire surveys. As such, this hypothetical technique has been applied in healthcare settings, and previous results have revealed that SP results have internal validity and consistency (Viney et al. 2002).

  6. 6.

    They interestingly discovered that the rate of time preference was robust with respect to the different assumptions regarding habit formation, while the coefficient of relative risk aversion changed substantially across specifications.

  7. 7.

    In pachinko, the object is to increase the number of pachinko balls to exchange for cash or prizes.

  8. 8.

    Tsuge et al. (2005) is interesting because it applies the DCE analysis of risk preference.

  9. 9.

    In our survey, a respondent was told that when choosing Alternative 2, which included delay and risk, she first drew lots; when a winning number was drawn, she would get a prize after a given period of time.

  10. 10.

    As is commonly known, the exponential discounted utility model was advocated by Samuelson (1937) and axiomatically defined by Koopmans (1960) and Fishburn and Rubinstein (1982). The expected utility model is attributed to von Neumann and Morgenstern (1953).

  11. 11.

    If we consider index s the state of nature, s = 1,…,S, expected utility is written as Σ s=1,…,S probabilitys*utility(rewards). Note that we simply assume here that one alternative has only one state of nature other than the state of zero reward.

  12. 12.

    This is partly because both the constant rate of time preference and the coefficient of relative risk aversion still provide good benchmarks.

  13. 13.

    ML models are also called random parameter models if focusing on the distribution of parameters, or error component models if focusing on flexible substitution patterns (Revelt and Train 1998; Brownstone and Train 1999).

  14. 14.

    Louviere et al. (2000, p. 201) suggest that 100 replications are normally sufficient for a typical problem involving five alternatives, 1,000 observations, and up to 10 attributes (Revelt and Train 1998). The adoption of the Halton sequence draw is an important problem to be examined (Halton 1960). Bhat (2001) found that 100 Halton sequence draws are more efficient than 1,000 random draws for simulating ML models.

  15. 15.

    Louviere et al. (2000, pp. 142–143) showed that the variance is an inverse function of the scale as \( {\sigma}^2={\pi}^2/6{\alpha}^2 \). Therefore, the associated variance σ 2 becomes 1.645.

  16. 16.

    It is not necessarily a long-established hypothesis that smoking is positively correlated with impulsive delay discounting. Famous research by Fuchs (1982) reported weak relations between them, for example.

  17. 17.

    Our finding that social drinking exhibited more self-control than no drinking was predicted by Ainslie (2001) and Rachlin (2004).

  18. 18.

    The correction of the asymptotic covariance matrix at the second step requires some additional computation (Murphy and Topel 1985).

  19. 19.

    Whether addiction is intertemporally rational or irrational depends on whether choice is time-consistent or time-inconsistent. Several studies have regarded addiction as time-inconsistent behaviour. For example, Gruber and Koszegi (2001) demonstrated that preferences with respect to smoking were time inconsistent; individuals both failed to recognize the true difficulty of quitting and sought self-control devices to help them quit. Kan (2007) empirically studied time-inconsistent preferences in the context of cigarette smoking behaviour and concluded that a smoker who wanted to quit had a demand for control devices, e.g., a smoking ban in public areas or a hike in cigarette taxes.

  20. 20.

    Mitchell (1999) and Reynolds et al. (2003) reported negligible correlations between them.

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Authors and Affiliations

  1. Graduate School of Economics, Kyoto University, Yoshida, Sakyoku, Kyoto, 606-8501, Japan

    Takanori Ida & Rei Goto

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  1. Takanori Ida
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  2. Rei Goto
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Correspondence to Takanori Ida .

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Editors and Affiliations

  1. Inst. of Soc. and Econ. Research, Osaka University, Ibaraki, Osaka, Japan

    Shinsuke Ikeda

  2. Nagoya University Graduate School of Economics, Nagoya, Aichi, Japan

    Hideaki Kiyoshi Kato

  3. Institute of Social and Economic Research, Osaka University, Ibaraki, Osaka, Japan

    Fumio Ohtake

  4. Faculty of Economics, Konan University, Kobe, Hyogo, Japan

    Yoshiro Tsutsui

Addendum: Recent Developments

This addendum has been newly written for this book chapter.

Addendum: Recent Developments

Smoking is still the most common cause of morbidity and mortality in Japan, with about 130,000 people estimated to die annually from smoking-related diseases (Ikeda et al. 2012). Decreased tobacco use has been shown to reduce the development of smoking-related diseases and death in smokers (Glantz and Gonzalez 2012). Therefore, anti-tobacco policies have been a global issue. In Japan, the enforcement of the Health Promotion Law (2002) promote various tobacco-controlling approaches such as restricting smoking in public places and raising the tax on tobacco. However, in Japan, these measures have proven inadequate compared with other industrialized nations (WHO 2013).

In order to explore factors drive smokers’ attempts to quit as well as the investigations about different features of preferences according to smoking history, Goto et al. (2007) have analyzed the willingness of smokers to quit their habit in given hypothetical conditions using discrete choice experiments (DCEs). See also Goto et al. (2011) for a developed research.

In the DCE, any goods or services are described by bundling their attributes or characteristics. The extent to which an individual values goods or services can be evaluated by the selection of hypothetical choices that mimic the daily decision-making process. This technique has often been applied in health-care settings. In this study, the following five attributes were identified as the most important factors: the price of a pack of cigarettes, fines for smoking in public places, long-term health risks (mortality risk), short-term health risks (risk of upper respiratory infection), and health risks to others.

Table 7.8 shows summary of results of the DCE which collects the data from 616 smokers, stratified with Fagerstrom test for nicotine dependence (FTND). The impacts of attributes other than the cigarette price differ remarkably among smokers with different levels of nicotine dependence. The price of cigarettes has the shortest term and certain effect on smokers relative to other variables such as health risks and penalties—that is, our DCE results indicated that the shortest term and certain effects are significant or all types of smokers, while the longer and risky term effects such as health risks are found only in smokers with lower nicotine dependence. These results imply the importance of time/risk preference parameters also from tobacco-controlling policy perspective.

Table 7.8 Impacts of attributes on smoking on quit attempts
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Ida, T., Goto, R. (2016). Interdependency Among Addictive Behaviours and Time/Risk Preferences: Discrete Choice Model Analysis of Smoking, Drinking, and Gambling. In: Ikeda, S., Kato, H., Ohtake, F., Tsutsui, Y. (eds) Behavioral Economics of Preferences, Choices, and Happiness. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55402-8_7

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