By Dylan Mortimore
Unless you’re as nerdy as me, economics is probably one of the last things on your mind when you chance your arm at the casino. That said, the wisdom of microeconomics provides some of the most interesting insights into the workings of the gambling industry and its effect on society. Specifically, the theory of externalities and how they precipitate market failure has an application to gambling that some might see as obvious: gambling creates external costs that the private market doesn’t capture, and so inefficiency arises. But unlike the externality problems we encounter in textbooks, Pigou might not have a perfect solve for this one. In fact, the interaction between many different economic and psychological factors makes regulating the gambling industry one of the trickiest challenges in microeconomic policy.
As the coronavirus reduced casino access and put professional sport on hold for some time, many forms of gambling became briefly unavailable. While we could still bet on what colour tie Scott Morrison would wear when next addressing the nation, any gambling activities that compromised social distancing were suspended. Yet as COVID-19 restrictions ease, the lights are back on for pokies machines, and casinos are reopening; the ubiquity of gambling endures.
Critics of the industry consider gambling’s return to omnipresence particularly disconcerting, arguing that the negative externalities could be bigger than ever. And these worries are not unfounded – there’s evidence that the stress and uncertainty ushered in by the pandemic can function as a trigger for mental health problems in at-risk or pathological gamblers, and renewed access to gambling venues can be a sort of release (Paterson, 2020). If this is true, we’re likely to see a large rightward shift in the demand curve, and policies will need to adjust.
So to determine the truly optimal level of gambling, the textbook approach would have us apply the modified demand-supply framework. Left unfettered, the market will clear at a level of gambling where the gambler’s marginal benefits are equal to the marginal costs incurred by gambling institutions. But we know that gambling has many secondary and tertiary ramifications that result in additional costs to society and produce a deadweight loss in the absence of intervention. The standard market-based fix for this is a Pigouvian tax set equal to the external marginal cost at the efficient level of output.
If this is to work, we’d need to accurately quantify the external costs of gambling. Economic literature from the late 1990s emphasised the need to appreciate the difference between technological and pecuniary externalities when calculating said social costs. A technological externality is one which directly affects real wealth, like the classic example of the damage that polluting firms cause the environment. Conversely, a pecuniary externality, while affecting a third party, results only in a transfer of wealth. An example of this is if a gambler loses money at the casino that would otherwise have been used to pay for groceries for that person’s family; the family is an adversely affected third-party. However, net societal wealth remains unaffected, as the funds were simply transferred from the gambler’s family to the casino. As a result, this pecuniary externality shouldn’t be included when quantifying the true ‘social costs’ of gambling, as it doesn’t contribute to overall welfare loss (Walker & Barnett, 1999). Understanding this distinction, while very important, certainly doesn’t remove all the challenges, especially when highly relevant technological externalities are difficult quantify. For example, the significant mental health consequences associated with gambling clearly have the potential to actively destroy utility, but how much is this utility worth?
We also shouldn’t see this as a reason to completely ignore pecuniary externalities. While they don’t qualify as a source of inefficiency based on stringent economic definitions, they create serious challenges in the equity space. A gambler’s family being unable to pay for groceries is certainly undesirable, even if society retains the funds through the transfer to the casino (Walker & Barnett, 1999). This means policymakers need to develop a solution which also addresses externalities beyond market mechanisms. In doing this, a decision needs to be made on how much of the family’s grocery budget (if any) should be transferred to the casino; this is a question for social welfare functions.
Equity aside, for simple market interventions to even achieve an efficient solution, it is necessary that all participants in the private gambling market make rational choices. It’s easy to see why this might not be the case, particularly in ‘at-risk’ gamblers. A gambler who suffers from addiction may not be able to make a truly utility-maximising decision, as they perceive their utility inaccurately. This creates an additional layer of inefficiency that is even more difficult to address. Quantifying how much the gambler ‘overestimates’ their utility would then be necessary to correct this through a market-based intervention. But utility is subjective, and at what point do we deem a person’s decision irrational?
An answer to this controversy came in 1988, through the Becker-Murphy (B-M) model of ‘rational addiction’. Supported by some fancy calculus, the B-M model suggests that an addict can be completely rational, provided that, when deciding to gamble, the marginal utility from increased consumption today outweighs the costs of accumulating a greater stock of ‘addictive capital’ in the future and incurring the associated harms. If this is the case, the gambler has made a rational, utility-maximising decision. Were all gamblers like this, we’d certainly have fewer worries about the private demand curve, and Pigouvian methods could be used to focus on tackling externalities. But is the average person who becomes hooked on gambling really a ‘rational addict’, or are they instead myopic? The myopic addict lacks the foresight to consider costs that will be incurred in the future and cannot maximise utility when a decision has inter-temporal consequences (Becker & Murphy, 1988). In this instance, our market-based solution would need to correct for such irrationality (in addition to the myriad of externalities).
Yet even our rational addicts have their preferences obscured when information asymmetry is at play. This is why gambling advertising is strictly monitored in Australia: individuals can be misled by the misrepresentation of odds or potential winnings, and it is often in the gambling institution’s best interest to withhold certain information (Petty, 2018). Efforts to regulate this (and create transparency) manifest themselves in the myriad of disclaimers and exclusions we hear at the end of gambling advertisements. In theory, breaking down this asymmetry should position individuals to make rational choices, leaving our demand curve much less compromised.
But beyond all these difficulties quantifying costs and the potential irrationality of demand-side actors, it might seem like any intervention which reduces the prevalence of gambling would be a positive one (even if we don’t reach the true social optimum). But perhaps gambling also entails some positive externalities, in which case there’s a chance that any efforts to correct market failure could result in greater deadweight loss than would prevail otherwise. There is evidence that physical gambling venues can result in injections into local economies through wages and as a form of attraction which has secondary benefits for surrounding businesses (Walker, et al., 2015). Were we to omit these factors and only consider the external costs of gambling, we run the risk of underestimating the truly optimal level.
In many ways, the gambling industry behaves like no other market. Its inefficiencies (and inequities) are a multifaceted problem, so it’s unsurprising that governments respond with a very multifaceted solution: Education campaigns and transparency laws are used to support rational decision making, while taxes are used to control gambling’s prevalence. These are all efforts to balance the overwhelming interaction between a plethora of microeconomic forces when the straightforward Pigouvian answer eludes us – and that’s probably because there isn’t one.
Our policymakers are left to take a gamble.
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Becker, G. & Murphy, K., 1988. A Theory of Rational Addiction. Journal of Political Economy, 96(4), pp. 675-700.
Paterson, M., 2020. There’s another health crisis looming – what happens when the pokies switch back on?. [Online]
Available at: https://theconversation.com/theres-another-health-crisis-looming-what-happens-when-the-pokies-switch-back-on-137995 [Accessed 1 August 2020].
Petty, L., 2018. The value of asymmetric information in sports betting. [Online]
Available at: https://www.pinnacle.com/en/betting-articles/educational/asymmetric-information-in-sports-betting/J3T2578E83PXH3XF [Accessed 28 July 2020].
Walker, D. & Barnett, A., 1999. The Social Costs of Gambling:. Journal of Gambling Studies, 15(3), pp. 181-211.
Walker, D., Nower, L. & Choi, K., 2015. Societal and Economic Impact of Gambling, s.l.: Gambling Research Exchange.