Newall, Walasek, Hassanniakalager, et al. (2023) on Gambling Risk Warnings

Philip W.S. Newall, Lukasz Walasek, Arman Hassanniakalager, et al., “Statistical Risk Warnings in Gambling.” Behavioural Public Policy 7(2), 219-239, 2023 [pdf available here].

• Warning messages in the gambling arena, when they are provided, tend to be generic and do not facilitate comparison across various betting options.

• Theoretical loss = (house edge) times (total amount bet), or, the expected price of a bet or bets; for instance, in European roulette, the house edge is 2.7%, so the theoretical loss of betting $100 is $2.70.

• Theoretical loss is a long-run concept and not salient for bettors, while their recent gambling experience is quite salient. But given that most of the social harm from gambling is tied to bettor losses, theoretical loss is a decent metric for the social risks of alternative wagers. 

• Expected prices (or theoretical loss) of gambling tends to be hidden from gamblers – but it would be possible to provide (sometimes approximate) theoretical loss information, or other related metrics such as house edge. (For games where player behavior affects the odds, the risk could even be personalized based on player characteristics.) Presumably gamblers (all else equal) would be dissuaded from forms of gambling with high theoretical losses. 

• Should gambling warnings also note volatility and the slow convergence to theoretical loss levels?

• Gamblers cannot identify vast differences in expected price on seemingly identical games.

• Some jurisdictions mandate “return to player”-style info; but players often do not understand it. And sometimes the info is hard to find and to see.

• Should the automatic reinvestment of small wins into a player's available gambling account be banned?

• In sports betting, longshots and “exact score” or other prop bets tend to have higher house edges – and these are heavily advertised.

White and Perfors (2022) on Ambiguity Aversion in Vignettes

Joshua P. White and Andrew Perfors, “Ambiguity Aversion in Qualitative Contexts: The Role of Prior Beliefs,” May 22, 2022; available here.

• The idea is to test for ambiguity aversion in more-or-less familiar risky situations that are not about money, such as blind dates or election outcomes. Further, the issue of whether ambiguity aversion arises from people holding pessimistic beliefs about the actual odds facing them in ambiguous situations is explored.

• The three lab experiments employ Amazon Mechanical Turk (overall n>2000) and the analysis is pre-registered, including the data exclusion criteria.

• The 24 vignettes: Would you rather be in the risky situation or the ambiguous situation? Half of the vignettes concern potential gains (e.g., new job) and half concern potential losses (e.g., losing a job). 

• The results: ambiguity aversion is typically present on average in both the gain and loss framings; ambiguity aversion is greater, however, in the gain scenarios, and the amount of aversion varies quite a bit across scenarios. 

• The scenario that tracked an Ellsberg urn problem showed (easily) the highest ambiguity aversion. 

• For some individuals, the aversion to ambiguity seems to derive from pessimistic feelings about how ambiguity would be resolved. (The Ellsberg-style urn vignette – which involved a casino! – is particularly likely to be affected by pessimism.) But there remains a good deal of ambiguity aversion that does not derive from pessimistic beliefs (nor from "comparative ignorance," the concern that a decision maker is up against better informed folks – such as casino owners, perhaps?).

Folkvord, Codagnone, Bogliacino, et al. (2019) on Online Gambling

Frans Folkvord, Cristiano Codagnone, Francesco Bogliacino, et al., “Experimental Evidence on Measures to Protect Consumers of Online Gambling Services.” Journal of Behavioral Economics for Policy 3(1): 20-29, 2019 [pdf here]. 

• Internet gambling might be particularly likely to induce problematic play. 

• The outcome variables tracked in both a laboratory (n=522) and an online (n=5997) experiment are the average amount bet, the time between plays, and the likelihood of ending a gambling session when given the opportunity. 

• In the first stage of the laboratory experiment, gamblers receive one of four interventions: a pop-up warning with a picture about gambling addiction; the warning without a picture; a task to reveal overconfidence; and a picture of a logo of a gambling treatment service. A control group skips those pre-play interventions. 

• None of the first-stage (pre-play) interventions reduce the extent or speed of play, though two of the interventions seem to speed up play! 

• The second stage of the laboratory experiment and the online experiment expand the number of treatments, including the possibility to set monetary limits and using pop-up messages requiring an action to continue gambling. 

• Most of the interventions have no effects. Monetary limits and the warnings that require a response reduce average bet amounts and slow down the rate of play. Registration forms incentivize people to quit.

Beine, Charness, Dupuy, and Joxhe (2020) on Earthquakes and Preferences

Michel Beine, Gary Charness, Arnaud Dupuy, and Majlinda Joxhe, “Shaking Things Up: On the Stability of Risk and Time Preferences.” IZA Discussion Paper No. 13084, March 2020. 

• It seems as if most economists believe that an individual’s risk and time preferences are pretty stable. 

• Patient people and the risk averse would seem to be less likely to migrate, and some empirical evidence supports this view. 

• Albanian per-capita GDP of just over $4000 per year is 30% of the EU average, despite recent high growth in Albania 

• The researchers converge on Tirana, where the currency is the Albanian lek, worth a bit less than one cent. Participants on average get about 12 dollars for a 20-minute or so interview, more than a day’s pay. 

• The 9 enumerators conducting the interactions speak Albanian. Geolocation data for the interviews is automatically collected, with n≈1500. 

• The first choice, aimed at gauging risk preferences: you have 100 coins, each worth 10 lek. You can put some of them in a bag. With probability .5, you will get triple what you put in; with probability .5, you will get nothing. How many coins will you put in the bag? (You keep the coins that you choose not to put in the bag). 

• For time preferences, the question concerns whether you would rather have 1000 lek today or some larger amount of money one month from today. The goal is to see how much more people will have to be paid to induce them to wait one month for their money. 

• The study started on August 31, 2019, and lasted through the end of the year. But on September 21 and November 26, 2019, two major earthquakes hit Tirana. 

• The control group in this (re-imagined post-quake) study is those people whose preferences were tested prior to the first earthquake. The two treatment groups are (1) those who experienced one earthquake, and (2) those who experienced two earthquakes, prior to their testing. 

• “the first earthquake reduces the amount invested in a risky asset (versus a safe asset) by about 25%, while the second one leads to an additional similar effect [p. 3].” Why the big change after the second one, when earthquakes have lost the element of surprise? And why should any changes in risk aversion be reflected in incentivized laboratory games with fixed probabilities? 

• Migration intentions share no connections with risk preferences among the study population, until after the second quake. (But pre-earthquake, already 70% of Albanians intend to migrate.) More exposure to the quakes makes more risk averse people more likely to migrate. More patience also means a lower intention to emigrate. 

• Before the first earthquake, about 42 coins are invested on average in the risk preferences situation: 144 people invest zero, 102 invest all 100 coins. (Aren’t there anti-gambling laws in Albania?) The number of coins risked falls from 42 to 34 to 23 with the earthquakes. 

• Would you take 2590 lek one month from now instead of 1000 lek today? Almost half of the participants would take the immediate 1000 lek. Patience (limited as it is) is cut in half with the first quake, and almost halved again with second. 

• Being exposed to heavier shaking (the geo data proxy for exposure) seems to be connected with a bigger change in risk and time preferences. 

• The earthquakes affect migration intentions indirectly, through their influence on risk and time preferences: the earthquakes mean that the now more risk averse people become willing to emigrate. More impatient people also are more interested in emigration.

Golman, Gurney, and Loewenstein (2020) on Information Gaps

Russell Golman, Nikolos Gurney, and George Loewenstein, “Information Gaps for Risk and Ambiguity.” Psychological Review 128(1): 86–103, 2021; http://dx.doi.org/10.1037/rev0000252 

• The authors argue that risk and ambiguity aversion arise from the desire to avoid unpleasant thinking about unanswered questions. (Risk and ambiguity loving, alternatively, is associated with the prospect of being spurred to think about pleasant matters.) 

• If you have a question with an unknown answer, you have an information gap. The attention that this gap attracts from you depends on salience (contextual factors which highlight the gap) and importance. 

• Gambling raises the importance of certain information gaps – which team will win? – and hence, directs our attention towards them. We therefore like to gamble when we welcome the increased attention, and are dissuaded from gambling on topics we don’t like to think about. 

• A key information gap concerns uncertain outcomes. Risk aversion (even with minimal stakes) can arise from our desire to avoid thinking about the uncertainty. Compound lotteries, er, compound the uncertainty, and the aversion. 

• The previous two bullet points offer new explanations for (1) betting on your favorite team and (2) low-stakes risk aversion. (A risk averse person presumably would want to bet against their favorite team, as a way of buying insurance against the bad outcome that arises if the preferred team loses.) 

• When shown risky prospects one-at-a-time, people seem to respond similarly to more and less ambiguous situations. When there is a choice between prospects, however, ambiguity aversion emerges. The comparison among alternatives presumably makes the information gaps (not knowing the precise probabilities) more salient. 

• People with relevant expertise enjoy ambiguity, as in racetrack betting. But those who feel uninformed find the ambiguity unsettling. 

• Study 1: Pittsburgh Pirates fans choose how much to bet on either their team’s hits or the number of strikeouts suffered by batters on their team. These bets involve no ambiguity – once the fans choose a bet size, their probability of being assigned the “winning” side of the bet is .5. Nevertheless, the fans bet more when hits are the relevant subject. Presumably they do not enjoy having to think about the strikeouts that the players on their team will suffer. 

• Study 2: Carnegie Mellon University alumni are given the opportunity to bet on the future relative rankings of two excellent CMU computer science departments – or on the relative future prospects of two not-so-good natural science departments. In this case, objective probabilities are not known, there is ambiguity in the prospects. The alumni display aversion to the ambiguity; however, they show a lot less aversion to that ambiguity when betting on the great departments. It seems that thinking about the future success of CMU star departments is a happy thought that they, to some extent, welcome.