J. K. Sax and N. Doran, “Ambiguity and Consumer Perceptions of Risk in Various Areas of Biotechnology.” Journal of Consumer Policy 42(1): 47-58, March 2019 [gated copy here].
• Biotechnology-driven consumer goods such as vaccines, fluoridated water, and foods produced with GMOs seem particularly susceptible to exaggerated views of health and safety risks. Does ambiguity aversion drive these risk misperceptions?
• A survey with 14 scenarios is administered to 318 American adults with at least a high school education. Four questions attempt to measure the respondent's underlying ambiguity aversion. These questions are followed up with a series of items concerning views on vaccines, organic foods, bottled water, and embryonic stem cells, where at least one response to each item is (treated as) inconsistent with the consensus scientific view.
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These preliminaries are succeeded by vignettes about fluoridated water, GMO foods, and so on, where the information presented is either conflicting or less-than-complete. The respondents rate the scenarios on the basis of risks and benefits, where the most positive response would view the scenario as one holding great benefit at low risk.
• The idea is that scientists often are willing to assign low risk/high benefit status to various innovations even in the absence of complete information, or in the presence of some conflicting information. Do the respondents behave similarly, and does being more ambiguity averse in general lead to more pessimistic assessments of such innovations?
• People view ambiguity concerning food to be particularly off-putting. Nonetheless, respondents who prefer bottled water to fluoridated tap water tend in other domains to go with the scientific consensus.
• The bottom line, from the Abstract (p. 47): "Participants who reported greater aversion to ambiguity tended to respond in a way that signals the assignment of high risk, and low benefit, when presented with some unknown or uncertain risk."
Ted
O’Donoghue and Jason Somerville, “Modeling Risk Aversion in Economics.”
Journal of Economic Perspectives
32(2): 91-114, Spring, 2018.
• As Rabin and Thaler (2001) indicate, expected utility (EU) maximization seems incapable of explaining people’s risk preferences – even though it does suggest some nice measures of the degree of risk aversion.
• Other models of risk aversion, however, might prove more empirically sound, while maintaining tractability. That is, we might not need expected utility to analyze problems involving risk aversion, as alternative models could replicate current standard, EU-based results, while offering still more or avoiding the shortcomings associated with the assumption of EU maximization.
• Consider standard findings associated with insurance: (1) A more risk averse person is willing to pay more for insurance (than is a less risk averse person); and (2) at a fixed price per dollar of insurance (fixed in excess of the actuarially fair price), a more risk averse person will purchase more insurance (than will a less risk averse person).
• Consider standard findings associated with financial investments: (1) In a world with one safe (riskless) and one risky asset, more risk averse people invest less in the risky asset; and (2) if the population as a whole becomes more risk averse, the price of the risky asset must fall (equivalently, the expected return from holding the risky asset must rise).
• Consider standard findings of principal/agent analysis, say, when a risk neutral principal hires a risk averse agent: (1) if the agent’s effort is not observable, then to encourage effort, the agent will have to bear some risk (so that lower output leads to less pay); and (2) the unobservability of effort is costly to the principal, who would prefer to contract on effort directly.
• The various claims made concerning risk aversion in the three previous bullet points do require risk aversion – but they do not require expected utility maximization.
That is, many of the ideas that have been developed around the concept of risk aversion – developed in the context of expected utility maximization – remain valid even when expected utility maximization is not descriptively accurate.
• Consider loss aversion as an alternative approach, one where outcomes are judged against a reference point and “losses loom larger than gains.” For prospects with some loss and some gain outcomes, loss aversion can generate risk averse behavior. (This style of loss aversion does not require "diminished sensitivity," the feature of prospect theory that leads to risk averse behavior in the gains domain and risk seeking behavior in the losses domain.)
• A second alternative, also featured in prospect theory, is probability weighting. The general notion is that, in practice, decision weights might not equal objective probabilities. Specifically, probability weighting typically involves the overweighting of low probability events and the underweighting of high probability events. This type of probability weighting can generate, depending on the options, either risk seeking or risk averse behavior. Lotteries, for instance, might be attractive (induce risk seeking behavior) due to the overweighting of the low-probability outcome of a large win.
• Finally, consider contextual features and salience. Extreme or vivid outcomes (like deaths in terrorist attacks) might garner intense attention, leading to higher decision weights on those outcomes. The contextual feature of the available (although unchosen) options can exert influence by shifting the salience of other outcomes. Again, choices displaying risk aversion can arise from these factors. Expected utility maximization is neither necessary nor sufficient for explaining risk-averse behavior.
Weijia (Daisy) Dai and Michael Luca, “Digitizing Disclosure: The Case of Restaurant Hygiene Scores.” Harvard Business School, Working Paper 18-088, 2018 [pdf of 2019 version here].
• San Francisco does not mandate that restaurants post their hygiene scores – which are public information generated by unannounced inspections – but is willing to facilitate the posting of the scores on Yelp. (The scores already are available on the City's Department of Public Health website -- but people don't usually go there to order food online!) The (common) reluctance to require disclosure by the restaurants themselves might draw in part from restaurant industry opposition.
• Two interventions are examined: (1) Yelp posts the hygiene scores on its restaurant webpages; and (2) Yelp makes low scores salient via a “hygiene alert” box (which covers the customer reviews part of the Yelp listing)
• A “Poor” restaurant hygiene score (70 or below) results from multiple high-risk violations
• The hygiene alert box informs the webpage visitor that food safety is the point of the hygiene score, and that the score is based on government inspection; further, the alert reveals that the restaurant received a Poor rating in its most recent review, which puts it in the bottom 5% of hygiene ratings.
• Prior to the Yelp interventions, less hygienic restaurants see slightly lower consumer purchasing intentions than do their more hygienic counterparts. Those purchasing intentions are measured via Yelp page visits, “leads,” and the number of Yelp reviews. A "lead" is tallied through various behaviors by online shoppers, such as calling the restaurant, seeking directions to the restaurant, or checking out the restaurant's own webpage (as opposed to its Yelp listing).
• Leads and Yelp reviews respond in the expected direction to Yelp posting of the hygiene scores; Yelp (star) ratings do not
• “Poor” restaurants see a 12% decline in leads compared to the non-Poor
• The salience intervention enhances the posting effect: take-out orders for Poor restaurants fall 12.8%. That is, how information is disclosed seems to matter, along with the disclosure itself.
• Poor restaurants seem to be (somewhat) motivated to clean up their act after Yelp posts the alert
Oren Bar-Gill, David Schkade, and Cass R. Sunstein, “Drawing False Inferences from Mandated Disclosures.” Behavioural Public Policy, published online 15 February 2018.
• When the government mandates that sellers (of food products, say) reveal some information to potential purchasers, the message that the consumers take away from the disclosure might not be what the government intended to convey.
• The perceived motivation(s) behind the government's requirement could affect consumer responses. Some mandates are aimed to convey a verified health risk; others might satisfy a somewhat nebulous consumer "right to know," even if no health risk is involved. Interest group pressures or social values of some sort (e.g., supporting domestic employment) are other motivations for disclosure mandates.
• People are more disposed to be influenced by the information relayed in a mandated disclosure if they believe the motive behind the mandate is new research findings (as opposed to political pressures). Problems arise when consumers are misled by mandated
information; such misleading is likely when consumers misperceive the
motives behind the mandate.
• The Bar-Gill, Schkade, and Sunstein article itself seems motivated by proposed and sometimes enacted government mandates that require firsm that sell foods including GMOs to indicate that fact. The potential issue is that there seems to be no evidence that GMO-containing foods possess higher health risks than do other foods; nonetheless, the mandated information could lead consumers to believe that GMOs are known to be unsafe.
• The authors’ Mturk survey (n=1675) concerns either GMOs or a fictitious synthetic food preservative, Z25.
• The government could: (1) let voluntary disclosure do all the work (that is, take no action); (2) mandate disclosure; or (3) mandate a warning. Government motives are either: (1) right-to-know; (2) political pressure; or (3) new research.
• After learning the government action, some subjects are told the government motive, while others are asked what they think the motive is.
• Subjects rate perceived risk (ex post and, for GMOs, ex ante, too) on a 0 to 100 scale, and indicate their intentions to purchase.
• False inferences may be a problem: posterior risk changes as much from new research as from right-to-know motivations; perhaps consumers do not trust that right-to-know motives are pure.
• A political pressure motive seems to lower the perceived risk of GMOs after disclosure (relative to no action).
• Subjects with strong prior beliefs about GMOs do not appreciably alter their beliefs based on government actions and motives.
• Can counter-advertising fix the false inference problem?
David N. F. Bell and David G. Blanchflower, “The Well-Being of the Overemployed and the Underemployed and the Rise in Depression in the UK.” NBER Working Paper No. 24840, July 2018. [A later version appears in the May, 2019 issue of the Journal of Economic Behavior and Organization.]
• Unemployment is very detrimental to subjective well-being (SWB); but what about underemployment?
• It turns out that in the UK, working fewer hours than you would like to work (at the same rate of pay) also undermines SWB – though not by as much as does poor health or unemployment.
• Overemployment also lowers well-being!
• Though unemployment in the UK has recovered from the 2008 crisis, underemployment has not recovered; earlier this year [2018], it stood at about 3% of the labor force.
• Incomes and real wages also have not recovered, perhaps because underemployment is a sign of slack in the labor market.
• Men are more likely than women to be underemployed, and lower wage workers are more likely to desire more hours.
• Data are drawn from four subjective well-being questions that focus on different conceptions of life assessment: (1) satisfaction; (2) worthiness; (3) happiness; and (4) anxiety. The first three measures show improvements in well-being over the 2011-2017 period; not so for anxiety.
• The usual age effects show up, with well-being minimized at ages 50-54; things again head south after age 75 (but from global highs at 70-74). Retired people display high well-being.
• Depression is fairly common (and much more so now than ten years ago), with 2.3% of workers being depressed and almost 10% of the unemployed being similarly situated.
Arie Sherman and Tal Shavit, “The Thrill of Creative Effort at Work: An
Empirical Study on Work, Creative Effort and Well-Being.” Journal of
Happiness Studies 19(7): 2049–2069, October 2018 [pdf].
• Maybe work isn’t just a means to the end of having money? Could it be that there are some non-pecuniary benefits of work?
• Sherman and Shavit suggest that workers might invest creative effort to build up their “hedonic capital.”
• They survey 922 Israeli adults who are salaried employees (that is, not self-employed). The idea is to see if those who invest more creative effort at work (for the purpose of making work more enjoyable) have higher subjective well-being.
• The authors check four measures (on 0-to-10 scales) of subjective well-being: overall satisfaction; meaning and purpose; positive feelings; and, negative feelings.
• The results indicate that creative effort (self-rated on a 1-to-7 scale) at work improves subjective well-being (SWB) when SWB is measured as life satisfaction, meaning and purpose, or positive affect.
• Creative and intellectual work raises SWB.
• Good health and financial satisfaction raise SWB; income does not aid meaning and purpose.
• Having children does not raise SWB but does add meaning and purpose.
• There are U-shaped age effects on SWB and positive affect (that is, there's a trough in midlife), but not for meaning and purpose.
• Good health, financial satisfaction, and religiosity all seem to reduce negative affect.
Erik Lindqvist, Robert Östling, and David Cesarini, “Long-run Effects of Lottery Wealth on Psychological Well-being.” NBER Working Paper No. 24667, May 2018 [pdf of a similar version here].
• Adaptation might suggest that the (exaggerated?) hedonic benefits from a monetary windfall will be short-lived.
• Lottery data can help us identify the extent to which wealth causes increased happiness or life satisfaction, in both the short and the long run.
• The authors look at Swedish lottery winners 5 to 22 years after their stroke of good fortune.
• The estimation undertaken here of how much happiness flows from wealth compares very similar people: they are all lottery winners, but the amounts they won differ.
• Happiness and Life Satisfaction are reported on an 11-point scale. They are highly positively correlated, though are influenced differently by wealth. Other variables collected are Mental Health, and Financial Life Satisfaction.
• Life Satisfaction is raised by an extra $100,000, and the effect is lasting.
• The source of the increased Life Satisfaction is improved Financial Life Satisfaction. (Yes, a financial windfall improves one's financial satisfaction!)
• Happiness and Mental Health are not improved (in the long run) by a lottery win.
• This research was all pre-registered: opportunities to p-hack are minimal; N ≈ 3350
• Lottery winners in this sample tend to behave prudently – they don't squander their winnings in a short period of time.
