Social norms, defaults, and tipping taxi drivers

When you come from a culture (like New Zealand) where tipping is not a social norm, understanding when and how much to tip in a tipping culture (like the US) can be a bit of a mystery. I admit that my tipping behaviour is strongly driven by the menu options that are available on screen when I pay by credit card. If the screen suggests 15%, 20%, and 25%, I'll often choose one of those. That way, I don't have to try and work out how much the tip should be. Choosing one of the default menu options lowers the cognitive cost of the tipping decision. Besides, if it wasn't a social norm to tip those percentages, why would they display them on-screen?

Obviously, they are important for me, but how important are the on-screen menu options in general? That is essentially the question addressed in this 2021 working paper (with a non-technical summary here) by Kwabena Donkor (Stanford University). Donkor has data on over 250 million Yellow Taxi trips in New York City between 2010 and 2018, but only uses a randomly-selected subset of that data (a 20% sample of the data from 2014, and a further 10% sample from the full dataset) to make the task more manageable. To understand how the default menu options affect tipping behaviour, Donkor looks at:

...variation in tipping behavior a year before and a year after the CMT [Creative Mobile Technologies] default tip menu changed on February 8, 2011. The menu showed default tips of 15%–20%–25% then changed to 20%–25%–30%.

If taxi customers were purely rational, then the default options should not affect tipping behaviour at all. They would automatically choose the size of the tip that was 'best' for them. However, as we discussed in my ECONS102 class this week, people are not purely rational, and are affected by (among many other things), how a decision is framed. If you change the default tipping options, then you are changing the context of the decision. In turn, this may affect tipping behaviour. Indeed, Donkor finds that taxi customers are not purely rational. That is:

...the average tip rate increased from 17.45% of the taxi fare to 18.84% (an 8% increase), but the share of default tips decreased from 58.39% to 47.13% (a 19.3% decrease). However, the share of passengers who do not tip stayed [the] same (no extensive margin adjustments).

So, changing the default increased the amount of tipping on average, but as the defaults increased in value, fewer people chose the default. Interestingly, this result supports both rational and quasi-rational behaviour. It was quasi-rational because changing the default menu options affected the amount of tipping. It was rational because, as choosing the default costs more, people do a little bit less of it.

Donkor then looks at what happens when you shift from three default options to five default options (as happened in 2017). Comparing 2016 and 2018 data, he finds that:

...default tips increased by 11.5% (up from 59% to 66%).

Perhaps that means that more people were able to see a social norm tip that they could agree with, when there were more options available? This reduces the cognitive cost of calculating an alternative tip, and so more people choose one of the (five) default options.

There were also some other interesting results that Donkor notes in the paper:

The norm tip increases by 24% on New Year’s, 6% on Thanksgiving, and 18% on Christmas. Norm conformity increases by 89% on New Year’s Day, by 42% on Christmas day, but not significantly on Thanksgiving. The norm tip increases by 5% and 1%, respectively, when it snows or rains. However, norm conformity does not change much during bad weather.

Traveling with co-riders reduces the norm tip by 3.5% and norm conformity by 12.3%. This finding aligns with the bystander effect: when traveling in a group, no one person feels directly responsible for the guilt of not tipping or paying a low tip.

The takeaway message overall is that people tend to follow social norms because it is less costly to do so than the alternative. The costs of not following a social norm are not monetary. They fit into the category of 'social incentives' (which Levitt and Dubner note in their book Freakonomics are the incentives that arise from other people thinking that something is right or wrong). However, as the costs of following the social norm rise, more and more people will choose not to follow the norm. So, fortunately there is a limit to how high taxi companies can push the default tips in the menu before they induce too many customers to opt out.

[HT: Marginal Revolution, earlier this year]

Loss aversion and the endowment effect in health-seeking behaviour

When I teach loss aversion in my ECONS102 class, I raise one of the consequences of loss aversion as the endowment effect. The explanation is fairly simple. When people are loss averse, they value losses much greater than otherwise equivalent gains. Giving something up therefore makes people very unhappy, and so people prefer to hold onto the things that they have. That means that, when a person owns something, they have to be given much more to compensate them for giving it up than what they would have been willing to pay to get it in the first place.

However, it turns out that loss aversion may not be the best (or only) explanation for the endowment effect. In a new NBER Working Paper (ungated version here, with a non-technical summary here), Emily Beam (University of Vermont), Yusufcan Masatlioglu (University of Maryland), Tara Watson (Williams College), and Dean Yang (University of Michigan) look at how people respond to a $50 incentive to attend a health service provider, when it is framed as a loss versus when it is framed as a gain. More specifically:

In this study, we implement a randomized field experiment that compares loss versus gain framing to promote preventive health care utilization. We offer individuals in and near Dearborn, Michigan, an incentive to visit a health clinic run by our partner organization, the Arab Community Center for Economic and Social Services (ACCESS). In the “Visa gift card” (loss framing) treatment, participants are given a Visa gift card of either $50 or $10 that can be activated by visiting the clinic; they will effectively lose the value of the card if they choose not to visit a clinic. In the “reminder card” (gain framing) treatment, participants are given a physically similar generic reminder card with the promise that it will be exchanged for a gift card if they visit the health clinic, but they are not given the gift card up front. In both cases, any individual who went to the health clinic would receive an active Visa gift card, and any funds remaining after the visit could be spent elsewhere. Because of random assignment to the treatments, differences in responsiveness to the incentives are attributable to the differences in the frames.

Research participants who were given a Visa gift card essentially face a loss if they choose not to activate it. That's because, once they finish the initial survey, they have the card in hand and choosing not to activate it is like losing $50. The other participants only receive a reminder card, which can be converted into a gift card. So, if they don't go to the clinic, they aren't losing in the same way. So, if there is an endowment effect, we'd expect those who received the gift card to be more likely to visit the clinic.

However, that isn't really what Beam et al. are looking at. They are investigating why there is an endowment effect. So, in the initial survey, they ask questions that are designed to provide an estimate of how loss averse people are. If the endowment effect is related to loss aversion, then the effect should be larger for people who are more loss averse. However, the endowment effect might also arise because of trust. As Beam et al. explain:

A second possible explanation for the effectiveness of loss framing is that giving an incentive up front induces an individual to have more confidence that the incentive will be provided as promised. The perceived probability of receiving a reward is likely higher for someone who has a tangible reward in hand relative to someone hearing about a promised reward. This trust‐related response is likely more relevant in field contexts outside the lab, and it is expected to be most relevant when individuals do not initially trust the person or institution offering the incentive.

If the endowment effect arises because of trust issues, then it should be larger for people who report less trust in the health care organisation, ACCESS. So, armed with measures of trust and loss aversion for around 1500 people (whose gift card was worth $50, and ignoring a smaller group whose gift card offer was only $10), and knowing which of the research participants visited the clinic (to receive or activate their Visa gift card), Beam et al. then find that:

The overall average difference in take‐up between those who receive the $50 Visa gift card (loss frame) and $50 reminder card (gain frame) is about 2.2 percent... The differences between Visa gift card and reminder card redemption rates are 4 to 5 percentage points for more loss‐loving participants and 1 to 2 percentage points for more loss‐averse participants. These results are not statistically significant... There is no clear pattern linking loss aversion to take‐up rates, nor to the gap in take‐up rates between gift card and reminder treatments.

So, there is a small endowment effect, but it isn't related to loss aversion. What about trust? Beam et al. find that:

Participants without trust of the organization at baseline are much more responsive to the gift card treatment (loss frame); the impact of the gift card is 7.2 percentage points for this group... The statistically significant interaction term... suggests that there is no comparable effect for those who do trust ACCESS at baseline.

In other words, there is an endowment effect for research participants who do not trust ACCESS, but no endowment effect for research participants who do trust ACCESS. When I first read those results, I was a little concerned that they arose only because Beam et al. combined people who reported low trust with people who had no opinion because they hadn't heard of ACCESS before. However, when those categories are separated, the results remain similar.

So, it really does seem that it is trust, and not loss aversion, that likely explains the endowment effect in this context. That doesn't necessarily mean that loss aversion is never a source of the endowment effect though, so I think I am safe (for the moment) in continuing to teach it as closely related to loss aversion.

The Beam et al. paper is also interesting in noting some of the real-world difficulties in research, especially this bit:

During our first survey wave, we encountered several safety issues: some interviewers were harassed by residents; on another day, interviewers witnessed gunfire a few blocks away. After these experiences, we excluded tracts that reported relatively high recent crime levels, and we contacted the Dearborn police department to exclude any additional tracts that they considered to be unsafe...

 Yikes! And slightly more mundane, this bit on how they had to adapt the measurement of loss aversion:

Although these questions are typically worded as a gamble, we adjusted the wording to be an “opportunity” after pilot testing revealed many subjects would reject all gambles because of religious objections to gambling.

Real-world field research is often not as straightforward as we hope it would be.

[HT: Ranil Dissanayake]

Framing, loss aversion, transaction utility, and reusable coffee cups

This article in The Conversation yesterday, by Sukhbir Sandhu, Robert Crocker, and Sumit Lodhia (all University of South Australia) caught my attention, because it nicely illustrates some of the concepts from behavioural economics that I discussed with my ECONS102 class last week:

Many cafe owners offer discounts ranging from 10c - A$1 to customers who bring in their own reusable cups.

But our findings reveal these discounts are ineffective in changing consumer behaviour.

A cafe owner we interviewed described how, despite providing a 20c discount for reusable cups, she didn’t think saving money motivated her customers:

The regulars were people who’d happily drop in a dollar tip into the jar kept on the counter. They were therefore not that concerned about 20c discount.

We know from previous behavioural psychology literature consumers are more likely to be what’s called “loss averse” as opposed to “gain seekers”. In other words, people hate paying extra for takeaway coffee cups more than they like getting a discount for bringing their reusable cups.

So, if you own a cafe, focus on making consumers pay extra for choosing takeaway coffee cups rather than offering discounts for reusable cup use. It’s more likely to motivate customers.

Let's say that a cafe owner wants to encourage customers to use reusable cups. They might do this because of concern for the environmental effects of disposable coffee cups, or the cafe owner might simply recognise that disposable cups cost them money, and so offering to fill a customer's own cup must be slightly more profitable for the cafe owner, because then they don't incur the cost of providing a cup.

Putting aside any cost differences, cafe owners could discourage their customers from disposable cups by making coffee sold in disposable cups more expensive. We know that when something is more costly, rational consumers will buy less of it. This also makes coffee in reusable cups relatively cheaper, and so would encourage some consumers to switch. Let's consider two different framings of the price difference: (1) consumers who use a reusable cup receive a 20 cent discount; or (2) consumers who use a disposable cup have to pay an extra 20 cents. 

How many consumers would switch? If consumers were purely rational, it wouldn't matter how the price difference was framed. A 20-cent discount for using a reusable cup and paying 20 cents extra for a disposable cup are exactly the same (provided the prices are the same in each case). Both options would lead to the same number of customers switching to a reusable cup.

Now here's where some behavioural economics comes in. Consumers (like every decision-maker) are not purely rational, they are quasi-rational - they are affected by cognitive biases and use heuristics when making decisions. Framing makes a difference to quasi-rational consumers, but it's not clear which framing should make consumers use fewer disposable cups.

One of the cognitive biases that quasi-rational decision-makers are affected by is loss aversion - decision-makers dislike losses much more than they like equivalent gains. In this case, the loss in utility (or satisfaction, or happiness) for the consumer from paying 20 cents extra for a disposable cup, is 'worth' much more than the gain in utility (or satisfaction, or happiness) for the consumer who receives a 20-cent discount for using a reusable cup. So, we would expect the 'loss framing' (20 cents extra) to have a much bigger effect on consumer behaviour than the 'gain framing' (20-cent discount). 

However, another cognitive bias that affects consumers is transaction utility, which I have blogged about before. Transaction utility recognises that consumers not only receive utility from the good or service that they purchase, but also from the act of purchasing. If a consumer feels that they are 'getting a good deal', this makes them happier (higher utility), and makes them more likely to purchase. So, based on transaction utility, we would expect the 'gain framing' (20-cent discount) to have a bigger effect on consumer behaviour than the 'loss framing' (20 cents extra).

Given that Sandhu et al. found that the negative framing had a bigger effect overall, it appears that the loss aversion effect is larger than the transaction utility effect. It would be good to see more research on this though, that disentangles those two effects more.

Overall, the takeaway message from this research is that if you, as a seller, want to steer consumers away from something using a price difference, present it as involving a loss to them (they have to pay extra). On the other hand, if you want to steer consumers towards something using a price difference, present the alternative as involving a loss to them. At least until this has been investigated a bit more, it appears that paying extra is a more powerful motivator for changing consumer behaviour than a discount.

Auckland Airport passport control's accidental nudge fail

I just got back from Europe, where I was attending the EduLearn 2018 conference. On arriving back at Auckland Airport, we were confronted as usual with rows of SmartGate (or eGate) machines, which scan your e-passport and take a photo of you, rather than having to have your passport physically checked by an officer. These SmartGates at Auckland Airport are now usable by many different passport holders (which caused me some disquiet when we arrived in London to find that we couldn't use the same facilities there and yet UK citizens can do so in New Zealand - whatever happened to reciprocity?). Anyway, I digress.

Nudge theory was brought to prominence by Richard Thaler and Cass Sunstein's excellent 2008 book Nudge. The idea is that relatively subtle changes to the decision environment can have significant effects on behaviour. If I remember correctly, one of their examples was the difference between opt-in and opt-out retirement savings schemes, where opt-out schemes have much higher enrolment rates compared with otherwise-identical opt-in schemes. One of the most important insights of behavioural economics and nudge theory is the idea that how a decision is framed can make a difference to our decisions. Governments are making increasing use of nudges to modify our behaviour, including the Behavioural Insights Team in the UK, and similar efforts in the U.S. and Australia.

Not all nudges are intentional or helpful though, as we discovered at Auckland Airport passport control. Above the SmartGate machines was a helpful row of the flags representing all the nations whose passport holders could use SmartGate. However, these flags were lined up in groups of three or four (or two, in the case of Australia and New Zealand), with each group of flags located above a corresponding group of SmartGate machines (I'm really sad I can't share a photo, because of laws prohibiting photography in this area, so you'll have to make do with my description). Unsurprisingly, this gave a strong impression to arriving passengers that they should go to the machines corresponding to the flag of their passport. Passport control framed our decision about which machine to choose by making it seem that the flags mattered. In actuality, all SmartGate machines could handle any of the e-passports.

So, when my wife and I arrived at passport control, there was a huge line for the machines with the New Zealand and Australian flags, and virtually no lines at all for the machines with the European flags. We weren't caught out by this unintentional nudge (because we knew that all of the machines worked the same, and we were willing to buck the trend and not line up in the 'New Zealand and Australia' line), and managed to substantially jump the queue.

I wonder how long it will take for Auckland Airport (or Customs or whoever controls that area) to realise their error and correct it? I'm off to Ireland in August for another conference, so I guess I will see then.

Economists are susceptible to framing too

Back in August, I blogged about a paper showing that philosophers suffer the same cognitive biases as everyone else. Now, a recent NBER Working Paper (pdf) by Daniel Feenberg, Ina Ganguli, Patrick Gaule, and Jonathan Gruber has shown that economists (or at least, the readers of NBER Working Papers) are affected by framing too. Neil Irwin also wrote about it at the Upshot last month.

The authors looked at how the order that NBER Working Papers appear in the Monday "New This Week" email update affects the number of downloads, and subsequently the number of citations, that each paper receives. Now, since the papers are listed in numerical order, which papers appear at the top of the list is essentially random. If all readers of "New This Week" were rational, the order that papers appear in the list would make no difference to which ones they chose to read.

However, it appears the order does matter. The authors write:

Our findings are striking: despite the effectively random allocation of papers to the NTW ranking, we find much higher hits, downloads and citations of papers presented earlier in the list. The effects are particularly meaningful for the first paper listed, with a 33% increase in views, a 29% increase in downloads, and a 27% increase in citations from being listed first. For measures of downloads and hits, although not for citations, there are further declines as papers slide down the list. However, the very last position is associated with a boost in views and downloads.

On top of that, it isn't just all readers of the NBER email that are affected. The framing effects are significant when the authors restrict the sample just to 'experts', being those in academia.

Why would these framing effects occur? A rational reader would weigh up the costs and benefits of reading the email (or the rest of the email) to identify papers that interest them. Given that the order of papers is essentially random, the first paper has the same chance of being of interest as the tenth paper (i.e. the costs and benefits are the same for every link in the NTW email). So, if a rational person reads the first link, they should read every link.

However, people are not purely rational. Framing can make a difference. I can think of two reasons why framing might be important in the case of NTW emails. First, perhaps we suffer from a short attention span. So, when reading through the NTW email, the early papers have our close attention but by the time we get towards the end of the email, we are mainly skimming the titles very quickly. I sometimes catch myself doing this when reading eTOCs sent by journals, especially if I get a lot of them on the same day. However, the authors test the effect of the length of the list, and the effects are not significant.

Second, perhaps we only have limited time available to read NBER Working Papers each week. Think of it as a time budget, which is exhausted once we've read one or two (or n) papers. So, we stop paying attention once we have opened the first one or two (or n) links because we know we won't have enough time to read them. Clearly I wish I had this problem. Instead I print them out and they sit in an ever-increasing pile of "gee-that-would-be-interesting-to-read" papers (which is why I occasionally blog about some paper that is quite dated - you can tell I picked a random paper from the middle of my pile). The authors actually test the opposite - whether having a first paper that has a 'star' author encourages people to read more papers that appear later in the list (i.e. that people decide whether the whole list is worth perusing based on the quality of the first link). They find some fairly weak evidence that having a star author on the first paper reduces the favouritism of the last paper. So maybe the latter of my two explanations alternatives explains the framing effect here.

So, knowing that this is a problem, what to do about it? I guess it depends on what your goal is. If you're an author of an NBER Working Paper, you want to ensure your paper gets to the top of the list so it will be downloaded and cited more. So, maybe there's an incentive for side-payments to whoever puts the NTW list together, or whoever assigns the working paper numbers? More seriously, the authors suggest that randomising the order of papers in the list would improve things, from the authors standpoint. It wouldn't solve the framing problem, but at least it would ensure that authors couldn't game the system.

[HT: Marginal Revolution]

Philosophers suffer the same cognitive biases as everyone else

Behavioural economics is essentially founded on the principle that decision-makers are affected by a range of cognitive biases. In his book "Thinking Fast and Slow" Daniel Kahneman distinguishes between two systems of thought: 'System 1' is fast, instinctive, emotional and subject to many of the observed cognitive biases; and  'System 2' is slower, logical and more deliberative and able to avoid at least some of the biases that System 1 is subject to. The obvious implication is that if you could train people to slow down their thinking and apply more logical reasoning and be more deliberative, you could help them avoid many of the common cognitive biases.

Which brings me to this recent paper (ungated version here) by Eric Schwitzgebel (University of California at Riverside) and Fiery Cushman (Harvard). In the paper, the authors test whether academic philosophers are subject to some common cognitive biases to the same extent as similarly-educated non-philosophers. They use two common experiments: (1) the trolley problem (a common ethics problem); and (2) the 'Asian disease' problem described by Kahneman and Tversky (which is explained here and here, and which I use in my ECON110 class each year).

Essentially the authors were looking for two cognitive biases: (1) Ordering effects, where the order that scenarios are presented affects how they are evaluated; and (2) Framing effects, where the way that different options are framed (or presented) affects how they are evaluated. They find:

...substantial order effects on participants’ judgments about the Switch version of trolley problem, substantial order effects on their judgments about making risky choices in loss-aversion-type scenarios, and substantial framing effects on their judgments about making risky choices in loss-aversion-type scenarios.

Moreover, we could find no level of philosophical expertise that reduced the size of the order effects or the framing effects on judgments of specific cases. Across the board, professional philosophers (94% with PhD’s) showed about the same size order and framing effects as similarly educated non-philosophers. Nor were order effects and framing effects reduced by assignment to a condition enforcing a delay before responding and encouraging participants to reflect on “different variants of the scenario or different ways of describing the case”. Nor were order effects any smaller for the majority of philosopher participants reporting antecedent familiarity with the issues. Nor were order effects any smaller for the minority of philosopher participants reporting expertise on the very issues under investigation. Nor were order effects any smaller for the minority of philosopher participants reporting that before participating in our experiment they had stable views about the issues under investigation.

In other words, even academic philosophers are subject to the same cognitive biases as non-philosophers, and even when they are familiar with the problems they are being asked to evaluate. Scary stuff, particularly as the authors conclude:

Our results cast doubt on some commonsense approaches to bias reduction in scenario evaluation: training in logical reasoning, encouraging deliberative thought, exposure to information both about the specific biases in question and about the specific scenarios in which those biases manifest.

All of which suggests that nudging may be one of the few solutions to cognitive bias.

[HT: Marginal Revolution]

Apes are affected by framing too!

Classes start next week, and the first week of ECON110 covers (among other things) rationality and quasi-rationality (how human decision-makers deviate from pure rationality). One of the effects that leads to deviations from pure rationality is framing. That is, the way that different options are framed (or presented to us) can affect how we evaluate equivalent choices.

The classic example of framing is an experiment that was run in the early 1980s by Nobel prize winner Daniel Kahneman and Amos Tversky (who almost certainly would have shared the Nobel prize had he not died six years before Kahneman's success). I won't explain the experiment in detail (you can read an explanation of it here or here), but essentially the experiment demonstrates that people are more willing to choose the 'safe' (low risk) option when the options are framed positively, and more willing to choose the riskier option when the options are framed negatively. I run this experiment in my ECON110 class every year, with similar results every time.

So essentially, the particular phrasing that we use to describe a problem can affect the choices we make. Now, new research has demonstrated that chimpanzees and bonobos are also affected by framing. From Duke Today:

A Duke University study has found that positive and negative framing make a big difference for chimpanzees and bonobos too.

In experiments conducted at Tchimpounga Chimpanzee Sanctuary in the Republic of Congo and Lola ya Bonobo Sanctuary in the Democratic Republic of Congo, researchers presented 23 chimpanzees and 17 bonobos with a choice between two snacks -- a handful of nuts and some fruit.

In one series of trials, the researchers framed the fruit option positively -- by offering one piece of fruit, with a 50 percent chance of a surprise bonus piece.

In another series of trials, the researchers framed the fruit option negatively. This time they offered two pieces of fruit rather than one, but if the apes chose the fruit, half the time they were shortchanged and received only one piece instead.

Chimps and bonobos were more likely to choose the fruit over the nuts when they were offered a smaller amount of fruit but sometimes got more, versus when they were initially offered more but sometimes got less -- despite receiving equal average payoffs in both scenarios.

So, it turns out that humans aren't so special after all, and our susceptibility to framing might be hardwired into us. Interestingly, only male apes were significantly affected by framing - maybe that means that female apes are more rational than males? You can read the research paper by Christopher Krupenye (Duke), Alexandra G. Rosati (Yale), and Brian Hare (Duke) here.

[HT: Marginal Revolution]