Here's what caught my eye in research over the past week (a very quiet week, it seems!):
Before Ryan Oprea caused us to question all lab experimental measures of risky choice behaviour (as noted in yesterday's post), one main concern about experiments in the lab was whether they accurately reflected real-world decisions. The news is somewhat mixed, as I've written about before (see here and here). And that is quite aside from concerns that experimental subject pools made up of (usually undergraduate) students are not representative of real-world populations (see here).
Nevertheless, the last somewhat hopeful point in yesterday's post suggested that real-world behaviour might still be consistent with the experimental results (even if we cannot believe the experiments). On that note, I recently read this 2016 article by Arjan Verschoor, Ben D’Exelle, and Borja Perez-Viana (all University of East Anglia), published in the Journal of Economic Behavior and Organization (open access). They compare a measure of risk preferences estimated from a 'lab-in-the-field' experiment among over 800 farmers in rural Uganda, with measures of risk taking based on their agricultural choices.
Verschoor et al. compare two types of decisions. The first they term 'narrow-bracketed', where:
...the decision-maker does not consider their consequences together with the consequences of other decisions)...
So, narrow-bracketed decisions are those that are quite independent of other decisions, and therefore simpler. In contrast, a decision that is interdependent with other decisions, which Verschoor et al. liken to "portfolio management", is more complex.
Comparing the results of the lab experiment with real-world decisions that are narrow-bracketed (a fertiliser purchase decision) and not (the decision on whether or not to grow and sell crops for the market), Verschoor et al. find that:
Controlling for other determinants of risk-taking in agriculture, we find that risk-taking in the experiment is associated with the relatively straightforward investment decision of fertiliser purchase. However, for more involved livelihoods strategies that call not only on willingness to take risks but also on other attributes of entrepreneurship, viz. moving away from subsistence farming to growing crops for the market (measured in two alternative ways), we find no evidence of an association with risk-taking in the experiment. By contrast, a hypothetical willingness to take large-scale risks, elicited through a questionnaire, is associated with both fertiliser purchase and growing crops for the market (however measured), suggesting that this is a better proxy for entrepreneurship broadly defined.
In other words, when the real-world decision was reasonably straightforward, and reasonably independent of other decisions ('narrowly bracketed') the farmers behaved in line with their risk preferences measured in the experiment. However, when the real-world decision was more complex and inter-related with other decisions, there is little association with the risk preferences measured in the experiment. Verschoor et al. note that:
The decision to buy fertiliser is a straightforward investment decision that raises both the expected profit and the spread of possible profits within an existing livelihoods strategy... Decisions to grow cash crops or to grow for the market more broadly, on the other hand, are complex, multi-dimensional decisions that invoke not only risk preferences but also the nebulous notion of entrepreneurship.
It is interesting to think about these results alongside those in the Ryan Oprea research I discussed yesterday. Oprea found that risk preferences consistent with behavioural economics (specifically Prospect Theory) only arose because of the complexity of the experimental task used to measure them. Verschoor et al. note in the discussion of their underlying theoretical model that:
...prospect theory, which only considers changes to wealth relative to a reference level, correspondence between the two domains [risky choices in lab experiments and risky choices in real life] is assured provided both are narrowly bracketed...
Combining the two sets of results (from Verschoor et al. and Oprea), I infer that perhaps narrowly-bracketed decisions, which nevertheless involve complex choices in the lab, may show preferences consistent with Prospect Theory. Real-world decisions that are narrowly bracketed demonstrate similar preferences. An open question is whether the real-world decisions are consistent with Prospect Theory because of the complexity of those decisions. Verschoor et al. don't give us any steer on that (and neither should they, given that their article was published eight years before Oprea's).
When you move beyond narrow bracketing, adding interdependence with other decisions and therefore even more complexity, then decisions are not consistent with the lab-estimated risk preferences. We don't know whether that makes them inconsistent with Prospect Theory, but I expect it does. Does that mean that adding even more complexity makes decision-makers more rational? Or perhaps, more salience of the decision (or higher stakes of the decision) makes them more rational? It's not simply the real-world context, or the fertiliser decisions would also be affected.
Now of course, I am trying to reconcile just two sets of results from a much larger literature here, and probably going too far in doing so. However, it will be interesting to see where the lab experiments vs. real-world research literature goes next.
Read more:
Loss aversion has been under fire in the economics literature recently (see here and here). As one of the foundations of behavioural economics, this is a big deal. So, I was interested to read this recent paper by Ryan Oprea (University of California, Santa Barbara), published in the journal American Economic Review (ungated earlier version here). Oprea essentially tests the key tenets of Prospect Theory, that when faced with a risky choice such as a lottery, people are risk averse when it comes to gains, but risk seeking when it comes to losses. Oprea's argument is that we observe that behaviour in lottery experiments, not because it is real, but because it is an artefact of the complexity of the lotteries that the research participants are faced with.
Here's what Oprea did:
In each task in our experiment, we elicit subjects’ dollar valuations for a set of 100 “boxes,” each of which contains some dollar amount. For example, in one of our tasks (called G90), we ask subjects to value a set consisting of 90 boxes that each contain $25 and 10 boxes that each contain $0. Acquiring a set of boxes influences the subject’s earnings in the experiment according to a payoff rule, and we compare how subjects value these sets under two contrasting payoff rules.
By opening one of the boxes from the set at random and paying the subject the amount inside, we turn the set into a lottery (i.e., G90 becomes a risky prospect of earning $25 with probability 0.9), and the dollar value the subject attaches to it becomes a certainty equivalent: the certain dollar amount the subject judges to be equivalently valuable to the risky lottery.
Using those results, Oprea replicates the key results from Prospect Theory, which he refers to as the 'fourfold pattern' of risk (a term that actually comes from Kahneman and Tversky), as well as loss aversion. Then:
Our contribution is to compare these valuations to the valuations of what we call “deterministic mirrors” of the same lotteries. A deterministic mirror of a lottery consists of the same set of 100 boxes used to describe the lottery but is characterized by a different payoff rule: instead of paying the dollar amount in one of the 100 boxes selected at random as a lottery does, a mirror pays the sum of the rewards in all of the boxes, weighted by the total number of boxes. Thus, instead of paying $25 with probability 0.9 (as a lottery does), the mirror of G90 pays 0.9 × $25 = $22.50 with certainty.
In other words, the 'deterministic mirror' of a lottery retains all of the complexity associated with the choice, but eliminates all of the risk (because the amount received is certain, rather than risky). So, if the 'fourfold pattern' is real and arises from the riskiness of the lottery, it should disappear in these experiments. Instead, using data from 673 research participants (and with similar results in a second sample of 489 research participants):
...we find that
(i) The fourfold pattern arises in the valuations of deterministic mirrors just as it does in lotteries, and with roughly the same strength. Importantly, this means that we find strong evidence of what is usually called “probability weighting” in settings without probabilities.
(ii) Loss aversion arises in deterministic mirrors even though at the relevant margins they cannot actually produce losses. Thus, we find strong evidence of what is usually called “loss aversion” in settings without risk of loss.
(iii) Across subjects, the severity of each of these anomalies in lotteries is strongly predicted by their severity in deterministic mirrors, suggesting that the behaviors in the two settings are strongly linked, deriving from a common behavioral mechanism (which, clearly, cannot be grounded in risk or risk preferences).
In other words, Oprea finds strong evidence that it is complexity that drives the 'fourfold pattern' of risk in lottery experiments, because when risk is removed (but complexity remains), the 'fourfold pattern' is still there. On top of that, loss aversion remains even when there is no risk of loss. So, loss aversion may also be an artefact of complexity of lottery experiments. Oprea concludes that:
First, theories of risk preferences designed to explain these anomalies (e.g., prospect theory) are unlikely to contain much normative content and therefore should not be accommodated in the inference of welfare or the design of policy. Second, our finding of systematic departures from neoclassical benchmarks in perfectly deterministic settings suggests that many of our descriptive theories of preferences for risk are really descriptive theories of the way people evaluate complex things.
That's a really nice way of saying that behavioural economists may need to reconsider some of their key theories, because the lab experiments they have been using to verify them do not stand up to this scrutiny. And Oprea's results may also help to explain some of the recent anomalies in the loss aversion literature (see here and here).
Oprea's results are important, and even though the working paper version of this article has already been cited over 50 times, I still don't think this research has received the attention that it deserves (and see Eric Crampton's take here). However, it may not be time to throw away behavioural economics or loss aversion entirely. Oprea notes that:
We do not claim, for instance, on the basis of these data that risk preferences or even loss preferences do not exist but only that they are unlikely to be reliably revealed in lottery valuations.
That is an important caveat. Behavioural economists may simply need to find a new way of demonstrating the 'fourfold pattern' of risk, and loss aversion, without resorting to complex lotteries. These effects may still be real. After all, there is a lot of real-world behaviour that is very consistent with loss aversion (see my various posts on that topic here).
Read more:
The New Zealand Herald reported yesterday (the original story on the Telegraph is here, but behind their paywall):
Topping the traditional Italian favourite with pineapple now comes with a hefty price tag at one trendy pizzeria.
Lupa Pizza, in Norwich, is charging customers £100 ($220) for their Hawaiian pizza on food delivery service Deliveroo because they disapprove of the combination so strongly.
Lupa Pizza is demonstrating their knowledge that demand curves slope downwards. As the price increases, the quantity demanded decreases. A high price of £100 is likely to lead to a quantity demanded of zero. That is, no one buys the Hawaiian pizza.
However, the publicity generated by this stunt may perversely lead Lupa Pizza to sell their absurdly priced pizza. I can just imagine some wannabe social media influencer paying £100 for the memes. Any day now. That would be an example of conspicuous consumption - buying a high-price good simply to signal the wannabe influencer's high status as a purchaser (because who, other than someone of high status, would be willing to pay £100 for a pizza? - see here, for more on that point).
I wonder how much Lupa Pizza's owners would complain when they eventually sell a Hawaiian pizza? Probably not as much as the article would have you believe - the profit margin on a £100 pizza is likely to be substantial (even when you factor in the carrying cost of pineapple as an ingredient that they would rarely use, and probably have to run to the store to get if anyone orders the Hawaiian pizza!).
The pizza may even be underpriced. If lots of wannabe influencers start buying the pizza, Lupa Pizza might need to increase the price even further, in order to really price them out of the market. I wonder what the maximum willingness-to-pay for a Hawaiian pizza is among wannabe social media influencers? We may soon find out.
