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]

Changing global inequality, migration and open borders

In the last couple of months, I've written a couple of blog posts on Branko Milanovic's research on global inequality over recent centuries (see here and here). In this post, I want to update to some of his latest research on global income inequality published in Global Policy in 2013 (ungated version here).

In the paper, Milanovic again looks at how global inequality has changed over time. This time the important comparisons are only from 1952-2011 (rather than over past centuries) - his Figure 2 is reproduced below.

"Concept 1" inequality is inequality between countries, i.e. differences in average incomes between countries (without weighting by country size, so for example India and Israel would count the same). "Concept 2" inequality takes the population size into account, but still measures inequality as if everyone had the average income in their country, i.e. it ignores inequality within countries. "Concept 3" inequality is closest to true global inequality because it is between individuals the world over (or at least, those covered adequately by household surveys). Concept 3 is obviously the best measure of inequality of the three, and I guess you can see almost whatever pattern you want to see from those dots (maybe it is trending upwards; or maybe you focus on the downward trend of the last three dots?). Milanovic labels this diagram "the mother of all inequality disputes".

Anyway, regardless of what you think is happening to "Concept 3" inequality, it is clear that "Concept 1" inequality increased substantially from the 1950s to 2000, then declined since then, while "Concept 2" inequality has been declining slowly over most of the period, before accelerating since the 1990s. If you remember my post of Milanovic's earlier work, he showed that inequality between countries had grown substantially over the last two centuries. The lastest data is showing a reversal of that long term trend. The poorest countries are growing the fastest, and this is lowering between-country inequality substantially. And when you consider that the most populous poor countries (China, India) have been growing fast, then the decrease in "Concept 2" inequality has been substantial.

What's surprising then is the persistence of "Concept 3" inequality remaining high, which must be due to increases in within-country inequality, particularly in fast-growing populous countries like China. So, while the growing middle class in poor countries is getting much better off, the poorest in those countries may not be much better off than they were years ago.

Milanovic notes that there are three ways in which to reduce global inequality:

1. Increasing the growth rates of poor countries (relative to rich countries), especially those of populous poor countries like China, India, Indonesia, Nigeria, etc.
2. Introducing global redistributive schemes, e.g. through much-increased development assistance for poor countries
3. Migration.

Migration would enable the poor to improve their living standards. Even if they are within the poorest sections of the population in a rich country, they may be better off than being around the median (or below) in a poorer country. Michael Clemens has made a similar case for the benefits of freer migration. However, completely opening borders for economic migrants is unlikely to happen any time soon, even though rich western nations could benefit greatly from an influx of young migrants to offset their rapidly ageing labour forces (more on that in a later post). Milanovic notes:

...there are seven points in the world where rich and poor countries are geographically closest to each other, whether it is because they share a border, or because the sea distance between them is minimal. You would not be surprised to find out that all these seven points have mines, boat patrols, walls and fences to prevent free movement of people.

For the record, those seven borders are on land: U.S.-Mexico; Greece-Macedonia/Albania; Saudi Arabia-Yemen; North Korea-South Korea; Israel-Palestine; and by sea: Spain-Morocco; and Indonesia-Malaysia.

Read more:

• The last two centuries of global inequality
• Inequality was similar, or higher, in ancient times than it is today

Video on signalling

One of my favourite topics to teach in ECON100 and ECON110 involves information asymmetry, including adverse selection and moral hazard. Long-time readers of my blog will have noticed that a number of  my posts cover similar topics. That's both because these topics are difficult for students to understand (so blogging about it helps them), and because there are lots of real-world applications that I can discuss (such as yesterday's blog post on technology and health insurance).

Anyway, the point of this post was to draw attention to one of the latest MRUniversity videos, which is on signalling:

Enjoy!

[HT: Marginal Revolution]

Why your Fitbit or Apple Watch could soon get you cheaper health insurance

Last year I wrote a post about the impact of technology on car insurance, noting that car insurers had started offering discounts to car owners who installed a black box in their car that could monitor their driving behaviour. Now, a Swiss insurer is looking to introduce the health insurance version:

Swiss health insurers could demand higher premiums from customers who live sedentary lifestyles under plans to monitor people’s health through wearable digital fitness devices.

CSS, one of Switzerland’s biggest health insurers, said on Saturday it had received a “very positive” response so far to its pilot project, launched in July, which is monitoring its customers’ daily movements...

The pilot also aims to discover to what extent insured people are willing to disclose their personal data, and whether self-monitoring encourages them to be more active in everyday life, pushing them to take 10,000 steps a day.

I noted in the car insurance example last year that the companies were using the black box mainly to overcome moral hazard. However, in this case the technology probably much more effective for solving adverse selection problems.

An adverse selection problem arises because the uninformed party cannot tell those with 'good' attributes from those with 'bad' attributes. To minimise the risk to themselves of engaging in an unfavourable market transaction, it makes sense for the uninformed party to assume that everyone has 'bad' attributes. This leads to a pooling equilibrium - those with 'good' and 'bad' attributes are grouped together because they can't easily differentiate themselves. This creates a problem if it causes the market to fail.

In the case of insurance, the market failure may arise as follows (this explanation follows Stephen Landsburg's excellent book The Armchair Economist). Let's say you could rank every person from 1 to 10 in terms of risk (the least risky are 1's, and the most risky are 10's). The insurance company doesn't know who is high-risk or low-risk. Say that they price the premiums based on the 'average' risk ('5' perhaps). The low risk people (1's and 2's) would be paying too much for insurance relative to their risk, so they choose not to buy insurance. This raises the average risk of those who do buy insurance (to '6' perhaps). So, the insurance company has to raise premiums to compensate. This causes some of the medium risk people (3's and 4's) to drop out of the market. The average risk has gone up again, and so do the premiums. Eventually, either only high risk people (10's) buy insurance, or no one buys it at all. This is why we call the problem adverse selection - the insurance company would prefer to sell insurance to low risk people, but it's the high risk people who are most likely to buy.

How does a pedometer help solve this problem? Well, if the insurance company provides a short-term insurance contract conditional on wearing the pedometer, then they can use that time to gather information about the wearer. The pedometer won't tell the insurance company about your eating habits, but it will tell them how active your lifestyle is, allowing them to some extent to separate the high risk and low risk people, and then price future insurance accordingly.

Couldn't you just refuse to be part of this and not wear the pedometer? I guess you could. But think about it from the insurance company's perspective. Who is going to refuse the pedometer? The low risk people will pay a lower premium by agreeing to wear it, since it will show they are low risk. So, only high risk people will refuse. Which the article picks up as well:

The implication is that people who refuse to be monitored will be subject to higher premiums, said Blick.

And, if you think that you could just avoid this completely, or attach the pedometer to your dog, or some other workaround:

Fitness wristbands such as Fitbit are just the beginning of a revolution in healthcare, believes Ohnemus.

“Eventually we will be implanted with a nano-chip which will constantly monitor us and transmit the data to a control centre,” he said.

Which sounds very much like the future that Adam Ozimek is foreseeing:

Constant measurement will include many things that to our eyes look like serious encroachments on privacy. Our health, spending, and time use will be easily and often measured. These will start off as opt-in systems, but the better they work the more economic incentive people will have to sign up. For example, for a big enough discount on health insurance you will probably agree to swallow the health tracking devices. Eventually, it probably won’t be a choice. The good new is after opting in to so much voluntary tracking this won’t seem like as big of a deal to people in the future as it does to us.

In a way, this will make us much less free as we are faced with prices for many behaviors that used to be costless to us. But it will also mean that the costs that we bare for other people’s behaviors will decline and the dollar cost of government will shrink, which will make us more free in a sense.

Finally, what about moral hazard? Moral hazard is the tendency for someone who is imperfectly monitored to take advantage of the terms of a contract (a problem of post-contractual opportunism). I'm not sure the case is nearly as strong for moral hazard being a problem of health insurance. However, this is how we would explain it. In countries that have a private or insurance-based healthcare system, people without health insurance have a large financial incentive to eat healthily, exercise, and so on, because if they get sick they must cover the full cost of their healthcare themselves (or go without care, substantially lowering their quality of life). Once they are insured though, people have less financial incentive to eat healthily and exercise because they have transferred part or all of the financial cost of any illness onto the insurer (though they would still face the opportunity cost of lost income while they are in hospital, etc.). The insurance contract creates a problem of moral hazard - the insured person's behaviour could change after the contract is signed.

Now, health insurers aren't stupid and insurance markets have developed in order to reduce moral hazard problems. This is why we have excesses (deductibles) and co-payments - paying an excess or a co-payment puts some of the financial burden of any illness back on the insured person and increases the financial incentive for eating healthily and exercising. The pedometer clearly gives the insurer the ability to more closely monitor people's behaviour, but would people exercise more if they know their insurer is watching? That's harder to say.

Overall though, wearable technology is going to make it easier for health insurance companies to price their premiums according to risk. So, if you're the healthy type your Fitbit will likely earn you a lower health insurance premium.

[HT: Marginal Revolution]

Read more:

• Could technology eliminate moral hazard in car insurance?
• Is there adverse selection in the life insurance market?