Home bias in sovereign ratings

 [Rather irritatingly, I wrote the below post at the end of last week and had been meaning to publish it on Monday. Unfortunately, I got snowed in with work and now see that Tyler Cowen and a bunch of other people have already covered the paper in question. Still, in a bid to get some blogging activity going around these parts again, here's my two cents.]

"The Home Bias In Sovereign Ratings" 

Fuchs and Gehring conduct empirical analyses of variation in nine different credit ratings agencies around the world that offer ratings of at least 25 sovereigns[...] The paper is motivated by two good questions: (1) Do ratings agencies assign better ratings to their home countries? (2) Do they assign better ratings to countries that have close cultural, economic, or geopolitical ties to their home country? 

[...] 

Fuchs and Gehring find clear evidence of “home bias”. Specifically, their analysis finds that agencies do indeed assign higher ratings to their home country governments compared to other countries with the same characteristics. This result was especially strong during the global financial crisis (GFC) years–nearly a 2 point “bump” in ratings.

As someone who has been both a consumer and producer of sovereign rating reports prior to starting a PhD, I find this sort of thing very interesting. The role of inherent biases in the industry is scope for bemusement and alarm. This paper by Fuchs and Gehring would at least seem to go some of the way in explaining why, say, Fitch places the United States in its highest credit ratings category... while (Chinese-based agency) Dagong only places the US in its third highest category.

That being said, Daniel McDowell (author of the above blog post) points out that it is not especially clear how such findings actually stand to affect future ratings. For one thing, changes in sovereign ratings sometimes have zero, or even paradoxical effects, such as when the demand for US treasuries actually rose following the country's downgrade by Standard & Poors in 2011.[*]

On the other hand, it should also be noted that if one of the other major agencies -- i.e. Fitch or Moody's -- had followed S&P's lead in downgrading the US credit score in 2011, then that probably would have had fairly major financial implications. Most obviously, a large number of investment funds have specific mandates regarding the type of securities they must hold... as determined by the average score among the big three credit ratings agencies. For example, a fund might be legally required to hold a minimum proportion of "triple-A-rated" bonds. Given how ubiquitous US treasuries are, some major portfolio rebalancing would almost certainly be required if the US lost its "average" credit rating. You may recall that this is something that a lot of people were worried about at the time. It is also one reason that the ratings agencies continue to have a practical (and potentially deleterious) relevance to financial markets.

Anyway, apologies for getting sidetracked. Interesting paper and blog post. Check them out.
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[*] A popular explanation at the time was that the downgrade provided the shake-up that Congress needed in order to overcome the political impasse over the debt ceiling...

McDermott and Shleifer double-team Taleb and Kahneman

Not really. But I still enjoyed reading the following passage from Andrei Shleifer's review of Daniel Kahneman's (superb) Thinking, Fast and Slow:

The fourth assumption of Prospect Theory is quite important. [i.e. In assessing lotteries, individuals convert objective probabilities into decision weights that overweight low probability events and underweight high probability ones.] The evidence used to justify this assumption is the excessive weights people attach to highly unlikely but extreme events: they pay too much for lottery tickets, overpay for flight insurance at  the airport, or fret about accidents at nuclear power plants. Kahneman and Tversky use probability weighting heavily in their paper, adding several functional form assumptions (subcertainty, subadditivity) to explain various forms of the Allais paradox. In the book, Kahneman does not talk about these extra, assumptions, but without them Prospect Theory explains less.  

To me, the stable probability weighting function is problematic. Take low probability events. Some of the time, as in the cases of plane crashes or jackpot winnings, people put excessive weight on them, a phenomenon incorporated into Prospect Theory that Kahneman connects to the availability heuristic. Other times, as when investors buy AAA-rated mortgage-backed securities, they neglect low probability events, a phenomenon sometimes described as black swans (Taleb 2007). Whether we are in the probability weighting or the black swan world depends on the context: whether or not people recall and are focused on the low probability outcome. [Emphasis mine.]

This exactly the issue I was trying to point out here. Sometimes people greatly overweight the risks of low probability events (as suggested by Kaheman and Prospect Theory)... other times they completely underestimate them (as suggested by Taleb's black swan metaphor). As a result, we should be cautious in trying to make generalisable statements about human behaviour from either one of these theories alone.

You may also recall that -- for my temerity in pointing out this apparent tension between Kahneman and Taleb's theories -- I was labelled an "idiot" by none other than Taleb himself. As I coyly suggested in that second post, Taleb's affinity for labelling others as idiotic meant that I was at least likely to be in good company. I am sure of that now having read Shleifer's article.

TEDxBergen

I mentioned the other day that I acted as moderator for the recent TEDxBergen conference. Videos of the various talks have now been posted online, but here are two that I particularly enjoyed as a sample.

1) Mads Nordmo gave a talk on moral psychology, which challenges the traditional "transactional" view of behaviour -- as is favoured by a lot of economic theory.

Mads is actually doing a PhD with me -- albeit in the strategy department -- and also has a degree in clinical psychology. His opening remark about showing that "it wasn't just beginner's luck" was in reference to a quip that I made about him winning a 'Best lecturer' award from NHH bachelor students. (Link in Norwegian.)

He used various examples to underscore his points, including the growing popularity of CrossFit and the paleo diet.[*] For instance, a purely transactional view provides us with very little insight into why people pay such exorbitant sums of money to join CrossFit gyms. The exercises mostly require far less equipment than ordinary gyms and we could all do as many sit-ups and push-ups as we want at home (for free!). However, Mads argued that these "movements" actually constitute a quasi-religious experience -- much like we would encounter at a rock concert or sports match -- where the sense of communal spirit and exaltation actually enable participants to achieve some kind of transcendence.

In the Q&A afterwards (not shown), I suggested that economics would normally explain the high membership fees paid to crossfit gyms as a commitment device. Mads agreed that this too is an important psychological driver. However, there is at the least no reason to regard such phenomena as mutually exclusive. (Interestingly, he also said that psychology is moving closer to economics... not simply the other war around, as is often asserted in some heterodox circles.) Anyway, he is a smart and funny guy, and I think that both traits are evident in his talk. Check it out:




2) The Grammy-nominated violinist, Peter Sheppard Skærved talked about reinvention and finding new purposes for old tools. Peter is a fascinating person -- the Library of Congress has described him as a polymath -- and I thoroughly enjoyed chatting to him about a range of topics, from anthropology to haptic technology, over the course of the day. In this video, he not only makes a compelling case for preserving "museum pieces" by actively using them as much as possible, but also treats the audience to a range of music pieces from across the ages.

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[*] As someone who has a number of friends into (at least one of) CrossFit and the paleo diet, I freely admit that I am predisposed towards finding this discussion both amusing and enlightening.

It's not every day that you're called an idiot by Nassim Taleb

Or a "bloggist" for that matter.

Here and here.

To be fair, Taleb has charged that many minds superior to my own are beset by idiocy, so I'm in reasonable company. More seriously, he did at least tone down his bombast when I pointed out that he had misunderstood what I was asking.

The background is this post, where I wondered (quite respectful like!) what Taleb made of the research that shows people have a tendency to overestimate the likelihood of low-probability events if they were framed in highly dramatic terms. This seemed to run counter to a recurring theme in his writings, which is that people are blind to "black swans"... basically that they consistently underestimate low-prob, high impact events.

Taleb pointed me towards a short paper on "binary" (up vs down) versus "vanilla" (+500 vs +5,000,000 vs -5,000,000) outcomes, which was supposed to refute the relevance of such studies. However, I remain rather unconvinced. Consider the key figure in my previous post:

Perceived versus actual fatalities. Adapted from Lichtenstein et al. (1978).

As I wrote back then: What we see here is that people have a clear tendency to overstate -- by an order of several magnitudes -- the relative likelihood of death arising due to "unusual and sensational" causes (tornadoes, floods, etc). The opposite is true for more mundane causes of death like degenerative disease (diabetes, stomach cancer, etc).

Now, I certainly agree with Taleb that it is important to distinguish between between binary and continuous outcomes. Asking whether a stock will go up/down is a much less interesting (and less complex) question to ask than whether it will go up/down by a certain amount. You are clearly not comparing apples with apples if you say that a stock will go up by 5% or 500%. In short, binary and continuous ("vanilla") outcomes are incommensurable in terms of evaluating payoffs.

However, the studies that I linked to are interesting exactly because they are comparing the *same* outcome (i.e. death). It makes no sense to say that death by tornado equals five times death by stroke. They are obviously equivalent. The "payoff" is thus the same because the outcome is the same. Further, I'm not claiming that the insights from these particular studies are fully generalisable to all other low probability, high-impact outcomes (especially those in finance). Yet they do show that underestimation of black swan events is hardly a universal phenomenon either... In fact, people here are shown to rely on heuristics that lead them to a diametrically opposite conclusion! I was ultimately interested in hearing from Taleb whether he thinks these heuristics are efficient or not. I didn't get an answer unfortunately, so I guess we'll have to judge for ourselves.

A final observation is that I disagree with the paper's assertion that "binary is limited to probability". (In other words, that binary outcomes say nothing about the size of a payoff.) This is certainly true in many cases -- again, especially in finance -- but not always. In some instances, binary outcomes imply payoffs directly. The obvious example is the one that we have been discussing in this very post, i.e. death. Indeed, I would think that Taleb probably agrees with me, given that one of his favourite analogies is that of a turkey being fattened up in preparation for Thanksgiving.

What Taleb calls his "classical metaphor". A turkey on his way to becoming dinner. (Source)

With apologies to Monty Python, you might say that the prospect of becoming an ex-turkey implies a very obvious payoff indeed.

UPDATE: Andrei Shleifer agrees.

Are there any four-minute miles in economics?

3:59.4

Roger Bannister's four laps of the Iffley Road Track on 6 May 1954 have been immortalised in the annals of sporting lore and human achievement. By becoming the first man to run a sub-four minute mile, he had broken the "impossible" barrier and so made clear the importance of mind over matter. Athletes from all over the world would soon replicate Bannister's feat now that he had liberated them from their mental shackles...

Except... no. The problem with this romantic narrative is that it has been hopelessly embellished. The idea of a four-minute "barrier" was almost entirely the invention of the media, which fanned the idea to sell papers as runners increasingly closed in on the mark. Wikipedia (indulge me) puts it quite nicely:

The claim that a 4-minute mile was once thought to be impossible by informed observers was and is a widely propagated myth created by sportswriters and debunked by Bannister himself in his memoir, The Four Minute Mile (1955). The reason the myth took hold was that four minutes was a nice round number which was slightly better (1.4 seconds) than the world record for nine years, longer than it probably otherwise would have been because of the effect of World War II in interrupting athletic progress in the combatant countries.

I was reminded of this yesterday, as my Twitter and Facebook feeds were flooded by excitable and angry complaints about the Dollar-Rand exchange rate breaching the symbolic threshold of 1:10.

Source: Bloomberg

Now, to be sure, the Rand is at it's weakest level for several years following a number of social upheavals, government scandals and political infighting, questionable economic policy, and wider trends in emerging markets. (Here, here and here for more context.) I should also say that I am not endorsing a "weak Rand" strategy here in any shape or form. I am, however, interested in the question of whether a 1:10 exchange ratio is significant in of itself.

Put differently, do we have reason to believe that the Rand's rate of depreciation will accelerate further as a result of having passed this threshold? I must confess that I don't see it. That's not to say that further depreciation can't happen, but rather: a) That would be the result of existing economic fundamentals rather than surpassing some magic metric mark, b) A full-blown currency crisis seems very unlikely from my perspective. (If nothing else, the South African Reserve Bank is on record as saying that they will tighten policy in the advent of further weakening, although that remains very open to interpretation.)

Moving beyond the case of the USD-ZAR exchange rate, the notion of thresholds pervades much of economics and finance... Or, at least, it pervades talk about economics and finance. Consider, for example, some of the headlines from recent weeks concerning the fall of gold prices to below $1,500 and then $1,400 per ounce... or the brouhaha surrounding that Rogoff-Reinhart paper and their fabled elusive "90 percent" cut-off rate for debt-to-GDP ratios and its supposedly dire consequences on economic growth.

Some of this -- let's call it -- threshold affinity in economics and finance could be justified by underlying factors, such as physical laws, regulatory limits, etc. However, most of it is probably just good copy for selling financial news. At worst, it may even be self-referential nonsense designed to confuse lay investors and the general public. Here are two stylised explanations for why "round number" thresholds shouldn't matter in of themselves:

1. Valuations should ultimately be set according to economic fundamentals. These would not be much different for a stock or trade that is valued at, say, R9.90 versus R10.10.
2. An alternative reason is that traders don't target levels per se. Rather, they target the levels implied by momentum and trend lines (with predefined margins of safety), or algorithmic strategies (which are similar in principle). There's no a priori reason to think that these implied levels will accord to nice round numbers.

Having said that, market psychology can obviously work very differently to the cool, rational calculations implied by standard theory. "Round numbers" will become important, as long as enough people believe them to be important. More precisely, symbolic levels will gain significance if I believe that other people regard them as being significant. (Ye old beauty contest story.) It should also be said that even standard theory does not suppose that change should evolve in a linear fashion...

Let me end this post by saying that I haven't bothered with any kind of literature research; I'd be interested in hearing about studies investigating this type of phenomena. Alternatively, if not much has been done and someone is interested in looking at it further... drop me a line. Two possibilities for checking the existence of "four-minute mile" numbers is that they should act as focal points or thresholds. For the former, we would expect data to bunch around particular levels from both above and below. For the latter, we would expect a discontinuity in the rate of change for a particular stock or currency valuation (i.e. once a threshold is breached). Several ways of testing this empirically immediately spring to mind.

A question for Nassim Taleb fans

I read an interesting article last night, detailing a public exchange between Daniel Kahneman and Nassim Taleb.

[E]ach man was asked to write a biography of seven words or less. Taleb described himself as: “Convexity. Mental probabilistic heuristics approach to uncertainty.” Kahneman apparently pleaded with the moderator to only use five words, which were: “Endlessly amused by people’s minds.” Not surprisingly these two autobiographies are descriptive of the two men’s bodies of work. Much of the discussion at this event, however, was not about making decisions under uncertainty, but a sort of tit for tat, with Kahneman asking probing questions and making pointed observations of Taleb. Little of the Nobel laureate’s [i.e. Kahneman's] work was discussed.

It would seem that Kahneman had Taleb on the back foot at various times during the exchange, pointing out (among other things) that the latter's framing of situations suffered from a clear "anchoring" bias. 

The above article also reminded me of a lingering question that I have about Taleb's work -- not least of all because it relates to the type of research that made Kahneman famous (i.e. the limits of heuristics in the face of statistical problems). Having failed to get any responses to my query on Twitter, I'd like to try and flesh it out here.

Let me state up front that I have yet to read, in full, any of Taleb's books. (They are patiently waiting on my kindle.) However, I have read several chapters from them and, moreover, a number of the articles that Taleb has penned in different media outlets. For instance, this essay for Edge magazine which seems to nicely sum up his position. 

So, I'm reasonably confident that I know where Taleb is coming from. I should also say that I think some of his points are very well made. Such as the "inverse problem of rare events" -- basically, that it is incredibly difficult to gauge the impact of extremely rare events exactly because they occur so infrequently. We lack the very observations that are needed to build up a decent idea of the probability distribution of their associated impact. As Taleb explains in the Edge essay: "If small probability events carry large impacts, and (at the same time) these small probability events are more difficult to compute from past data itself, then: our empirical knowledge about the potential contribution -- or role -- of rare events (probability × consequence) is inversely proportional to their impact."[*]

My reading of Taleb also leads me to think that he that he more or less regards everyone as blind to "black swan" (low probability, high impact) events. If that is true, however, I'm wondering how he squares that notion with the consistent empirical finding that people tend to overestimate the likelihood of low probability, high impact events. (And vice versa for more common, low impact events.) Consider the following chart, for example, which was originally produced in a seminal study by Lichtenstein et al. (1978):

Relationship between judged frequency and actual number of fatalities per year for 41 causes of death.

What we see here is that people have a clear tendency to overstate -- by an order of several magnitudes -- the relative likelihood of death arising due to "unusual and sensational" causes (tornadoes, floods, etc). The opposite is true for more mundane causes of death like degenerative disease (diabetes, stomach cancer, etc).

Similarly, have a look at Table 2 (p. 19) in this follow-up study by the same authors, where various groups of people were asked to rank the relative risks of different technologies. We clearly see a incompatibility between the opinions of experts and those expressed by laymen. For example, nuclear power is perceived to be far more risky by members of the general public than by those familiar with the actual number of fatalities and diseases brought on by this technology.

Now, Taleb might respond by that saying these are the exactly the type of misleading comparisons that he is talking about! He could argue that the "actual" observed fatalities are not necessarily an accurate representation of the underlying risks. After all, a single major event could significantly alter the average number of deaths of any particular cause (e.g. nuclear meltdown)... 

Well, perhaps, but I'm not totally convinced. For one thing, that says very little about the flipside of this problem, which is the degree to which "normal" causes of death are underestimated -- both in absolute terms and relative to more sensational outcomes. Second, by now we have accumulated decent data on numerous low-probability events that have occurred (rare as they are), from the outbreak of plague to massive natural disasters. Third, even disregarding my previous points, it doesn't seem at all obvious to me that the public is guilty of consistently underplaying the role of black swan events. Indeed, if anything they appear to be using a heuristic which causes them to significantly overestimate the likelihood of rare events.... Perhaps as a way of adjusting for the -- unquantifiable? -- impact that these outcomes could have if they do occur?

To restate my question then to those of you that know Taleb better than myself: Does he ever integrate (or reconcile) his theory about the ignorance of black swan events with the empirical evidence that people consistently overestimate the likelihood of low probability, dramatic outcomes?

UPDATE: This post appears to invoked Taleb's ire in somewhat amusing fashion. See follow-up here.
UPDATE 2: Second follow-up and some big name support of my basic point here.

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[*] This type of unquantifiable uncertainty happens to be a big area of research in the climate change literature. In particular, the 'dismal theorem' proposed by Marty Weitzman, whom I have mentioned numerous times before on this blog. See here for more.

Great TED talk on the evolutionary basis for religion

..., spirituality and co-operation by the psychologist Jonathan Haidt. My economist self was particularly interested in his thoughts on free-riding. The rest of me was particularly interested in the discussion as a whole.



It's curious to reflect on the things that give meaning and purpose to our lives. On that note, I've often wondered whether the appeal of atheism would diminish if there were no believers to convince otherwise?

UPDATE: Haidt has just published a new book that is getting rave reviews.

Free will in a world of Mad Men

Mark Thoma links to a study discussing the limits -- or "origins" might be more correct -- of free will. I'll just highlight the snippet on implications:

How Free Is Your Will? (Daniela Schiller and David Carmel, Scientific American): 

[The findings] indicate that some activity in our brains may significantly precede our awareness of wanting to [act]. Libet suggested that free will works by vetoing: volition (the will to act) arises in neurons before conscious experience does, but conscious will can override it and prevent unwanted movements. 

Other interpretations might require that we reconstruct our idea of free will. Rather than a linear process in which decision leads to action, our behavior may be the bottom-line result of many simultaneous processes: We are constantly faced with a multitude of options for what to do right now – switch the channel? Take a sip from our drink? Get up and go to the bathroom? But our set of options is not unlimited (i.e., the set of options we just mentioned is unlikely to include “launch a ballistic missile”). Deciding what to do and when to do it may be the result of a process in which all the currently-available options are assessed and weighted. Rather than free will being the ability to do anything at all, it might be an act of selection from the present range of options. And the decision might be made before you are even aware of it. ...

Thoma himself is sceptical about whether this actually says much about free will. Among the more interesting comments on the thread, from my perspective, are those pointing out the mistakes of trying to separate the conscious from the subconscious.

Now, I'm no neuroscientist (clearly). However, I have read a fair bit of research related to neuroeconomics.[*] My understanding is that many of our decisions and actions are formed at a level that involves very little conscious cognitive thought. Indeed, our brains tend to shift activities from the cognitive, "thinking" cortex... to the affective, "instinctual" cortex as we become familiar with repeated actions. In other words, there's a deeper truth in the meme "practice makes perfect": Our minds (bodies) begin to respond to external stimuli in a far more efficient way over time, simply because we spend less time thinking about our best course of action and instead just react according some (pre-) programmed optimal response.

In this regard, there is a fascinating body of research on the psychology and mental processes of chess players. In particular, what separates the top-ranked players from the rest of us? The answers are rather surprising. Grandmasters, for instance, spend far less time thinking about their moves than simply recognising patterns in play. For their part, players of lesser rank typically analyse and consider a wider variety of possible moves (and their consequences) at each stage of the game, but this is unfortunately much less efficient. The superiority of top chess players does not lie with intelligence per se, but in the ability to recognise meaningful patterns and respond accordingly. [An interesting side note: Grandmasters and other top-ranked players have a tremendous capacity to memorise a multitude of "plays" and board positions. However, arrange chess pieces in unfamiliar positions and their memory advantage regresses to that of ordinary punters.]

Added to all this is the fact that humans are fantastic rationalisers. We naturally seek order. Not only do we have an innate ability to seek out patterns and coincidences, but we look to provide (ex post) justification for our actions and even the actions of others. Along these lines, one of the most interesting findings to come out of hypnosis is the phenomena of rationalisation under post-hypnotic suggestion. A hypnotised patient can be made to (unwittingly) perform an action on a given cue; for example to open a window when the hypnotist claps his hands. Unaware of the true underlying causes, when the patient is asked by the hypnotist why he opened the window, the former will strive to provide plausible -- yet invalid -- reasons (e.g. "I was getting hot"). I believe that the subject of ex post rationalisation also underpins a lot of research in area of addiction studies...

Anyway, all this reminds me of a great Derren Brown clip that I saw a while ago. The influence of subliminal advertising is well publicised (if not entirely understood), but this is perhaps the most impressive exposition that I've seen of it. What makes it all the sweeter is that he is turning the tables on advertising execs here:

(I note that there is a US version of the same set-up here.)

THOUGHT FOR THE DAY: Fascinating stuff. Somewhere, Don Draper is smiling. And boozing. And womanizing. Damn his smooth ways!

"Yes, I believe you heard me correctly. I own your mind.
And I slept with your wife."

[*] If you're interested in reading more about neuroeconomics, this paper by Camerer and Lowenstein (2004) is the standard reference point in the literature.

Karl Smith on the importance of maths-free papers

... And simple allegorical stories to help our intuitive understanding of economic concepts. Here is an excerpt:

I posted a link to Bryan Caplan’s paper on Behavioral Economics and the Welfare State. Many of the comments I got from economists were predictable:  

   1. Where is the formal model and existence proofs?

   2. Where is the data analysis?

   3. How is this a paper?

   4. Do you mean to tell me this is publishable? 

I too was shocked initially by these features or lack thereof. However, that’s part of what made the paper compelling.

Some papers get a wonderful data set, perform magnificent identification and get a result that really changes your mind about something you care about. Most don’t.

Most are cases that are of very narrow interest or do a 90% good job at the ID but leave enough doors open that you are not really sure if  the result is meaningful or not.

On the other hand, one could as Bryan and his co-author did, attack an important question, string together some non-obvious points and in my case leave the reader thinking about whether he or she should reexamine an import view.

The profession should rightly celebrate the first kind of paper. However, what about the relative worth of the second and the third?

I submit that bringing up arguments that use the economic way of thinking matter. This is true even if the argument is not definitive, has no mathematical proof behind it and marshals no data.

Now, clearly I've written in support of using maths in economics on this blog before. However, in case anyone missed it, my point was not to say that we have to have put forward a mathematical equation for each and every economic argument or study. Indeed, I took some pains to make it explicit that this wasn't the case... Shoehorning a maths proof into an economics paper does not (cannot) constitute analytical rigour, let alone intellectual honesty.

I wholeheartedly agree with the excerpt above. We should embrace any economic paper and/or argument that aids our conceptual understanding, or forces us to re-examine our views on a particular subject. However, I continue to submit that theory alone is insufficient... 

Smith goes on to describe the baby-sitting coop allegory, which he says did more to make him a "confident Keynesian" than any other analysis. The important caveat here is that - as pointed out in the comments section - we have competing parables such as Bastiat's "Broken Window" that appear to offer completely different policy prescriptions. Again, this reinforces my belief that we ultimately need to seek empirical validation/refutation of our theories, whether they come in the form of a complex mathematical proof or a simple children's story. As I wrote here:

Knowing when to use your tools is just as important as knowing how to use them. Also, the ultimate test for any model - mathematical or otherwise - should always be how well it describes real-life data.

THOUGHT FOR THE DAY: It's always good to have a explanation at hand that everyone can understand.

PS - The Bryan Caplan paper that Smith is making reference to here is well worth a read. There are also some interesting critiques in the comments section of Smith's initial post about it.

Facts vs Beliefs

I should really be studying... but my attention has been drawn to several articles and interviews over the last few weeks that coincide with a recurring theme here at Stickman's Corral: The tendency of beliefs to trump facts, and a priori biases to cloud objective decision-making.

For instance, the below radio interview discusses new research on the problem of "backfire". As the name suggests, this is the phenomenon whereby facts don't necessarily have the power to change people's minds... Indeed, quite the opposite, as people actually tend to cling to their beliefs more strongly when presented with opposing evidence!

A related article on the same research can be found here:

The general idea is that it’s absolutely threatening to admit you’re wrong,” says political scientist Brendan Nyhan, the lead researcher on the Michigan study. The phenomenon — known as “backfire” — is “a natural defense mechanism to avoid that cognitive dissonance.

Similarly, this article (which links to this report) discusses the problems of the "Enlightenment Model", which

holds that people make rational decisions by assessing facts. All that has to be done to persuade people is to lay out the data: they will then use it to decide which options best support their interests and desires.

A host of psychological experiments demonstrates that it doesn’t work like this. Instead of performing a rational cost-benefit analysis, we accept information which confirms our identity and values, and reject information that conflicts with them. We mould our thinking around our social identity, protecting it from serious challenge. Confronting people with inconvenient facts is likely only to harden their resistance to change. [HT: WTD]

Regular readers will know that I've been trying to make a similar point on this blog for a while (e.g. here, here and here).  Stickman's Corral tries to abide by the relaxed principles of El Duderino and this approach was motivated by the realisation that: a) Making purely unequivocal statements is a one-way ticket to intellectual stagnation, and b) The fear of embarrassment or being wrong is among the most powerful motivators out there. If you don't offer people a way out that preserves their sense of dignity, you don't really offer them anything all. I'm always taken aback by how many people don't seem to grasp this simple rule of human behaviour. Or, as I've said several times now: Calling someone an "idiot" is not the best way to convince them of your position.

Now, of course, being respectful of someone you disagree with is hardly the same as not having an opinion. I take numerous angles on this blog that I feel are pretty clearly laid out. Further, I abhor false equivalences. Being open to changing your mind is of fundamental importance, but there are many issues where I think the evidence is simply too compelling for any reasonable person not to embrace a particular side. On this topic, it really grates me to see how tautological the defensive arguments against, say, evolution and climate change are. The first of these is well documented, but the latter typically goes something like this: 

Knee-jerk Sceptic: There is no scientific consensus about humans causing climate change.

Response: Well, actually every major survey shows that over 95% of practising climate researchers support this mainstream view...

Knee-jerk Sceptic: Those studies are flawed. [Or: Those mainstream scientists are wrong and the minority who disagree and are correct and have simply been marginalised.]

Response: Come on, that's a real stretch. The dissenting research simply doesn't hold up to scientific evidence and peer-reviewed scrutiny... 

Knee-jerk Sceptic: The peer review process has been corrupted. We can't trust it any more as opposing views have been silenced. Just look at the "Climategate" emails.

Response: Well, actually, the whole thing was blown ridiculously out of proportion and three independent reviews have cleared the involved parties of any significant scientific malpractice. 

Knee-jerk Sceptic: The reviews were just a sham and a cover up.

Response: Seriously? Okay, how about the fact that independent media analyses have come to a similar conclusion and even sceptics have offered compelling reasons not to put stock into the conspiracy theories...

Knee-jerk Sceptic: I don't care about those reviews; they aren't official. And there is a conspiracy: The governments of the world want to institute a new communist world order by imposing a huge carbon tax so to regulate the free peoples of the world.

Response: That is ridiculous. The amount of money spent on fighting climate change pales in comparison to money spent on, say, oil exploration and research. Even if it didn't, why do you suppose governments would sabotage their own economies by potentially depriving themselves of "cheaper" fuel? Think about it: They can't even agree to binding emissions targets!

Knee-jerk Sceptic: Governments are just fighting it out to see who gets greatest share of the pie.

Response: Look, scientists working separately all over the world have arrived at the same basic hypothesis that CO2 is the most likely culprit behind the observed warming of the last 150 years. Yes, there is uncertainty, but that should call for more caution if anything. More to the point, putting a price on carbon is ultimately about saving us money, since it corrects  for the negative costs that climate change is likely to entail.

Knee-jerk Sceptic: Scientists/Economists are part of the global conspiracy.

Etcetera, etcetera...
Sealed argument, much?

THOUGHT FOR THE DAY: Facts are important, but you have to play - and be sensitive - to peoples' emotions and values if you really want to win hearts and minds.

Why we need maths in economics 2(b) - Schelling's segregation model

Slightly later than planned... Here is the second example of a little maths helping to improve our analysis of a real economic problem. Seeing as I received some complaints about the calculus in my first example being too much for a blog post, I've tried to go for something much more basic this time. As such, the only maths that we'll only be using here is the arithmetic that everyone was taught in school. Again, however, those that are only interested in the final outcome can skip to the concluding "THOUGHT FOR THE DAY" and accompanying video at the bottom of the post!

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Topic: The formation of segregated neighbourhoods.

Aim: To show how seemingly innocuous discriminatory preferences among neighbours (in terms of race, sex, etc) can lead to completely segregated outcomes at the aggregate level.

When research has been done in racially segregated neighbourhoods, one interesting (and consistent) finding is that respondents from these areas generally claim to desire more integration. “We don’t want to live in segregated neighbourhoods!” they implore. However, there are usually some important caveats thrown in and a typical response might be, “I want to live in an integrated neighbourhood... just as long as I am not in too much of a minority”. Nevertheless, what if such “very minor” discriminatory preferences are still enough to lead us to completely segregated outcomes?

This is the question that nobel laureate Thomas Schelling first explored in a seminal paper back in 1969. He later extended his analysis in a series of subsequent books and articles (e.g. here). Alongside his contributions to game theory and conflict strategy, the brilliance of Schelling's work was to examine not only the underlying motivations characterising individual behaviour, but also the implications of individuals acting on each other in the aggregate.

I say “in the aggregate”, though this is a potentially misleading phrase. We have become used to interpreting “aggregates” as something like the average behaviour of individuals. However, much of Schelling’s research has been aimed at proving the exact opposite; i.e. that aggregate results in society are not necessarily simple extrapolations from the individual. Instead, aggregate outcomes are often much more complex since they result from a system of interactions between individuals and their environment. In other words, we impact others and our environment by our actions, while they impact us in turn. These complex interactions can lead to the emergence of surprising and even undesirable outcomes when considered at the societal level. This led Schelling to make the famous distinction between "Micromotives and Macrobehaviour".[*]

Right, so let’s establish the stylised “facts” for the particular model that we’ll be using here. The most important assumptions are as follows:

• People live in different neighbourhoods. If someone is unhappy with their current neighbourhood, then they can costlessly move to a new one. In this model, the only thing that makes people (un)happy about where they live is the racial profile of their neighbours.
• For simplicity we specify a population that consists of only two ethnic groups: greens and reds. In this example, we’ll assume that there are 50 greens in the population and 100 reds. (I briefly consider a different scenario at the end of this post.)
• Both green and red individuals have a variety of “tolerance levels”, reflecting the maximum ratio of race mixing that each person is prepared to accept in his or her neighbourhood. If the colour ratio exceeds a person’s particular tolerance ratio, then they will move to another neighbourhood where they are satisfied. (Those with the highest intolerance will move first.)
• Finally, we assume that tolerance levels among greens and reds can be ordered sequentially from high to low.[**] For both groups, let’s say that the most tolerant individual will accept a ratio of 2:1... In other words, be willing live in a neighbourhood as a one-third minority. The median individual will tolerate a ratio of 1:1, while the least tolerant will accept no person of opposite colour in their neighbourhood.

From the above, it should be obvious that there are a number of greens and reds who would be happy to live together in some combination. However, in order to analyse which combinations are most likely to occur, as well as the processes that cause people to leave or join a neighbourhood, we must turn to a little maths...

The first thing to do is create tolerance schedules for our two groups. Recalling our tolerance ratios from earlier (most = 2:1, median = 1:1, least = 0:1, etc), we depict these as follows:

Next, we translate these tolerance schedules into “absolute-numbers” curves by simply multiplying the population level by the corresponding tolerance ratio. In other words, we're finding out how many greens each red is prepared to tolerate, and vice versa. The parabolic shape of the resulting curves reflect the diminishing level of tolerance among each population, as you move from the most "tolerant" individual of the group to the most “racist”:

Note the placement of the green population on the vertical axis, and how this allows us to easily compare the interaction with the red population. There are three areas: 1) Any point within the overlap area (bottom left-hand corner) represents a combination of reds and greens that can coexist happily in the same neighbourhood. 2) Points beneath the red curve, but to the right of the green curve, represent a mixture where all the reds will be satisfied, but not all the greens. 3) In contrast, any point within the green curve and above the red curve corresponds to a combination where all the greens in the neighbourhood are content, but not all the reds.

Importantly, the above figure also depicts the dynamics of motion of the system. This is what the arrows are showing us: We can see how the populations of the two groups will be changing at any particular point.[***] For example, the bottom-left arrow (pointing up and to the right) indicates that the numbers of reds and greens will be increasing together at low population levels. However, if reds begin to settle in the neighbourhood at a faster rate than greens, then some greens will be motivated to leave. This in turn exacerbates the problem, since the ratio of greens to reds now becomes even worse which prompts more greens to leave! And so... we inexorably move towards neighbourhood comprised entirely of reds. (This is depicted by the bottom-middle arrow that is pointing down to the right.) In this way, the dynamics of motion show us that we can approach three possible equilibria. However, only two of these -- the completely segregated outcomes -- are stable. The mixed equilibrium combination is unstable since any disturbance, i.e. the departure or arrival of a new neighbour, has the potential to set off a chain reaction that will ultimately lead to one colour completely dominating the neighbourhood!

Now, of course, this was a rather specific example used for illustration. You might ask whether the segregated outcome depends for instance, on the relative sizes of our green and red populations? The answer to that question, however, is “not really”. A one-colour equilibrium is still the inevitable result even when we have reds and greens in equal numbers. Having said that, having equal numbers together with steeper tolerance schedules will tend to produce a stable equilibrium. For example, if there are 100 reds and greens and they both have a tolerance schedule where the median individual can tolerate being in a 2.5:1 minority, then we end up with the following:

In this alternative schedule, we see that all three equlibria are stable. Importantly, this includes the interior solution (a mix of 80 reds and 80 greens), which is robust to fairly large perturbations. (However, if we are already at a segregated outcome, then a move towards a stable mixed result will require the concerted entry of more than 25 percent of the other colour.)

THOUGHT FOR THE DAY: It’s easy to assume that people living in segregated neighbourhoods are relatively racist. Similarly, we might also assume that people who express a desire to live in integrated neighbourhoods will automatically arrive at such an outcome through conventional market processes. However, the basic Schelling model shows that even small preferences for a degree of homogeneity – for just a few of our neighbours to be “like us” – is enough to cause segregated outcomes at the aggregate. (In other words, completely segregated neighbourhoods may be inevitable even when the majority of people are fine with being in a minority!) The model depicted here is very simplified and hardly perfect, but still provides extremely valuable insights into the emergent dynamics of segregation. It also illustrates how relatively simple maths can be used to deal with complex and counter-intuitive phenomena.

PS - The above model is part of a broader literature called “agent-based modelling”, which is used for analysing anything from traffic flows to health epidemics. While maths was crucial to proving that his results held generally, Schelling initially used coins and a chessboard to illustrate his point. For a pretty cool illustration of agent-based modelling at work, try one of these two online versions of the segregation model. Or just watch the below video!

[Note: Those of you paying attention might notice that this video is slightly different in terms of set-up to the model that I have discussed above, in that it each person (/egg's) neighbourhood is limited to the spaces immediately alongside them. Schelling called this a "spatial proximity model". In contrast, the model presented above analyses the make-up of the neighbourhood as a whole and is called the "bounded neighbourhood model".]

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[*]  "Micromotives and Macrobehaviour" is the title of Schelling's brilliant book, which forms the basis for today's post. If the type of emergent economic outcomes that I discuss here is of interest to you, then M&M is a must-read.
[**] In technical language: we assume that the cumulative frequency distribution of the “tolerances” of individuals is represented by a straight line. This is done for ease of illustration, although it is not overly problematic to experiment with different distributions (as Schelling does here). 

[***] What we have here is a simple phase diagram, which is very useful for analysing the stability of any dynamic system where you have to worry about things like multiple equlibria, tipping points, saddle paths, etc. You usually determine the direction of your arrows in a phase diagram by taking the first derivatives of your equations, but since I'm trying to keep things simple here I won’t bother with that now.

God, morality and monkeys

And by "monkeys" I really mean "altruistic chimpanzees", but I'm a sucker for alliteration...

I stumbled on a really excellent opinion piece in today's New York Times: "Morals without God" by the Dutch primatologist and ethologist, Frans De Waal. I'm loathe to highlight any particular parts because the whole thing is so good, but here are three excerpts...

First up: Morality without God.

Can we envision a world without God? Would this world be good? Don’t think for one moment that the current battle lines between biology and fundamentalist Christianity turn around evidence. One has to be pretty immune to data to doubt evolution, which is why books and documentaries aimed at convincing the skeptics are a waste of effort. They are helpful for those prepared to listen, but fail to reach their target audience. The debate is less about the truth than about how to handle it. For those who believe that morality comes straight from God the creator, acceptance of evolution would open a moral abyss.

Echoing this view, Reverend Al Sharpton opined in a recent videotaped debate: “If there is no order to the universe, and therefore some being, some force that ordered it, then who determines what is right or wrong? There is nothing immoral if there’s nothing in charge.” Similarly, I have heard people echo Dostoevsky’s Ivan Karamazov, exclaiming that “If there is no God, I am free to rape my neighbor!”

Perhaps it is just me, but I am wary of anyone whose belief system is the only thing standing between them and repulsive behavior. Why not assume that our humanity, including the self-control needed for livable societies, is built into us? Does anyone truly believe that our ancestors lacked social norms before they had religion? Did they never assist others in need, or complain about an unfair deal? Humans must have worried about the functioning of their communities well before the current religions arose, which is only a few thousand years ago. Not that religion is irrelevant — I will get to this — but it is an add-on rather than the wellspring of morality. 

This very closely describes my own feelings. I've often tried to point out that morality derived from personal and social value systems just seems more genuine than morality which is (passively?) adopted as part of a religious system. If a religious person does something “good” because of the threat of hell -- or lure of heaven -- can this really be framed as a question of morality?[*] I doubt it... Now, obviously there are healthy reasons for keeping reward and punishment systems that protect the stability of a society as a whole, but the concept of "managed morality" still appears to me as little more than a lame oxymoron.

Next: Thoughts on Altruism.

Modern popularizers [have argued] that true moral tendencies cannot exist — not in humans and even less in other animals — since nature is one hundred percent selfish. Morality is just a thin veneer over a cauldron of nasty tendencies. [However], instead of blaming atrocious behavior on our biology (“we’re acting like animals!”), while claiming our noble traits for ourselves, why not view the entire package as a product of evolution? Fortunately, there has been a resurgence of the Darwinian view that morality grew out of the social instincts. Psychologists stress the intuitive way we arrive at moral judgments while activating emotional brain areas, and economists and anthropologists have shown humanity to be far more cooperative, altruistic, and fair than predicted by self-interest models. Similarly, the latest experiments in primatology reveal that our close relatives will do each other favors even if there’s nothing in it for themselves. 

[snip] 

Even though altruistic behavior evolved for the advantages it confers, this does not make it selfishly motivated. Future benefits rarely figure in the minds of animals. For example, animals engage in sex without knowing its reproductive consequences, and even humans had to develop the morning-after pill. This is because sexual motivation is unconcerned with the reason why sex exists. The same is true for the altruistic impulse, which is unconcerned with evolutionary consequences. It is this disconnect between evolution and motivation that befuddled the Veneer Theorists, and made them reduce everything to selfishness. 

[snip] 

Nature often equips life’s essentials — sex, eating, nursing — with built-in gratification. One study found that pleasure centers in the human brain light up when we give to charity. This is of course no reason to call such behavior “selfish” as it would make the word totally meaningless. A selfish individual has no trouble walking away from another in need. Someone is drowning: let him drown. Someone cries: let her cry. These are truly selfish reactions, which are quite different from empathic ones. Yes, we experience a “warm glow,” and perhaps some other animals do as well, but since this glow reaches us via the other, and only via the other, the helping is genuinely other-oriented.

Quite so. I'm tired of all the Ayn Rand types bleating on about selfishness all the time. Trust me, I get it: self-interest is very important... But I feel much of the Randian contribution these days is simply to fixate on meaningless semantics. Apart from the fact that altruistic acts often confer no obvious or immediate benefits to us, surely the exact point is that altruism is concerned with the well-being of others? "Altruism" exists as a singular -- and separate -- construct because it reflects a very specific set of actions and motivations.

Finally: Extending an olive branch to religion.

While I do consider religious institutions and their representatives — popes, bishops, mega-preachers, ayatollahs, and rabbis — fair game for criticism, what good could come from insulting individuals who find value in religion? And more pertinently, what alternative does science have to offer? Science is not in the business of spelling out the meaning of life and even less in telling us how to live our lives. We, scientists, are good at finding out why things are the way they are, or how things work, and I do believe that biology can help us understand what kind of animals we are and why our morality looks the way it does. But to go from there to offering moral guidance seems a stretch.

Even the staunchest atheist growing up in Western society cannot avoid having absorbed the basic tenets of Christian morality. Our societies are steeped in it: everything we have accomplished over the centuries, even science, developed either hand in hand with or in opposition to religion, but never separately. It is impossible to know what morality would look like without religion. It would require a visit to a human culture that is not now and never was religious. That such cultures do not exist should give us pause.

[snip]

Other primates have of course none of these problems, but even they strive for a certain kind of society. For example, female chimpanzees have been seen to drag reluctant males towards each other to make up after a fight, removing weapons from their hands, and high-ranking males regularly act as impartial arbiters to settle disputes in the community. I take these hints of community concern as yet another sign that the building blocks of morality are older than humanity, and that we do not need God to explain how we got where we are today. On the other hand, what would happen if we were able to excise religion from society? I doubt that science and the naturalistic worldview could fill the void and become an inspiration for the good. Any framework we develop to advocate a certain moral outlook is bound to produce its own list of principles, its own prophets, and attract its own devoted followers, so that it will soon look like any old religion.

As something of a secular humanist myself, I'll have to mull over the very last of these points. I strongly identify with many of the moral teachings that I've read in religious texts... But I also think that this reflects the innate strength of certain religions: They simply codified a set of moral guidelines that societies needed to "evolve" if they wanted to survive and flourish over the long-run. This, in turn, acted as the ballast for these religions to endure. The fact that we -- at least in Western societies -- seem far less concerned with certain rules than we might have been in previous years (e.g. don't eat shellfish, no sex before marriage) reinforces my belief that our morality will partly evolve with the times. (We even reject outright certain notions from religious texts, such as the right to own slaves.) Nevertheless, I completely agree that there is no need to insult someone who finds value in religion; provided their beliefs cause no demonstrable harm to others. And, as I have said previously, I look forward to the day when we come around to the idea that calling someone an "idiot" is not the best way of convincing them of your position.

THOUGHT FOR THE DAY: Too much, I fear, in this piece to sum up in a few lines. Perhaps I can do no worse than...

Oh, oobee doo!

I wanna be like you (oo-oo-oo)

I wanna walk like you

Talk like you, too (oo-oo-oo)

You'll see it's true (oo-oo-oo)

An ape like me

Can learn to be human too!

[*] An analogy is the paradox of intrinsic versus instrumental ethics that you often hear about in courses on business ethics... The basic idea being that trying to “manage” the ethics of employees is a contradiction in terms: By subjecting ethical matters to regulation and management control, employees aren't necessarily doing something good because of it's innate goodness, but rather because they are told to so or suffer the consequences. Similarly, it could be argued that ethics derived from any authority – moral or otherwise – has some element of inherent contradiction. 

Maths and Economics - The Interlude

Those of you paying attention may have noticed that I yet to deliver on my promise to provide a second economic-maths example. Apologies for the delay, but I've had a workload from hell this passed week. Honestly, I'll try and get around to it during the next few days when the storm clears. (The good news is that I at least know what I am going to post about...) 

Anyway, I'd thought I'd share a little statistic in the interim:

As of the present moment, my original post on why we need maths in economics has been viewed more than five times as much as the follow-up oil-tank model.

I found this pretty interesting. The first post was meant to act as a general defence of the subject. However, realising that general defences can be a bit vague I was motivated to offer specific examples to illustrat my points. I really thought that this was where the "value" would lie, since readers would be able to see the actual mechanics at work. Not the case apparently...

Perhaps the calculus in the “oil-tank” example put a few people off. Fair enough, I don't expect everyone to care for going through the maths... But I at least expected them to look over the post and skim to the model's conclusions. However, the click-through rates* indicate that even this hasn't been happening. Rather, it seems that people simply aren't as interested in a specific example of maths being useful to shed light on an economic problem, as they are in having a general discussion about it. In their own little way, these posts offer some insight into behavioural attitudes towards maths in economics – a sort of informal experiment if you will, which shows people leaning towards what I would regard as an important, but less precise approach.

THOUGHT FOR THE DAY: It's easy to take a position on things without getting to specifics. Providing concrete examples to back-up or demonstrate your point can be harder, but at least you give people something to work with. However, whether everyone will be interested in the evidence at hand is still open to question.** 

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* Clearly, Stickman's Corral isn't competing with any blogs worth mentioning in terms of numbers. Still, I think that my first maths post in particular has drawn a pretty respectable audience for a lowly grad student blogging in a sea of anonymity :)

** For the dramatic version of what I’m talking about, we have some classic Hollywood.

Bringing a priori bias back to the level of the mundane

[UPDATE: The situation has been (partially) resolved. Not so much an apology, but at least acknowledgement that I am probably not a backpacking Sheila on a pre-Uni world jaunt "with my girlies". How did I manage this? The way any self-respecting man would: By getting his GF to email and sort things out. (She insisted.)]

A strange thing happened to me today:

I was minding my own business searching the internet for mail-order brides crushed rhino horn very intellectual school stuff, when up popped an email from a B&B that I stayed at during a recent Croatia trip with my girlfriend.

I scanned the first few lines and “realised” what the problem was: Having completed our Croatia holiday, I was requested to review all our various accommodations on Hostel World (the site I originally used to make our bookings). However, due to some computer glitch, the same review ended up getting posted twice for two different places; one in Split, the other in Hvar. As we had enjoyed the latter (i.e. the B&B in question) more than the former, I had tried to edit this double post only to encounter difficulties in doing do so. I eventually left it thinking that readers and the Hostel World team would notice something was amiss; if for no other reason that I referred to a different city in my actual review (Hvar vs Split)!

So, instead of reading through the whole email, I skipped straight to the reply button with an “Oh, yes, sorry about the misunderstanding. This is what happened, can you help us fix it? Blah Blah Blah Kind Regards...” response. This is the reply I got:

“Stop playing , my mail gave you an answer already.Next time don´t close doors for yourself by lies.Your writings on trip advisor gave me a sight in your personality. 

I HAVE NOTHING MORE TO SAY ABOUT THIS.”

Note to self: WTF?

I decided that a second reading of the initial email was warranted and, in keeping with the El Duderino theme* of stickman’s corral, my response upon doing so was: “What in God’s Holy Name are you blathering about??”