The ultimatum game, a key experiment showing intrinsic fairness and altruism among strangers

Knowledge will come only if economics can be reoriented to the study of man as he is and the economic system as it actually exists.
Ronald Coase

There is a line of economic research on altruism that get only little attention in the media, which is why I want to report on it here. There is by now solid evidence that humans can behave altruistically towards strangers. This is surprising because a naive version of evolutionary theory would expect that altruism is only possible among kin. It also goes against the basic assumptions of economics, game theory and public choice theory, which all assume that humans only have an eye for their self-interest. These assumptions are often defended referring to evolution by stating that you need to be an unapologetic egoist for optimal reproduction. I mention this, because non-academics may think it is natural to assume humans can be altruistic and wonder why one would research something that trivial.

It is not controversial science. There are hundreds of scientists working on it. Almost every month Nature or Science publishes an article on altruism. And at the University of Bonn, where I work, Reinhard Selten is emeritus professor and got his Nobel price for experimental research on the ultimatum game. That is also how I heard about it, our University Magazine had an article on Selten and this beautiful experiments.

In a social setting, where there is an opportunity to build up a reputation, altruism can be explained. In this case, altruism may lead to future benefits and one may even argue that it is thus not real altruism. However, this type of altruism is expected to break down when a group is under pressure and may soon dissolve, but humans also collaborate under such difficult circumstances. Furthermore, reputation-building naturally does not work under conditions of anonymity, while experiments show that humans also collaborate with strangers they will never see again. Our ability to collaborate with non-kin is an important innovation that contributes much to our success as dominant animals.

Ultimatum game

A very simple and pure economic game, which thus shows the problem very clearly, is the ultimatum game (Güth et al., 1982). In the ultimatum game, two players must divide a sum of money. The first player has to propose a certain division. The second player (responder) can accept this division or reject it; in the latter case both players do not receive any money. In its purest form, the experiment is played only once and anonymously with players that do not know each other.

When the article described the experiment, I wondered what was interesting about that. Naturally people offer 50% and the responder accepts this. Not? That only showed my lack of economic training.

Be careful with the new daily temperature dataset from Berkeley

The Berkeley Earth Surface Temperature project now also provides daily temperature data. On the one hand this is an important improvement, that we now have a global dataset with homogenized daily data. On the other hand, there was a reason that climatologists did not publish a global daily dataset yet. Homogenization of daily data is difficult and the data provided by Berkeley is likely better than analyzing raw data, but still insufficient for robust conclusions about changes in extreme weather and weather variability.

The new dataset is introuduced by Zeke Hausfather and Robert Rohde on Real Climate:

Daily temperature data is an important tool to help measure changes in extremes like heat waves and cold spells. To date, only raw quality controlled (but not homogenized) daily temperature data has been available through GHCN-Daily and similar sources. Using this data is problematic when looking at long-term trends, as localized biases like station moves, time of observation changes, and instrument changes can introduce significant biases.

For example, if you were studying the history of extreme heat in Chicago, you would find a slew of days in the late 1930s and early 1940s where the station currently at the Chicago O’Hare airport reported daily max temperatures above 45 degrees C (113 F). It turns out that, prior to the airport’s construction, the station now associated with the airport was on the top of a black roofed building closer to the city. This is a common occurrence for stations in the U.S., where many stations were moved from city cores to newly constructed airports or wastewater treatment plants in the 1940s. Using the raw data without correcting for these sorts of bias would not be particularly helpful in understanding changes in extremes.

The post explains in more detail how the BEST daily method works and presents some beautiful visualizations and videos of the data. Worth reading in detail.

Daily homogenization

When I understand the homogenization procedure of BEST right, it is based on their methods for the monthly mean temperature and this only accounts for non-climatic changes (inhomogeneities) in the mean temperature.

The example of a move from black roof in a city to an airport is also a good example that not only the mean can change. The black roof will show more variability because on hot sunny days the warm bias is larger than on windy cloudy days. Thus part of this variability is variability in solar insolation and wind.

Also the urban heat island could be a source of variability, the UHI is strongest on wind and cloud free days. Thus part of the variability in observed temperature will be due to variability in wind and clouds.

A nice illustration of the problem can be found in a recent article by Blair Trewin. He compares the distribution of two stations, one in a city near the coast and one at an airport more inland. In the past the station was in the city, nowadays it is at the airport. The modern measurements in the city that are shown below have been made to study the influence of this change.

For this plot he computed the 0th to the 100th percentile. The 50th percentile is the median, 50% of the data has a lower value. The 10th percentile is the value where 10% of the data is smaller, and so on. The 0th and 100th percentile in this plot are the minimum and maximum. What is displayed is the temperature difference between these percentiles. On average the difference is about 2°C, the airport is warmer. However, for the higher percentiles (95th) the difference is much larger. Trewin explains this by cooling of the city station by a land-sea circulation (sea breeze) often seen on hot summer days. For the highest percentiles (99th), the difference becomes smaller again because offshore wind override the sea breeze.



Clearly if you would homogenize this time series for the transition from the coast to the inland by only correcting the mean, you would still have a large inhomogeneity in the higher percentiles, which would still lead to non-climatic spurious trends in hot weather.

Thus we would need a bias correction of the complete probability distribution and not just its mean.

Or we should homogenize the indices we are interested in, for example percentiles or the number of days above 40°C. etc. The BEST algorithm being fully automatic could be well suited for such an approach.

Falsifiable and falsification in science

"You keep using that word. I do not think it means what you think it means."

In a recent post, Interesting what the interesting Judith Curry finds interesting, I stated that "it is very easy to falsify the theory of global warming by greenhouse gasses." The ensuing discussions suggest that it could be interesting to write a little more about the role of falsifiable hypotheses and falsification in science. The main problem is that people confuse falsifiable and falsification, often do not even seem to notice there is a difference, whereas they have very different roles in science.

The power of science and falsification are beautifully illustrated in this video by asking normal people on the street to discover the rule behind a number sequence (h/t U Know I Speak Sense).

Falsifiable

Karl Popper only asked himself what distinguishes a scientific hypothesis from an ordinary idea.
Popper's beautiful thesis was that you can distinguish between a scientific and a non-scientific statement by asking oneself if it can be falsified. If it cannot, it is not science. Thus the worst one can say about an idea that is supposed to be scientific is that it is not even wrong.

Important side remark: Please, note that also non-scientific ideas can be valuable, Popper's philosophy itself is not science, just like most philosophy, political ideas, literature and religion.

And please note that wrong hypotheses are also scientific statements; that they are wrong automatically shows that they can be falsified. Even falsified hypothesis are still scientific hypothesis and can even still be useful. An good example would be classical mechanics. This illustrates that Popper did not think about whether hypothesis were right or wrong (falsified), useful or not, but whether a statement is scientific or not scientific.

To be falsifiable, falsification is only needed to be possible in principle. It does not matter whether falsification would be hard or easy for the question whether it is science. This is because the main value of the criterion is that it forces you to write up very clearly, very precisely what you are thinking. That allows other scientists to repeat your work, test the idea and build upon it. It is not about falsification, but about clarity.

That also implies that the daily job of a scientist is not to falsify hypothesis, especially not solid and well-validated ones. Scientists are also not writing down new falsifiable hypothesis most of the time, in fact they rarely do so. Those are the rare Eukeka moments.

The terms scientist and science are clearly much broader and also much harder to capture. The ambitious William M. Connolley set out to define science and what a scientist does in a recent post. Definitely worth reading, especially if you are not that familiar with science. Disclaimer: not surprisingly, the aim was not completely achieved.

Psycho analysis

A classical example for Popper of a non-scientific hypothesis would be Freud's psycho-analysis. The relationship between the current psychological problems of a patient and what happened long ago in the patients childhood is too flexible and not sufficiently well defined to be science. That does not mean that what happens to a child is not important, there are many modern findings that point into that direction (Joachim Bauer, 2010). If someone else would succeed in making Freud's ideas more specific and falsifiable, it would even be a valuable contribution to science. It also does not mean that psycho-analysis does not help patients. Finally, it also does not mean that it is wrong, rather it means that it is not even wrong. It is too vague.

Morphic fields

Another example is the idea of Rupert Sheldrake about morphic fields. Sheldrake claims that when an idea has been invented before, it becomes easier to reinvent it. He has a large number of suggestive examples where this seems to be the case. Thus there is a lot of information to validate his idea.

The problem is, it is impossible to falsify the idea. This idea is, again, too vague and if you do not find the effect in an experiment, you can always claim that the effect is smaller, that the experiment was not sensitive enough or not well executed.

When I was studying physics in at Groningen University, Sheldrake gave a talk and afterwards naturally got the question whether his ideas were falsifiable. He dogged the question and started about the science philosophy of Thomas Kuhn on paradigm changes that shows that in practice it can be hard to determine whether an idea is falsified. However, whether an idea is falsifiable is clearly another question as how falsification works, which will be discussed below. Then Sheldrake started fueling tribal sentiments, by complaining that only physicists would be allowed to have hypotheses with fields, why not biologists? Discrimination! As the climate "debate" illustrates, adding some tribal conflict is an effective way to reduce critical thinking.

This does not mean that the ideas of Sheldrake may not turn out to be valuable. The list of examples that validate his ideas is intriguing. This may well be a first step towards making a scientific hypothesis. That is also part of the work of a scientist, to translate a creative, fresh idea you got during a hike into a solid, testable scientific idea. Morphic fields are, however, not yet science.

Anthropogenic global warming

The hypothesis that the man-made increases in the concentration on greenhouse gasses leads to an increase in the global mean temperature can be falsified and is thus a scientific hypothesis. There is no need to go into details here, because Hans Custers just wrote an interesting post, "Is climate science falsifiable?", which lists ten ways to falsify the "AGW hypothesis". One would have been sufficient.

A clear example is that if the average world temperature drops one degree, back to values before 1900 and stays there for a long time without there being other reasons for the temperature decrease (e.g. volcanoes, sun, aerosols) the theory would be falsified. To get to ten ways, Custers has to come up with rather adventurous problems that are extremely unlikely because so many basic science and experiments would need to be wrong.

Seen in this light, the climate ostriches are almost right, it is highly unlikely that the theory of man-made global warming will be refuted, that would require highly surprising new findings and in most cases it would require basic physics, used in many sciences, to be wrong. However, just because it is highly unlikely in practice that the hypothesis will be falsified because there are so many independent lines of evidence and the hypothesis is well nested into a network of scientific ideas, that does not make it theoretically impossible, thus AGW is falsifiable.

Falsification

It doesn't matter how beautiful your theory is, it doesn't matter how smart you are. If it doesn't agree with experiment, it's wrong. Richard P. Feynman

This quote is a favorite one of the climate ostriches. Unfortunately, falsification is a little more complex in practice.

THE HOCKEY SCHTICK: I am ostridge practitioner of the CAGW religion

Maybe this is the right background music to the name calling orgy the climate ostriches are throwing this month.

My comment below was not published by the Hockey Schtick (THS), which has a post about the new manuscripts of the Connelly family, below which I wrote a comment to point the readers to my post about these manuscripts.

In my post I wrote that I did not think it was a good idea that the authors of the manuscripts are also the editors and the owners of the journal. I think that at the very least, this should be made very clear on their homepage. The Hockey Schtick does not see any problems with such a pal review and praised the reviews for being open. When I explained that the editor has to make an impartial decision on whether to publish or not, THS no longer replied.

And in my post, I summarized the long discussion at the blog And Then There's Physics about one of the manuscripts about the greenhouse effect. The discussion suggests that the Connolly's do not believe in the greenhouse effect, but cannot explain for what other reason the surface temperature is 33°C higher as it would be without greenhouse effect.

In this respect the Connolly's are much more moderate as THS, who thinks that greenhouse gasses cool the atmosphere. No typo (the webcite for history).

The argument of THS uses the dry adiabatic lapse rate, would thus only work for the greenhouse gas water vapor and not for the others. And it uses the current effective radiative height as natural constant, not determined by the concentration of greenhouse gases. The result is also physically impossible, for the radiative transfer of heat radiation (cooling of the Earth), an atmosphere without greenhouse gasses is the same as no atmosphere. Whereas the theory of THS claims that in the first case, the surface is 49°C warmer and would consequently radiate stronger toward space.

My comment

For full transparency, I thought it would be a good idea to post my forbidden comment here. I am curious whether my readers also feel that I misbehaved. Feel free to be honest. (You can also comment anonymously.)

Global Warming Solved in Open Peer Review Journal

Roger Pielke Sr. pointed our attention to a new game-changer article.

'.. poor siting biases..has probably led to..overestimation of the amount of global warming" since the 19th century." http://t.co/EndeTSV9o9

— Roger A. Pielke Sr (@RogerAPielkeSr) February 22, 2014

If you click on the link, you come to an unknown scientific journal and a manuscript open for peer review.

Everything looks very professional and it could have been the homepage of a real scientific journal. The article looks good, lay-outed perfectly with LaTex and it surely looks like a real scientific article. Maybe almost a bit too good. The article cites the main studies on the topic. Well made.

However, if you look a little further, there are some disappointments. If you look at the list of articles, you notice that the journal is very new. They have not published any articles yet and eight manuscripts are under review. All manuscripts have been uploaded in January 2014, and all are written by Ronan Connolly & Michael Connolly or by Michael Connolly & Ronan Connolly. Father Michael and son Ronan.

Open Peer Review Journal

The journal is called "Open Peer Review Journal", subtitle: "for rigorous open peer review". Being an unknown journal, I was curious who was behind this journal, but the homepage does not mention an editorial board. Fortunately, there is also a blog by the Connolly family called Global Warming Solved. At this blog they state that they themselves have started the journal.

The idea of peer review is to give a paper more credibility, that can only be achieved by sending the manuscripts to an independent journal. Getting published in your own journal will not lead to much credibility, I am afraid scientists will not see this as different from publishing your ideas here on your blog. This will thus not create much incentive to read the eight long articles. I would advice the authors: If your ideas are strong, you should have nothing to fear with going to a real scientific journal. There is also an open review journal: Climate of the Past. If I had a controversial paper, that is where I would go.

Workshop on novel approaches to homogenization, Boulder, July 2014

By Peter Thorne.

We have long recognized that the enabling framework aspects of the Initiative (databank, benchmarks, data serving) are but one aspect of the problem. What is needed in addition are new approaches to the data homogenization so that we can better understand the data and their uncertainties. This is not something the Initiative can mandate nor something that the 10 cents coin I found following exhaustive searching down the back of my sofa will get us very far in funding. So, we have been and continue to pursue novel means to increase the number of independent groups and individuals undertaking the analysis of the data.

As one such activity, the Initiative put forward a proposal for a SAMSI (Statistical and Applied Mathematical Sciences Institute) summer program activity - which got selected. Over the past few months we have been working with colleagues from SAMSI and NCAR IMAGe (Institute for Mathematics Applied to Geosciences) who joined as substantive co-sponsors to arrange the meeting logistics. We are now in a position to announce the workshop.

So, without further ado ...

Applications are invited for participation in a workshop to be held in Boulder, Colorado July 8th-16th. The aim of the workshop is to develop new and novel techniques for the homogenisation of land surface air temperature data holdings. The workshop participants will have access to the almost 32,000 stations held in the first version databank release (which will be publicly available by then) and also to several of the benchmark datasets. The workshop will mainly be practically based - with few talks and lots of coding and discussions either in plenary or in smaller breakout groups. A final agenda will be forthcoming nearer the time.

Applications are welcome from all. The final meeting is space limited to 44 people. Participants from non-traditional backgrounds, early career scientists and members of under-represented groups are particularly encouraged to apply.

Further meeting details and application form are available at https://www2.image.ucar.edu/event/summerprog.surfacetemps.

(Reposted from the ISTI surface temperatures blog, please comment there.)

WUWT and Co. not interested in my slanted opinion, part II

The Hockey Schtick broke a story about homogenization, which was picked up by Watts Up With That? They found an article, which they claimed showed that homogenization makes the influence of an enhanced Urban Heat Island stronger. I disagreed with their conclusions, the homogenization method in the paper was designed to study the UHI more accurately and removed other effects that masked it. However, for the global data sets other homogenization methods are used that reduce the influence of urbanization.

There was one thing about this interaction with WUWT and Co, that I found interesting. Interesting in the way Judith Curry uses the word, suggestive and non-committal.

I wrote a comment (see below) on five blogs that had covered the story, quite neutral comments not to violate any comment policy. They had a link to my blog article for more information. One would expect skeptical people, in the original meaning of the word, to be interested in an alternative opinion, especially so if it comes from someone that is reasonably well informed. However, only one of the five comments was published. [UPDATE: now two comments, see below.]

The post was published on the 1st of February, at the time of writing 3 days ago.

Five blogs

The Hockey Schtick: New paper finds adjusted temperature data in China has significantly exaggerated warming
Below the post at The Hockey Schtick are two comments, but mine did not appear.
[UPDATE: After a twitter exchange, I have resubmitted my comment and it has appeared. Problem solved.]

Watts Up With That?: Important study on temperature adjustments: ‘homogenization…can lead to a significant overestimate of rising trends of surface air temperature.’
Anthony Watts thought the homogenization article was very important. My comment has not appeared yet. Last time I tried a similar comment, at least the text "[sorry, but we aren't interested in your slanted opinion - mod]" appeared.
I am on the WUWT black list and normally it takes a few hours before my comments appear, at which time the discussion has typically progressed for fresh posts and most people do not seem to notice the comment any more. Three days would be a new record.

Tips on How to Study: Important study on temperature adjustments: 'homogenization…can …
Then I wrote a comment for Tips On How To Study. Looking in more detail now, it does not seem to be an ostrich blog, but rather someone who copies articles from other blogs, mostly not about How To Study.

The Drinking Water Advisor: Beijing adjusted surface temperature data found to have exaggerated warming trends
The fourth comments was at The Drinking Water Advisor, a blog about water, fluoridation and climate change. My comment did not yet show up here.

Errors in IPCC climate science: How many times does a truth have to be told ? – UHI warming has been cemented into global temperature series by adjusting for steps outward from cities
There is one blog where my comment was posted: Errors in IPCC climate science. Chapeau. One of the bloggers, Warwick S. Hughes, has written some scientific articles and comments on station data quality. He should have been able to see the mistake in the WUWT article.

Conclusions

The last few month I have trouble with getting comments published, also on science blogs, but I would estimate this to affect a few percent of my comments. Getting only one [two] comment[s] out of four or five published is less than expected. Being a scientist, I will naturally assume good faith, the reason may well be some sort of spam filter. I hope my critical readers can make up their own mind.

The comment

At WUWT and Tips, I wrote the comment below. On the other blogs shorter ones with a similar tone.

The authors wanted to accurately study the influence of the urban heat island effect and thus removed the cooling effect of two relocations using a special homogenization method. Without this method the importance of urbanization would have been underestimated.

This special homogenization method is not used for global climate data, where the aim is to remove the effect of urbanization as well. Thus this WUWT post is unfortunately inaccurate. For details, please have a look at my blog.

I would personally say, that that is quite neutral. Certainly compared to the way scientists are described in the comments of WUWT.

Further reading

WUWT comes right out and says "We Aren't Interested" in facts
HotWhoppers take on the previous time WUWT was not interested in my slanted opinion.

Effect of data homogenization on estimate of temperature trend: a case of Huairou station in Beijing Municipality

The climate ostriches are having some fun with an article (Zhang et al., 2013) published spring last year in Theoretical and Applied Climatology (TAAC). According to The Hockey Schtick, the article corroborates that "leading meteorological institutions in the USA and around the world have so systematically tampered with instrumental temperature data that it cannot be safely said that there has been any significant net “global warming” in the 20th century.

And Anthony Watts writes: "From the “we told you so” department comes this paper out of China that quantifies many of the very problems with the US and global surface temperature record we have been discussing for years: the adjustments add more warming than the global warming signal itself.

Not bad!Those are huge implications for a paper about the homogenization of one station, written by a first author that can only cite one previous study written by him in Chinese and in a journal with a rather modest impact factor. I will come back to these two statements at the end.