In the past month, I ran posts on the limits to certainty in economics. On the theory side, I talked about how mathematical tractability limited the economic phenomena you can describe well with models. On the empirical side, the inability in social science to measure any abstract concept (ranging from aggregate production to femininity) to any reasonable degree of precision means that we end up relating vague proxies to vague proxies. I then talked about what these problems mean for those wanting to be as scientific as possible about economics.
The reactions of the many commenters to these three posts call for an update though. The first update is to make it clearer really just how constrained we are in economics by our inability to measure the phenomena we have in our minds, and how the societal role of economists binds us to those constraints. The second update is to tackle the question of whether economics is a science even if it cannot offer high levels of certainty. I of course say it is, having never been remotely jealous of other sciences. Just because our job is much harder than that of some other sciences doesn’t mean we are any less scientific. It means we have to be that much better to make progress.
The key thing about measurement and theory is that one would ideally have a theory that builds causal storylines between a set of concepts, measure those concepts and their relations and then improve the theories. This iterative process is pretty much the process held up as the ideal across everything calling itself a science.
It is within this process that definitions and meanings arise: it is the supposed relation with other concepts that gives a whole group of concepts their ‘meaning’ and it is these relations that suggest an empirical definition and a measurement procedure. The ‘meaning’ of time for instance is in terms of what supposedly happens during intervals of time to other phenomena: a second is defined as ‘The time needed for a cesium-133 atom to perform 9,192,631,770 complete oscillations.’, linking the concept of time to the concepts of movements.
Similar interactions between ‘theoretical stories’ about a concept and its measurement are around in economics, such as when the ‘meaning’ of aggregate production is partially derived from its supposed relation with consumption and investments, leading to its measurement to include flows of consumption and investments. The same goes for gender, whose meaning starts to coincide with the stories told about gender, such as the relation between gender and income, gender and work-roles, gender and child-bearing roles. Those roles then become measurement tools. To many people for instance to be female is defined as being the one that has the potential to bear children. This is not how the Olympics or the population register defines or measures it, but is an example of how a concept gets ‘meaning’ from its supposed relation to other concepts and how this translates into measurement.
Now, the problem with measurement in social science is that the underlying characteristics of anything we measure are radically different for any two instances. No two women are the same in their underlying ability to get children, to earn money, or even in terms of the reaction they invoke in others. To nevertheless ‘capture’ femininity in a single gender ‘dummy’, a 0-1 variable, is then from a formal point of view, bad science. The use of such ‘gender dummies’ in any analyses (i.e. anything going on the right-hand side of an estimation equation) then leads to biased inferences because a variable with a high degree of unknown measurement error is then included in an analysis. The fact that the same problem of measurement extents to everything we measure in social science, right down to the level of brain activity, in a formal sense means we cannot trust any analysis of any data: our theories of how the world works tell us that we are not really measuring what we should measure when it concerns gender, attitudes, GDP, education, race, IQ, profit, income, or anything else. We know we are not measuring what we really want to know but find ourselves without a way to measure the concepts we use to think about the world.
Let us explore this crucial point a bit more and see if this ‘trap’ is avoidable.
In our stories (theories) we think of clean and crisp concepts like ‘purchasing power’, ‘in-groups’ or ‘technological frontier’ and we define those things by their relation with other concepts (like profit maximisation). The obvious thing would be to then go out and measure these things. The problem we keep hitting is that despite huge efforts at measurement the things we end up measuring are easily 50% off what we were trying to measure. With technology we often end up counting patents or official R&D expenses, for instance then falsely presuming that any two patents in different legal systems denote the same amount of technology. Worse, what we measure is not comparable in that no two instances of measured ‘same amounts’ of profit or technology really relate in the same way to the other concepts in our theory, just as no two females are the same in terms of the underlying characteristics that carry the relations with other concepts. We thus keep coming up with new concepts, but keep hitting the same measurement problems over and over, leading us to settle for all those infamous ‘proxies’ which we then run against other proxies of other concepts. It should come as no surprise to you that the ‘range of estimates’ for things as esoteric as ‘average risk aversion’ include extremely high risk loving and extremely high risk aversion! So in many areas we’re stuck in a seemingly endless cycle of poor measurement and hamstrung theories, going round and round with the same basic ideas, just filling up the journals and making careers out of pretending we are all super original. For sure, we make some progress, but the constant pretense of certainty is a show put on for the outsiders who would otherwise not fund us as much.
The seemingly obvious ‘way out’ is to radically re-think social science in terms of those things that can be consistently measured, even if that means abandoning all the concepts we have hitherto thought in. If we can’t truly compare two instances of measures then someone who cannot live with uncertainty might conclude we should not measure it and we should not theorise in terms of it.
An example of this kind of ‘new economics’ could be ‘chemical economics’ whereby all that an economic statistician would do would be to go around measuring levels of chemicals and observable luminescence around the country, theorising about and statistically relating say, the number of particular chemicals in the rivers and the intensity of light in the evening in regions with particular soil compositions. As long as this ‘chemical economist’ would stay away from the temptation to start interpreting his results in terms of concepts the rest of society thinks in (such as ‘production levels’ or ‘sustainability’ or ‘regulations’) such an economist would be involved in replicable and measurable ‘science’. There is no guarantee that that kind of endeavour would get him anywhere but, by the same token, there is no certainty that it would turn into a completely useless exercise either.
Would it really be economics however? By design, economics is not about how it measures things or how it theorises about things, but about examining phenomena society thinks are economic phenomena: the boundaries of what economics is and can be are not really set by economists. We are ‘just’ the social scientists subsidised by our countries to think about production, recessions, poverty, etc. These are concepts that may be impossible to measure with any degree of accuracy, but they are concepts actively debated and thought about in political arenas and by whole populations: our populations believe in the meaningfulness of poverty, production, good economic times, bad economic times, inequality, etc. That belief buys us our daily dinner. Economists do not really have the option to walk away from these subsidies and become chemical engineers. Our ‘field of study’ is socially determined. Indeed, economists are in competition with other social science for its field of study: ‘we’ are forever trying to encroach on the subsidies given to psychologists, finance people, sociologists, etc., and they in turn are doing the same with our territory. Like it or loathe it, economics is a business as well as a social science, just like any other science has to vie for the resources of its society and is thus constrained by what society thinks its territory is.
So the brutal reality of economics is that we do not really get to choose what our core areas of study are. We can nudge the limits, try and steal bits of territory within economics from other economists, steal the territory of other social sciences and defend our turf against the encroachments of other social sciences, but we cannot quickly change course. By design, our territory is the study of the vague concepts in which our populations and politicians are interested. They might in the longer run adopt economic terminology for how they talk about poverty and production, but the bottom line remains pretty constant, which is that we economists are mainly there to help our pay masters be materially more successful, however vaguely that goal can be measured.
So no, it is not an option for economists to ‘retreat’ to the concepts that can be well-measured. Like it or loathe it, we are stuck with analysing innately fuzzy things that have the frustrating property of not get any clearer the closer we look and being too hard to model properly. These limits were not necessarily clear in 1900 or even 1950, but they are clear now.
Can economics then be a science or is economics innately an ‘art form’. It of course all boils down to your definition of science.
For me, science is a process of theorising and critical thought, whereby one attempts to get at better and better predictive storylines about current and future phenomena, discarding the bad storylines that fail to describe both historical events or predict new events and adopting better storylines that more successfully fit historical events and help manipulate the future.
Does this happen in economics and social science in general? Yes it does, but progress is very very slow. Our ability to forecast GDP is almost as abysmal now as it was in 1950, but we do now, for instance, have highly successful causal storylines as to why hyperinflation arises and how you can avoid it happening again (dont print too much money!). Agreed, it is a very simple storyline that you might have thought logical and obvious 300 years ago, but that has not prevented many countries from trying it out based on delusional theories. So we have whittled down the truly idiotic storylines. Similarly, we might not be perfect at running a capitalist mixed economy, but we have reasonably good storylines as to how you can wreck it via central planning, another ‘bad storyline’ that we have found out the hard way to be really dysfunctional. Our ability to regulate monopolies and forecast tax receipts has similarly allowed a reasonable amount of budgetary planning and faith in the fact that we will not see a huge increase in price coordination next year. Not rocket science, very imperfect, but a big improvement on the ‘Tableau Economique’ we started out with 250 years ago.
Similarly, we have gotten a better handle on how to organise and fund education and we have a pretty successful (but not perfect) predictive story about how we can get richer by cleaning up as many market imperfections as we can. Mainly though, we have amalgamated an awful lot of ‘stylised facts’ that allow us to dismiss the vast majority of lay theories about an economy. Whilst I for instance cant tell you what the stock market will be like next year I can confidently claim Russia will not take over the world economy any time soon and China will be the largest economy the coming decades, allowing me to dismiss as stupid and uninformed all the hordes who think China’s economic growth is a statistical trick and China will not soon become the biggest economy. Note that I have just given you an economic prediction that is very important for the mining industry and the ministry of trade (part of the group of paymasters).
So we are making ‘scientific progress’. We are just being very very slow about it, learning more from huge catastrophes than from mountains of statistical data. Can’t we make progress quicker? Yes: if you start to accept the limitations you can avoid all the dysfunctional wastes of time associated with desperately hanging on to illusions of certainty. Am I then trying to progress economics? Yes, I am trying mate, I am trying.
Interestingly, most of the world’s successful large corporations are fine examples of central planning, albeit superimposed over just enough internal ‘disorder’ to keep the fires burning brightly. As per the management theory and praxis developed by Alfred P Sloan (with some help from Peter Drucker before they fell out) to take GM to the forefront of world corporations in his day.
Besides, to take up your own thesis, what exactly do you mean by “central planning” – especially in the context of a capitalist mixed economy ? Are there degrees of “central planning” or is it a simple binary ? Are there different modes of “central planning” or is there only one practice that qualifies for that title ?
When you advocate “…better storylines that more successfully fit historical events and help manipulate the future,” aren’t you talking about a form of “central planning” ? Otherwise, why are you trying to “manipulate the future” ?
Degrees, of course. The big planning ministry of the kind they still have in North Korea is too stifling and runs into a span of control problem. Yes, major corporations also do planning at a lower scale, though I would argue they are far less top-down planned than ministries are. Internal competition and lower-down experimentation is rife in successful big companies, but that is an issue for another day!
Now that this thread has somewhat quiesced and I’m is less danger of committing gratuitous digression, here’s a few things you may enjoy reading:
http://notes.kateva.org/2008/03/american-corporation-and-centrally.html
which is commenting on this:
http://www.irle.berkeley.edu/events/spring08/governance/DeLong,%20B.-Corporation-1997.pdf
And also, too, unless you are already a Henri Fayol cognoscenti, you may find this thought-worthy:
http://en.wikipedia.org/wiki/Fayolism
Now that is how you do top-down control and central planning. It was also the basic frame – of the ‘internal subsidiaries’, namely Chevrolet, Buick, Pontiac, Cadilac etc – onto which Sloan imposed the ‘corporate central’ that unified it all, at the top level, into a single, massive entity.
Also, I look forward to someday reading your analysis of how, given your desire to “influence the future” (a desire possessed by every right-(and/or left) thinking economist worth his breakfast muesli) you are not advocating ‘central planning’. How many hairs do make a beard ?
Hi Gruebleen,
an important point. I looked through your links. Their declaration of love for planning is clear.
Yet, economics has much more to say about this. What about ‘Whither Socialism’ by Joseph Stiglitz in which he argued that much of modern macro-economics is based on assumptions under which central planning should have been a big success? There were the earlier writings of Samuelson in which he talked of a tradeoff between high production (under the Soviets) and liberty (where there was less planning). And of course the towering opinions in this debate was that of the Austrian school who, though not dominant in economics, still provided the dominant reason for the failure of central control, which is the role of market as a generator and user of decentralised information.
I have written a lot on this topic, see for instance here: http://ideas.repec.org/p/vie/viennp/0406.html
As to my attempt at influencing the future you wont have too long to wait. Just follow the link at the end of the post!
Paul,
Just a quick response since I will now have to take the time to follow up your links (including the one at the end of the post that I just glided over previously), but you are, of course, familiar with the idea of “steam engine time”, viz: that until a certain time, the steam engine is technically (and socially, politically and economically) impossible but that there comes a time when the combination of all the right factors (as above) are such that the steam engine is inevitable.
So, are we approaching “central planning time” ? What do you think of IBM’s Watson ?
nope, I dont think we are approaching central planning time. Maybe world weather planning is on the horizon, but in terms of what happens in our economies I see decentralised entities rule.
What is an interesting trend is that you are getting these large organisations where some things are centrally planned whilst, at the same time, at the lower level it operates like a collection of small private firms. Think of banks with sales people who get paid by commission. Think of universities where academics get paid by the publication.
These ‘new big firms’ are a bit like shopping centers with a central registry and yet with for-profit individual shops. Whilst they might all look the same and hence make it appear that they are the product of planning, they are a far cry from the old soviet planning ministries in which each individual shop is planned centrally!
Indeed, and it was just that ‘conglomerate of small(er) firms’ that Sloan took under a ‘central planning’ function to make GM (each of the small(er) firms being separate Fayol entities in their own right).
But the trouble with atomising everything is that, periodically, creeping entropy (ie divergent objectives) becomes galloping chaos (and we end up with a GFC).
As to ‘central planning time’, I do think you should contemplate IBM’s Watson more seriously :-)
Yes economics is a science. But our economists don’t treat it as such.
“So we are making ‘scientific progress’. We are just being very very slow about it, learning more from huge catastrophes than from mountains of statistical data. Can’t we make progress quicker?”
What is this “we” business. You might wish to progress beyond Keynesian goose-stepping 101 and learn economic science.
We economists. I am one too. Are you?
As a physical scientist (Physics) I have difficulty in thinking of Economics as science. Too many of the decisions are made by those irrational squishy bits of organic material for any consistency to occur in decision making on spending or investment. Couple that with economics based on ideology where data is shoe horned into fitting a preconceived position and anything goes. In passing I did do economics at high school and I got the impression that the same questions were set on the exam paper every year, but the answers were different.
Yes, as actors in our own field of observation it is nigh impossible not to let ideology and culture influence us. Another reason why good social science is so hard, together with the erratic behaviour of those goey globs! I can only repeat though that science is not about finding certainty but about getting as close as we can. If you think you can do better, give it a go! Economics has a long ancestry of physicists joining economics. One if the first, Tinbergen, was instrumental in setting up the planning models of the whole economy. Not very precise, but politically useful.
What does economics really give us, but a depiction or spaghetti diagram image of the battles for justification fought between conflictive groups and individuals of or within a subjective neo-ape species?
Definitely arty, but must sleep on the article which seems to talking of some sort of barometer that will demonstrate if your rival is already sucking your brains out ( too late,she cried!) or you are sucking their brains out.
I think you are too negative about measuring variables. Everything has error in it, but if it can predict other things at a reasonable level, then it may be useful (I seem to remember the Box quote here, which is something like:”All models are wrong, some are useful”). Things like gender, for example, has enormous predictability. This is why I think the context of what you are doing is important. Gender might be important in marketing clothes, but it isn’t so useful in many other things. It also depends on the problem. If I had a variable that predicted the stock market 1% better than everyone else, it would of course be a big deal even if the validity was poor.
Also, this idea of whittling down areas rather than trying to find the “answer” is pretty common, not just in economics. Curiously, however, the idea is weighted differently in different fields. In psychology, for example, no-one seems to care about it, and they just come up with crazy story after crazy story where the story can predict just about anything (just look at the brain-junk that hits the papers that everyone loves. Or think about it with your right hemisphere…). Alternatively, in linguistics, people are very concerned about it, even with quite similar problems to psychology (for example, people have tried to work out how word stress works since the 60s, but the best they think they can do is offer constraints as to what is reasonable). I’m not sure why different fields think differently about essentially the same methodological point, but it’s clear that they do.
The Bird returns?
I am not sure what Nick De Cusa is on, but I think that he needs to up the dose
For those wondering if a few comments have gone missing: yes. I axed Nick de Cusa’s last 6 or 7 comments as they were beyond the pale. I hope if he returns that he can keep it civil.
You mean I can return?
This is progress.
Well I’ll wait to I calm down and I’ll wait until Paul or someone else wants to talk economic science. But I go to catallaxy. I come here. And its like watching CNN and then watching FOX. Its just dopey-ville and Murdoch dopey-ville’s loyal opposition.
I’m sick of this total denial of scientific innovation that is TOTAL and bipartisan. And if it does not stop, then we must look for people to blame. I’m so sick of it. I’ve been on this argument since 2005. And I cannot teach anyone anything even simple.
AND I’M GOING TO BLAME SOMEONE, IF THIS CONTINUES.
So lets get back to learning. Lets get back to science. Or else just let me go and blame who I think is responsible.
How can a person be interested in economics AND visit Catalepsy?
A fair point. But the unscience is bipartisan. Its like Fox News versus CNN.
A better question would be: which parts of economics could be considered a science? I like the way wikipedia defines science:
There’s a certain portion of economics that could be considered to be testable explanations and capable of (reliable) predictions, but I’m not sure all of it can. In order to produce the things you identify as expected of economics there is a certain amount of bridging to be done from the foundations of the ‘scientific’ knowledge by the less sturdy art of economics. I think it’s important to distinguish these two portions as they deserve different forms of respect.
In engineering much of the formal education is orientated towards the scientific foundations: maths, physics, chemistry, etc. Yet part of what makes a good engineer is the ability to adopt the institutional knowledge of their field, which is built up through generations of experience rather than scientific experimentation. In many cases this is because, like economics, it’s not always feasible to run experiments. It’s important to note that although this knowledge isn’t scientific it’s still reliable, useful and hence valuable.
As far as I can see, the examples of progress in economics fall into this later category and so I wouldn’t classify them as examples of ‘scientific’ progress. That’s not to say that this useful progress might have been made possible by some underlying scientific progress (i.e improvements in understanding fundamental economic phenomenon), but I don’t think it fits the general meaning of scientific progress.
I think the another barrier to studying economics as a science is the fact that many of the phenomena you’re attempting to study are likely to change their very nature faster than you can develop a complex system of science around them. In many ways it’s the study of current circumstances rather than the study of natural forces that will be consistent over the long term. This fundamentally limits the testability and predictability elements of knowledge of these economic phenomenon.
Finally, it seems to me that this urge to call economics a ‘science’ seems to be just another form of “desperately hanging on to illusions of certainty”.
Sounds like physics envy to me. Maths by definition is not a science since it predicts nothing. It is just busy telling you some implications of your prior assumptions. The whole ‘foundation’ stuff is very unhelpful in economics because it needs a unit to start with that you can measure well and we don’t have one.
Take the hyperinflation example. There is a testable theory with predictions (print money, beget inflation). Works like a charm. In which way does it violate mine or wikipedia’s definition (which are close, but not the same: falsification cannot be absolute in economics because measurement is so fuzzy).
That is a very succinct clarification, thanks Paul.
It’s not about envy. It’s about appreciating the epistemological nature of the field you’re working in and selecting an appropriate paradigm that will effectively and efficiently increase and improve the knowledge in that field. The scientific process might not be the best way to advance the study of many areas within economics.
I also acknowledged that parts of economics might be scientific. If inflation is an economic theory supported experimentally, rather than simply observationally, then it might be part of the scientific ‘foundation’ I’m talking about (perhaps a qualitative rather than quantitative foundation). Yet, as you point out our (current) capacity to test or predict GDP is quite limited. So the study of the relationship between printing money and GDP might be something other than science.
I would draw another parallel with climatology. It’s often called ‘climate science’, but I would suggest that this is a bit of a misnomer. It’s not a science, but an applied science. We use a heap of knowledge developed through the scientific process about the parts of the system to develop an understand the whole, but the nature of the system we’re studying prevents us from studying it in a scientific fashion directly.
I disagree. Is the study of stars not a science because you cannot do experiments with stars? Were the early biologists who thought the platypus was a reptile and chemists still looking for ways to make gold out of lead not scientists because they were so widely off the mark with the benefit of hindsight? No on both accounts, so it is not the level of certainty or the ability to do experiments that makes a science.
A scientific mindset is is primarily about being open to change ones opinion on the relative merits of different causal story lines on the basis of more and more information. A science is then the process of searching for whatever information and story lines one can find to help one get better causal stories. So the early biologists were scientists as long as they were willing to accept their earlier ideas were wrong when better information came along. Ditto for chemists and ditto for economics. And, in all cases will you find that many people refuse to change their minds because of vanity and career reasons, hence the saying that science progresses one funeral at a time. In economics I would amend this by saying it progresses three catastrophes at a time.
“A scientific mindset is primarily about being open to change ones opinion on the relative merits of different causal story lines on the basis of more and more information.”
I think you need to specify what you mean by “relative merits” here. The reason for this is that some people would argue that having a consistent way to interpret data (and hence find causal chains) is more important than relative merits found in other story lines, otherwise you end up telling stories that sound good, but this just leads to confirmation bias and hence the incorrect weighting of evidence.
Not being an economist, I can’t think of an economic example off hand, but I can think of ones related to my work, so I’ll use an indulgent example.
So here is the story: There is something called ultra-cognitive neuropsychology, which proposes a method for identifying independent parts of the mind. This is called double-dissociation logic, and it’s used a lot (people argue about it a lot too). The basic idea is that, after brain damage, if someone can do X and not Y (e.g., read but not write), and someone else can do Y but not X (e.g., write but not read), there must be something separate about these two things.
Now, as it happens, it’s actually very easy to find the above example, and people really do think some different things are going on when you read and write. But you can find crazier examples. For example, it’s possible to find people who can spell aloud but not write the spellings of words and vice-versa, despite no other obvious impairments (e.g., motor movements for writing, memory, etc.).
Now, if you believe in the scientific methodology used for double-dissociation logic then you have to say there is something really different about writing and spelling aloud. But no-one can say what it is, and so intuitively, no-one believes this.
But the problem here is that if you don’t believe it, then you are ignoring the methodology which allows you to claim there is a causal chain for many other examples that people agree on. So even if you get lots of other evidence that writing and spelling aloud aloud are really much the same thing, you are still left with a violation of your scientific methodology, and one could argue here that this should really trump other forms of evidence. So actually specifying relative merits here becomes very difficult and if you believe in particular forms of scientific inquiry, then these can trump all others, and hence it isn’t relative anymore.
Doesn’t this cover all fields of serious academic endeavour? The only field that is completely dogmatic would be theology. Historians will ‘rewrite history’ in response to a new archaeological discovery that shows previous views were incorrect. Judges will ‘restate’ the common law in response to a novel case that shows the inadequacy of its current status. A writer might adjust their style in response to how their previous works are received in order to attempt to better tell their fictional story. Do all of these fields fit into the category of science too? They all utilise empirical evidence to some degree, and yet typically they will be referred to as ‘humanities’ rather than ‘science’. How is economics different from these fields?
I guess in one sense you could argue those fields do fit under science, as the word ‘science’ was at one stage more or less synonymous with philosophy, but I don’t think they fit the modern understanding of what is meant by ‘science’. I think it’s important to acknowledge the difference between knowledge merely deduced from observation and knowledge confirmed by explicit testing. Given its modern usage, ‘science’ seems to me to be the best word to use to make that distinction.
I would argue that taxonomy by itself is not a science; knowing a platypus lays eggs is not science, it’s merely observation. However given it fits into the overall process of science where that knowledge is used to make testable predictions, it could be considered part of science. To the extent that it does this, economics could also be considered a science. To the extent it comes up with causative stories that only explain past data it’s not.
Really? No one in neuropsych has an explanation for that?
desipis,
I was making a distinction between a scientific mindset (which non-scientists can also have) and then science as combining the mindset with an active search for available information. If the historian in your example is not just reacting to information from archeological sites but is also searching for it (digging up stuff himself or reading prime data sources) and adjusting his opinions according to how the new information makes some things less or more likely than before, he is under my definitions doing science. Digging up remains is not experimental but it is certainly an active search for new information, so yes, it is a scientific activity. No?
Conrad,
interesting. I had in mind a kind of Bayesian updating of causal story lines on the basis of new but highly imperfect information. Yes, the weighting in practice is imperfect and usually not explicit but there is re-appraisal of prior positions.
The case you mention sound as if two current theories that both capture a lot of prior information (if two observable activities are catered for by different locations in the brain then their content cant be the same; and ‘but these particular two activities do in fact seem to have the same content) are coming up against each other. Like disipis, my first question would be how sure you are about the two statements. I guess though that if I were to ‘buy’ your observations (and you know more than me on this topic, obviously) then my natural inclination would be to ask the question why would the brain have two different centers for what seems to be the same content? Can I think of more roughly similar examples? Are there advantages of such functional redundancy, etc. So yes, I would take the observation as informative on existing storylines (in a Bayesian way) but would be open to then start to think of new ones that keep the usefulness of the previous theories but incorporate the new information too (i.e. the observation would effectively mean the existing stories are not enough to capture the observed regularity).
IMO, no. But then it seems we’re just arguing about word definitions, so it probably doesn’t really matter.
“Really? No one in neuropsych has an explanation for that?”
There are rather ad-hoc explanations of bits and pieces of the data, but nothing really great (which is not to say the ad-hoc explanations are poor — many are quite interesting and pretty creative — just not even close to definitive).
Paul “three catastrophes ” ?
No-one ought to be envious of physics as it stands at the moment. The subject is far from scientific, in its practice, and its rife with fairy-tales, locked in by relentless lying.
Your hyperinflation theory isn’t all that correct. Currently the US and Europe are effectively printing money as fast as they can. No sign of inflation, Japan is doing something similar as well with some intended inflation. There is not a lot of prediction in economics, which is why most economic forecasts are usually wrong (even worst than the weather forecasters)
Phil
p.s. Anyone else noticed that Troppo’s RSS feed has stopped working since the upgrade?
I have a worse problem. If I leave “Notify me of followup comments … ” ticked on a thread that thread stops showing new comments altho I get them in my email. If I use Manage Subscriptions to untick the box I no longer get new comments in my email plus they still don’t appear on the thread.
ps Nick De Cusa is Graeme Bird. As Graeme is currently running a Jail the Jews campaign on his blog, you may wish to reconsider running his comments.
Hi Mel,
yes, I have been dubbing about this. Bird was completely out of line in his previous comments and, currently, elsewhere. However, I am not the police and cant monitor things people do elsewhere so am sticking to the simple rule that if people are sufficiently polite on their comments and somewhat on track, I am not going to punish them for what they do elsewhere. I agree he is pushing the envelope though and that he is quite probably liable in what he wrote previously and is writing elsewhere.
I think it is a call for Nick and Ken though since they are the main owners of troppo and hence are more naturally in charge of whether or not we should allow polite comments here by people who are out of line somewhere else.
Shouldn’t be hard to putsch him over the edge if anyone wants shot of him.
Perhaps physics fraud EDNEY will happen by…
… preserve our bodily fluids from Jewish fluoride, is possibly a bit over the line, yes?
Desipsis: “I would argue that taxonomy by itself is not a science; knowing a platypus lays eggs is not science, it’s merely observation. ”
That is an odd comment for many reasons. First of all, there is no such thing as a “mere observation”. The “theory dependence of observation” has been discussed at least since Kuhn coined the phrase. Google it and you’ll get a lazy 17 million plus hits.
Taxonomy is important and heavily theory laden and taxonomy has wider implications. The last Nobel prize in chemistry went to a guy who saw a hitherto “impossible” quasi-chrystal. That finding was revolutionary.
Think of all the taxonomical debates re the Hobbit and its implications.
The taxonomical nomenclature of monotremes like the platypus is embedded in evolutionary theory.
I strongly suggest that anyone with a genuine interest in this topic read Chalmers “What is this Thing Called Science?“, it is a short well written introductory book that quickly dispatches many of the arguments we’re seeing on this thread and on the fractal measurement thread.
Yeah, fair enough. Probably not the best choice for an example of things that aren’t science. I suppose even the knowledge that platypuses lay eggs is essentially predicting that if you find a healthy mature female platypus, it will at some point lay an egg. This is a reasonably testable hypothesis, ergo science.
Umm, I think the “mere observation” of a mammal with a cloaca and a propensity for egg laying is more significant than that. Indeed it is more than a “mere observation” to class monotremes as mammals.
I am only an artist, but much of this thread and the fractal threads discussion seems to be based on a idea that observation, meaning , stories/narrative (complex syntax) and definitions are not ultimately intertwined aspects of the same thing.
John, as someone that does work in-between “fluffy” (hard) science and slightly less than fluffy science (and occasionally gives “big-picture” talks), I think that all of these things are intertwined aspects of the same thing, but that people can’t actually work out how they are intertwined a lot of the time.
This is a big problem everywhere because you often end up with models that have pretty decent predictive power at one level, but you don’t really know how that model would actually emerge from the lower level. This means your great predictive model might just be something that correlates very well with behavior, but uses the entirely wrong principles to actually generate those numbers. This is a potential outcome of Paul’s fractal problem and happens occasionally.
A really simple example of this is with heliobacteria and stomach ulcers. Once upon a time people used to think stress predicted stomach ulcers. As it happens, stress does, and people would make simple models of this. But they had causation around the wrong way — if you have stomach ulcers, you will be stressed, but if you look at the next level down (what’s going on in your stomach), you end up finding that it’s heliobacteria and not stress.
Of course, that’s an easy example, because you can physically observe and test it. In many areas, there will be no simple cause and effect you can observe, and furthermore, our knowledge at all levels is pretty messy. This doesn’t mean we should give up on these areas, because they’re often important questions that will never have physics style answers.
For example, you might like to know why some people do crime and others don’t. That’s a very important question, but there is no simple answer. You can look at the level of society (e.g., inequality), who the individual hangs around with (social sphere), social characteristics of the individual (personality), lower level character of the individual (e.g., frontal lobe function), and so on. Now, we know a little bit about all these levels, but they’re all also messy. Despite this, we do get a lot of benefit from looking at these things (e.g., what to do with individuals who do crime, trying to prevent crime and so on).
Conrad I reckon that is about as wise as it gets.
Somebody once said that for Leonardo, to observe and make a drawing of something was to make a theory of that something.
“Just filling up the journals and making careers out of pretending we are all super original.” Nice quote.
All variables have measurement error. I find your example of gender bemusing. Gender per se is binary. Gender the concept is a scale of yin to yang. I only care whether the measure x-variable can be used to predict the y-variable. If a psych scale of yin-yang works better than a dummy for the y-chromosome then I will take it.
Is there a chance that economists worry too much about “stories”. Quantum mechanics kind of gave up on convincing stories a long time ago in favour of calculation regimes that actually work. And for me, physics is just about the paradigm of science.
Conrad, “I think that all of these things are intertwined aspects of the same thing, but that people can’t actually work out how they are intertwined a lot of the time.”
Exactly, we can’t work it out using the current methods and that is what the fluffy ducks are so interested in ideas like dynamic systems theory, which do offer a way of working out how to get a handle on this ‘intertwining’, which happens ‘all’ the time. Well, ‘all’ the time when the topic is anything that actually matters; such as predicting or explaining why do people do what they do.
This intertwining means that it will always be impossible to understand anything through a reductionist framework.
And another great idea that some of we fluffies are interested in and that could provide some structure for thinking outside the square – but the square is so easy and neat and makes such good sense – for you ‘dismal-types’ – is consilience; not to mention ‘the singularity’ :)
But really isn’t the problem for economics that at least half of the profession has been stupidly and blindly following false prophets for the past several decades?
Some people see the trees and others see the woods, and interdisciplinary collaboration that is inclusive of all the different ways humans have of making sense of things has to be the way to go – moving forward and all that.
I’m with Chris Lloyd:
“Quantum mechanics kind of gave up on convincing stories a long time ago in favour of calculation regimes that actually work. And for me, physics is just about the paradigm of science.”
Absolutely. Physics dropped the convincing stories long ago. Physics started by it dropped convincing stories. Gravity—action at a distance—was spooky magic. It was so implausible it took over a century for it to be accepted. The calculation that works—what I called relationship in that previous thread—is vital.
The great mistake of social science is coming up with hypotheses that are reasonable. Galileo said the period of a pendulum was independent of the amplitude. His rivals experimented and said he was wrong. Galileo said his pendulum had no friction, had a string with no weight and weight with no size. He was very unconvincing. But he was right, and we learn, too, that “falsifiability” is not to be viewed simplistically.
Science is not a convincing story. Rather the contrary, never reasonable, never plausible, ever a surprise. Don’t the most famous and durable economic theories also fall into this category?
John,
No long comment on the three catastrophes: something for another day, though I can say that I am here thinking about the inability of exceedingly large economic shocks to move the crowd relying on Solow-residuals to change from throwing their hands into the air afterwards to more seriously trying to analyse what their models miss and really incorporate those lessons into their first-year and second-year economic stories :-)
Chris (and Mike),
gender is certainly talked about in our culture as a binary thing, but as soon one spins theories about gender and other outcomes, like gender and income or gender and sport or gender and politics, then one is in fact not theorising on the basis of the binary label but on some deeper-lying characteristic of gender. And that characteristic is NOT binary but continuous. Worse, it is not measurable any better than other phenomena. And to use a simple binary variable to capture is does not invoke a little bit of measurement error, but can easily be 50% off. Just think of the huge variation in testosterone levels amongst males and the notion that a 0-1 variable would adequately capture it. Not of course that just the testosterone level is really what you were after…..etc etc
As to story telling, we seem to talk cross-purposes. Scientific stories need not be intuitive or even reasonable from an existing point of view (indeed, the less intuitive the more interesting they are!), but they are still causal stories that, if accepted, become reasonable and intuitive. That includes quantum mechanics with its dual particle/wave story. For sure, there are highly abstract frameworks in which quantum mechanics becomes a statistical predictive story, but from such highly abstract frameworks alone you would be hard-pressed to generate new theories or ideas in order to tell you about refinements or radical alternatives.
The unscience is deliberate and starts at the core. Where you say that economics is the science of dividing resources. This is nice for the practitioners, because as a result of societal injustice, very often, the economists get to help advise in how the resources are divided.
But none of this is science. Nor ought we have thought that science should emerge from such shabby foundations.
Others have said that economics is about wealth creation. For there on in you have the possibility of science.