Category: Science

Kalle and me. Schumpeter, too.

[One of my intellectual heroes, Karl Marx, had his 200th birthday (May 5) this weekend. So I decided to reflect on his influence.]

My first encounter with Kalle was when I was still in (the equivalent of) high school. Things were heating up in (West) Germany around that time: students started marching against a “system” that had allowed atrocities abroad (Remember Vietnam, that last and long-lasting proxy battle of the Cold War?) and also at home where the old Nazis (Remember “Silver Tongue” Kiesinger?) were still very much in power and, it seemed, had adopted the Social Democrats (being themselves quite an old-boys network, although of another kind) via a Grand Coalition with him and his.

The suffocating stuffiness that still hung over Germany in the early sixties soon fell by the wayside, culturally as much as politically, and by the late sixties Kiesinger was gone and in the fall of 1969 that “traitor”, Willy Brandt, was German chancellor. People like Udo Lindenberg, and a number of the Krautrock and Schneeball groups, started to sing in German and it was not embarrassing. Alles klar auf der Andrea Doria! Keine Macht fuer Niemand! (Of course, all of these German bands had to fight the onslaught of bands from Great Britain and the United States … .) There were charismatic figures such as the informal leader of the extraparliamentary opposition, Rudi Dutschke, the Kommune 1 with its fun guerilla faction, and the no-fun guerilla of the Red Army Faction (Baader, Ensslin, Mahler, Meinhof, et al.) which soon after went from agitating to murder and brought about, in 1977, The German Autumn. There was also an emerging environmental movement in the seventies that did its fair share, and then some, to change the policy discourse in Germany for decades to come. All of this happened against the backdrop of a divided Germany, in a key theatre of the Cold War, where one part called itself the German Democratic Republic but was hardly that.

Around the same time (ca 1967 – 1970) my parents fought hard a battle of the roses that saw my (younger, by three years) brother’s life derailed (and him dead of an overdose a decade later) and me dropping out of school, leaving “home” prematurely, moving to the big city (well for me, that was what Bielefeld was then), and becoming part of the proletariat at age 18, working for about a year as warehouse worker and delivery driver for Thyssen-Schulte, before — after a few months of hitch-hiking through Europe -, I joined the army. I spent much of the next two years deep in the heart of conservative and catholic Bavaria (1972 – 1974), much of it in an alpine communication unit. Quite an experience it was.

After the years in the military, I entered an experimental college back in Bielefeld, studying political economy, math, Russian, and Portuguese during 1974 – 1978. I also spent a couple of weeks in Oberhof, Thuringia (then part of the German Democratic Republic), on an all-expenses paid trip where I was taught the Socialist way of thinking in the morning and got to ski in the afternoon, with enough space left for plenty of drinking and carousing in the evenings. Paid by the Konsumgenossenschaft, the trip was the East-German Communist Party’s attempt to pry away from the West promising young things. I was not quite persuaded and did not take it up on the invitation.

It was during that first year in Bielefeld, and way before my trip to Oberhof, when I started reading Marx. In reading groups we slugged our way through The Communist Manifesto (quickly) and then (way more slowly) through Das Kapital, volume one. Never quite finished it from what I vaguely recall. Not even close. And, frankly, we all got quite bored reading it and had trouble buying into the promises of the discussion leaders that, in the end, it all would make sense. It did get me interested enough though that — when I entered that experimental college in Bielefeld — political economy was my choice of major, together with math. And it was there that I studied Marx’s work more carefully. And I was not the only one … several fellow students and teachers were into it … (a couple of the teachers being true armchair Marxists who thought that interpreting the world on a decent salary was good enough after all.)

I read a lot those years, often sitting in my small rented basement room in the Von-Ossietzky-Strasse until deep in the wee hours, sipping cheap Moroccan red wine, popping Adumbran to be able to sleep, with good old Brecht looking over my shoulder from a huge poster. Among the things I read – I can tell because I still have the marked-up copy — was Wygodski’s book, published in East Berlin in 1976, on how Das Kapital emerged from Marx’s early writings. Wygodski’s books were remarkable in that they showed how early some of Marx’s (and Engels’s) theories about society, economics, politics, and culture were fixed. There are interesting parallels here to how the ideas underlying Adam Smith’s Wealth of Nations emerged over decades of thinking about them. I also read Theorien über den Mehrwert, often called the fourth volume of Das Kapital which demonstrates that Marx knew his stuff and was indeed a first-rate historian of thought to start with. But of course, he was much more: Philosopher, sociologist, economist, political scientist, activist, agitator, …

As I progressed in my career, I lost sight of the insights to be found in Marx’s writings. With the fall of socialism, in the USSR and its satellite states in Central Europe, the evidence seemed to suggest that certain realizations of Marxian ideas (or what some people considered them) had overstayed their welcome. Of course, Marx’s ideas do live on these days in China where Xi Jinping just recently made clear the importance of The Communist Manifesto. Marx’s ideas havea also lived on in some academic branches such as sociology. The authors of the Wikipedia entry on Kalle seem to assert correctly that he is typically cited as one of the principal architects of modern social science. Even that curmudgeon of a historian, Schumpeter, who thought little of Adam Smith but can hardly be accused of having communist sympathies, was surprisingly positive about Marx, calling him a “first-rank economist” (History of Economics Analysis p. 224), among other laudatory names. It was no coincidence that Schumpeter featured Marx prominently in Ten Great Economists. In contrast, Smith did not make the cut. Go figure.

Here are some selected excerpts from Schumpeter’s History of Economic Analysis (Perlman edition), for your easy perusal:

p. 370 Any economist who wishes to study Marx at all must resign himself to reading carefully the whole of the three volumes of Das Kapital and of the three volumes of Theorien über den Mehrwert.Fn

Further, there is no point whatever in tackling Marx without preparation. Not only is he a difficult author but, owing to the nature of his scientific apparatus, he cannot be understood without a working knowledge of the economics of his epoch, Ricardo in particular, and of economic theory in general. This is all the more important because the necessity for it does not show on the surface. Again, the reader must be on his guard against being misled by traces of Hegelian terminology. It will be argued below that Marx did not allow his analysis to be influenced by Hegelian philosophy. But he sometimes uses terms in their specifically Hegelian sense, and a reader who takes them in their usual sense misses Marx’s meaning.

Fn. The Communist Manifesto is also indispensable, of course. But for any purpose short of becoming a Marxologist, I think that nothing need be added except the Class Struggles in France, articles written in 1848–50, published as a book, with an introduction by Engels in 1895. Only the Marxologist need go into Marx’s correspondence.

p. 366 … nobody will ever understand Marx and his work who does not attach appropriate weight to the erudition that went into it—the fruit of incessant labor that, starting from primarily- philosophical and sociological interests in his early years, was concentrated increasingly on economics as time went on, until his working hours were all but monopolized by it. Nor was his the kind of mind in which scholarly coal puts out the fire: with every fact, with every argument that impinged upon him in his reading, he wrestled with such passionate zest as to be incessantly diverted from his main line of advance. On this I cannot insist too strongly. This fact would be my central theme were I to write a Marxology. Perusal of his Theorien über den Mehrwert suffices to convince one of it. And, once proved, it serves to establish in turn another fact and to solve a much discussed riddle: it serves to establish that he was a born analyst, a man who felt impelled to do analytic work, whether he wanted to or not and no matter what his intentions were; … our information warrants the statements that he was very much a philosopher dabbling in sociology and politics (as do so many philosophers) until he went to Paris; that there he quickly made headway and found his feet as an economist; and that by the time he and Engels wrote the Communist Manifesto (1847; published 1848); that is to say, at the age of 29,7 he was in possession of all the essentials that make up the Marxist Social Science, the only important lacunae being in the field of technical economics. For the rest, the main line of his intellectual life may be described as a series of efforts to work out that Social Science and to fill those lacunae—tasks which, I believe, Marx did not expect would involve any insurmountable difficulties, though he did expect that a great deal of further work would be required to straighten out and co-ordinate everything that was to find a place within the vast structure.

p. 33 Half a century before the full importance of this phenomenon [ideological bias, AO] was professionally recognized and put to use, Marx and Engels discovered it and used their discovery in their criticisms of the ‘bourgeois’ economics of their time. Marx realized that men’s ideas or systems of ideas are not, as historiography is still prone to assume uncritically, theprime movers of the historical process, but form a ‘superstructure’ on more fundamental factors, as will be explained at the proper place in our narrative. Marx realized further that the ideas or systems of ideas that prevail at any given time in any given social group are, so far as they contain propositions about facts and inferences from facts, likely to bevitiated for exactly the same reasons that also vitiate a man’s theories about his own individual behavior. That is to say, people’s ideas are likely to glorify the interests and actions of the classes that are in a position to assert themselves and therefore are likely to draw or to imply pictures of them that may be seriously at variance with the truth. … Such systems of ideas Marx called ideologies.4 And his contention was that a large part of the economics of his time was nothing but the ideology of the industrial and commercial bourgeoisie. The value of this great contribution to our insight into the processes of history and into the meaning of social science is impaired but not destroyed by three blemishes, …

p. 20 … an economics that includes an adequate analysis of government action and of the mechanisms and prevailing philosophies of political life is likely to be much more satisfactory to the beginner than an array of different sciences which he does not know how to co-ordinate—whereas, to his delight, he finds precisely what he seeks ready-made in Karl Marx. An economics of this type is sometimes presented under the title Political Economy. …

p. 363 The difficulty is that in Marx’s case we lose something that is essential to understanding him when we cut up his system into component propositions and assign separate niches to each, as our mode of procedure requires. To some extent this is so with every author: the whole is always more than the sum of the parts. But it is only in Marx’s case that the loss we suffer by neglecting this2 is of vital importance, because the totality of his vision, as a totality, asserts its right in every detail and is precisely the source of the intellectual fascination experienced by everyone, friend as well as foe, who makes a study of him. Marx figures in this book only as a sociologist and an economist. Of course, that creed-creating prophet was much more than this. And his creed-creating activity, on the one hand, and his policy-shaping and agitatorial activity, on the other hand, are inextricably interwoven with his analytic activity. So much is this the case that the question arises whether he can be called an analytic worker at all. This question may be answered in the negative from two very different standpoints. …

p. 364 My answer to our question is, however, in the affirmative. The warrant for this affirmative answer is in the proposition that the bulk of Marx’s work is analytic by virtue of its logical nature, for it consists in statements of relations between social facts. For instance, the proposition that a government is essentially an executive committee of the bourgeois class may be entirely wrong; but it embodies a piece of analysis in our sense, acceptance or refutation of which is subject to the ordinary rules of scientific procedure. It would be absurd indeed to describe the Communist Manifesto, in which this proposition occurs, as a publication of scientific character or to accept it as a statement of scientific truth. It is not less absurd to deny that, even in Marx’s most scientific work, his analysis was distorted not only by the influence of practical purposes, not only by the influence of passionate value judgments, but also by ideological delusion. Finally, it would be absurd to deny the difficulty that in some cases rises to impossibility of disentangling his analysis from its ideological element. But ideologically distorted analysis is still analysis. It may even yield elements of truth. …

To sum up: … we simply recognize him as a sociological and economic analyst whose propositions (theories) have the same methodological meaning and standing and have to be interpreted according to the same criteria as have the propositions of every other sociological and economic analyst; we do not recognize any mystic halo.

p.367 The ‘pieces’ divide up into two groups, one sociological and the other economic. The sociological pieces include contributions of the first order of importance such as the Economic Interpretation of History, which, as I shall argue, may be considered as Marx’s own, quite as much as Darwin’s descent of man is Darwin’s own. But the rest of Marx’s sociology—the sociological framework that, like every economist, he needed for his economic theory—is neither objectively novel nor subjectively original. His preconceptions about the nature of the relations between capital and labor, in particular, he simply took from an ideology that was already dominant in the radical literature of his time. If, however, we wish to trace them further back, we can do so without difficulty. A very likely source is the Wealth of Nations. A.Smith’s ideas on the relative position of capital and labor were bound to appeal to him, especially as they linked up with a definition of rent and profits—as ‘deductions from the produce of labour’ (Book I, ch. 8, ‘Of the Wages of Labour’)—that is strongly suggestive of an exploitation theory. But these ideas were quite common during the enlightenment and their real home was France. French economists, ever since Boisguillebert, had explained property in land by violence, and Rousseau and many philosophers had expanded on the subject. There is, however, one writer, Linguet, who, more explicitly than others, drew exactly the picture that Marx made his own: the picture not only of landlords who subject and exploit rural serfs, but also of industrial and commercial employers who do exactly the same thing to laborers who are nominally free, yet actually slaves.This sociological framework offered most of the pegs that Marx needed in order to have something upon which to hang his glowing phrases. And since historians are primarily interested in these, no matter whether they admire them or are shocked by them, it is difficult to gain assent to what is the obvious truth about the nature of thepurely economic pieces of the Marxist system. This obvious truth is that, as far as pure theory is concerned, Marx must be considered a ‘classic’ economist and more specifically a member of the Ricardian group. Ricardo is the only economist whom Marx treated as a master. I suspect that he learned his theory from Ricardo. But much more important is the objective fact that Marx used the Ricardian apparatus: he adopted Ricardo’s conceptual layout and his problems presented themselves to him in the forms that Ricardo had given to them. No doubt, he transformed these forms and he arrived in the end at widely different conclusions. But he always did so by way of starting from, and criticizing, Ricardo—criticism of Ricardo was his method in his purely theoretical work.

p.369 … admit that Marx could ever grow out of date in any respect. However, in order to drive home a point that seems important, I have strictly confined myself in the preceding paragraph to Marx’s theoretical technique. But there are two features of Marxist theory that transcend technique. And these were not period-bound. The one is his tableau économique. In his analysis of the structure of capital, Marx developed Ricardo once more. But there is an element in it that does not hail from Ricardo but may hail from Quesnay: Marx was one of the first to try to work out an explicit model of the capitalist process. The other is still more important. Marx’s theory is evolutionary in a sense in which no other economic theory was: it tries to uncover the mechanism that, by its mere working and without the aid of external factors, turns anygiven state of society into another.

p.408 … the period’s great performance in the field of political sociology stands in the name of Karl Marx. … I wish merely to say by way of anticipation that Marx’s theories of history, of social classes, and of the state (government) constitute, on the one hand, the first serious attempts to bring the state down from the clouds and, on the other hand, the best criticism, by implication, of the Benthamite construct. Unfortunately, this scientific theory of the state, like so much else in Marxist thought, is all but spoiled by the particularly narrow ideology of its author. What a pity, but at the same time, what a lesson and what a challenge!

p.413 [Marxist Evolutionism] I have just adverted to the possible implications for sociology that a despiritualized Hegelian philosophy might harbor. This suggests that here we have after all more than a phraseological influence of Hegel upon Marx. If, nevertheless, we maintain substantive autonomy of Marx’s so-called Materialistic Interpretation of History as against Hegelism, and if we list it as a separate type of evolutionism, we allow ourselves to be guided by two considerations. First, Marx’s theory of history developed independently of Marx’s Hegelian affiliation. We know that his analysis started from a criticism of the current (and apparently immortal) error that the behavior that produces history is determined by ideas (or the ‘progress of the human mind’), and that these in turn are infused into actors by purely intellectual processes. To start with this criticism is a perfectly sound and very positive method but has nothing to do with Hegelian speculation. Second, Marx’s theory of history is a working hypothesis by nature. It is compatible with any philosophy or creed and should therefore not be linked up with any particular one—neither Hegelianism nor materialism is necessary or sufficient for it. What remains is, again, Marx’s preference for Hegelian phrasing—and his own and most, though not all, Marxists’ preference for anything that sounds anti-religious.

p.414 Both the achievement embodied in that hypothesis and the limitations of this achievement may be best conveyed by means of a brief and bald statement of the essential points. (1) All the cultural manifestations of ‘civil society’—to use the eighteenth-century term—are ultimately functions of its class structure.8 (2) A society’s class structure is, ultimately and chiefly, governed by the structure of production (Produktionsverhältnisse), that is, a man’s or a group’s position in the social class structure is determined chiefly by his or its position in the productive process. (3) The social process of production displays an immanent evolution (tendency to change its own economic, hence also social, data). To this we add the essential points of Marx’s theory of social classes, which is logically separable from points (1) to (3) that define the economic interpretations of history but forms part of it within the Marxian scheme. (1′) The class structure of capitalist society may be reduced to two classes: the bourgeois class that owns, and the proletarian class that does not own, the physical means of production, which are ‘capital’ if owned by employers but would not be ‘capital’ if owned by the workers who use them. (2′) By virtue of the position of these classes in the productive process, their interests are necessarily antagonistic. (3′) The resulting class struggle or class war (Klassenkampf) provides the mechanisms—economic and political—that implement the economic evolution’s tendency to change (revolutionize) every social organization and all the forms of a society’s civilization that exist at any time. All this we may sum up in three slogans: politics, policies, art, science, religious and other beliefs or creations, are all superstructures (Überbau) of the economic structure of society; historical evolution is propelled by economic evolution; history is the history of class struggles.

This is as fair a presentation of Marx’s social evolutionism as I am able to provide in a nutshell. The achievement is of first-rank importance although the elements that enter into it are of very unequal value or, rather, unequally impaired by obvious ideological bias. … … the economic interpretation of history … . If we reduce it to therole of a working hypothesis and if we carefully formulate it, discarding all philosophical ambitions that are suggested by the phrases Historical Materialism or Historical Determinism, we behold a powerful analytic achievement. Points (1) and (3) may then be defended against objections, most of which turn out to rest upon misunderstandings. We have reached a point of vital importance for a proper understanding of Marx’s work. … we can now visualize his unitary Social Science, the only significant all-comprehensive system that dates from this side of utilitarianism: we see the manner and the sense in which he welded into a single homogeneous whole all branches of sociology and economics—a venture that might well dazzle the modern disciple even more than it dazzled Engels, who stood too near the workshop. .. Here I wish only to insist on the greatness of the conception and on the fact that Marxist analysis is the only genuinely evolutionary economic theory that the period produced.14 Neither its assumptions nor its techniques are above serious objections—though, partly, because it has been left unfinished. But the grand vision of an immanent evolution of the economic process— that, working somehow through accumulation, somehow destroys the economy as well as the society of competitive capitalism and somehow produces an untenable social situation that will somehow give birth to another type of social organization—remains after the most vigorous criticism has done its worst. It is this fact, and this fact alone, that constitutes Marx’s claim to greatness as an economic analyst.

Some of Marx’s insights have stayed with me,. Here is a list of ten great insights and phrases, straight from the horse’s mouth. Memorable, and still rather pertinent.

10. “The philosophers have only interpreted the world, in various ways. The point, however, is to change it.” [These words are also inscribed upon his grave]” (Eleven Theses on Feuerbach)

9. “There is no royal road to science, and only those who do not dread the fatiguing climb of its steep paths have a chance of gaining its luminous summits.” (Capital, Vol 1: A Critical Analysis of Capitalist Production)

8. “The tradition of all dead generations weighs like a nightmare on the brains of the living.” (The Eighteenth Brumaire of Louis Bonaparte)

7. “In the social production of their existence, men inevitably enter into definite relations, which are independent of their will, namely relations of production appropriate to a given stage in the development of their material forces of production. The totality of these relations of production constitutes the economic structure of society, the real foundation, on which arises a legal and political superstructure and to which correspond definite forms of social consciousness. The mode of production of material life conditions the general process of social, political and intellectual life. It is not the consciousness of men that determines their existence, but their social existence that determines their consciousness. At a certain stage of development, the material productive forces of society come into conflict with the existing relations of production or – this merely expresses the same thing in legal terms – with the property relations within the framework of which they have operated hitherto. From forms of development of the productive forces these relations turn into their fetters. Then begins an era of social revolution. The changes in the economic foundation lead sooner or later to the transformation of the whole immense superstructure.” (A Contribution to the Critique of Political Economy)

6. “It is not the consciousness of men that determines their being, but, on the contrary, their social being that determines their consciousness.” (A Contribution to the Critique of Political Economy)

5. “The ideas of the ruling class are in every epoch the ruling ideas, i.e. the class which is the ruling material force of society, is at the same time its ruling intellectual force. The class which has the means of material production at its disposal, has control at the same time over the means of mental production, so that thereby, generally speaking, the ideas of those who lack the means of mental production are subject to it. The ruling ideas are nothing more than the ideal expression of the dominant material relationships, the dominant material relationships grasped as ideas.” (The German Ideology)

4. “The history of all hitherto existing society is the history of class struggles.

Freeman and slave, patrician and plebeian, lord and serf, guildmaster and journeyman, in a word, oppressor and oppressed, stood in constant opposition to one another, carried on an uninterrupted, now hidden, now open fight, that each time ended, either in the revolutionary reconstitution of society at large, or in the common ruin of the contending classes.” (The Communist Manifesto)

3. “Modern bourgeois society with its relations of production, of exchange, and of property, a society that has conjured up such gigantic means of production and of exchange, is like the sorcerer, who is no longer able to control the powers of the nether world whom he has called up by his spells.” (The Communist Manifesto)

2. “Let the ruling classes tremble at a Communistic revolution. The proletarians have nothing to lose but their chains. They have a world to win. Workingmen of all countries unite!” (The Communist Manifesto)

1. “Religion is the sigh of the oppressed creature, the heart of a heartless world, and the soul of soulless conditions. It is the opium of the people.” (A Contribution to the Critique of Hegel’s Philosophy … )

Review: Tomer’s Advanced Introduction to Behavioral Economics

In the next couple of months I shall, in preparation for an invited longer review essay on recent books on BE, post reviews of individual books such as Tomer’s, Angner’s A Course in Behavioral Economics, Cartwright’s An Introduction to Behavioral Economics, and Dhami’s The Foundations of Behavioral Economic Analysis. Comments are welcome.

Here is the first review, for your entertainment:

Tomer, John F. Advanced Introduction to Behavioral Economics. Elgar (2017). ISBN: 978 1 78471 991 3 (cased), ISBN: 978 1 78471 993 7 (paperback)

Tomer, an Emeritus Professor of Economics at Manhattan College, covers much ground in a fairly superficial manner. We are lectured about the scientific practices of “mainstream economics” (narrow, rigid, intolerant, mechanical, separate, individualistic; see p. 10) and the emergence of behavioral economics (BE). In passing, we hear about different “strands” of BE (chapter 3: “The bounded rationality strand”, chapters 4 and 5: “the psychological economics strand”, chapter 6: “behavioral finance”), “BE, public policy, and nudging” (chapter 7), “law and BE” (chapter 8), “behavioral macroeconomics” (chapter 9), “the empirical methods of BE” (chapter 10), and neuroeconomics (chapter 12). We are also treated to an answer (I am sure you can guess it) to the question: “Are mainstream economists open-minded toward behavioral economics or do they resist it?” (chapter 11) In chapter 13 the author enlightens us about paths “Toward a more humanistic BE” and in chapter 14 we can read about “Behavioral economic trends”.

Each of these chapters are about 10 – 12 pages long. Along the way we hear about ENE’s (Early Neoclassical Economics) and NE’s (Neoclassical Economics) “lack of behavioral realism. NE’s lack of connection to other social sciences in particularly regrettable for those who place a high value on a unified social science or at least on having many viable linkages among the different social sciences.” (p. 9) Referring to a decade-old study of his that was published in an inconsequential journal, we learn that “The results for NE (also referred to as mainstream economics) are quite clear. NE is rated high on all six dimensions (narrowness, rigidity, intolerance, mechanicalness, separateness, and individualism,” (p. 12). After this paper tiger has been successfully constructed, we are told how it is being torn to smithereens: “ In contrast, the eight strands of BE … are in general far less narrow, rigid, intolerant, mechanical, separate, and individualistic than NE. … Overall, there is clear evidence that BE is 1) less positivistic than NE … , 2) distinctively different from NE, and 3) much more integrated with other social science disciplines than NE. In other words, BE is arguably better than NE in the way it conducts its scientific practices.” (p. 12)

This tired rhetorical figure has been used by those marketing BE for a long time. It also shows up regularly in the press (e.g., Elliott 2017 but see Attanasio et al. 2017 or for that matter Ortmann 2012), the related blogosphere, and even literature (Schumacher 2014): while BE is much more realistic and useful, NE is the old staid economics (that has done little for us). In the words of the protagonist of Dear Committee Members, “ … sociology has gone the way of poli-sci and econ, now firmly in the clutches of rabid number crunchers who have abandoned or forgotten the link between their abstruse theoretical musings and the presence of human beings on the planet’s surface; .. ” (p. 152)

That lack of behavioral realism is, so we learn, addressed by behavioural economists’ wholesale adoption of psychological insights which inevitably “enrich” the dismal models of mainstream economists. Ignoring the interesting question what the trade-off is that these richer models come with – in this book this trade-off is never discussed -, there are at least two issues here.

First, and to repeat a theme that I have belabored elsewhere (see also this comment here), there is no such thing as a monolithic body of evidence in psychology that economists could mine to inject more behavioral realism in their allegedly dismal models. The fact is, much of the evidence on heuristics and biases that is being appealed to has been questioned left and right. Every halfway knowledgeable (behavioral) economist will agree that the only interesting question about cognitive biases (such as reference dependence, endowment effects, availability, anchoring & adjustment, and representativeness) is when, and under what circumstances, they exist (if they exist at all).

Second, and more importantly, psychology as a field has, at least since Bem (2011), gone through what many people have called a replicability crisis (e.g., OSC 2015, Spellman 2015, Schimmack 2018) that played out at first in blogs and discussion groups such as the Facebook Psychological Methods Discussion Group, but increasingly also in journals and their practices. You would not know that some such upheaval is happening from reading Tomer’s book.

Take, for example, Tomer’s telling discussion of Zak’s oxytocin research in chapter 13. We learn that he is “a well-known economist who appreciates the softer, more intangible side of human behavior” (p. 145) and has shown through his research that “there is a direct link between the amount of oxytocin in humans’ blood and brains and humans’ concerns for each other. … Most importantly, oxytocin fosters trust. Oxytocin surges in a person’s bloodstream when an individual is shown a sign of trust and/or when something engages in a person’s sympathies and they experience empathy. ” (lit cit) Unfortunately, these claims have been thoroughly debunked and even effectively ridiculed in one of John Oliver’s excellent shows. All the literature I know suggests strongly that Intranasal oxytocin has no discernible effect and claims to the contrary are about as much bogus science as claims of ego depletion and the empowering effects of power poses: what these alleged phenomena reflect is little but shoddy science that people got away with for too long, demonstrating a cavalier attitude to questionable research practices from p-hacking over lack of proper powering up to hiding unsuccessful trials in drawers. You would not know about this crisis if you trusted Tomer who seems completely unaware of these developments that are slowly also starting to be recognized in economics.

Yes, I am not impressed by Tomer’s book. The knowledge laid out in Tomer’s slim volume is severely out of date and unabashedly partisan. According to the December 2017 IDEAS/RePeC data, there are at least 50,000 research economists out there world-wide and they innovate every day in what is most likely one of the most brutally competitive industries the world has seen. The idea that somewhere someone (“mainstream economics”) has a monopoly on doctrinal truth and can enforce it, shows a stunning cluelessness about the current state of the art (and science) of economics and its sociology. In his recent presidential address, Alvin E. Roth – an outsider of sorts himself — has argued that economics has been very open to various outsiders and their ideas and practices and you have surely seen that in the emergence of experimental economics and also in some quarters of BE (although BE remains afflicted with many charlatans, often of the non-academic kind that sell BE as panacea to everyone who thinks they can get something for nothing).

I doubt that Tomer’s slim volume is “particularly useful for advanced undergraduate students, graduate students, policymakers, and other professionals who participate economic-related matters.” (statement on the back of the book) In fact, I fear it will promote more sloppy science of the kind that is on display in this book. That kind of sloppy science is also too often on display when you speak with policy makers and Behavioral Insights architects and the like these days.

When all is said and done, it is this kind of sloppiness that undermines trust in the joint enterprise called science.

Lemonade and the question of (laboratory) evidence

Lemonade Inc., the New York based fintech startup that sells home and renters insurance has been in the news recently. It has raised tens of millions in venture capital and also considerable interest in the top echelons of corporate Australia. I know because I was asked to reflect on it as part of a workshop on behavioral economics/behavioral science that I conducted a couple of months ago. I have to admit that I did not know about Lemonade before that request.

Turns out that Lemonade uses “Behavioral Science (and Technology) To Onboard Customers and Keep Them Honest”, so the title of a piece in Fast Company earlier this year. Lemonade bets that insights from Behavioral Economics (BE) will give it the edge over incumbent competitors. It bets specifically that the BE insights of Dan Ariely (he of Predictably Irrational and TED talk fame, and now Lemonade’s CBO = Chief Behavioral Officer) will provide that edge, important components being “trusting our customers” and “giving back” to charity all unused excess funds. On top of these components, or maybe undergirding it, is the promise that Lemonade commits to spending at most 20 percent of its income on administration and marketing, which presumably prevents it from profit maximizing at the expense of its customers. Lemonade also promises that it will process claims fast and relatively un-bureaucratically, at least by the standard of an industry that has a reputation for delaying tactics and for its persistent attempts to evade having to pay up. Examples of speedy processing are featured prominently on Lemonade’s website.

And not only that: A couple of months ago, Lemonade launched its Zero Everything policy which gets rid of deductibles and rate hikes after claims and is supposed to pay for itself through elimination of the paperwork that comes with relatively small claims.

BE principles are also appealed to when customers that make claims are asked to submit a brief video outlining their claim and to provide at the same time a honesty pledge which supposedly induces more honesty.

In sum then, Lemonade builds its business allegedly on the trust(worthiness) of its customers, and of itself, and also honesty on the part of both parties.

Let’s start with the (laboratory) evidence for trust(worthiness). On its web page, Lemonade illustrates the advantages of trust(worthiness) with one of the workhorses of experimental economics, the trust, or investment, game. According to the web page, a person that invests (the trustor) will see her investment to a trustee of $100 quadruple and then see the trustee return half of that $400 to herself (the trustor), for an impressive ROI of one hundred percent. Trust pays off, we learn: “We are more trusting and reciprocating than what standard economic theory predicts.”

Ignoring the stab at economic theory (which shows little more than a lack of elementary knowledge of modern economic theory), there are at least three problems with the Lemonade narrative. First, it is not clear at all why this particular game, in this particular parameterization, captures the customer – insurance company situation. Second, I am not aware of anyone ever having experimentally tested this game with that specific parametrization (specifically, a multiplication factor of 4), and I am not aware — the multiplication factors typically used being 3 or 2 — of responders returning more than what was invested. In fact, the results of my own work (which are very much in line with the literature in this area) suggest that trustors invest about half of what they were given and trustees return slightly less than what was invested. It is noteworthy that there is much heterogeneous behavior to be found in these experiments, with many of those that trust (“invest”) being brutally exploited.

“Everyone has a price, the important thing is to find out what it is.” (P. Escobar)

Which brings us to the question of honesty. There is indeed some evidence that the way in which people are being prompted makes a difference and, more generally, that context matters (see Various, JEBO 2016). Friesen & Gangadharan (Economics Letters 2012) use an individual performance task (“matrix task”) after which they ask their subjects to self-report the number of successes that participants had. While very few of their participants – only one out of 12 — are dishonest to the maximal extent, about one out of 3 are to different degrees, with men (in particular those of Aussie and NZ provenance) being more dishonest, and more frequently so, than female participants. Rosenbaum, Billinger, & Stieglitz (Journal of Economic Psychology 2014) review experimental evidence of (dis)honesty 63 experiments from economics and psychology (including Friesen and Gangadharan EL 2012) and find the robust presence of unconditional cheaters and non-cheaters with the honesty of the remaining individuals being particularly susceptible to monitoring and intrinsic lying costs. Most of these experiments involve fairly low stakes, so those intrinsic lying costs are unlikely to be much of a constraint when stakes increase. The fraction of unconditional non-cheaters is almost certain to shrink towards the Escobar limit when stakes increase.

Interestingly, notwithstanding its public declarations in the good of people, Lemonade tells itself that, while trust is good, control is better. It runs its claimants, on top of the honesty pledges, through 18 different fraud detection algorithms before it pays up. On top of this, Lemonade engages in blatant cream-skimming. For example, it did not quote half of their customers that wanted to insure their homes. And it reports that the customers that are joining, or allowed to join, are younger, educated, tech-savvy, above-average earners, and female. So much for trust, trustworthiness, and all that BE marketing horsemanure. Pretty cold-blooded standard economic theory if you ask me. Note that this screening takes care of a key problem with their advertised approach: the likely adverse selection of bad types that mere trusting would invite, a very likely whammy on top of the moral hazard problem that every insurer faces.

So is Lemonade a viable business model?

Time will tell.

In the State of New York, Lemonade claims to have overtaken Allstate, GEICO, Liberty Mutual, State Farm, etc. in what is probably the single most critical market (renters and home insurance) share metric of all: NY renters buying new insurance policies since 1 Jan 2017.

Lemonade, we are told, is growing “exponentially” = “new bookings have doubled every ten weeks since launch, and show no sign of letting up.” According to its most recent Thanksgiving Transparency ‘17 report, Lemonade has now branched out into, and is selling in, Illinois, California and Nevada, Texas, New Jersey and Rhode Island, and has been licensed in 15 other states.

Of course, collecting insurance premia is one thing. Paying insurance claims and balancing the books is another thing altogether and the verdict on that one will be out for a while.

If Lemonade succeeds – and we all should hope it does –, it will do so because it engages in cream-skimming, targeting of low-risk market segments, and massive control and surveillance of its clientele. It will not do so because of its invocation of the feel-good alleged BE findings so prominently displayed on its web page.

 

 

 

 

 

 

 

 

How to lie with statistics: the case of female hurricanes.

I came across an article in PNAS (the Proceedings of the National Academy of Sciences) with the catchy title ‘Female Hurricanes are deadlier than male hurricanes’. It is doing the rounds in the international media, with the explicit conclusion that our society suffers from gender bias because it does not sufficiently urge precautions when a hurricane gets a female name. Intrigued, and skeptic from the outset, I made the effort of looking up the article and take a closer look at the statistical analysis. I can safely say that the editor and the referees were asleep for this one as they let through a real shocker. The gist of the story is that female hurricanes are no deadlier than male ones. Below, I pick the statistics of this paper apart.

The authors support their pretty strong claims mainly on the basis of historical analyses of the death toll of 96 hurricanes in the US since 1950 and partially on the basis of hypotheticals asked of 109 respondents to an online survey. Let’s leave the hypotheticals aside, since the respondents for that one are neither representative nor facing a real situation, and look at the actual evidence on female versus male hurricanes.

One problem is that the hurricanes before 1979 were all given female names as the naming conventions changed after 1978 so that we got alternating names. Since hurricanes have become less deadly as people have become better at surviving them over time, this artificially makes the death toll of the female ones larger than the male ones. In their ‘statistical analyses’ the authors do not, however, control adequately for this, except in end-notes where they reveal most of their results become insignificant when they split the sample in a before and after period. For the combined data though, the raw correlation between the masculinity in the names and the death toll is of the same order as the raw correlation between the number of years ago that the hurricane was (ie, 0.1). Hence the effects of gender and years are indeed likely to come from the same underlying improvement in safety over time.

Using the data of the authors, I calculate that the average hurricane before 1979 killed 27 people, whilst the average one after 1978 killed 16, with the female ones killing 17 per hurricane and the male ones killing 15.3 ones per hurricane, a very small and completely insignificant difference. In fact, if I count ‘Frances’ as a male hurricane instead of a female one, because its ‘masculinity index’ is smack in the middle between male and female, then male and female hurricanes after 1978 are exactly equally deadly with an average death toll of 16.

It gets worse. Even without taking account of the fact that the male hurricanes are new ones, the authors do not in fact find an unequivocal effect at all. They run 2 different specifications that allow for the naming of the hurricanes and in neither do they actually find an effect unequivocally in the ‘right direction’ (their Table $3).

In their first, simple specification, the authors allow for effects of the severity of a hurricane in the form of the minimum air pressure (the lower, the more severe the hurricane) and the economic damage (the higher, the more severe the hurricane). Conditional on those two, they find an insignificant effect of the naming of the hurricanes!

Undeterred and seemingly hell-bent to get a strong result, the authors then add two interaction terms between the masculinity of the name of the hurricane and both the economic damage and the air pressure. The interaction term with the economic damage goes the way the authors want, ie hurricanes with both more economic damage and more feminine names have higher death tolls than hurricanes with less damage and male names. That is what their media release is based on, and their main text makes a ‘prediction graph’ out of that interaction term.

What is completely undiscussed in the main text of the article however is that the interaction with the minimum air pressure goes the opposite way: the lower the air pressure, the lower the death toll from a more feminine-named hurricane! So if the authors had made a ‘prediction graph’ showing the predicted death toll for more feminine hurricanes when the hurricanes had lower or higher air pressures, they would have shown that the worse the hurricane, the lower the death toll if the hurricane had a female name!

The editors and the referee were thus completely asleep for this pretty blatant act of deception-by-statistics. Apparently, one can hoodwink the editors of PNAS by combining the following tricks: add correlated interaction terms to a regression of which one discusses only the coefficients that fit the story one wants to sell; then make a separate graph out of the parameter one needs in the main text, whilst putting technically sounding information in parentheses to throw editors, reviewers, and readers off the scent.

And the hoodwinking in this case is not small either. In order to accentuate what really is a non-result, the authors in the main text claim that “changing a severe hurricane’s name from Charley (MFI=2.889, 14.87 deaths) to Eloise (MFI=8.944,41.45 deaths) could nearly triple its death toll.” This, whilst in the years since 1979 the average death toll for their included hurricanes is 16 for both ‘female hurricanes’ and 16 for ‘male hurricanes’ (own calculations)! The authors conveniently forgot to mention in their dramatic result that Charley would have had to have been a hurricane that did immense economic damage but that had a very high minimum air pressure, ie was actually a very weak hurricane. Only for such an ‘impossible hurricane’ would their own model predict the increase in deaths from a female name. Put differently, I could have claimed that if the hurricane was very strong in terms of low air pressure, that changing the name from Charley to Eloise would have halved the death toll!

The authors also quite willingly pretend to have found things they have not in fact researched. They thus write “”Feminine-named hurricanes (vs. masculine-named hurricanes) cause significantly more deaths, apparently because they lead to a lower perceived risk and consequently less preparedness”” and the conclusions even speak of “gender biases”! Where do they try and measure this supposed bias in actual preparations? You guessed it, nowhere. PNAS should really clean up its act and not allow this sort of article, with its fairly blatant statistical artefacts, to slip through the cracks.

Let me explain the trickery in a bit more depth for the interested reader: air pressure and economic damage are highly related (the correlation is apparently -0.56), which means that one gets a strongly significant interaction between femininity and economic damage only because one simultaneously has added the interaction with minimum air pressure. One then talks about the interaction that goes the way one wants and happily neglects to mention the other one. And one needs both interactions at the same time to get the desired result on the interaction between the names and economic damage: without this interaction with minimum air pressure, what you get is a whole shift upwards of the male death prediction and a loss of significance on the interaction term with economic damage. You see this in the ‘additional analyses’ run by the author, in very small font after the conclusions, wherein the whole thing becomes insignificant for the first period and the reduced coefficient for the later period on the interaction with air pressure coincides with a halving of the coefficient on the interaction with economic damage as well. Hence, without including both interactions you would probably get that the female hurricanes are predicted to be less deadly than the male ones when the economic damage is small and more deadly when the damage is large (to an insignificant extent). So you need the interaction that is almost invisible in the main text and the conclusions to ‘get’ the result that the headlines are based on.

There is another, even more insidious trick played in this article. You see, with only 96 hurricanes to play with, which really only includes 26 to 27 ‘male’ hurricanes, the authors are asking rather a lot from their data in that they want to estimate 5 parameter coefficients, three of which based on names. If you then only use a simple indicator for whether or not a hurricane has a male name, you have the problem that you don’t have enough variation to get significance on anything.

So what did the authors do? Ingeniously, they decided to increase the variation in their names by having people judge just how ‘masculine’ their names were. Hence many of the ‘female’ hurricanes were ‘re-badged’ as ‘somewhat male hurricanes’. So the female hurricanes of the pre 1979 era had an average “masculinity index” of 8.42, whilst those of the new post-1979 era had an average of 9.01. Simply put, according to the authors the female hurricanes ‘of old’, which were of course more deadly as they occurred earlier, were also more masculine, contributing to the headline ‘results’.

Supposedly masculine female names included “Ione”, “Beulah”, and “Babe”. And who judges whether these are masculine names? Why, apparently this was done by 9 ‘independent coders’, by which one presumes the authors meant colleagues sitting in the staff room of their university in 2013! Now, even supposing that they were independent, one cannot help but notice that the coders will have been relatively unaware of the naming conventions in the 1950s and 1960s. How is someone born in 1970 sitting in a staff room in 2013 supposed to judge how ‘masculine’ the name ‘Ione’ was perceived to be in 1950? These older names probably just sounded unusual and hence got rated as ‘more probably male’. Similarly, it is beyond me why ‘Hugo’ would be rated as less masculine than ‘Jerry’ or ‘Juan’.

The authors’ own end-notes called ‘additional analyses’ indeed show that you get insignificant results without this additional variation begotten from making the names continuous. So the authors need to fiddle with the names of the hurricanes, pool two eras together whilst not controlling for era, and add two strongly correlated and opposing interaction terms in the same analyses to get the results they want. It is what economists refer to as ‘torturing the data until it confesses’.

Finally, for the observant, there is the following anomaly telling you something about the judgements made in this research: the masculinity of names is judged on a 1 to 11 scale (only integers) by 9 raters. Yet the averages reported in the authors’ appendices include such values as 1.9444444 (Isaac) and 9.1666666 (Ophelia). Note that if it were true that there were indeed nine raters, then all values should be an exact multiple of one-ninth, ie 0.11111111. The discrepancy indicates that either there were not always nine raters, or else that not all coded values were integers (an impossibility according to the main text). The 9.16666 for instance is a multiple of one-sixth and thus suggests only 6 rates were used for ‘Ophelia’. the 1.9444444 is a multiple of one-eigteenth, suggesting that there were twice as many raters for ‘Isaac’. Alternatively, in both cases, there were nine raters but one of the nine raters picked two values simultaneously (one even and one uneven) and thus added 0.055555 to a multiple of one-ninth in the displayed average. It is not a big thing as this kind of judgement is made all the time but I can’t find the footnote that owns up to this in the paper.

Predictions versus outcomes in 2013?

In the last 5 years, I have made a point of giving clear predictions on complex socio-economic issues. I give predictions partially to improve my own understanding of humanity: nothing sharpens the thoughts as much as having to actually predict something. Another reason is as a means of helping my countries (Australia/the Netherlands) understand the world: predicting socio-economic events is what scientists are for!

Time to have a look at my predictive successes and failures over the last few years, as well as the outstanding predictions yet to be decided. Let us start with what I consider my main failure.

Failed predictions

The main area I feel I haven’t read quite right is the conflict in Syria, as part of the general change in the whole Middle East. I am still happy with my long-run predictions for that region, where I have predicted that urbanisation, more education, reduced fertility rates, and a running out of fossil fuels will lead to a normalisation of politics in a few decades time. But at the end of 2012 I was too quick in thinking the Syria conflict was done and dusted. To be fair, I was mainly following the ‘intrade political betting markets’ which was 90% certain Assad would no longer be president by the end of this year, but the prophesised take-over of the country by the Sunni majority has not quite happened. The place has become another Lebanon, with lots of armed groups defending their own turf and making war on the turf of others. The regime no longer controls the whole country, but is still the biggest militia around.

What did I fail to see? I mainly over-estimated the degree to which the West would become involved. I expected the Americans and the Turks to put a lot of resources into the more secular militias, giving them training grounds and more modern equipment. As far as I can tell, this did happen a bit, but simply not to the degree I thought likely, and I don’t really know why. There were several attempts by the US and Turkey to identify an ‘opposition coalition’ to then support, so something hidden from view must have prevented actual support. Perhaps the US has decided it prefers Assad to the alternatives after all.

The willingness of the Iranians and Russians to support the regime has also been stronger than I thought, and the efforts of the Sunni-neighbours to support the non-regime militias have been less cogent than I thought: instead of backing a clear group that had a real future in terms of leading the country (the more secular groups), foreign anti-regime support came mainly for the crazies who went along with the ideology of fanatics elsewhere. That suggests a lack of pragmatic involvement from the neighbours.

I wouldn’t call it a complete predictive failure because Syria as a country no longer exists: it now does have all kinds of regional power brokers and so one could ‘claim’ the regime indeed has lost (most of) its power, but the conflict has gone on longer than the betting markets that I went along with predicted. So this also educates me about the lack of intellectual weight to that kind of political betting market: these are probably more feel-good markets with low turnover that simply don’t aggregate much hidden information. As a related failure, I can mention that I put a low probability on the event that the Muslim brotherhood would overplay its hand when in government in Egypt. I did mention the possibility (see later), but didn’t think it would happen.

 

Successful predictions

A very recent prediction of mine was on bitcoins. A month ago, I said governments were going to intervene because of the money laundering opportunities in the bitcoin network, and that it hence would not become a dominant trading currency. The next week, the Chinese came down with severe restrictions on bitcoins in their country: financial institutions were not allowed to trade in it and individuals trading in it had to register with their real names, killing off most laundering opportunities. As a result, the value of the bitcoins halved. I wouldn’t claim bitcoins are quite dead yet. It is when many other countries start to enact similar regulation (as some are doing) that it becomes an official curiosum.

Other predictions have been on various aspects of the GFC in Europe. I predicted such things as the Greek defaults when European governments were still pretending they would not occur, the survival of the Euro when there was lots of speculation on imminent euro exits, the inability of the ECB to actually meaningfully monitor banks, and the failure to get agreements on tax evasion (which have all been painfully clear in 2013). My proudest moment was to predict in December 2011 the overall trajectory of where the politics of the financial crisis was heading: support for weak new institutions in exchange for continued bailouts and forms of money printing, with national sovereignty as the sticking point preventing stronger institutions. We are still on that trajectory now, as this very recent report by the Bruegel Foundation argues which dryly summarises recent events: “Five years of crisis have pushed Europe to take emergency financial measures to cushion the free fall of distressed countries. However, efforts to turn the crisis into a spur for “an ever closer union” have met with political resistance to the surrender of fiscal sovereignty. If such a union remains elusive, a perpetual muddling ahead risks generating economic and political dysfunction.” The latest banking deal fits this mould perfectly.

I am also proud of my predictions on the ill-fated Monti-government in Italy of 2012. Before he was in power, I predicted he was unlikely to have the personality to change anything, and within weeks of him in government (December 2011) I mentioned the reforms he was talking about were dead in the water, months before the magazine The Economist still put him up as a great reformer. Only in 2013 did mainstream media outside of Italy wake up to his failure. I am similarly looking good on my observations regarding the problems in Spain.

On the Middle East, in 2011 I picked the current Lybian chaos coming from its resource curse. A few weeks into the Arab spring I predicted the ensuing grand coalition in 2012 between islamists and the military in Egypt, whereby the islamists would form government but with a tacit agreement with the military not to interfere with the economic interests of that military. I also predicted that the torture machine of the Egyptian military would first deal with the urban youth and then become oriented towards the islamists should they step out of line, which they did.

The main prediction I have been making since 2007 (and which has gotten me into the most trouble!) is the uselessness of looking for a world coalition to reduce CO2 emissions, mainly because the temptation to free-ride is irresistible both within countries and between them. I have thus consistently called to forget about emission strategies and to instead think of technological advances, geo-engineering and adaptation. In each year since 2007, the developments have been accordingly: steady increases in actual emissions with a growing number of scientists and research groups thinking more seriously about geo-engineering: previous agreements on emissions have not been kept and new ones are toothless, whilst you get many beautiful political speeches designed for consumption by the gullible during each new conference on the issues.

In 2013 for instance, the Japanese reneged on their earlier Kyoto promises because they decided to switch from nuclear to fossil, following on from a previous reneging by Canada. Similarly, the EU watered down its commitments in order not to upset the German car industry, whilst China and India and others helped prevent emission agreements with any bite. A nice write-up of the recent Warshaw talk-fest can be found here. Conspicuous in that write-up is the increased awareness of the importance of adapting to climate change, and the degree to which hope lies with new technology, not massive emission reductions under existing ones. The Australian deal with the EU trading scheme, which was all smoke-and-mirrors anyway, has fallen through, essentially replaced with a policy of ‘business as usual till the bigger players come up with a plan’, which I see as a sensible policy for Australia at the moment.

 

Predictions on the ledger

In many ways, the ‘emission controls are hopeless’ prediction is a running prediction for decades, so that one is very much still on the ledger. And one in which I am quite willing to bet against those who say they believe serious emission reductions will come about via emission markets or other controls.

Another prediction coming ‘half-good’ recently is the bet with Andrew Leigh on happiness and incomes in rich countries, where my prediction was that richer countries getting even richer would not get happier. For the data we agreed to look at it, this indeed held, but more because I got lucky with the data available – other data showed different results. Read about it in my recent blog on the topic by following the link!

Another prediction ‘on the ledger’ is that there is going to be no real change in Chinese politics till several years after they run out of easy growth opportunities, say 20 years from now. After that, I predict stronger and stronger pressure to adopt a Western-style political system from the Chinese business community. I gave a possible trajectory for how it might happen (local experimentation growing into national systems), but that is not the only way change might happen, if it happens at all. The prediction is the consolidation of the one-party rule till years after the growth has levelled off. That consolidation has indeed been in full swing this last year: as a recent piece of the Institute of Peace and Conflict Studies argues, in 2013 we got more media control and control over the economy by the party. Still, there are some embryonic signs of attempts to get some kind of separation of powers in that country, such as via more independent judiciary and financial institutions.

The prediction that the ‘behavioural genetics’ crowd is going nowhere soon is also a prediction ‘on the ledger’. The same goes for the prediction that Australia is not going to seriously improve its education-for-the-masses anytime soon, and the unlikelihood of solar replacing fossil fuel for mass electricity-generation anytime soon.

There is then a whole heap of predictions that I am quite happy to say have come true, but where it is also a certainty someone else would disagree. For instance, I predicted that the Melbourne Model, which is a change in how the University of Melbourne structures undergraduate education, would lead to dumbed-down degrees. Everything I hear about that place confirms it, but I would be astounded if the chancellery of the University of Melbourne would agree with that assessment! Similarly, my stated fears regarding the Gonski reforms (not quite predictions as I made it clear I had a hard time finding out what was actually going to happen) are looking all-too-true, but I am sure the ministries involved would disagree. One can trawl my archives for several more such ‘debatable’ prediction outcomes.

Finally, I have a bet on with Conrad Perry for what is going to happen in Egypt next. My prediction is that the next elected government will again be an islamist-lead government, a kind of Brotherhood 2.0. They may change labels and be even more careful, but I thought it likely that they would be involved as a dominant player in the next elections simply because of the high level of religiosity in that country. Conrad Perry bets on ‘all other outcomes’ with a bottle of red to the winner. Jim Rose also made an implicit prediction, which is that the new generation of military are going to be successful in their bid to monopolise power in Egypt, but he didn’t bet anything. Still, Jim is looking rosy on that prediction.

The prediction+bet with Conrad on Egypt was entered into around August/September and things have moved on a bit since then. The Egyptian military has proven more popular and bent on total control than I thought, but we are still looking at a situation in which one is likely to get democratic elections (though the military might well rig them). I will say I am less confident about my prediction now than 3 months ago, essentially because the military has been more brutal than I thought they would be, but there is still a chance for my prediction to happen so I am not ready to concede defeat on that one yet!

Rich countries and happiness: the story of a bet.

Do countries that are already rich become even happier when they become yet richer? This was the essential question on which I entered a gentleman’s bet in 2004 with Andrew Leigh and which just recently got settled.

The reason for the bet was a famous hypothesis in happiness research called the Easterlin hypothesis which held that happiness did not increase when rich countries became even richer. When I was preparing a presentation on this matter in 2004 I used the following graph to illustrate the happiness income relation across countries:

This graph shows you the relation between average income (GDP in purchasing power terms) and average happiness on a 0-10 scales for many countries. As one can see, the relation between income and happiness is upward sloping for low levels of income, but becomes somewhat flat after 15,000 dollars per person. I championed the idea that this was not just true if you looked across countries, but that this would also hold true over time.

Andrew Leigh’s thinking was influenced by other data, particularly a paper by Stevenson and Wolfers which – he thinks debunks the Easterlin hypothesis. Here’s one of their graphs:

 

What’s striking about this graph is that the dotted line slopes up in the top right corner. In other words, the relationship between happiness and income becomes stronger, not weaker, for countries with average incomes over $15,000. Andrew thinks that this is because they specify income in log terms (in other words, we’re looking at the effect on happiness of a percentage increase in income rather than a dollar increase in income). I think it’s because the Gallup poll isn’t measuring happiness, but is instead asking people to rank themselves on the Cantrill ladder of life scale.

So our gentleman’s bet was in effect a bet on whether happiness in the world value surveys behaved different to the ladder question of the Gallup polls, and on whether the short-run relation between income and happiness was strong enough to show up in periods of 5 to 10 years as well. Andrew thought it would, I thought 5-10 years would be long enough for the typical long-run no-effects findings to show up and that happiness has a different relation with income than the Cantril-question. So we bet on whether one would get a significantly positive relation between GDP growth and happiness changes for the rich countries when one looked at the World Value data for 2005. We agreed to look at the relation between income and happiness using country-average variation. The winner would get 100 bucks.

Now, both of us forgot about the bet for a few years as the data was supposed to become available. Only recently did Andrew remind me of our bet and asked to check what had happened.

When I (with research assistance from Debayan Pakrashi) started to look into this data again, it quickly became apparent that Andrew and I had been pretty sloppy in formulating the precise conditions of the bet. In many ways, our bet had been far too vague.

For one, the World Value survey is not in fact held in particular years. Rather, some survey is run almost every year in some country that adds to the collection of surveys known as the World Value Survey. Hence there was really no such thing as a ‘2005 wave’. Taken literally, only Australia, Finland, and Japan had a survey in 2005 and were countries that in the previous wave already had a GDP of 15,000 dollars. In all those countries, income had gone up a lot since their previous survey, with Australian happiness down and Japanese and Finnish happiness up. That is a bit meagre as ‘waves’ go.

So the first ‘addition’ was to have a bandwidth of years for the ‘2005’ waves that included 2004, 2005, 2006, 2007, and 2008. That gave 12 countries that were rich enough in the previous wave to qualify. The raw data was:

The next ‘snag’ was of course that there are many ways to define the dependence on income: linear or logarithmic. With logarithmic income one normally gets stronger statistical significance on income, so we went for logarithms.

Then, of course, there are still many other things one can put into the regression. Does one account for effects of particular years (in bands) and for the level of happiness that a country starts? We decided to try it all. Hence the final ‘deciding’ set of regressions were as follows:

 

Which tells you that the relation between income changes and happiness changes (the last two columns) was either quite insignificantly positive or even negative if one entered year-bands.

When one reflects on the list of countries used in the analysis though, it is clear that the outcome of the bet will have had little to do with the true relation between income and happiness. It will have hinged on hidden aspects of the data. For instance, the Australian world value survey in 1995 was run differently from the 2005 version. Hence the big drop in Australian happiness you see in this period for this data does in fact not show up for other Australian data (like the HILDA). So one suspects some change in the data-gathering to be responsible for it. Indeed, the level of Australian happiness in this data is markedly below the level found for the HILDA (where it is almost 8.0).

Similarly, the big increase in Japanese happiness in this period doesn’t show up either in other Japanese data and so probably has something to do with changes in how the survey was run there. The changes can relate to the months in which the surveys were held, the precise words used for the happiness question, the questions preceding the happiness questions, the cities in which the survey was run, how the survey was run (face-to-face or via telephone), etc.

So I may have gotten lucky and won the bet, but one cannot see the outcome as decisive evidence that income and happiness have no long-run relation within rich countries. The data for the 2010 post-GFC wave might well show the opposite!

The water you drink has been piss at least 10 times already!

Last thursday I posed the question of how often the water you drink has been pissed by a vertebrate already. If the number is very small, then those who baulk at drinking recycled water have more cause to complain than if the number is very high.

As some commentators to that post pointed out, in reality we are all drinking water that includes some recycled piss: every dam from which we drink has ducks, lizards, and all sorts of animals pissing and shitting in it, so it is already a bit of a myth to think one can drink water that has not been recently mixed with piss. Still, as another comment revealed, many think the idea of copying Singapore and drinking water that is officially recycled sewage is deemed ‘gross’. So the question how often water has been piss in the past still matters for the ‘yuk factor’.

The answer comes from a very simple formula, which requires a few guesstimates as inputs:

Piss ratio = (total water pissed)/(total water) = (total vertebrate biomass ever lived* piss rate)/ (total water) = (average biomass vertebrates * piss rate per year * years of vertebrates) / (total water)

This simple formula thus boils down to 4 inputs for which we can search for good guesstimates.

The amount of water on the planet (total water) is the easiest one because it is the sort of thing geologists and physicists are good at estimating. As this linked article computes, there is around 1.386 billion cubic kilometers of water on the planet. Whilst it is true that this water comes in various forms, that is not relevant for the calculation: since we are considering hundreds of millions of years, it doesn’t matter how much of that water is currently salt, fresh, stored in ice, or whatever: compared to such long time horizons it all circulates pretty fast so there is no problem in taking it all as one blob of water.

I can already say that my best guess for how much water we humans have pissed during our existence is around 800 cubic kilometers, meaning that only one 2-millionth of the atoms in the average water molecule will have been pissed out by a human. So we might be drinking reconstituted piss, but not much is reconstituted human piss.

Now, onto the other three inputs into our crucial equation. What is the average wet biomass of vertebrates? If we take the present as a reasonable guess for how much vertebrate biomass the earth continuously houses, then the answer we can gleam here is around 10% of total animal biomass (zoomass), or in the order of 5 billion tonnes of wet biomass (a lot more than dry biomass which you will often see reported). This includes up to 2 billion tonnes of dry-biomass fish, a little under half a billion tonnes of human, close to a billion tonne of things we might eat that walk on land (cattle and such), and 2 billion other wet biomass. In turn, this is in the order of one thousands of total biomass.

Admittedly, the estimate of 5 billion tonnes of wet vertebrate biomass may be out by a factor of 2 or so, but can easily be an under-estimate since I only found a dry biomass estimate for fish.

Then the next part of the equation: how much does a vertebrate piss per year? Again, this turns out to be a tricky question because only birds and mammals produce concentrated urine like we do. The rest pisses much weaker stuff, though things like fish still produce ammonia and the other normal elements of piss because the basic physiology is not that different between us and a fish. So the process and form of piss is not the same across species but the substances produced by our bodies and eventually excreted somehow are not that dissimilar.

So we need to slightly alter the definition of what we are looking for and think of piss as a ‘human-like’ substance. We can then again take a conservative approach and don’t count the watery piss that fish produce as ‘100% piss’ but rather as a much weaker variety of what we produce. We can then take ourselves as the measure of what a body produces and simply scale up, getting an easier question to start out with: how much do we humans piss in a year? The answer turns out to be that we piss around 1.5 liters per day, or 500 liters per year. Another way to put this is that we piss out 8 to 9 times our weight in wet biomass per year.

Then onto the last unknown, which is the number of years that vertebrates have been around in the abundant form of life we have now. Again, a tough one. The earth is now quite a bit cooler and probably less fertile than it was in the times of the dinosaurs, so the amount of biomass walking around now is probably quite a bit less than it was in the more productive phases of earth, but by the same token for much of the earth’s inhabited history the inhabitants were bacteria and not things with spines. If we concentrate on the period of the vertebrates, the best guess is that fish arose some 500 millions years ago, whilst land was conquered by vertebrates some 380 million years ago. Taking a conservative guess for the total period of time that the volume of vertebrates we have now has been present, this means that the wet vertebrate biomass we have now has occupied earth for around 350 million years.

We can now put the pieces together to compute our piss ratio: 350 million years of 5 billion tonnes of wet vertebrates pissing 8 times their body weight per year equals 14,000 million cubic kilometers of piss. This means the atoms in your average water molecule will have been concentrated piss some 10 times already. And that is a conservative estimate. In the more likely scenario, there would have been more like 10 billion tonnes of vertebrate biomass on average, pissing 10 times their own body weight, living 400 million years, equating to water having been piss around 25 times already.

Perhaps equally interesting I can give some idea how often the water has been piss from a particular group of vertebrates. Starting from the best guess estimate, water has been fish piss some 10 times, mammal piss around twice, and other forms of piss 13 times. Only a trickle has been monkey piss.

As per usual, champagne to all those who thought the answer was ‘often’ (which is all commentators game to give a guess). Unflavoured recycled filtered desalinated naturalised piss for the rest!

Thoughts on “Thinking, fast and slow”

I couldn’t resist buying a copy of Daniel Kahneman’s best-seller when returning from holidays. Several friends and colleagues told me it was a great book; it got great reviews; and Kahneman’s journal articles are invariably a good read, so I was curious.

Its general message is simple and intuitively appealing: Kahneman argues that people use two distinct systems to make decisions, a fast one and a slow one. System 1, the fast one, is intuitive and essentially consists of heuristics, such as when we without much thought finish the nursery rhyme ‘Mary had a little…’. The answer ‘lamb’ is what occurs to us from our associative memory. The heuristic to follow that impulse gives the right answer in most cases but can be lead astray by phrases like ‘Ork, ork, ork, soup is eaten with a …’. Less innocuous examples of these heuristics and how they can lead to sub-optimal outcomes are to distrust the unfamiliar, to remember mainly the most intense and the last aspect of an experience (the ‘peak-end rule’), to value something more after possessing it than before possessing it (the ‘endowment effect’) and to judge the probability of an event by how easily examples can come to mind.

System 2, the slow way to make decisions, is more deliberative and involves an individual understanding a situation, involving many different experiences and outside data. System 2 is what many economists would call ‘rational’ whilst System 1 is ‘not so rational’, though Kahneman wants his cake and eat it by saying that System 1 challenges the universality of the rational economic agent model whilst nevertheless not wanting to say that the rational model is wrong. ‘Sort of wrong sometimes’ seems to be his final verdict.

Let me below explore two issues that I have not seen in the reviews of this book. The first is on whether or not his main dichotomy is going to be taken up by economics or social science in the longer-run. The second, related point, is where I think this kind of ‘rationality or not’ debate is leading to. Both issues involve a more careful look at whether the distinction between System 1 and 2 really is all that valid and thus the question of what Kahneman ultimately has achieved, which in turn will center on the usefulness of the rational economic man paradigm.

Continue reading “Thoughts on “Thinking, fast and slow””

The Importance of Peer-Review in Journal, Department, and Individual Research Rankings

Preamble

I recall that some time in the mid 2000s, when the Research Quality Framework (which preceded the current ERA) was being discussed, Arden Bement, the director of the National Science Foundation, was asked what he thought. He responded as one would expect of a serious researcher, by saying that the only method he knows for judging academic outcomes is peer review.

In fact, Peer review is the gold-standard in science. We simply don’t trust any finding, method, conclusion, analysis, study that is not reported in a peer reviewed outlet. Yet there has been rapid growth in the use of indices in ways that have not been tested through peer review and which are being used to measure journal ranking, individual academic performance, and even the standing of departments.

Here, I argue that we should return to published methods that have been tested through peer review. The unchecked use of non-peer reviewed methods runs the risk of misallocating resources, e.g. if university promotion and appointment committees and bodies like the ARC use them. Even more troubling, is that non-peer reviewed methods are susceptible to manipulation; combined with the problem of inappropriate rewards, this has the potential to undermine what the profession, through peer-review, regards as the most valuable academic contributions.

Economics journal rankings

In the last two decades or so, there has been an explosion in the use of online indices to measure research performance in economics in particular (and academia generally). Thomson-Reuters Social Science Citation Index (SSCI), Research Papers in Economics (RePEc) and Google Scholar (GS) are the most commonly used by economists.

These tools display the set of publications in which a scholar’s given article is cited. While SSCI and GS take their set from the web as a whole, RePEc––hosted by the St Louis Fed–– is different, in that it refers only to its own RePEc digital database, which is formed by user subscription. Further, RePEc calculates rankings of scholars, but only of those who subscribe. Referring to its ranking methods, the RePEc web page states:

This page provides links to various rankings of research in Economics and related fields. This analysis is based on data gathered with the RePEc project, in which publishers self-index their publications and authors create online profiles from the works indexed in RePEc.

While it has been embraced by some academic economists in Australia as a tool for research performance measurement it is important to note that the RePEc ranking methodology is not peer-reviewed. This departure from the usual strong commitment to the process of peer-review by academics is puzzling, given that there is a long history of peer review in economics in in the study of, you guessed it “Journal Ranking”.

A (very) quick-and-dirty modern history

Coates (1971) used cites in important survey volumes to provide a ranking; Billings and Viksnins (1972) used cites from an arbitrarily chosen ‘top three’ journals; Skeels and Taylor (1972) counted the number of articles in graduate reading lists, and; Hawkins, Ritter and Walter (1973) surveyed academic economists. (Source: Leibowitz and Palmer JEL 1984, p78.)

The modern literature is based on a paper by Leibowitz and Palmer in the Journal of Economic Literature,1984. In their own words, their contribution had three key features

…(1) we standardize journals to compensate for size and age differentials; (2) we include a much larger number of journals; (3) we use an iterative process to “impact adjust” the number of citations received by individual journals

Roughly speaking, the method in (3) is to: (a) write down a list of journals in which economics is published, (b) count up the total number of citations to articles in each journal; (c) rank the journals by this count; (d) weight the citations by this count and, finally; (d) iterate. The end result gives you a journal ranking based upon impact-adjusted citations.

The current best method, is Kalaitzidakis et al Journal of the European Economics Association, 2003, hereafter KMS. This study was commissioned by the European Economics Association to gauge the impact of academic research output by European economics departments.

KMS is based on data from the 1990s and, as far as I am aware, has not been updated. No ranking can replace the wisdom of an educated committee examining a CV. However, KMS at least comes from a peer-review process. Unlike simple count methods, it presents impact, age, page and self-citation adjusted rankings, among others.

But even KMS-type methods can be misused: One should be ready to use the “laugh test” to evaluate any given ranking. KMS deliberately uses a set economics journals, roughly defined as journals economists publish in and read. It passes the laugh test because, roughly speaking the usual “top five” that economists have in their heads (AER, Econometrica, JPE, QJE and ReStud) do indeed appear near the top of the ranking, and other prestigious journals are not far behind.

The Economics Department at Tilburg University has included statistics journals in its “Tilburg University Economics Ranking”. The result? “Advances in Applied Probability” beats out the American Economic Review as the top journal: Their list can be found at https://econtop.uvt.nl/journals.php, but you need look no further than their top five to see that this does not pass the laugh test:

  1. Advances in Applied Probability
  2. American Economic Review
  3. Annals of Probability
  4. Annals of Statistics
  5. Bernoulli

Would I be remiss in suggesting that a statistics-oriented econometrician might have had an input into this ranking? Yes I would oops!

Finally, let us turn to the new RePEc impact-adjusted ranking. A laugh-test failure here, among others, is the inclusion of regional FED journals: Quarterly Review, Federal Reserve Bank of Minneapolis is ranked 14–just above the AER; the Proceedings Federal Reserve Bank of San Franscisco is ranked 16 ahead of the Journal of Econometrics at 19 and; Proceedings of the Federal Reserve Bank of Cleveland is 24, ahead of the European Economic Review at 29.

The RePEc top 5 is:

  1. Quarterly Journal of Economics
  2. Journal of Economic Literature
  3. Journal of Economic Growth
  4. Econometrica
  5. Economic Policy

It would be interesting to investigate whether macroeconomists and policy scholars had influence here.

My conclusions

If we are going to use ranking methods be very careful. Use methods that have emerged over decades of rigorous peer review, like the European Association’s 2003 study by KMS. And stick to their method rigorously lest we all have to retrain in statistics.

Update on Gene Patents 2010

Here’s an excellent update on Gene Patents covering the year 2010: http://genepatents.info/2011/02/24/gene-patents-2010-update/. It is written by my student Rachel Goh, a 5th year medical student at the University of Melbourne. She discusses the controversy surrounding the Myriad and Monsanto cases in the US and Europe, as well as legal decisions in Australia surrounding breast cancer tests and the Australian Senate review on gene patents. Of particular interest is her observation that we are moving increasingly towards “multi-genomic” tests, so the patenting of individual genetic sequences will cause greater problems for follow-on and systemic innovation. I see here a parallel to software patents and patent thickets, which have been said to have had similar effects. Rachel also included a thoughtful commentary along with her summary.