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 Topic: Economics.

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  • Economics.
     Reply #120 - March 05, 2015, 01:55 AM

    Hey Qtian, you seem to be the 'go to guy' for all things economic on this forum so I'm wondering if you're familiar with the idea of(and I suspect you are) http://en.m.wikipedia.org/wiki/Anarcho-capitalism or free market capitalism and what your thoughts are on it?
    From what I gather it's the concept of reducing state interference in the free market to essentially 0. One of it's biggest advocates is a guy called Stefan Mollyneux who considers himself to be a 'State-iest' and argues things would all be alot fairer, work more smoothly and most of us would be a lot happier/better off under such an economic model. I've also heard him try to back this model up by claiming, contrary to prior belief, 99% of business/trade is based on co - operation as opossed to competition. Not sure though where he's pulling those figures from to be honest.  Cheesy
  • Economics.
     Reply #121 - March 05, 2015, 10:16 AM

    Try running an airline or a railway on those principles. Whilst I agree with the idea of commonwealth -see ostrom - to get anything done does need management! The issues are really about checks and balances on managers and institutionalisation as well as working out cooperative ways. Anarchy capitalism simplifies dangerously

    When you are a Bear of Very Little Brain, and you Think of Things, you find sometimes that a Thing which seemed very Thingish inside you is quite different when it gets out into the open and has other people looking at it.


    A.A. Milne,

    "We cannot slaughter each other out of the human impasse"
  • Economics.
     Reply #122 - March 06, 2015, 06:53 PM

    What your thoughts are on it?


    Can't say that I hold a massive interest in Anarcho-capitalism, nor is it an area that I have encountered through formal studies of Economics. However, I am aware of what it is.

    Nevertheless, I am very interested in the history of economic thought so I will share a few things with you with reference to the particulars of "Anarcho Capitalism".

    My initial thoughts are that the attempted usage of "Anarcho" (which implies association with Anarchism) is a misnomer. As far as I know, anarchists are in and of themselves, directly opposed to Capitalism as they see it as a form of exploitation. I guess this general view is similar to what Marx had to say (Marx framed it in terms of his circuit of industrial capital), where his specific view was that Capitalism would eventually collapse due to its own inner contradictions.

    Anarchists would claim that something can either be Anarchism or Capitalism as both systems cannot coalesce. They would therefore vehemently disagree with the Anarcho-capitalism synthesis.

    I sense that Anarcho capitalists would respond with something along the lines of: "The definition of Anarchism is the belief in the abolition of all government."

    This however ignores the fact that Anarchism exists as a political theory and not just a reductive mission statement. One could argue that being opposed to government is a necessary but not sufficient condition for being an anarchist.

    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #123 - March 08, 2015, 02:43 PM

    The things we don't notice impact our decision making much more than we think.

    https://www.youtube.com/watch?v=4pzveZYt9N4

    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #124 - March 08, 2015, 05:33 PM

    Great video.
  • Economics.
     Reply #125 - March 08, 2015, 05:50 PM

    Quote
    A map should be an aid to decision making, not a substitute for decision making.


    That was one of my favourite parts of the talk.

    The above is how I currently view neoclassical paradigms.

    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #126 - March 09, 2015, 04:28 PM

    Try running an airline or a railway on those principles. Whilst I agree with the idea of commonwealth -see ostrom - to get anything done does need management!


    The "Anarcho Capitalist" will argue that there are indeed management structures in place but they only go up as far as a coropate level, this is all that's needed for things to still work.
  • Economics.
     Reply #127 - March 09, 2015, 04:58 PM

    Thanks for the feedback Qtian, unfortunately I don't often get a chance to write into this forum these days as my life seems to be more busy than ever. So I can't get into as much of a 'to and fro' with op's as I'd like.

    Anarchists would claim that something can either be Anarchism or Capitalism as both systems cannot coalesce. They would therefore vehemently disagree with the Anarcho-capitalism synthesis.


    Well that is an interesting observation, perhaps the term is an an oxymoron, I'll need to look into it a little closer myself but to be honest from what I've learned so far it's not an economic model I think I'd be comfortable living under.
    Let me give my reasons for and against the near reduction/total removal of state/state interference.
    For example I'm renting where I live now and currently there is an upward surge in rental prices so much so that I know other families nearby who are being forced to move out because they cannot continue to afford these annual rent increases, the same may be true of myself in the future if this trend continues. Now there's talk by some (whether it's true or not) of government restricted rent rates/a cap on how much the landperson ask for from his/her tennant.
    Surely to the 'anarcocapitalist' such a notion screams of market meddling by the State(Protect the free market at all costs and so what if peoples living arrangement are harshly comporomised). I on the otherhand would welcome such a move as it means I may not necessarily need to start looking around for a new place to live in.
    Another example is emergency healthcare, persumable in an 'AnarchoCapitalist' society those who can afford to be will be insured beyond belief but what about those who aren't, are they left to die on the street or can they pay it back by taking up whatever way/labour they can find or perhaps a short stint in prison but then again how would prisons be run and what private coporations should judge who is sentenced. What kind of penal system could even exist under such an idea or would we all be such well adjusted members of society we could simply do away with the need for one.
    However I'll end this line of thought on one point in favour of less state interference. Speaking from my experiences in the business world, very simply, show me a new start-up company and I'll show you a government body that want to rap a nice tax ribbon around it.


  • Economics.
     Reply #128 - March 09, 2015, 05:14 PM

    Can't say that I hold a massive interest in Anarcho-capitalism, nor is it an area that I have encountered through formal studies of Economics. However, I am aware of what it is.

    Nevertheless, I am very interested in the history of economic thought so I will share a few things with you with reference to the particulars of "Anarcho Capitalism".

    My initial thoughts are that the attempted usage of "Anarcho" (which implies association with Anarchism) is a misnomer. As far as I know, anarchists are in and of themselves, directly opposed to Capitalism as they see it as a form of exploitation. I guess this general view is similar to what Marx had to say (Marx framed it in terms of his circuit of industrial capital), where his specific view was that Capitalism would eventually collapse due to its own inner contradictions.

    Anarchists would claim that something can either be Anarchism or Capitalism as both systems cannot coalesce. They would therefore vehemently disagree with the Anarcho-capitalism synthesis.

    I sense that Anarcho capitalists would respond with something along the lines of: "The definition of Anarchism is the belief in the abolition of all government."

    This however ignores the fact that Anarchism exists as a political theory and not just a reductive mission statement. One could argue that being opposed to government is a necessary but not sufficient condition for being an anarchist.

    Libertarian Communism by Isaac Puente, written in Spain in the early 30s shortly before the civil war and revolution, gives a good idea of the mainstream anarchist position: https://libcom.org/library/libertarian-communism . There's nothing in this that's remotely compatible with anarcho-capitalism.
  • Economics.
     Reply #129 - March 09, 2015, 05:23 PM

    Just came across an interesting post, the introduction is very similar to my initial argument lol.

    I like this section:

    As such, it would be fair to say that most "anarcho"-capitalists are capitalists first and foremost. If aspects of anarchism do not fit with some element of capitalism, they will reject that element of anarchism rather than question capitalism (Rothbard's selective appropriation of the individualist anarchist tradition is the most obvious example of this). This means that right-"libertarians" attach the "anarcho" prefix to their ideology because they believe that being against government intervention is equivalent to being an anarchist (which flows into their use of the dictionary definition of anarchism). That they ignore the bulk of the anarchist tradition should prove that there is hardly anything anarchistic about them at all. They are not against authority, hierarchy or the state -- they simply want to privatise them.


    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #130 - March 09, 2015, 06:28 PM

    ^
    Good find. It sounds about right, the last sentence is particularly poignant, it sums up the contradiction of such a notion in a nutshell.
  • Economics.
     Reply #131 - March 09, 2015, 10:39 PM

    Some decision theory....
    The asymmetric dominance effect


    Let’s consider a situation. There is a company with two products, A and B. Both these products have their own merits and demerits. Product A has relatively less features, but it’s price is low. Product B, on the other hand, has more features but it’s more expensive. Consumers tend to pick both these products depending on their needs. Now the company introduces a third product, C. The asymmetric dominance theory says that you can affect the consumer behavior using this third product. You can make the consumers shift towards product A or product B by designing product C in different ways. Now how is that possible? How can we change consumer preference between A and B without even modifying these products?  

    Asymmetric Dominance is a phenomenon observed in Decision Theory. The asymmetric dominance effect (also called the decoy effect) is a phenomenon where consumers tend to have a change in preference between two options when presented with a third option that is asymmetrically dominated. Wait a minute, asymmetrically dominated? An option is said to be asymmetrically dominated when it is inferior in all aspects with respect to one option but inferior in some aspects and superior in other aspects with respect to the other option. This makes it look like an even balance with respect to the other product.

    This third product is completely dominated by one option and only partially dominated by the other. When the asymmetrically dominated option is present, a higher percentage of consumers will prefer the dominating option than when the asymmetrically dominated option is absent. Sounds silly right? Are consumers that naive? Well, turns out they are! The third option is therefore used as a decoy which is used to increase preference for the dominating option.

    An Example

    Let’s consider the following products:

    A) Hard Drive with 500 GB for $150.
    B) Hard Drive with 300 GB for $100.

    Now, between these two products, people can either prefer A, because it has more hard drive space, or B, because it has a lower price point. This is where asymmetric dominance comes into picture. If I want to increase the number of consumers buying product A, then I will introduce a third option:

    C) Hard Drive with 400 GB for $170.

    The introduction of a third option (C) that is more expensive than A and B, and has less hard drive space than product A, makes it asymmetrically dominated by product A. Hence, consumer preference will shift towards A just because of the introduction of this third option, making it look like the best deal. Similarly, if you want to shift the consumer preference towards (B), what would you do? Think about it.

    What if you get caught with this decoy?

    There will also be a percentage of consumers that will realize that you offering a decoy to try to attract them to one model. Even though this is a small percentage that will “catch on” to what you are doing, some of them will still think otherwise. So how do we deal with these people? If you want to lower this percentage, you can introduce a new feature. This new feature must be something totally irrelevant in the decision making process that nobody cares about. But at the same time, it must be something that can be used as a justification to the consumer. The most common example is by offering a strange color, like orange, on the dominated option (C in this example) that nobody wants in the first place. Who will buy an orange colored hard drive?

    This theory has vast applications. It can be applied to anything from pricing in your ads to pricing on your sales page. Keep in mind that even a Google Adwords ad, people are making a decision where to click. Anytime someone is making a decision and there are many price points and product features available as options then the decoy theory can be utilized. This theory comes up everywhere in our daily lives. In fact, we fall for it more often than we realize. That’s the beauty of a good decoy!

    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #132 - April 21, 2015, 12:10 PM

    Paul Mason on the future of capitalism
    https://m.youtube.com/watch?v=s5teO3W4LrM
  • Economics.
     Reply #133 - July 12, 2015, 04:30 PM


    A Little Disruption, Big Economic Shocks


    Sometimes a piece of macroeconomics research is so cool I just have to write about it. A new working paper by Daron Acemoglu, Ufuk Akcigit, and William Kerr is one of those papers.

    Time and again, you have heard the critics of macroeconomics say that the economy is too complex to model with math -- especially the straightforward kind of math used in most of macro. Most macro models lump all consumers into one giant superconsumer, all companies into one giant supercompany and so forth. Even the models that differentiate people and companies tend to do so only in a limited way -- limiting the economy to two types of people, for example, or having people differ only in their level of wealth.

    This frustrates a lot of people. The economy isn’t just some simple machine that takes in labor and capital and spits out dollars of gross domestic product, right? It’s a complex web of business relationships, inputs and outputs, expectations and interactions. Blogger Arnold Kling, for example, has criticized the idea of the economy as a “GDP factory,” and urged us to think about “patterns of sustainable specialization and trade,” or PSST.

    There are a couple of reasons we would really like a PSST or network-based macro model. First of all, it would solve the problem of what causes recessions. Currently, we have very little idea of what tips economies from boom over to bust -- there is usually no big obvious change in productivity, technology or government policy at the beginning of a recession. If the economy is a fragile complex system, it might only take a small shock to send the whole thing into convulsions. A second reason is that modeling the complex guts of the economy would give us a lot more data to look at -- instead of just thinking about aggregates like national consumption and investment, we could look at the pattern of how recessions spread from company to company or region to region.

    The problem -- as any macroeconomist would tell you -- is that actually modeling PSST with math is really, really hard. But without the concrete language of mathematical theory, you’re left just waving your hands, relying on intuition or anecdotes, or (at best) subjective interpretations of empirical studies.

    People have wanted to model the economy as a system of moving parts for a while now. John Long and Charles Plosser took a stab at it back in the 1980s. Their basic idea was to model the economy as a system of inputs and outputs, with linkages connecting the pieces -- kind of like a bunch of balls connected by sticks. Acemoglu et al. use a somewhat updated version of this model, adding  linkages between different regions.

    What the authors then do is to look at the pattern of how economic disturbances propagate throughout the industrial and regional network. They examine several types of disturbances such as changes in Chinese imports, government spending and productivity. Some of these shocks propagate upstream through the value chain, from retailers to suppliers. They call these demand shocks. Others move in the opposite direction, and they call these supply shocks

    Their main conclusion is the result we would want from a model like this -- small disturbances to any of these things create big effects.

    This is very different from the way many macroeconomists would like to think about the economy. Robert Lucas, considered by many to be the father of modern macroeconomics, wrote in 1977 that the movements of the various pieces of a complex economy should average out. It was shown much later that this wasn't necessarily the case, but not until Acemoglu et al. have we really seen concrete examples and hard numbers.

    The implication is that the rosy picture of the economy as a smoothly functioning machine isn't necessarily an accurate one. The tinker-toy web of suppliers and customers and regional economies in Acemoglu et al.’s paper is a fragile thing, easily disturbed by the winds of randomness.

    The model also has policy implications. One of the biggest and longest-lasting economic debates is whether government spending can affect the real economy.  Lucas and others have claimed that it can’t. But in Acemoglu et al.’s model, it absolutely can, since the government is part -- a very big, very important part -- of the network of buyers and sellers.

    So thanks to the hard work and insight of Acemoglu and others, the old dream of a network model of the economy is a little closer to reality. Someday we may draw maps of economic linkages the way we now draw circuit diagrams, and use supercomputers to simulate economic disturbances as they make their way through the web. We may look back on the simple pen-and-paper models of yesteryear and laugh.



    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #134 - July 16, 2015, 12:07 PM

    Game Theory Is Useful, Except When It Is Not

    Ariel D. Procaccia

    Although game theory is now a household name, few people realize that game theorists do not actually study “games” — at least not in the usual sense of the word. Rather, we interpret a “game” as a strategic interaction between two or more rational “players.” These players can be people, animals, or computer programs; the interaction can be cooperative, competitive, or somewhere in between. Game theory is a mathematical theory and, as such, provides a slew of rigorous models of interaction and theorems to specify which outcomes are predicted by any given model.

    Sounds useful, doesn’t it? After all, many people are familiar with one of game theory’s most famous test cases: the Cold War. It is well-known that game theory informed U.S. nuclear strategy, and indeed, the interaction between the two opposing sides — NATO and the Warsaw Pact — can be modeled as the following game, which is a variation of the famous “Prisoner’s Dilemma.” Both sides can choose to either build a nuclear arsenal or avoid building one. From each side’s point of view, not building an arsenal as the other side builds one is the worst possible outcome, because it leads to strategic inferiority and, potentially, destruction. By the same token, from each side’s point of view, building an arsenal while the other side avoids building one is the best possible outcome.

    However, if both sides avoid building an arsenal, or both sides build one, neither side has an advantage over the other. Both sides prefer the former option because it frees them from the enormous costs of a nuclear arms race. Strangely enough, though, the only rational strategy is to build an arsenal, whether the other side builds one (in which case you are saving yourself from possible annihilation) or does not (in which case you are gaining the strategic upper hand). This analysis gave rise to the doctrine of MAD: Mutually Assured Destruction. The simple idea is that the use of nuclear weapons by one side would result in full-scale nuclear war and the complete annihilation of both sides. Given that nuclear stockpiling is unavoidable, MAD at least guaranteed that no side could afford to attack the other.

    So it would seem that game theory has saved the world from thermonuclear war. But does one really need to be a game theorist to come up with these insights? Game theory tells us, for example, that different forms of stable outcomes exist in a wide variety of “games” and computational game theory gives us tools to compute them. But the type of strategic reasoning underlying Cold War policy does not directly leverage deep mathematics — it is just common sense.

    More generally, one can argue that game theory — as a mathematical theory — cannot provide concrete advice in real-life situations. In fact, one of the most forceful advocates of this point is the well-known game theorist Ariel Rubinstein, who claims that “applications” of game theory are nothing more than attaching labels to real-life situations. In an article that rehashes his well-known views, Rubinstein cites the euro zone crisis, which some say is a version of the Prisoner’s Dilemma, to argue that “such statements include nothing more profound than saying that the euro crisis is like a Greek tragedy.” In Rubinstein’s view, game theory is first and foremost a mathematical theory with a “nearly magical connection between the symbols and the words.” By contrast, he contends, for the purpose of application, we should see game theory as a “collection of fables and proverbs” that can provide an interesting perspective on real-life situations but not give specific recommendations.

    Michael Chwe, a professor of political science at the University of California, Los Angeles, offers a different take, arguing in his latest book that novelist Jane Austen is, in fact, a game theorist. After describing a scene from Mansfield Park, Chwe writes: “With this episode, Austen illustrates how in some situations, not having a choice can be better. This is an unintuitive result well known in game theory.” Another of Austen’s game-theoretic insights has explicit applications: “When a high-status person interacts with a low-status person, the high-status person has difficulty understanding the low-status person as strategic. … This can help us understand why, for example, after the U.S. invaded Iraq, the resulting Iraqi insurgency came as a complete surprise to U.S. leaders.”

    To Chwe, Austen studied the principles of strategic interaction on the level of Rubinstein’s “fables and proverbs.” But if we take his conclusion — this makes Austen a game theorist — this means that these fables and proverbs lie at the core of game theory, rather than at game theory’s periphery, where it interfaces with popular culture. Chwe makes a convincing case that Austen was keenly interested in studying how people manipulate each other — and, indeed, that is one of the things that make Austen a great writer. But that does not necessarily make her a great game theorist.

    In fact, as a mathematical and scientific theory, game theory often falls short when it is applied to complex situations like international relations or parliamentary balance of power. However, in some situations, game theory can be useful in the scientific, prescriptive sense. For example, game theory is useful for, well, playing games. Modern software agents that play games like poker (such as the ones from Tuomas Sandholm’s group at Carnegie Mellon University) do in fact use rather advanced game theory, augmented with clever equilibrium-computation algorithms. Game theory actually works better when the players are computer programs, because these are completely rational, unlike human players, who can be unpredictable.

    Game theory is also useful for designing auctions. To give a concrete example from my own experience, consider the surprisingly lively Pittsburgh real-estate market, where multiple buyers typically submit simultaneous bids for one house without seeing each other’s offers. The house is sold to the highest bidder, and the price is equal to the highest bid. In this procedure, which is called a first-price auction, buyers try to second-guess each other, and their bids are normally lower than the price they are actually willing to pay.

    Suppose that, instead, the seller chooses to sell the house to the highest bidder for a price that is equal to the second-highest bid. This seemingly far-fetched idea is known as the second-price auction. In a second-price auction, one can never benefit from submitting a bid that is different from one’s true value for the house. Indeed, intuitively, a buyer’s bid does not affect the price he pays if he wins, so the buyer’s bid should be no lower than his true value in order to maximize his chances of winning. But bidding a value that is higher than the buyer’s true value will change the outcome only if the second-highest bid is higher than the buyer’s true value (otherwise, the buyer could have won by bidding his true value), in which case the buyer does not want to win the auction, and he overpays. In game-theoretic terms, the second-price auction is incentive compatible.

    The beautiful idea underlying the second-price auction has inspired similar insights that guide the design of sophisticated auctions for goods worth billions of dollars, such as rights to transmit over bands of the electromagnetic spectrum. And while this application of game theory seems fundamentally different from playing poker, the two are in fact similar: both involve interactions taking place in closed, controlled environments, where the rules of the game are specified exactly.

    But not all of game theory’s success stories are like that. An especially exciting example comes from Milind Tambe’s group at the University of Southern California, a project I have collaborated on. Their work models security situations as a game between a defender (e.g., airport security) and an attacker (e.g., a terrorist organization or a smuggling ring). The defender’s strategy is a randomized deployment of its resources (e.g., cameras, patrols) specifying how likely it is that each of its resources would defend each of the possible targets (e.g., airport terminals).

    The defender moves first by committing to a security strategy, which the attacker then observes via surveillance. The attacker must choose which target to pursue knowing the likelihood that it will be defended, but without knowing whether a specific target is defended on the actual day of attack. The defender must therefore anticipate the attacker’s response and commit to a strategy that guarantees the best outcome by deploying resources randomly and broadly. This forces the attacker to be less effective.

    Similar game-theoretic models have been around since the 1960s, but it is only in the last decade that researchers have begun to understand the computational aspects of these games. Tambe and his group have gone as far as implementing and deploying algorithms that prescribe a security policy by computing the defender’s optimal strategy. These algorithms are currently in use by the Los Angeles International Airport, the U.S. Coast Guard, and the Federal Air Marshal Service.

    These success stories explain game theory’s relevance, but not its huge popularity. The latest edition of a massive open online course (MOOC) on game theory, taught by professors from Stanford and the University of British Columbia, had 130,000 registered students. Are many of these students hoping that game theory will help them in their jobs or their daily lives? If so, they are in for a disappointment. Game theory is typically not useful, but when it is, it shines.


    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #135 - July 18, 2015, 08:03 PM

    Paul Mason on postcapitalism
  • Economics.
     Reply #136 - July 20, 2015, 12:49 PM

    I don't really like her insistence that philosophical inquiry is necessarily deductive, because it isn't.  However, this is a still a pretty cool post.



    The Trouble with Mathematics and Statistics in Economics


    If you will forgive me, I will be very simple here. The two points I am making are simple, and do not need to be dressed up in fancy clothing. I want to state the points in a way that they cannot be evaded. I'm not optimistic that this tactic will work, but I owe it to a field I love to try. If I am right in my criticism of economics—I pray that I am not —then much of what economists do nowadays is a waste of time. If this is so it is very desirable that we economists do something about it, right now.

    I was told recently by a former editor of the American Economic Review that he "basically agrees" with what I am saying here. But then he went on to excuse continuing to waste scientific time—for example, in the pages of the American Economic Review— as necessary for the careers of young people. This will not do. Either you agree with me, and will then of course join me in demanding that economics change right away; or you disagree, in which case it is incumbent upon you as a serious scientist to explain exactly why I am mistaken.

    The usual objections to mathematical and statistical reasoning in economics seem to me to be unsound. For example, it is often said that economic data is not "strong enough to bear the weight of elaborate mathematics and statistics." People who say this seem to believe that data in, say, physics is superior to that in the social sciences. But a moment's reflection suggests that this cannot in general be true. Data on stock-market transactions, for example, are available in unlimited amounts, whereas data on neutron stars or the early days of universe are strictly limited. Interestingly, it has also been long argued (I find explicit statements in the 1920s, and by Gerard Debreu more recently) that the weakness of the data is a reason for mathematics, the notion being that economists must therefore rely on axiom and proof. For the same reason as its opposite, and for some additional reasons, the argument is unsound.

    One hears sometimes that economic theory is not sufficiently developed to "bear the weight." The intricacies of pure rationality in game theory belie this objection. Surely the assumptions of Nash equilibrium can bear all the mathematical weight one wishes to pile onto them. Some say that mathematics is inherently too "abstract." But that, after all, is the point of any argument, i.e., to abstract from particular circumstances enough to say something interestingly general. That variables other than the life cycle contribute to savings is true, but that is no argument against Franco Modigliani's life and work. And some say, as Walras characterized the position in 1874, that "human liberty will never allow itself to be cast into equations." As Walras replied, "as to those economists who do not know any mathematics, who do not even know what it meant by mathematics and yet have taken the stand that mathematics cannot possibly serve to elucidate economic principles, let them go their way."

    The serious objections are, I think, two. (1.) The kind of mathematics used in economics is typically that of the Department of Mathematics, not that of the departments of Physics or of Engineering. It is existence-theorem, qualitative mathematics. It is of no use for science. (2.) The kind of statistics used in economics is that of Department of Statistics, which is also a species of "existence theorems." Tests of statistical significance claim to tell whether there "exists" an effect of interest rates on investment. But this, too, is of no use for science.

    The first, mathematical error has characterized economics since its beginning. It has nothing, really, to do with mathematics, since it can be committed, and was, in entirely verbal economics, such as that of Ricardo. But the coming of Mathematics-Department mathematics, which never asks how large something is, has continued this unhappy tradition. As Roberto Marchionnatti notes, the first generations of mathematical economists "were chiefly interested in the problems connected with the relationship between mathematical expressions and experimental [I think he means "experiential"] reality." They "generally seemed not to be worried about the formal establishment of equilibrium, am issue that dominated mathematical economics later."[3] He notes that "In the 1930s . . . the axiomatization of economic theory permitted mathematical developments that were free from problems of the realism of the model used." That's right.

    The second, statistical error has come to dominate economics since the cheapening of calculation in the 1970s. It was brought into economics by Tinbergen and Klein in the 1940s, but in statistics generally it dates back to R. A. Fisher in the 1920s and to Karl Pearson in the 1900s.
    * * * *

    The English political arithmeticians William Petty and Gregory King and the rest in the late seventeenth century—anticipated in the early seventeenth century by, like so much of what we call "English," certain Dutchmen—wanted to know How Much. It was an entirely novel obsession, and perfectly consistent with the Scientific Revolution going on at the time. You might call it bourgeois. How Much will it cost to drain the Somerset Levels? How Much does England's treasure by foreign trade depend on possessing colonies? How Much is this and How Much that? Adam Smith a century later kept wondering how much wages in Edinburgh differed from those in London (too much) and how much the colonies by then acquired in England's incessant eighteenth-century wars against France were worth to the home country (not much). By the late eighteenth century, it is surprising to note, the statistical chart had been invented. What is "surprising" is that it hadn't been invented before—another sign that quantitative thinking was novel, at least in the West (the Chinese had been collecting statistics on population and prices for centuries). European states from Sweden to Naples began in the eighteenth century collecting statistics to worry about: prices, population, balances of trade, flows of gold. The word "statistics" was a coinage of German and Italian enthusiasts for state action in the early eighteenth century, pointing to a story of the state use of numbering. Then dawned the age of statistics, and everything from drug incarcerations and smoking deaths to the value of a life and the credit rating of Jane Q. Public are numbered.

    The formal and mathematical theory of statistics was largely invented in the 1880s by eugenicists—those clever racists at the origin of so much in the social sciences—and perfected in the twentieth century by agronomists at places like the Rothamsted agricultural experiment station in England or at Iowa State University. The newly mathematized statistics became a fetish in fields that wanted to be sciences. During the 1920s, when sociology was a young science, quantification was a way of claiming status, as it became also in economics, fresh from putting aside its old name of political economy, and in psychology, fresh from a separation from philosophy. In the1920s and 1930s even the social anthropologists counted coconuts.

    Mathematics of course is not identical to counting or statistics. There have been some famously good calculators among mathematicians, Leonhard Euler being an instance—he also knew the entire Aeneid by heart; in Latin, I need hardly add. But most of mathematics has nothing to do with actual numbers. Euler used calculation in the same way that mathematicians nowadays use computers, for back-of-the-envelope tests of hunches on the way to developing what the mathematicians are pleased to call a Real Proof of such amazing facts as: eiπ + 1 = 0 (and therefore God exists). You can have a "real" proof, the style of demonstration developed by the Greeks, without examining a single number or even a single concrete example. Thus: the Pythagorean Theorem is true for any right triangle, regardless of its dimensions, and is proven not by induction from many or even millions of numerical examples of right triangles, but universally and for all time, praise God, may her name be glorified, by deduction from premises. Accept the premises and you have accepted the Theorem. Quod erat demonstrandum.

    Statistics or other quantitative methods in science (such as accounting or experiment or simulation) answer inductively How Much. Mathematics by contrast answers deductively Why, and in a refined and philosophical version very popular among mathematicians since the early nineteenth century, Whether. "Why does a stone dropped from a tower go faster and faster?" Well, F = ma, understand? "I wonder Whether the mass, m, of the stone has any effect at all." Well, yes, it does: notice that there's a little m in the answer to the Why question.

    Why/Whether is not the same question as How Much. You can know that forgetting your lover's birthday will have some effect on your relationship (Whether), and even understand that the neglect works through such-and-such an understandable psychological mechanism ("Don't you love me enough to know I care about birthdays?" Why). But to know How Much the neglect will hurt the relationship you need to have in effect numbers, those ms and as, so to speak, and some notion of their magnitudes. Even if you know the Why (the proper theory of the channels through which forgetting a birthday will work; again by analogy, F = ma), the How Much will depend on exactly, numerically, quantitatively how sensitive this or that part of the Why is in fact in your actual beloved's soul—how much in this case the m and a are. And such sensitivity in an actual world, the scientists are always saying, is an empirical question, not theoretical. "All right, you louse, that's the last straw: I'm moving out" or "Don't worry, dear: I know you love me" differ in the sensitivity, the How Much, the quantitative effect, the magnitude, the mass, the oomph.

    Economics since its beginning has been very often "mathematical" in this sense of being interested in Why/Whether arguments without regard to How Much. For example: If you buy a loaf from bread from the supermarket both you and the supermarket (its shareholders, its employees, its bread suppliers) are made to some degree better off. Economists have long been in love with this simple argument. They have since the eighteenth century taken the argument a crucial and dramatic step further: that is, they have deduced something from it, namely, Free trade is neat. If each deal between you and the supermarket, and the supermarket and Smith, and Smith and Jones, and so forth is betterment—producing (a little or a lot: we're not talking quantities here), then (note the "then": we're talking about deduction here) free trade between the entire body of Italian people and the entire body of English people is betterment producing, too. And therefore (note the "therefore") free trade between any two groups is neat. The economist notes that if all trades are voluntary they all have some gain. So free trade in all its forms is neat. For example, a law restricting who can get into the pharmacy business is a bad idea, not neat at all, because free trade is good, so non-free trade is bad. Protection of French workers is bad, because free trade is good. And so forth, to literally thousands of policy conclusions.

    Though it is among the three or four most important arguments in economics, it is not empirical. It contains no statements of How Much. It says there exists a gain from trade. "I wonder Whether there exists [in whatever quantity] a good effect of free trade." Yes, one exists: examine this page of mathematics; look at this diagram; listen to my charming parable about you at the supermarket. Don't ask How Much. The reasoning is Why/Whether.

    As stated it cannot be wrong, no more than the Pythagorean Theorem can be. It's not a matter of approximation, not a matter of How Much. It's a chain of logic from implicit axioms (which can be and have been made explicit, in all their infinite variety) to a "rigorous" qualitative conclusion (in it's infinite variety). Under such-and-such a set of assumptions, A, the conclusion, C, must be that people are made better off. A implies C, so free trade is beneficial anywhere.

    Philosophers call this sort of thing "valid" reasoning, by which they do not mean "true," but "following from the axioms—if you believe the axioms, such as A, then C also must be true." If you believe that any individual exchange arrived at voluntarily is good, then with a few extra assumptions (e.g., about the meaning of "voluntarily"; or, e.g., about how one person's good depends on another's) you can get the conclusion that free international trade among nations is good.

    Why/Whether reasoning, which is also characteristic of the Department of Mathematics, could be called philosophical. The Department of Philosophy has a similar fascination with deduction, and a corresponding boredom with induction. Neither Department bothers with How Much. In the Philosophy Department either relativism is or is not open to a refutation from self-contradiction. It's not a little refuted. It's knocked down, or not. In the Department of Mathematics the Goldbach Conjecture, that every even number is the sum of two prime numbers (e.g., 24 = 13 + 11), is either true or false—or, to introduce a third possibility admitted since the 1930s, undecidable. Supposing it's decidable, there's no question of How Much. You can't in the realm of Why/Whether, in the Department of Mathematics or the Department of Philosophy or some parts of the Department of Economics, be a little bit pregnant.

    Since about 1947 the front line and later the dominant and by now the arrogantly self-satisfied and haughtily intolerant if remarkably unproductive scientific program in economics has been to reformulate verbal—but still philosophical/mathematical, i.e. qualitative, i.e. Why/Whether—arguments into symbols and variables and diagrams and fixed point theorems and the like. The program is called "Samuelsonian." Paul Samuelson and his brother-in-law Kenneth Arrow led the movement to be explicit about the math in economics, against great opposition. They were courageous pioneers. In 1947 Samuelson set the tone with the publication of his Ph. D. dissertation, which had been finished in 1941. In 1951 Arrow carried it to still higher realms of Department-of-Mathematics mathematics with his own Ph.D. dissertation. Their enemies, a few of whom are still around, said, with the humanists, " This math stuff is too hard, too inhuman. Give me words. Sentiment. Show me some verbal argumentation or some verbal history. Or even actual numbers. But none of this new x and y stuff. It gives me a headache."

    But there was nothing whatever new about deductive reasoning in economics in 1947. In the 1740s and 1750s David Hume in Scotland and the physiocrats in France were busy inventing philosophical, entirely qualitative, Why/Whether arguments about economics). Deducing sometimes surprising and anyway logically valid (if not always true) conclusions from assumptions about the economy is a game economists have always loved. If you want to connect one thing with another, deduce conclusions C from assumptions A, free trade from characterizations of an autonomous consumer, why not do it universally and for all time? Why not, asked Samuelson and Arrow and the rest, with much justice, do it right? Getting deductions right is the Lord's work, if not the only work the Lord favors. Like all virtues it can be carried too far, and be unbalanced with other virtues, becoming the Devil's work, sin. But all virtues are like that.

    True, for practical purposes of surveying grain fields it would work just as well as Pythogoras' Greek proof to have a Babylonian-style of proof-by-calculation showing that the sums of squares of the sides of millions of triangles seem to be pretty much equal to the sums of squares of their hypotenuses. You might make a similar case for the free trade theorem, noting for example that the great internal free-trade zone called the United States still has a much higher average income (20 to 30 percent higher) than otherwise clever and hard working countries like Japan or Germany, which insist on many more restrictions on internal trade, such as protection of small retailing. And, true, the improvement of computers is making more Babylonian-style "brute force calculations" (as the mathematicians call them with distaste) cheaper than some elegant formulas ("analytic solutions," they say, rapturously). Economics, like many other fields—architecture, engineering—is about to be revolutionized by computation.

    But if beyond clumsy fact or numerical approximation there is an elegant and exact formula—F = ma or E = mC2 or, to give a somewhat less elegant example from economics, 1 + iusa = (eforward / espot) (1 + ifrance), "covered interest arbitrage"—why not use it? Of course, any deduction depends on the validity of the premises. If a sufficiently high percentage of potential arbitrageurs in the markets for French and U.S. bonds and currency are slothful, then covered interest arbitrage will not hold. But likewise any induction depends on the validity of the data. If the sample used to test the efficacy of mammograms in preventing premature death is biased, then the statistical conclusions will not hold. Any calculation depends on the validity of the inputs and assumptions.
    * * * *

    A real science, or any intelligent inquiry into the world, whether the study of earthquakes or the study of poetry, economics or physics, history or anthropology, art history or organic chemistry, a systematic inquiry into one's lover or a systematic inquiry into the Italian language, must do two things. If it only does one of them it is not an inquiry into the world. It may be good in some other way, but not in the double way that we associate with good science or other good inquiries into the world, such as a detective solving a case.

    I am sure you will agree: An inquiry into the world must think and it must look. It must theorize and must observe. Formalize and record. Both. That's obvious and elementary. Not everyone involved in a collective intelligent inquiry into the world need do both: the detective can assign his dim-witted assistant to just observe. But the inquiry as a whole must reflect and must listen. Both. Of course.

    Pure thinking, such as mathematics or philosophy, is not, however, to be disdained, not at all. Euler's equation, eπi + 1 = 0, really is quite remarkable, linking "the five most important constants in the whole of analysis" (as Philip Davis and Reuben Hersh note), and would be a remarkable cultural achievement even if it had no worldly use. But certainly the equation is not a result of looking at the world. So it is not science; it is a kind of abstract art. Mathematicians are proud of the uselessness of most of what they do, as well they might be: Mozart is "useless," too; to what would you "apply" the Piano Sonata in A?

    Nor is pure, untheorized observation to be disdained. There is something in narration, for example, that is untheorizable (though it is surprising to non-humanists how much of it can and has recently been theorized by literary critics). At some level a story is just a story, and artful choice of detail within the story is sheer observation—not brute observation, which is a hopeless ambition to record everything, but sheer.

    So pure mathematics, pure philosophy, the pure writing of pure fictions, the pure painting of pictures, the pure composing of sonatas are all, when done well or at least interestingly, admirable activities. I have to keep saying "pure" because of course it is entirely possible—indeed commonplace for novelists, say, to take a scientific view of their subjects (Balzac, Zola, Sinclair Lewis, the post-War Italian realists, among many others are well known for their self-conscious practice of a scientific literature; Roman satire is another case; or Golden Age Dutch painting). Likewise scientists use elements of pure narration (in evolutionary biology and economic history) or elements of pure mathematics (in physics and economics) to make scientific arguments.

    I do not want to get entangled in the apparently hopeless task of solving what is known as the Demarcation Problem, discerning a line between science and other activities. It is doubtful such a line exists. The efforts of many intelligent philosophers of science appear to have gotten exactly nowhere in solving it. I am merely suggesting that a science like many other human practices such as knitting or making a friend should be about the world, which means it should attend to the world. And it should also be something other than miscellaneous facts, such as the classification of animals in the Chinese Celestial Emporium of Benevolent Knowledge noted by Borges: (a.) those that belong to the Emperor, (b.) embalmed ones, (c.) those that are trained, (d.) suckling pigs, (e.) mermaids, and so forth, down to (n.) those that resemble flies from a distance. Not brute facts. And not mere theory.

    So I am not dragging economics over to some implausible definition of Science and then convicting it of not corresponding to the definition. Such a move is common in economic methodology—for example in some of the less persuasive writings of the very persuasive economist Marc Blaug. I am merely saying that economists want to be involved in an intelligent inquiry into the world. If so, the field as a whole must theorize and observe, both. This is not controversial.

    An economist at a leading graduate program listening to me will now burst out with: "Great! I entirely agree: theorize and observe, though of course as you admit we can specialize in one or the other as long as the whole field does both. And that, Deirdre, is exactly what we already do, on a massive scale. And we do it very well, if I don't say so myself. We do very sophisticated mathematical theorizing, such as in the Mas-Collel, Whinston, and Green textbook (1995), and then we test the theory in the world using very tricky econometrics, such as Jeffrey M. Wooldridge, Econometric Analysis of Cross Section and Panel Data (2001). You can see the results in any journal of economics. Some of it is pure theory, some econometrics. Theorize and observe."
    * * * *

    To which I say: Rubbish. She and her colleagues, when they are being most highbrow and Science-proud, don't really do either theorizing or observing. Economics in its most prestigious and academically published versions engages in two activities, qualitative theorems and statistical significance, which look like theorizing and observing, and have (apparently) the same tough math and tough statistics that actual theorizing and actual observing would have. But neither of them is what it claims to be. Qualitative theorems are not theorizing in a sense that would have to do with a double-virtued inquiry into the world. In the same sense, statistical significance is not observing.

    It is not difficult to explain to outsiders what is so dramatically, insanely, sinfully wrong with the two leading methods in high-level economics, qualitative theorems and statistical significance. It is very difficult to explain it to insiders, because the insiders cannot believe that methods in which they have been elaborately trained and which are used by the people they admire most are simply unscientific nonsense, having literally nothing to do with whatever actual scientific contribution (and I repeat, it is considerable) that economics makes to the understanding of society. So they simply can't grasp arguments that are plain to people not socialized in economics.[4]

    Why-Whether reasoning is in economics takes this form: A implies C. The crucial point is that the A and the C are indeed qualitative. They are not of the form "A is 4.8798." They are of the qualitative form, "A is 'everyone is motivated by P-Only considerations'," say, which implies "free trade is neat." No numbers. You realize your lover will be annoyed by the neglected birthday to some degree, but we're not talking about magnitudes. Why/Whether. Not How Much. The economic "theorists" focus on existence theorems. With such and such general (or not so general, but anyway non-quantitative) assumptions A there exists a state of the imagined world C. A typical statement in economic "theory" is, "if information is symmetric, an equilibrium of the game exists" or, "if people are rational in their expectations in the following sense, buzz, buzz, buzz, then there exists an equilibrium of the economy in which government policy is useless."

    For example, the non-free traders, often European and disproportionately nowadays French, point out that you can make other assumptions about how trade works, A', and get other conclusions, C' not so favorable to laissez faire. The free-trade theorem, which sounds so grand, is actually very easy to overturn, and numerous careers have been built in economics doing so (Paul Krugman's, for example). Suppose a big part of the economy—say the household—is, as the economists say, "distorted" (e.g., suppose people in households do things for love: you can see that we economists have a somewhat peculiar idea of "distortion"). Then it follow rigorously (that is to say, mathematically) that free trade in other sectors (e.g. manufacturing) will not be the best thing. In fact it can make the average person worse off than restricted, protected, tariffed trade would.

    The theorists don't have to operate in this existence-theorem way. They could instead—some do—use mathematics to develop functional forms into which the world's data can be plugged. It is the difference between abstract general equilibrium—a field of economics which practically everyone now agrees was a complete waste of time and talent—and computable general equilibrium, which has nothing whatever to do with the existence theorems and has everything to do with picking sensible numbers and simulating.

    The trouble with the qualitative theorems recommended by Paul Samuelseon in the Foundations is this. Naturally, if you change assumptions (introducing households who do not operate on Prudence-Only motivations, say; or [I speak now to insiders] making information a little asymmetric; or [ditto] introduce any Second Best, such as monopoly or taxation; or [ditto] nonconvexities in production) in general a conclusion about free trade is going to change. There's nothing deep or surprising about this: changing your assumptions changes your conclusions. Call the new conclusion C' . So we have the old A implies C and the fresh, publishable novelty, A' implies C'. But, as the mathematicians say, we can add another prime and proceed as before, introducing some other plausible possibility for the assumptions, A'' (read it "A double prime"), which implies its own C''. And so forth: A''' implies C'''. And on and on and on and on, until the economists get tired and go home.

    What has been gained by all this? It is pure thinking, philosophy. It is not disciplined by any simultaneous inquiry into How Much. It's qualitative, not quantitative, and not organized to allow quantities into the story. It's like stopping with the conclusion that forgetting your lover's birthday will have some bad effect on one's relationship—you still have no idea how much, whether trivial or disastrous or somewhere in between. So the pure thinking is unbounded. It's a game of imagining how your lover will react endlessly. True, if you had good ideas about what were plausible assumptions to make, derived from some inquiry into the actual state of the world, the situation might be rescued for science and other inquiries into the world, such as the inquiry into the probably quantitative effect of missing a birthday on your lover's future commitment to you. But if not—and such is the usual practice of "theoretical" pieces in economics, about half the items in any self-respecting journal of economic science—it's "just" an intellectual game.

    I have expressed admiration for pure mathematics and for Mozart's concertos. Fine. But economics is supposed to be an inquiry into the world, not pure thinking. (If it is to be justified as pure thinking, just "fun," it is not very entertaining. No one would buy tickets to listen to a "theory" seminar in economics. As mathematical entertainment the stuff is quite poor.) The A-prime/C-prime, existence-theorem, qualitative-only "work" that economists do is like chess problems. Chess problems usually do not have anything to do even with playing real chess—since the situations are often ones that could not arise in a real game. And chess itself has nothing to do with living, except for its no doubt wonderful purity as thought, � la Mozart.

    What kind of theory would actually contribute to a double-virtued inquiry into the world? Obviously, it would be the kind of theory for which actual numbers can conceivably be assigned. If Force equals Mass times Acceleration you have a potentially quantitative insight into the flight of cannon balls, say. But the qualitative theorems don't have any place for actual numbers. So the "results" keep flip-flopping, endlessly, pointlessly.

    Samuelson himself famously showed in the 1940s that "factor prices" (such as wages) are "equalized" by trade in steel and wheat and so forth—as a qualitative theorem, under such and such assumptions, A. It could be an argument against free trade. But shortly afterwards it was shown by Samuelson himself, among others that if you make alternative assumptions, A', you get very different conclusions. And so it went, and goes, with the limit achieved only in boredom, all over economics. Make thus-and-such assumptions, A, about the following game-theoretic model and you can show that a group of unsocialized individuals will form a civil society. Make another set of assumptions, A', and they won't. And so on and so forth. Blah, blah, blah, blah, to no scientific end.

    Such stuff has taken over fields near to economics, first political science and now increasingly sociology. A typical "theoretical" paper in the American Political Science Review shows that under assumptions A the comity of nations is broken; in the next issue someone will show that under A' it is preserved. This is not theory in the sense that, say, physics uses the term. Pick up a copy of the Physical Review (it comes in four versions; pick any). Open it at random. You will find mind-breakingly difficult mathematics, and physics that no one except a specialist in the particular tiny field can follow. But always, on every page, you will find repeated, persistent attempts to answer the question How Much. Go ahead: do it. Don't worry; it doesn't matter that you can't understand the physics. You will see that the physicists use in nearly every paragraph a rhetoric of How Much. Even the theorists as against the experimenters in physics spend their days trying to figure out ways of calculating magnitudes. The giveaway that something other than scientific is going on in "theoretical" economics (and, alas, political science) is that it contains not, from beginning to end of the article, a single attempt at a magnitude.
    * * * *

    "But wait a minute, Deirdre," the Insider Economist breaks in (he is getting very, very annoyed because, as I told you, he Just Doesn't Get It). "You admitted that we economists also do econometrics, that is, formal testing of economic hypotheses using advanced statistical theory. You, as an economist, can hardly object to specialization: some people do theory, some empirical work."

    Yes, my dear young colleague. Since I have been to your house and noted that you have not a single work on economics before your own graduate training I suppose you are not aware that the argument was first made explicit in 1957 by Tjalling Koopmans, a Dutch-American economist at Yale (Nobel 1975), who in his Three Essays on the State of Economic Science recommended just such a specialization. He recommended that "theorists" spend their time on gathering a "card file" of qualitative theorems attaching a sequence of axioms A', A'', A''', etc. to a sequence of conclusions C', C', C''', etc., separated from the empirical work, "for the protection [note the word, students of free trade] of both."

    Now this would be fine if the theorems were not qualitative. If they took the form that theorems do in physics (better called "derivations," since physicists are completely uninterested in the existence theorems that obsess mathematicians and philosophers), good. Then the duller wits like Deirdre McCloskey the economic historian could be assigned to mere observation, filling in blanks in the theory. But there are no blanks to fill in, no How Much questions asked, in the theory that economists admire the most and that has taken over half of their waking hours.

    Still, things would not be so bad if on the lower-status empirical side of academic economics all was well. The empiricists like me in their dull-witted way could cobble together actual scientific hypotheses, simply ignoring the "work" of the qualitative theorists. Actual players of chess could ignore the "results" from chess problems. In effect this is what happens. The "theories" proffered by the "theorists" are not tested. In their stead linearized models that try crudely to control for this or that effect are used. An empiricist could therefore try to extract the world's information about the price sensitivity of demand for housing in Britain in the 1950s, say.

    But unhappily the empirical economists also have become confused by qualitative "results." They, too, have turned away from one of the two questions necessary for a serious inquiry into the world (the other is Why), How Much. The sin sounds improbable, since empirical economics is drenched in numbers, but the numbers they acquire with their most sophisticated tools—as against their most common tools, such as simple enumeration and systems of accounting—are it turns out meaningless.

    The confusion and meaninglessness arises from "statistical significance." It has become since the cheapening of computation in the 1970s a plague in economics, in psychology, and, most alarmingly, in medical science. Consider the decades-long dispute over the prescribing of routine mammograms to screen for early forms of breast cancer. One school says, Start at age 40. The other says, No, age 50. (And still another, Never routinely. But set that aside.) Why do they differ? The American nurses' epidemiological study or the Swedish studies on which the empirical arguments are based are quite large. But there's a lot of noise in the data. So: although starting as early as age 40 does seem to have some effect, the samples are not large enough to be conclusive. By what standard? By the standard of statistical significance at the 5%, 1%, 0.1%, or whatever level.

    So the situation is this. The over-50 school admits that there is some positive effect in detecting early cancers from starting mammograms as early as age 40; but, they say with a sneer, it's uncertain. You'll be taking some chance of being fooled by chance. Nasty business. Really, something to avoid. Even though there is a life-saving effect of early mammograms in the data on average, Mr. Medical Statistician is uncomfortable about claiming it. The purpose of medical research is to save lives. His comfort is not what we are chiefly concerned with. The data is noisy. It is a pity that God arranged it that way. She should have been more considerate. But She's done what She's done. Now we have to decide if the cost of the test is worth the benefit. And the data shows a benefit.

    Mr. Medical Statistician replies, with some indignation: "No it's does not. At conventional levels of significance there is no effect."

    Deirdre, with more indignation: "Nonsense. You are trying, alas, to make a qualitative judgment of existence. Compare the poor, benighted Samuelsonian "theorist." We always in science need How Much, not Whether. The effect is empirically there, whatever the noise is. If someone called "Help, help!" in a faint voice, in the midst of lots of noise, so that at the 1% level of significance (the satisfactorily low probability that you will be embarrassed by a false alarm) it could be that she's saying "Kelp, kelp!" (which arose perhaps because she was in a heated argument about a word proposed in a game of Scrabble), you wouldn't go to her rescue?

    The relevant and quantitative question about routine mammograms, which has recently been reopened, is the balance of cost and benefit, since there could be costs (such as deaths from intrusive tests resulting from false positives) that offset the admittedly slight gain from starting as early as age 40. But suppose, as was long believed, that the costs do not offset the gain. That the net gain is slight is no comfort to the (few) people who die unnecessarily at 42 or 49 on account of Mr. Medical Statistician's gross misunderstanding of the proper role of statistics in scientific inquiries. A death is a death. The over-50 people are killing patients. Maybe only slightly more than zero patients. But more than zero is murder.

    Or consider the aspirin-and-heart-attack studies. Researchers were testing the effects of administering half an aspirin a day to men who had already suffered a heart attack. To do the experiment correctly they gave one group the aspirin and the other a placebo. But they soon discovered—well short of conventional levels of statistical significance—that the aspirin reduced reoccurrences of heart attacks by about a third. What did they do? Did they go on with the study until they got a large enough sample of dead placebo-getters to be sure of their finding at levels of statistical significance that would make the referees of cardiology journals happy? Of course not: that would have been shockingly (though not unprecedently) unethical. They stopped the study, and gave everyone aspirin. (A New Yorker cartoon around the same time made the point, showing a tombstone inscribed, "John Smith, Member, Placebo Group.")

    Or consider public opinion polls about who is going to win the next presidential election. These always come hedged about with warnings that the "margin of error is 2% plus or minus." So is the claim that prediction of a presidential election six months before it happens is only 2% off? Can that be reasonable?. What is being reported is the sampling error (and only at conventional levels of significance, themselves arbitrary). An error caused, say, by the revelation two months down the road that one of the candidates is an active child molester is not reckoned as part of "the error." You can see that a game is being performed here. The statement of a "probable error" of 2% is silly. A tiny part of all the errors that can afflict a prediction of a far-off political event is being elevated to the rhetorical status of The Error. "My streetlight under sampling theory is very bright, so let's search for the keys under the streetlight, even though I lost them in the dark." This cannot go on.

    The point here is that such silliness utterly dominates empirical economics. In a study of all the empirical articles in the American Economic Review in the 1980s it was discovered that fully 96% of them confused statistical and substantive significance.[5] A follow-up study for the AER in the 1990s found that the problem had become worse. [6] The problem is that a number fitted from the world's experiments can be important economically without being noise-free. And it can be wonderfully noise-free without being important. On the one hand: It's obvious, you will agree, that a "statistically insignificant" number can be very significant for some human purpose. If you really, truly want to know how the North American Free Trade Agreement affected the average worker in the United States, then it's too bad if the data are noisy, but that's not the point. You really, truly want to know it. You have to go with what God has provided. And on the other hand: It is also obvious that a "statistically significant" result can be insignificant for any human purpose. When you are trying to explain the rise and fall of the stock market it may be that the fit is very tight for some crazy variable, say skirt lengths (for a long while the correlation was actually quite good). But it doesn't matter: the variable is obviously crazy. Who cares how closely it fits? For a long time in Britain the number of ham radio operator licenses granted annually was very highly correlated with the number of people certified insane. Very funny.

    In short, statistical significance is neither necessary nor sufficient for a result to be scientifically significant. Most of the time it is irrelevant. A reseacher is simply committing a scientific error to use it as it is used in economics and the other social sciences and in medical science and (a strange one, this) population biology as an all-purpose way of judging whether a number is large enough to matter. Mattering is a human matter; the numbers figure, but after collecting them the mattering has to be decided finally by us; mattering does not inhere in a number. Physics and chemistry, though of course highly numerical, hardly ever use statistical significance. Economists and those others use it compulsively, mechanically, erroneously to provide a non-controversial way of deciding whether or not a number is large. You can't do it this way. No competent statistical theorist has disagreed with me on this point since Neyman and Pearson in 1933. There is no mechanical procedure that can take over the last, crucial step of an inquiry into the world, asking How Much in human terms that matter.
    * * * *

    The argument is not against statistics in empirical work, no more than it is against mathematics in theoretical work. It is against certain very particular and peculiar practices of economic science and a few other fields. Economics has fallen for qualitative "results" in "theory" and significant/insignificant "results" in "empirical work." You can see the similarity between the two. Both are looking for on/off findings that do not require any tiresome inquiry into How Much, how big is big, what is an important variable, how much exactly is its oomph. Both are looking for machines to produce publishable articles. In this last they have succeeded since Samuelson spoke out loud and bold beyond the dreams of intellectual avarice. Bad science—using qualitative theorems with no quantitative oomph and statistical significance also with no quantitative oomph—has driven out good.

    The progress of economic science has been seriously damaged. Most of what appears in the best journals of economics is therefore mistaken. I find this unspeakably sad. All my friends, my dear, dear friends in economics, have been wasting their time. You can see why I am agitated about the Two Sins. They are vigorous, difficult, demanding activities, like hard chess problems. But they are worthless as science.

    The physicist Richard Feynman called such activities Cargo Cult Science. Certain New Guinea tribesmen had prospered mightily during the Second World War when the American Air Force disgorged its cargo to fight the Japanese. After the War the tribesmen wanted the prosperity to come back. So they started a "cargo cult." Out of local materials they built mock airports and mock transport planes. They did an amazingly good job: the cargo-cult airports really do look like airports, the planes like planes. The only trouble is, they aren't actually. Feynman called sciences he didn't like "cargo cult sciences. By "cargo cult" he meant that they looked like science, had all that hard math and statistics, plenty of long words; but actual science, actual inquiry into the world, was not going on.

    I am afraid that my science of economics has come to the same point. Paul Samuelson, though a splendid man and a wonderful economist (honestly), is a symbol of the pointlessness of qualitative theorems. Samuelson, actually, is more than merely a symbol—he made and taught and defended the Two Sins, at one time almost singlehandedly. It was a brave stance. But it had terrible outcomes. Samuelson advocated the "scientific" program of producing qualitative theorems, developing qualitative-theorem-generating-functions, such as "revealed preference" and "overlapping generations" models" and above all the machinery of Max U. He was involved also, it turns out somewhat surprisingly, in the early propagation of significance testing, the "scientific" method of empirical work running on statistical significance without a loss function, through his first PhD. student, Lawrence Klein. So it is only fair to call both the sins of modern economics Samuelsonian.

    Until economics stops believing, contrary to its own principles, that an intellectual free lunch is to be gotten from qualitative theorems and statistical significance it will be stuck on the ground waiting at the cargo-cult airport, at any rate in its high-end activities uninterested in (Really) How Much. High-end theoretical and econometric papers will be published. Careers will be made, thank you very much. Many outstanding fellows (and no women) will get chairs at Princeton and Chicago. But our understanding of the economic world will continue to stagnate.


    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #137 - July 27, 2015, 07:48 PM

    Keynes and The General Theory: http://www.councilofexmuslims.com/index.php?topic=29115.new#new

    An FAQ for neoclassical economists: http://www.councilofexmuslims.com/index.php?topic=29043.0

    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #138 - July 27, 2015, 08:44 PM

    Does anyone here invest in stock market? Im curious about Iranian stockmarket, since the sanctions have lifted...
  • Economics.
     Reply #139 - July 27, 2015, 08:49 PM

    Not sure if this is the right section though :/
  • Economics.
     Reply #140 - July 27, 2015, 08:59 PM

    You may need to create another thread for financial babble.

    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #141 - July 29, 2015, 10:47 PM

    The Lucas critique.

    http://conversableeconomist.blogspot.co.uk/2012/11/robert-lucas-and-lucas-critique.html

    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #142 - August 01, 2015, 03:52 PM

    Mark Blyth on the Danger of Mathematical Models

    The Brown professor says that perfect mathematical models are ultimately too perfect, and can seduce economists into ignoring imperfections



    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #143 - August 11, 2015, 09:57 PM

    Nassim Taleb is one of the biggest opponents of VaR, a widely used measure of risk. Many of its shortcomings were made apparent during the global financial crisis of 08.

    Part one: https://youtu.be/6QiiFSOrJhQ
    Part two: https://youtu.be/T6rXannQTtI

    I highly recommend these videos...

    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #144 - August 23, 2015, 02:23 PM

    No, Economics Is Not a Science

    Economics is not a science in the way that physics or chemistry is a science. Yet, this is not something to be lamented. Economics is not, and will never be, at the stage where models can precisely predict the day on which a financial crisis will start before it happens, but this is not due to the lack of legitimacy of the field; instead, it is due to the inherently unpredictable sphere of study in which economics operates. People are not atoms—and this is exactly why economics is immediately relevant.


    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #145 - August 24, 2015, 09:51 PM

    What is a Complex System?

    Type 1: Lots of components, intricate interconnections.


    What makes a system complex? Fundamentally a system is complex, if its behavior cannot be easily described. One way this can arise is if the system consists of many components, with numerous relationships and interactions between these components. The presence, absence, or nature of these relationships may affect the behavior of the aggregate system, so a description of this behavior must take into account each of these relationships. (Notice that if the components of the system are identical and their interconnection is regular, then the aggregate behavior can be quite simple. This is well demonstrated by the behavior of a memory chip, which have the greatest density of transistors of any integrated circuit.

     Another way in which a system can be complex, is if the inherent behavior of a component is non-linear. Such systems can exhibit chaotic behavior. Examples of such systems are certain non-linear oscillators, weather systems (at almost all levels of fidelity) and the 3n+1 (Collatz) process. Such systems may possess succinct descriptions, but highly complex behavior. Detailed behavior of non-linear systems will not be the focus of this study, although the difficulties they induce will arise in systems of the type discussed above.

    Abstraction

    Thus, to understand a type I complex system (consisting of many components), we must reduce the number of components that must be examined. There appear to be two basic approaches that one might take. One can partition the components into collections of components, where each collections has a relatively well defined behavior. If the number of components in a collection is two large, then the process may be repeated recursively. This hierarchical partitioning is characteristic of top down or structured design. Notice that the boundaries that arise at the first partitioning persist at every refinement of the partitioning.

    An alternative approach to partitioning the system, is to approximate the behavior of the system by a simpler model containing fewer components and/or simpler interactions. These types of approximate models abound in physics and engineering. The most accurate model of a the behavior of a mechanical system can be obtained using a relativistic, quantum mechanical model of the system. However, this is often too complicated and a Newtonian or simple relativistic models are often used instead. These models approximate the behavior of the relativistic quantum mechanical model. The boundaries of the components and interactions in the each of the three modes are different.




    My mind runs, I can never catch it even if I get a head start.
  • Economics.
     Reply #146 - September 04, 2016, 10:09 PM

    Omg, I completely forgot about this thread.

    My mind runs, I can never catch it even if I get a head start.
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