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Nate Silver confuses cause and effect, ends up defending corruption
- DigitalJack 14y agoI'm not discounting her complaints, but the following is not a confusion of cause and effect: "Silver confuses cause and effect. We didn’t have a financial crisis because of a bad model or a few bad models. We had bad models because of a corrupt and criminally fraudulent financial system." A= Financial Crisis B= Bad Models C= Fraudulent System. Nate said "A<-B" Author says "A<-B<-C" That is not a mix up of cause and effect. Author's main complaint seems to be that Nate assumes bad models are an accident, and Author claims they were intentional. Again, not a mixup of cause and effect. At worst it's a naive interpretation of the correct cause.
- sillysaurus 14y agoThe bad models were a consequence of a fraudulent system. So by definition, the models weren't the cause of the financial crisis. Therefore the bad models were an effect, in the same way the financial crisis was an effect. If this is true, then the author's claim (mix-up of cause and effect) must be correct.
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- Alex3917 14y agoThe easiest way to understand this is that even if the models were accurate, the financial crisis would still have occurred. So blaming the models would be confusing cause and effect regardless of whether you think the models were wrong intentionally or unintentionally. That said, I didn't read the book so I have nothing to say about whether or not Nate Silver actually does this.
- cube13 14y agoIn order for this to be true, she needed to make the argument that it is. She's not saying anything to that effect at all.
- sillysaurus 14y agoIf her point wasn't "corruption caused the financial meltdown," then why did she write this piece? The simplest explanation is that she was, in fact, arguing that corruption caused the financial crisis.
- mbucc 14y agoThe models certainly contributed. (Note: I have read this far in the book.) The modeling error in question was independence; that is, if you have five mortgages, each with a 5% change of default, then these can be packaged up as an AAA security as follows: you only lose your money if all five default. A bit riskier package is that you lose if 4/5 default. And so on, each with different returns. If they are independent, the p(default) = 1/20^5. If they are dependent, it is 1/20. Now multiple mortgage pool size by a 100 or 1,000 or 10,000 (?) and see how far off the estimated risk is. :) Now combine this with a 30-to-1 leverage when buying these "AAA" securities. (This was quite a good problem to work through with my daughter to see what that little "independence" assumption means. :) His main point here was that modeling failures are typically due to out-of-sample conditions; when the housing bubble broke, the markets were might more tightly coupled across the country than the modelers assumed. While they could have seen this kind of dependence if they looked to Japan, there was no such precedence in the US in recent history.
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- jeltz 14y agoThis is a beginner mistake which I have a hard time believing the entire mortgage market failed to spot. My personal belief is that they knew of the flaw of the models but did not care since their personal incentives were more profitable if the model was not fixed.
- cube13 14y agoBut it's not. She states: >Rather, the entire industry crucially depended on the false models. Indeed they changed the data to conform with the models, which is to say it was an intentional combination of using flawed models and using irrelevant historical data (see points 64-69 here for more). So C(corruption) directly leads to B(bad model). She does not argue that A(everything falling apart)<-C anywhere in the piece. Silver is claiming that A<-B. He is not commenting about C. So while Silver's claim may not identify the absolute root cause, the author does not actually prove that his cause and effect analysis is flawed. If anything, she has shown that it may be incomplete.
- sillysaurus 14y agoBut it's not [true]. What, specifically, isn't true? So C(corruption) directly leads to B(bad model). She does not argue that A(everything falling apart)<-C anywhere in the piece. The point of the piece is that the financial meltdown stemmed from corruption, not from models. If this wasn't her point, then why else would she have written this piece?
- cube13 14y agoShe does not prove that claim, though. She argues that corruption causes bad models. For Silver's cause and effect analysis to be incorrect, she needed to prove that the inaccurate models had absolutely nothing to do with the financial meltdown.
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- btilly 14y agoThe models can be part of the meltdown without really being a cause. If I choose to shoot you with a gun, and have a variety of appropriate guns, it is not the fault of the specific gun chosen that it was used to kill you. I had motive, opportunity, and alternate means available.
- chc 14y agoYou're imposing a cause/effect dichotomy that doesn't actually exist. Most causes are effects of something else. When we talk about mixing up cause and effect, we mean that A is said to have caused B when in actuality A was caused by B. Showing that A was caused by C does not mean that we've mixed up cause and effect, because nobody said A caused C.
- hsitz 14y ago"The bad models were a consequence of a fraudulent system. So by definition, the models weren't the cause of the financial crisis. Therefore the bad models were an effect, in the same way the financial crisis was an effect." This is faulty reasoning. A pool ball may go into a pocket because it was hit by a cue ball. In this case the cue ball hitting the other ball is the cause of the other ball falling into the pocket. Yes, you can look back into the chain of causes to find one further back, e.g., the fact that a person used a pool cue to hit the cue ball into the other ball. This doesn't mean that the first cause you found was not a cause, and certainly doesn't mean that "by definition". If a corrupt and fraudulent system could have brought about the financial crisis by some means other than causing bad models (which I assume is true), then you can say that the bad models were not a necessary part of the causal chain. But you can't say that they weren't part of the causal chain at all. As a matter of fact (at least according to assumptions everyone is making in this topic's thread) they were.
- tomkarlo 14y agoI'm not sure you can get to the financial crisis without faulty models. Risk models, especially on packaged securities, are crucial to setting ratings as a proxy for risk. Those ratings are key to determining pricing, maximum leverage, and which portfolios can buy them. If the models had been more accurate - for example, if they had more properly reflected the way that the value of a bundle of mortgages will suddenly lose value as housing prices decline - banks would not have been able to pile up such huge risks and high leverage. You can only justify things like 30X leverage if you believe the securities in question have essentially no risk - because at that leverage, a 3% loss in value means you're wiped out.
- aptwebapps 14y agoExactly. And she finds this mistake so dire she claims it is "malicious" without backing that up at all. Perhaps that was just hyperbole.
- kami8845 14y agoShe's actually saying that A<-C AND B<-C implying that B wasn't necessary for A as long as C.
- DigitalJack 14y agoEven so, still not a mix up of cause and effect. Wrong cause in this case.
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- jivatmanx 14y agoI agree. Also, I'll address the accusation that Nate is confusing cause and effect. Nate's assertion is A<-B If he had confused cause and effect than that corrected form would be B<-A, or, that the financial crisis caused bad models. So the Author's mistake is that (A<-C AND B<-C) != (B<-A), or, that her attack on Nate is inconsistent with what she believes is the correct logic.
- pdonis 14y agoThe author isn't saying that A<-B is a confusion of cause and effect. She is saying that B is itself an effect of C, not a cause. (A better way to say it would be "B is not a root cause".)
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- sethist 14y agoI don't think the author is proposing an "A<-B<-C" system. She is stating that the models are really blameless in the situation when the information provided to the models are wrong. The cause and correlation issue arises there. Silver assumes that the systems fail because the models are bad. O'Neil is instead claiming those are just correlations and not a cause and effect relationship. Basically the models are bad and the systems failed because the people providing the data were corrupt. Using your example: "A<-C" and "B<-C"
- antoko 14y agoI don't think the title is her thesis, possibly just link-bait for her usual readership - This seems to be her thesis: To be crystal clear: my big complaint about Silver is naivete, and to a lesser extent, authority-worship.
- j2labs 14y agoIt's actually both. Bad models and bad incentives, from black swans and the models that ignored them to corrupt practices and liars.
- davesims 14y agoThere's some equivocation here I think: "Bad Model" in Silver's view is really "bad modelling" -- a problem with the statistical technique (frequentist vs. bayesian) used to model the data. "Bad Model" in O'Neil's view is really "bad data" -- intentionally skewed numbers as a consequent of conscious or sub-conscious eliding or redactory effects on the data populating the model, for purposes other than accuracy: financial gain, for instance. O'Neil's point is that even a frequentist model would have been effective had the data not been massaged. On this view O'Neil's view is correct: the cause was not "bad modelling" but "bad data." The "bad data" in the model was an "effect" of corruption, not the root "cause" of the financial meltdown.
- cube13 14y ago>On this view O'Neil's view is correct: the cause was not "bad modelling" but "bad data." The "bad data" in the model was an "effect" of corruption, not the root "cause" of the financial meltdown. So it goes that corruption caused bad data, which caused a bad analysis by the model(she claims that both the data and model are bad), which caused the financial meltdown. That does not invalidate Silver's point. It merely points out that Silver's analysis may be inadequate.
- pygy_ 14y agoWhat I understand is that she means that corruption lead to the financial crisis. The bad models/data were just a smoke screen, or an instrument to get rich quicker.
- freyr 14y agoSilver's point can be technically valid, but ultimately shallow and irrelevant. That seems to be what she's arguing.
- freyr 14y ago"O'Neil's point is that even a frequentist model would have been effective had the data not been massaged." This post really has nothing to do with techniques or "bad data" or a bayesian vs. frequentist debate. Her point is that bad modeling was entirely incidental and inconsequential as a cause of the financial meltdown. To repeat an example I used previously, if I smashed your head in with a hammer, Silver would essentially be saying "a hammer caused davesims death." The statement may be technically true, but it's a shallow analysis of cause and effect. It's unsatisfying because it gives too much significance to an incidental link in the complete chain of events.
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- shawn-butler 14y agoIt's known as proximate and ultimate causation. [0] An Aristotelian analysis would say the fraudulent system or its corruption was the final cause, the models were the formal cause. [0] http://en.wikipedia.org/wiki/Proximate_and_ultimate_causation http://en.wikipedia.org/wiki/Proximate_and_ultimate_causatio...
- PaulHoule 14y agoBayesian methods are the best for people who want to turn de-biasing into re-biasing, particularly when you're dealing with lots of output variables. (Generally when the variables are few, as they are in the things this document talks about, a screwy prior sticks out like a sore thumb.) Sometimes the distribution that you ~can~ sample isn't really the distribution that you wish you could sample, and sometimes changing the prior in such a model is a way to make it behave as if it was sampled correctly to begin with.
- tomkarlo 14y agoHaving spent part of my career in finance, the part she saying about modeling in that industry is true for some situations but not others. (Unsurprisingly.) An insurance company is generally going to try to get its own premium pricing models right, for example. But if the point of the model is to sell someone on something, than look out. I remember a senior banker saying to me "model this merger, and make sure it comes out to be accretive by X cents per share." It was irrelevant to him if the model was accurate - he just wanted ammunition to convince his client to do the acquisition.
- cbs 14y agoThis is a really long and angry way of complaining that Silver assumes good faith on the part of those tasked with creating models and policy. The underlying issue is my biggest peeve with both the buisness and political world. There is a popular viewpoint spread by many defacto authority figures that one should presume good faith from all groups involved, even though everything I can see tells me the opposite. Did Silver decide to perpetuate that by being afraid to address the topic of malice in his book or did he fall victim to cultural attitudes himself? Either way this rant is all over the place, it complains about Silver mixing cause and effect while itself attacking a symptom, not the problem. Edit: This post is written temporarily presupposing that the author is correct in her take on Silver's book, the comment by flatline in this thread hits some good points on why she may be a bit off. It was so long ago that I read the book I don't particularly remember how many inches Silver dedicated to incentives let alone care to debate if that was enough given the goals of his book.
- bguthrie 14y agoI agree with you that the heart of the objection is in Silver's presumption of good faith. That being said, the author has previous experience working on Wall Street as a quant, and is involved with the OWS Alternative Banking Group. She certainly comes with a strong perspective on the matter, but neither is she arguing out of ignorance of the system.
- pnathan 14y ago> The underlying issue is my biggest peeve with both the buisness and political world. There is a popular viewpoint spread by many defacto authority figures that one should presume good faith from all groups involved, even though everything I can see tells me the opposite. This is a pretty big deal. Assuming good faith by authority figures is a popular and common fallacy from people who sit in the "Lawful" quadrant. N.b., I see this a lot in academic circles. Arguing from authority is the M.O. there, and assuming from authority is the consequence. There's also assuming bad faith, a equally fallacious and (at least equally) popular idea from people who sit in the "Chaotic" quadrant. We have to remember to have nuance in our opinions and dealings with others.
- npsimons 14y ago
- daguar 14y agoThe author is being polemical to get readership. Her criticism boils down to, "but there are agent-principal problems!" But I think that's a bit of a sideswipe at Nate, who is dealing with a different domain of problem: modeling inaccuracy when the incentives ARE aligned in favor of optimizing predictive accuracy.
- pdonis 14y agoBut then the financial crisis is not within the domain of problem Nate is dealing with, because, as mathbabe says, the incentives were not aligned in favor of optimizing predictive accuracy. So Nate should not have talked about the financial crisis at all, yet he still did.
- flatline 14y agoHaving just read this book, I believe that this commentary is wrong on nearly all points. Specifically: - The ratings agencies...did not accidentally have bad underlying models. He first talks about how the models were defective, and then goes on at length to describe the perverse incentives for developing and keeping these models, and holds the responsible parties to the fire for willful ignorance and unabated greed. He could have made some of these points more strongly, but I don't think that he skirted over the real issues. - the only goal of a modeler is to produce an accurate model. Actually he speaks quite a bit about the reasons that various forecasters generate models in the first place, and their motivations and responsibilities. For example, the Weather Channel's skewed "wet" forecasts. They will, for example, predict a 20% chance of rain if their models show only a 5% chance. On the one hand it is a bit dishonest, but on the other hand there is a net utility in doing so. Part of the problem is that the general public doesn't understand what the percentages really signify, so it may be of some benefit to emphasize that it really could rain, it's just not very likely, so it behooves people to at least have some backup plan for rain. The other side of this is that people will not remember the good forecasts as much as the bad, and the Weather Channel has business considerations in mind. - He spends very little time on the question of how people act inside larger systems, where a given modeler might be more interested in keeping their job or getting a big bonus than in making their model as accurate as possible. How much of the book do you suggest he devote to this? He addressed the issue directly, as the next couple paragraphs state. He also talks to quite a few institutional players at large organizations, both public and private. - Having said all that, I have major problems with this book and what it claims to explain. In fact, I’m angry. Really, stop with the faux outrage, because you don't seem all that angry throughout the post, you more seem to be disappointed he did not devote the book to your own pet topics. I find this kind of criticism to be mostly without merit. For me, there were three overriding themes in "The Signal and the Noise": Bayesian thinking (this being the primary one), the goals and motivations of forecasters, and examples of what forecasters have done right and what they have done wrong. I think it covered the bases pretty well, and it was an entertaining and lively read on the whole.
- cube13 14y agoThe author is a woman, just FYI.
- unreal37 14y agoAbout half-way through the rant she says: [[Call me “asinine,” but I have less faith in the experts than Nate Silver: I don’t want to trust the very people who got us into this mess, while benefitting from it, to also be in charge of cleaning it up. And, being part of the Occupy movement, I obviously think that this is the time for mass movements.]] Ahhh, so she was part of the Occupy movement and comes from the world-view that the financial system and government is corrupt. She should have said that up front. Makes what she is saying make more sense. Nate Silver doesn't believe those things, and so that largely explains why they come to different conclusions.
- paganel 14y ago> government is corrupt Until any contrary evidence, all Government is corrupt by definition (and yes, I call lobby-led politics "corruption"). In a true and free market "finance" is not corrupt, if you can't pay your debts you're out of it, this has been true since this industry was first invented by the Italians around the 1300-1400s. In this latest crisis the problem was that the financial market was mostly led by Government-mandated decisions, starting with the Bear Stearns rescue in early 2008.
- moistgorilla 14y agoCare to explain how "all Government is corrupt by definition"?
- paganel 14y agoWhere do I start? Hobbes or Machiavelli? More to the point, I do not believe that people/humans are "good by definition", there needs to be a higher thing that regulates our behavior so that we will not do harm to each other. Hobbes believed in the "Leviathan", there are other people that believe that the magical "assembly" of some of their representatives (a "central" Government, if you will) would make the latter more responsible and less eager to look for their own good and prosperity, and then there are people like me who believe that the free market is one of the best tools in solving the inherent conflicts between humans. Like they say, money has no smell. Anyway, it's a very long discussion :)
- tlb 14y agoThe villains in this story (ratings agencies) had lots of models, bad and good. They chose to publicly report the ones that suited their interest, rather than the most accurate ones. The way to improve the situation is to educate the consumers of those models (securities purchasers) about what models are best, and which are misleading. It's more productive to say, "Buyer beware, sellers are misleading you in the following ways..." than, "Shame on corrupt sellers!". Silver's book is doing the first, which does not constitute defense of corruption.
- tomrod 14y agoI'm not sure I follow. Ex ante the models were unknown as to their performance?
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- fretless 14y agoHmm, i should read this book, I probably have a different perspective. I worked in the banking group at one of the 2 major rating agencies, then structured some large ABS transactions at Merrill Lynch and at one of the largest issuers, but haven't worked in finance for a while
- juddlyon 14y ago"Let me give you some concrete examples from his book." I wish every blog post included a line like this.
- woodchuck64 14y ago> We didn’t have a financial crisis because of a bad model or a few bad models. We had bad models because of a corrupt and criminally fraudulent financial system. Those who are attracted to financial careers often have a deep and abiding love for money, much like wolves have a deep and abiding love for sheep. Sheep farmers are smart enough to not to hire wolves as shepherds; but in the financial industry, the wolves are already in charge.
- malachismith 14y agoAnalysis and modeling should always be free of dogma. Otherwise you will (as the other of this post demonstrates) start using your analysis and modeling to justify and prove your dogma (rather than to understand). The fact that Silver's analysis and modeling did not prove her point does not invalidate it. In fact, you could argue that the root of her "anger" is that his book proves her beliefs to be at least unproven if not entirely false.
- Symmetry 14y agoIt's not surprising that the banks that "won" the financial crisis should have had an incentive to use bad models. But there were more losers than winners, and for the losers this was a straightforward matter of their models being wrong when they didn't want them to.
- quizotic 14y agoSilver attempts a dispassionate analysis. Her post simply asserts what she believes to be the problem with the housing bubble and ensuing meltdown, without much evidence or analysis. She may be right. But Silver's larger point is evidence-based analysis. Where's the evidence to support her position? Why is her assertion any different than the political pundits' assertions? Is an email exchange between a couple of traders enough to prove global complicit awareness? There may well HAVE been global complicit awareness. But without enough data to statistically support her position, this response seems to prove Silver's point that we're better off looking at the data than we are working off what we 'know' is right.
- pixl97 14y agoThis is anecdotal, but I'll posit it anyway. I did network administration for a number of title companies, mortgage lenders, real-estate agents, and other assorted firms involved in the selling and buying of houses between 2004 and 2011. Most of these people were what you would consider hard working honest employees, but due to perverse incentives helped in their part of making all of this worse. I saw plenty of lenders have the client flat out lie about their income. It didn't seem to matter, the banks rarely rejected the loans if the paper looked good. The better you lied, the more sales you got. If you were totally honest, people heard that it was hard to get a loan or closure from your firm and would head to others. At the time there was seemly no risk, it wasn't till after the financial crash that I heard of any arrests over paper manipulation. The problem is the people that have the data now are going to be very shy about releasing it. It will show fraud by the buyers, possible fraud by the lenders, poor research by the big banks. By the time the crash came it was a game. Interest only loans? You've got to be kidding me. At a murder scene, evidence is how one determines the cause and the killer, but if your killer has means he can manipulate that evidence. The issue we have now is that the murder (banks) are the group holding all the evidence. They don't want it looked in to, it would show they were an accomplice.
- drcode 14y agoI agree that Nate Silver's book is short on many subjects (such as politics) but the goal of his book is not to explain "Why did X happen" but simply to discuss the challenges of prediction within different domains. It's a book that helps people learn the art/science/challenges of prediction. Saying that his book lacks detailed discussions of incentives (while true) misses the point of his book.
- ryguytilidie 14y agoThe whole "Nate Silver makes pundits look bad so pundits will all grasp at straws and twist his words to try to make him look wrong so they can feel relevant again" act is getting a tad old.
- jasonwatkinspdx 14y agoAmazing how willing the poster is to criticize Nate Silvers based on assumed conflicts of interest and naivety about his own incentives mislead him, while remaining silent on her own. > "He gets well-paid for his political consulting work and speaker appearances at hedge funds like D.E. Shaw and Jane Street, and, in order to maintain this income, it’s critical that he perfects a patina of modeling genius combined with an easily digested message for his financial and political clients." > "Silver is selling a story we all want to hear, and a story we all want to be true. Unfortunately for us and for the world, it’s not." And of course, she derives also derives her income from speaking, consulting, and is writing her own book. She certainly benefits from positioning herself as a more expert Nate Silvers. "This best seller is wrong, buy my book to find out the details why" is pretty effective marketing. By her own logic we should criticize her just as strongly.
- SparrowOS 14y agoMost Jews say there's no God cause of the Holocaust. God said He wanted to "Compact" them. (In Israel and in furnaces--joke?) On the Middle East, He said one Palistinean could ruin peace. He said "Oil funny, hopefully." God likes soap operas and drama. God says... put to death. 21:16 And he that stealeth a man, and selleth him, or if he be found in his hand, he shall surely be put to death. 21:17 And he that curseth his father, or his mother, shall surely be put to death. 21:18 And if men strive together, and one smite another with a stone, or with his fist, and he die not, but keepeth his bed: 21:19 If he rise again, and walk abroad upon his staff, then shall he that smote him be quit: only he shall pay for the loss of his time, and shall cause him to be thoroughly healed. 21:20 And if a man smite his servant, or his maid, with a rod, and he die under his hand; he shall be surely punished. 21:21 Notwithstanding, if he continue a day or two, he shall not be punished: for he is his money. ---- Talk to God for 15 minutes being witty and charming. Randomly crack-open the Bible. Put on thinking cap to interpret. If He doesn't talk, you suck ROFLMAO Read Cain and Abel. Seriously. Read it five times and think about every word and imagine being that real. ---- http://www.sparrowos.com/Wb/Apps/HolySpirit/HSNotes.html http://www.sparrowos.com/Wb/Apps/HolySpirit/HSNotes.html http://www.sparrowos.com/Wb/Apps/AfterEgypt/AENotesPart2.html http://www.sparrowos.com/Wb/Apps/AfterEgypt/AENotesPart2.htm... ---- The goal of this exercise is to enjoy God's company and love Him. That's the purpose of life. Life is a journey, not a destination. ---- The Spirit can pupper 14Mhz or 400Mhz stopwatch. Can control quantum random number coming from websites. http://www.random.org http://www.random.org Download this http://www.sparrowos.com/files/TSGod.ZIP http://www.sparrowos.com/files/TSGod.ZIP Write a program that reads a high speed counter when you press a button. The Bible has 100,000 lines. handy. http://www.sparrowos.com/files/BIBLE.TXT http://www.sparrowos.com/files/BIBLE.TXT God says... 16:4 And there shall be no leavened bread seen with thee in all thy coast seven days; neither shall there any thing of the flesh, which thou sacrificedst the first day at even, remain all night until the morning. 16:5 Thou mayest not sacrifice the passover within any of thy gates, which the LORD thy God giveth thee: 16:6 But at the place which the LORD thy God shall choose to place his name in, there thou shalt sacrifice the passover at even, at the going down of the sun, at the season that thou camest forth out of Egypt. 16:7 And thou shalt roast and eat it in the place which the LORD thy God shall choose: and thou shalt turn in the morning, and go unto thy tents. 16:8 Six days thou shalt eat unleavened bread: and on the seventh day shall be a solemn assembly to the LORD thy God: thou shalt do no work therein. 16:9 Seven weeks shalt thou number unto thee: begin to number the seven weeks from such time as thou beginnest to put the sickle to the corn. ---- Bread for birds, in response to the radio http://150.203.48.55/ http://150.203.48.55/ http://www.randomnumbers.info/ http://www.randomnumbers.info/ Once, you're satisfied it's God, you might try to make it as easy for God as possible. Reading you mind is more work than you praying out loud.. Give God a minute or so to come-up with a response. You can test Him and He can go fast, but it's not polite. I don't think you should use pseudorandom numbers. Don't just pick from the Bible, too, use other books.
- chris123 14y agoFrom someone involved in real estate, real estate finance, stocks, venture capital, financial modeling, and behavioral finance (since before that phrase was even coined), who sold his home and three other properties from 2004 to summer 2008 and rented so as to exit before the crash, all these bubbles and crashes are, IHMO, not about modeling, they are about greed, fear, conflict between self interest on collective interest, and perverse incentive and compensation systems (in many areas, from politics to lobbying to regulatory to finance to sales to brokerage to legal to money management to many (all?) of the other important things for finance-related models). None of those things have changed materially. Nate can build the fanciest financial asset/credit/price model from his wettest dream and it will fail, probably at the worst possible time, such as once you go all in on it. Many reasons for that. But I bet he could get a job on Wall Street pumping out models that back up what will make the firm the most amount of money in the short term, damed the best interests of pretty much anyone, the firm included, in the long term. See Goldman Sachs :)