cchooper

In one case we have members of the public who have passed a driving test. In the other, we have the foremost experts in the field, using the latest theories of risk, working with millions of dollars of modelling and statistical equipment, with their jobs on the line. For what good reason would a single one of them look at the reserve rate and say "Although the government doesn't claim that this is a safe rate for banks to operate at, but instead sets it completely arbitrarily, and admits to the fact that it's totally arbitrary, and has not changed this rate in several decades because it is an obsolete tool of monetary policy, I am nevertheless going to take it to 'suggest' a safe level of reserves, totally ignore all of my models and education, and just pick that number on a completely irrational basis."

I suspect that the system is self-destructing right now. The more degrees that universities award, the less it will matter that it came from a university. This will bring about the end of most university education, and hence most universities (because they can't all be doing worthwhile research).

My point was that you analogy doesn't apply. Pointing to ice on the roads is completely missing the point: that the analogy doesn't hold in the first place.

>I do not think you have refuted my claim that regulation leads to people suspending critical judgement about risks.

I did not say this! I said that specifying a reserve requirement does not reduce bank reserves. Please keep this argument to reserve requirements, not general regulation.

>If you don't buy my argument then you probably believe that people are so stupid that without regulation banks would hold $0 in reserves.

The UK does not have reserve requirements and they don't have zero reserves. But they did not raise their reserves to safe levels either, refuting your original point.

Incidentally, it's you that's arguing that regulation encourages banks to hold lower reserves than they would without reserve requirements. You are constantly conflating reserve requirements and general regulation, moving an argument about one to a conclusion about the other.

You then go on to talk about TARP again, illustrating my point.

This was your original point. Let's stay on track.

Your claim that regulators decide how big Citibank's reserves should be is false. They set a minimum, not a maximum.

You then tried to draw an analogy between speeding and regulation, one that, as I have explained, is totally inappropriate.

You then claimed that "most people take the fact that a firm is regulated to mean that it's totally safe", which is a massive exaggeration. If that were true, bank bonds would be considered as safe as government bonds and bank runs would never happen. All other regulated industries would be exactly the same. Also, you are confusing reserve requirements with broader regulation as a whole.

You then claim that banks raising their reserves would be "competing against the government for their definition of soundness", despite the fact that no government has ever claimed any 'definition of soundness'. This appears to be something that you have invented.

You then give an argument as to why other forms of regulation encourage banks to hold lower reserves. This contradicts your original point, which was that if reserve requirements were abolished then the market would force banks to raise reserves. What you have demonstrated is that the market, bail-outs and broader regulation would actually force reserves to even lower levels in the absence of reserve requirements. You have changed your argument from one about reserve requirements to one about broader regulation, and bail-outs such as TARP.

If this were true (and it certainly is not!) then the market really would be just as incompetent as its critics say it is.

But that's obviously not what happened. Physicists were always capable of making exact calculations and predictions from Lagrangian mechanics. SICM contains no new theories, theorems or proofs, just a more explicit way of representing old ones. Nothing new was discovered and no old notions were clarified. Instead, they just found a better way of teaching mechanics, one that didn't rely on the implicit knowledge that masters of the subject already possessed. They were only capable of doing this because Lagrangian and Hamiltonian mechanics were well-defined in the first place. If they hadn't been then they would have had to advance a new theory of mechanics to replace them, rather than just re-presenting an old one.

There's a difference between using a convenient notation and lacking rigour. If you are always capable of discerning the true formal equations behind a convenient notation then everything is OK. If you can't, or people can't agree on what the formal meaning should be, then there is indeed a problem. The fact that the authors could derive a computational notation that no physicist would disagree with is proof that a lack of rigour never existed in the first place.

> [A]ny realistic mathematical proof will leave out a great many steps, which are considered to be the "required background knowledge"

Computer science papers are different how? Computer science != programs!

> [T]he inference rules are not always specified accurately, or are not believable if they are. This is why you will sometimes read a mathematical proof and say "I understand the reasoning, but I just don't buy it"

I think this guy just isn't too hot at mathematics. Omitting a trivial step (or domain specific knowledge) is not a lack of rigour, but a courtesy to the reader. The details can always be filled in cleanly. If you ever see a modern mathematical proof that is accepted by all mathematicians, but you don't "buy it", then I can assure you that it's you that's at fault, not the proof.

Oh, and computer science papers never leave out trivial steps or assume domain knowledge? Not the papers I've read. Once again, CS != programming!

> This is reminiscent of Whitehead and Russell's Principia Mathematica where hundreds of pages pass until the authors can prove that 1 + 1 = 2.

Surely Principia is a reductio ad absurdum of the argument that everyone should always spell out all the steps!

b) The point is that the concept of property rights is mostly vacuous unless you specify which system of property rights you are speaking of. cia_plant was pointing out that what one person considers oppression, another might consider fair use of property. Therefore any state can be considered libertarian unless you specify restrictions on what counts as a valid system of property.

b) If the enforcement of property rights justifies coercion, then almost any kind of coercion can be justified if the prevailing property system is chosen correctly. For example, if a totalitarian state were to have a system where everything belongs to the state, including the citizens, then it would have the right to do whatever it wants with its property, and any assertion of personal freedoms would be theft.

a) Property rights are a form of coercion.

b) 'Property rights' is a wide umbrella under which almost any form of coercion could be justified.

A standard technique goes like this: read just the first and last paragraphs of each chapter. Then read the first sentence of each paragraph of the first chapter. Then read the actual chapter as fast as you can (don't focus on details or bits you don't understand). Finally, go through it one last time and make notes. Now go on to the next chapter.

However, if you truly want to memorise an astounding number of facts (e.g. a list of a thousand pieces of information, or all the common words in a foreign language), then you need to use sophisticated mnemonic techniques. It takes a little practice, but you get surprising results very quickly. For example, after about 15 minutes practising the techniques in this book, http://www.amazon.co.uk/Use-Your-Memory-Understand-Improve/d..., I was able to memorise the order of a shuffled deck of cards with about 95% accuracy. It wouldn't have taken more than a few days to learn to memorise several decks at once with 100% accuracy.

However, if people moved their money from current accounts to savings accounts (which you would expect if people actually wanted to save for the future) then potential lending would increase because banks lend savings cash more readily that current account cash. But people are probably not saving for the future. They are saving because they have less access to credit and/or are worried about losing their job. If anything, that encourages people to liquidate savings accounts rather than increase them, so the potential money banks can lend could be decreasing.

And the email recall feature of Outlook/Exchange is also quite good. It even tells you how many emails couldn't be recalled (because people have already read them). It will only work within an organisation though, as it is a feature of the Exchange server.

Firstly, the author can't decide whether relations are an abstraction or not. At points he seems to be preferring graphs to relations because graphs are abstract and relations aren't ("the anti-abstraction argument rears its head in the RDBMS vs graph database debate"). At other points, he admits that relations are also abstractions, but argues that graphs are more suited to the data we actually use. Seeing as relations are just as abstract as graphs, we can ignore all the stuff about abstractions being a good idea. Yes, we know; that's why we use relations.

Secondly, despite this being a post about abstraction, he doesn't distinguish between a physical implementation and a logical representation. Yes, a SQL database can store graphs inefficiently, but that's a problem of how the relations are physically stored, not a problem with relations themselves. You can store a self-joining relation just like a graph, and optimise it for graph-like queries. That's the beauty of abstraction!

Thirdly, he claims that graphs are better when the structure of your system will change frequently. There's no argument for this, it's just a non sequitur he drops in at the end. It's true that most RDBMSs are very static in nature, but that's because they have been designed reap the rewards of static typing. They don't have the be that way, and I can't see that graphs give you any benefit here.

Fourtly, he claims that 'you want an abstraction that reflects how you really think about the data and not some jury-rigged representational model continuously intruding itself into your thought process.' True, but graphs are just as much a jury-rigged representational model as relations. Almost every system needs to store data about users, but users are not graphs (nor are they relations. Don't confuse your data model with reality!)

A database is something we build abstractions on top of. These could be graph abstractions, or object-oriented abstractions (ORMs) or whatever. A database does not dictate the abstractions you use, it simply provides an abstraction for data storage. Such an abstraction should be chosen because it can store all the different kinds of data you need, and provide constraints that prevent the data from becoming incoherent. These are the important considerations, and they aren't even mentioned.

The most interesting feature of this language is that all functions commute over lists. For example:

  [2,3,5,7,9,11].at(3)

  [2,3,5,7,9,11].at([1,3,4])

  [2,3,5,7,9,11].at([1,[2,3],4])