dingfeng_quek

1. It's possible to connect a keyboard to an iPad/Android tablet. (and larger screens as well) 2. You imply that only a minority of people would be doing "heavy" production work on a computer. The trends seem to be the opposite of that, at least in modern cities (I doubt office workers can avoid keyboards and decent-sized-screens.)

You got it for free - why should you expect more? If there's a demand for accurate, well-supported, and much harder-to-produce news and commentary, which someone is willing to pay for, many journalists would be happier as well. This, however, is a free publication that (simplifying) earns on a per-view basis. Perhaps there already exists another source of information that's accurate, but behind a paywall.

Really depends on your metric of "rate of advancement". If it's going to be about what common people think, then consumer-product and lifestyle innovations would be over-weighted. Viewed by a specialist in any field, that field's progress would be overweighted. From the perspective of productivity increase (or GDP per capita increase), qualitative changes in lifestyle would be underweighted. etc.

Furthermore, even after deciding on a vague sort of metric, it's hard to quantize (choose a measure, in math jargon), advancement to be able to have rates.

Consumer goods are, however, much cheaper now as compared to 50 years ago (at least in urban Asia where I live). It makes a huge difference between spending 10% of my income on daily necessities, as opposed to 50% like my ancestors did.

Arguably, this matters mostly to those below a certain threshold income (difference of 2% and 10% not as big as 10% and 50%), i.e. matters more to the poor than to the rich. I think American citizens tend to be richer than the rest of the world.

However, when working with good type inference (i.e. Haskell)... 1: it's possible to relax on the discipline a little; mental resources are limited (at least for me). 2: typed-based dispatch; refactoring based on static types; etc.

Static types are attractive to me. I haven't tried Typescript for other reasons:

1) I use CoffeeScript for the concise code, which Typescript doesn't have. The trade is a lot of verbosity for static types - verbosity above the static type declarations.

2) I don't know much about Typescript's type inference system, especially how it will develop. Not well documented, no vision. (Clojure's vision is one that I would consider exemplar.)

3) Suppose there are cases where Typescript is more appropriate. I don't know whether it is easy to expose functions to normal Javascript (while retaining types). Typed subsets of a language have often been problematic to expose to untyped parts of a language when more powerful inferences are being used (e.g. Typed Racket doesn't play well with Racket Macros). Especially if you want to pass typed => untyped => typed.

4) There's a cost to learning a new language. There's an overhead to remember an additional language.

5) Chances are, someone else is going to try it. Someone who actually has a good use case. If I wait, maybe they will talk/blog about it, and I can make a more informed decision later.

I haven't been persuaded to try Typescript in a substantial piece of code. The blog posts, they don't really address the issues of concern to me. Not yet.

You're not exactly describing the difference. I would say that:

1. We have statistical evidence from large numbers of SIMILAR people with similar tumors. Economic events tend to be highly dissimilar in terms of context (Great Depression? 1988 Savings and Loans Crisis? 1997 Asian Financial Crisis? 2008 Global Financial Crisis?), and only to be similar in terms of before-and-after on some narrow set of parameters. This makes prediction and counter-factual history for economic stuff really hard.

2. We also understand some of the mechanisms of how tumors work and affect physiology. These are founded upon a large body of knowledge of causation and empirics in medicine, chemistry, and biology. Economics lack a comparably reliable and large body of knowledge because of 1.

Because politicians run the country. Not economists.

I have to agree. The author hasn't dealt with all the unsolved problems with bounded rationality, which quite frequently involves the inability to compute the future (the case where even if perfect information is available). Then, somehow, he "models" the cost as computational complexity, of a particular sort. But that's why we have peer reviews.

EMH is actually a hypothesis (not a theory) that arises from non-arbitrage models. It's not meant to describe the real world, although it's thought-provoking to look at how "efficient" real markets are, so people like to characterize and "test" the EMH in its various forms. How markets fail to be "efficient" is often quite instructive for practical purposes.

For pedagogical purposes, I think it's a really good simplified and ideal illustrative model, until you learn the more axiomatic derivations of no-arbitrage (the arrow-debreau stuff). From your other posts, I gathered that you're not beyond undergrad studies in economics - you'll likely learn about the more complex models when you reach a more advanced and rigorous stage, if you pursue the theoretical path.

If I were you, I wouldn't be too concerned about others arguing about the EMH - without the proper foundations, you won't understand them beyond a superficial level.

Not to mention that it's popular for the less educated to bitch about the EMH, probably because it's an English acronym with commonly used words. I've almost never heard laymen talk about how unrealistic the nash equilibrium is (:

https://twitter.com/dingfengquek/status/239451710278483970 (13119) Removed tweet protection.

It's a pretty interesting game to master - the challenge isn't in hand-eye projectile-estimation/control. While that's important, it seems pretty easy to reach a satisfactory amount (as long as one doesn't need to cross the edge of the screen and wrap-around, which the human brain doesn't seem to handle well).

The parameter to optimize, at least at scores of 8k to 13k, is to quickly evaluate the best upward paths to take.

I've tried 5 games, all which ended above 6k, which ended when I hesitated on the path. Curiously, it isn't the situations where only 1 path is available where I lose. It is the situations when two somewhat equal paths exists, and I hesitate. At areas with white blocks, where the jumping height required to reach the next block is maxed, and the next block is horizontally displaced, there's very little time to think.

Hitting springs are the worst, as it changes the screen very rapidly, making it very hard to assess the situation (3 losses to this). The next worst is a series of whites at max height, which results in a high upwards speed (1 loss to this). Last loss was due to dropping a bag of chips.

https://twitter.com/dingfengquek/status/239445632832643073 (9160)

There's a list of approved food additives for most developed countries.

While the regulation on GMO labels is evident, it's hard to decide whether GMO is good or bad, and whether it is right or wrong to encourage or discourage GMO.

Bacteria in beef is problematic to justify because the bad outcomes tend to be low-probability events, and the events can often be attributed to other causes, so it's hard to pin it down on food safety practices.

Try something more clear-cut, like the history of trans-fat regulation as compared to when the adverse health-effects of trans-fat were identified, and whether trans-fat was allowed as a food additive with compelling evidence for its safety (by appeal to long-term epidemiological data or otherwise). Trans-fat is also clearer because the government has encouraged (with marketing dollars) its consumption over other kinds of fat.

I'm sure there are many better examples than GMO labeling and bacteria in food.

I assume you assert that out of ignorance. Modern pesticides are extremely toxic in small quantities, some with immediate and easily observed effects, others with delayed and long-lasting effects.

Regulatory limits are often based on immediate observable effects. Delayed hard-to-observe problems tend to be ignored. See the toxicity of organophosphates and COPIND, and the history of its regulation (when regulations were enforced; when the upper limit was revised to consider the problems of COPIND). There are research results that suggest some Americans have a sufficiently high dietary intake of pesticides to affect their lives.

Furthermore, for many pesticides, there's no way for the policy makers and public to estimate its toxicity, because research is often suppressed, dissemination of toxicity information is often suppressed, policy change is often suppressed, etc. It's a well-established problem with the political-economy of America.

In many less-developed-countries, MNCs like Monsanto and Bayer have used aggressive and deceptive sales techniques and misrepresentation of product toxicity to persuade farmers to use pesticides far in excess (over 100 times the level of) of regulatory limits in the US. These products do get exported. Search for such news and policy discussions in India and China.

Lastly, pesticides don't "often" break down into chemicals similar, in biological activity, to estrogen. Pesticides can cause quick death, physical deformities in fetuses and young children, autism, epilepsy, mental retardation, cancer, organ failure, rashes, ulcers, can be used in biological warfare, etc. Some pesticides take decades to breakdown; Some pesticides have metabolites that are extremely toxic. Do refer to toxicity and metabolism research and data when evaluating the health risks of pesticide exposure and consumption, and/or consult an expert with little conflict of interest.

PS: Organic farm allows the use of (some classes of) pesticides as well.

However, genetic differences between certain groups of people can be quite significant. Sometimes, they are clustered geographically, like immunity against malaria. Other times, they are clustered based on a shared history and selection pressure, like the Jews. Or math professors.

Afterall, humans came from the same small genetic stock, and races generally reflect adaptation/mutation to particular geographies - not to the very recent economic developments.

Not to mention that diversity and specialization is generally good for trade.

Hi zipdog, when such an article is published, it should (if you're doing real work/research in this area) be interpreted as X is one of hypothesized significant causes of Y. X is often a new finding, or an old hypothesis with new support, or with new relevance. There's little reason to think the author meant it literally, given the extensive literature (just search any journal) on how and why states fail, and it is both sensible and charitable to assume the authors at The Economist are well-educated and do their background research (:

In fact, you'll find that this is a popular style in economics and business articles.

Java is good for enterprise IT consultancies. It requires a lot more detail to attention to implementation most enterprise app features, yet it still works acceptably in the end, maximizing consultancy fees.

No. This is non-fiction in finance. "Dominic Connor is a City headhunter at QF Search with a sideline in teaching C++ to bankers", he's also a well-known and respectable enough online personality.

Such evidence also provides a basis for many explanations (appealing to the financial products being to complex) of the 2008 global financial crisis.

I've once played with the idea of a career in quantitative finance, but subsequently fled for my life. Yet, attesting to the wonders of biodiversity, many kinds of life have evolved to thrive in the harshest of conditions.

ahoyhere and pg's argument isn't clashing - while pg wrote his essay from his personal experience, ahoyhere demands (or at least appeals to) the consideration of a broad set of ideas related to a long history of thought and research.

However, pg's essay is clear that it doesn't aim to be a well-founded research paper. Although ahoyhere is right that pg's essay will never be recognized as a good research paper (by intelligent people, i.e. not those who were conned by the sokhal hoax), the essay is not designed to be one.

pg: I can give examples of great scholarly works where the author is confused, but the domain is highly specific, and probably outside of your interests. For less technical subjects outside of expert-to-expert communication where some spend years to develop new ideas, there's generally less preference for insight over clarity.

ahoyhere: If you're looking for well-researched expositions in this area, I'm sure you already know where to look. Hm... But I think today's social-psych/cognitive research is better than what Aristotle says.

If you restrict writing to only the "sounds" words produce when they are read, good writing should sound like spoken language is still hard to defend. Besides how the brain differently processes words seen from eyes, the varied methods of reading (reading linearly, scanning, searching, etc) gives multiple definitions of "good writing", depending on the context, goal, reader, and many other factors.

If you don't, then many other kind of glyphs and grammars arise. At the extreme, diagrams, mathematical expressions, etc, often lack even a correspondence with spoken language. Similarly, spoken languages have many subtle indicators and markers (often temporal or intonation-based) that isn't easily translatable to the written word.

So am I, but as a style, I find it much better than many conventional writers (excluding research papers, at least the good ones). More important to me, PG's style is consistent - once I get used to it (in the first few paragraphs), all the rest of his essays can be interpreted with the same "filter/transform".

Exactly. I don't think models, math, and simulations in the area of economics are evaluated by their predictive power or their fidelity to the real word.

I'd say that they are generally exploratory models and pedagogical models. That's why the critic by the original poster is off-target: it hardly addresses the commonly used/accepted metric for economic insight.

Unless we compare simulated models with reality via empirical studies? (:

I believe the same issues plague subjects like theoretical physics.

Then again, we do have the preference-utility and utility-maximization core of microeconomic theory, which appears quite well-accepted. Accepted, in spite of it's inability to reconcile with some of the non-rational parts of human behaviour.

Having said that, I'm quite partial to some of the PDE models (i.e. the works of Dr Yang Xiao Kai). And PDE models have at least one corresponding agent-based model simulation.

I think that at some point, a leap of faith based on intuition is taken enmasse. Although this really goes into the philosophy of science...

The paper is a study of a particular mathematical model and simulation.

The suggested association of the mathematical model to the model of markets (with many suppliers) where the buyer has a "slow reaction time" results in a price that would, in some sense, be analogous to the price generated by cartels.

The implication is likely that such a market doesn't reach the perfectly competitive price, which is what a simpler model that doesn't consider the buyer's reaction time would predict.

Neither the article nor the paper claims that this emergent phenomenon occurs (can occur) in all, or even the majority of, markets.

Quote: "Under certain market conditions, cartels arise naturally without collusion. This raises important questions over how the behavior should be controlled"

Neither the article nor the paper claims that cartels always "emerge" as "a product of the system". No systems were mentioned, and no definition of product was given.

Neither the article nor the paper claims that cartels do not emerge "as a product of immorality or deceit".

It seems plausible that people might not enjoy a misrepresentation of the authors, who did put in effort (authoring such a paper is never done in a night).

Cartel-like (monopoly/oligopoly) pricing leads to a non-optimal outcome (the loss is usually called the deadweight loss). The price is set higher than the socially optimal price - some consumers who would have benefited overall from the good (benefit from good > production cost of good) would not buy and consume the good because the price is higher than the production cost (price of good > benefit from good).

If your curiosity is strong enough, you can find a more detailed outline of the concept in an introductory economic text.

If this is an argument that, when there are economic profits to be made in a market: 1. The "size" of the firms will increase to compensate : Do take note of diseconomies of scale beyond a certain size. 2. New firms will enter to compete in the market : Depends on the barriers to entry.

The fast ones become rich. They perform trades equivalent to front-running and/or scalping. The enterprising fast becomes a middleman to the slow.

The issue with "cartel-like" price is that it is not the perfectly competitive price, and the perfectly competitive price is the most efficient price - the perfectly competitive price is, in the absence of externalities, the one that brings about the most benefit (by equally aggregated utility) to society as a whole.

The significance is because of the loss of efficiency, not because of the name/label given, or how the price is determined.

LOL is many more times more complex than CS. If you are weird, try running game-theory and stochastic simulation models. Try to optimize things like item builds, team-movement/formation, engagement sequence, allocation of champions to lanes at various times, allocation of gold/farm to champions. And then to apply it.