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Hillary Clinton Goes Back to the Dunning School

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Library of Congress

Last night Hillary Clinton was asked what president inspired her the most. She offered up Abraham Lincoln, gave a boilerplate reason why, and then said this:

You know, he was willing to reconcile and forgive.  And I don't know what our country might have been like had he not been murdered, but I bet that it might have been a little less rancorous, a little more forgiving and tolerant, that might possibly have brought people back together more quickly.

But instead, you know, we had Reconstruction, we had the re-instigation of segregation and Jim Crow.  We had people in the South feeling totally discouraged and defiant.  So, I really do believe he could have very well put us on a different path.

Clinton, whether she knows it or not, is retelling a racist—though popular—version of American history which held sway in this country until relatively recently.  Sometimes going under the handle of “The Dunning School,” and other times going under the “Lost Cause” label, the basic idea is thatReconstruction was a mistake brought about by vengeful Northern radicals. The result was a savage and corrupt government which in turn left former Confederates, as Clinton puts, it “discouraged and defiant.”

A sample of the genre is offered here by historian Ulrich Phillips:

Lincoln in his plan of reconstruction had shown unexpected magnanimity; the Republican party, discarding that obnoxious name, had officially styled itself merely Unionist; and the Northern Democrats, although outvoted, were still a friendly force to be reckoned upon … With Johnson then on Lincoln's path “back to normalcy”, Southern hearts were lightened only to sink again when radicals in Congress, calling themselves Republicans once more, overslaughed the Presidential programme and set events in train which seemed to make "the Africanization of the South" inescapable. To most of the whites, doubtless, the prospect showed no gleam of hope.

Notably absent from it is the fact that Lincoln was killed by a white supremacist, that Johnson was a white supremacist who tried to curtail virtually all rights black people enjoyed, that the “hope” of white Southerners lay in the pillage of black labor, that this was accomplished through a century-long campaign of domestic terrorism, and that for most of that history the federal government looked the other way, while state and local governments were complicit.

Yet until relatively recently, this self-serving version of history was dominant. It is almost certainly the version fed to Hillary Clinton during her school years, and possibly even as a college student. Hillary Clinton is no longer a college student. And the fact that a presidential candidate would imply that Jim Crow and Reconstruction were equal, that the era of lynching and white supremacist violence would have been prevented had that same violence not killed Lincoln, and that the violence was simply the result of rancor, the absence of a forgiving spirit, and an understandably “discouraged” South is chilling.

I have spent the past two years somewhat concerned about the effects of national amnesia, largely because I believe that a problem can not be effectively treated without being effectively diagnosed. I don’t know how you diagnose the problem of racism in America without understanding the actual history. In the Democratic Party, there is, on the one hand, a candidate who seems comfortable doling out the kind of myths that undergirded racist violence. And on the other is a candidate who seems uncomfortable asking whether the history of racist violence, in and of itself, is worthy of confrontation.

These are options for a party of amnesiacs, for people whose politics are premised on forgetting. This is not a brief for staying home, because such a thing doesn’t actually exist. In the American system of government, refusing to vote for the less-than-ideal is a vote for something much worse. Even when you don’t choose, you choose. But you can choose with your skepticism fully intact. You can choose in full awareness of the insufficiency of your options, without elevating those who would have us forget into prophets. You can choose and still push, demanding more. It really isn’t too much to say, if you’re going to govern a country, you should know its history.

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grayclhn
1770 days ago
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Iowa State
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satadru
1770 days ago
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People have been bitching that Coates is anti-Sanders and pro-Hillary... But he's not pulling his punches against anybody.
New York, NY

Baking Soda and Vinegar

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Sure, it may not meet science fair standards, but I want credit for getting my baking soda and vinegar mountain added to the Decade Volcanoes list.
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grayclhn
1825 days ago
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Iowa State
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minderella
1823 days ago
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Learning is fun!

Billion-Story Building

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popular shared this story from What If?.

Billion-Story Building

My daughter—age 4.5—maintains she wants a billion-story building. It turns out not only is that hard to help her appreciate this size, I am not at all able to explain all of the other difficulties you'd have to overcome.

Keira, via Steve Brodovicz, Media, PA

Keira,

If you make a building too big, the top part is heavy and it squishes the bottom part.

Have you ever tried to make a tower of peanut butter? It's easy to make a little tiny one, like a blobby castle on a cracker. It will be strong enough to stay standing. But if you try to build a really big castle, the whole thing smushes flat like a pancake.

The same thing happens with buildings. The buildings we make are strong, but we couldn't make one that went all the way up to space, or the top part would squish the bottom part.

We can make buildings pretty tall. The tallest buildings are almost 1 kilometer tall, and we could probably make buildings 2 or even 3 kilometers tall if we wanted, and they would still be able to stand up under their own weight. Higher than that might be tricky.

But there would be other problems with a tall building besides weight.

One issue would be wind. The wind up high is very strong, and buildings have to be very strong to stand up against the wind.

Another big problem would be, surprisingly, elevators. Tall buildings need elevators, since no one wants to climb hundreds of flights of stairs. If your building has lots of floors, you need lots of different elevators, since there would be so many people trying to come and go the same time. If you make a building too tall, the whole thing gets taken up by elevators and there's no space for regular rooms.

Maybe you can think of a way to get people to their floors without having too many elevators. Maybe you could make a giant elevator that takes up 10 floors. Or you could make fast elevators that work like roller coasters. Or you could fly people up to their rooms with hot air balloons. Or you could launch them with catapults.

Elevators and wind are big problems, but the biggest problem would be money.

To make a building really tall, someone has to spend a lot of money, and no one wants a really tall building enough to pay for it. A building many miles tall would cost billions of dollars. A billion dollars is a lot of money! If you had a billion dollars, you could rent a giant spaceship, save all the world's endangered lemurs, give a dollar to everyone in the US, and still have some left over. Most people don't think giant towers a few miles tall are important enough to spend a lot of money on.

If you got really rich, so you could pay for a tower to space yourself, and solved all those engineering problems, you'd still have problems making a tower a billion stories tall. A billion stories is just too many.

A big skyscraper might have about 100 floors, which means it's as tall as 100 little houses.

If you stacked 100 skyscrapers on each other to make a mega-skyscraper, it would reach halfway to space:

This skyscraper would still only have 10,000 floors, which is way less than your billion floors! Each of those 100 skyscrapers would have 100 floors, so the whole mega-skyscraper would have 100 times 100 is 10,000 floors.

But you said you wanted a skyscraper with 1,000,000,000 floors. Let's stack 100 mega-skyscrapers to make a mega-mega-skyscraper:

The mega-mega-skyscraper would stick out so far from the Earth that spaceships would crash into it. If the space station were heading toward the tower, they could use its rockets to steer away from it.[1]They'd probably get pretty grumpy after having to dodge your tower repeatedly, so you might want to launch fuel and snacks out the window with a rail gun as they go by. The bad news is that space is full of broken spaceships and satellites and pieces of junk, all flying around at random. If you build a mega-mega-skyscraper, spaceship parts will eventually smash into it.

Anyway, a mega-mega-skyscraper is only 100 times 10,000 = 1,000,000 floors. That's still a lot smaller than the 1,000,000,000 that you want!

Let's make a new skyscraper by stacking up 100 mega-mega-skyscrapers, to make a mega-mega-MEGA-skyscraper:

The mega-mega-MEGA-skyscraper would be so tall that the top would just barely brush against the Moon.

But it would only be 100,000,000 floors! To get to 1,000,000,000 floors, we have to stack 10 mega-mega-MEGA-skyscrapers on top of each other, to make one Keira-skyscraper:

The Keira-skyscraper would be pretty close to impossible to build. You would have to keep it from crashing into the Moon, being pulled apart by the Earth's gravity, or falling over and smashing into the planet like the giant meteor that killed the dinosaurs.

But some engineers have an idea sort of like your tower—it's called a space elevator. It's not quite as tall as yours (the space elevator would only reach partway to the the Moon), but it's close!

Some people think we can build a space elevator, but other people think it's a crazy idea. We can't build one yet because there are some problems we don't know how to solve, like how to make the tower strong enough and how to send power up it to run the elevators. If you really want to build a gigantic tower, you can find out more about some of the problems they're working on, and eventually become one of the people coming up with ideas to solve them. Maybe, someday, you could build a giant tower to space.

I'm pretty sure it won't be made of peanut butter, though.

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grayclhn
2405 days ago
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Oh, this one's great.
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The problems of HFT, Joe Stiglitz edition

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Never mind Michael Lewis. The most interesting and provocative thing to be written of late about financial innovation in general, and high-frequency trading in particular, comes from Joe Stiglitz. The Nobel prize-winning economist delivered a wonderful and fascinating speech at the Atlanta Fed’s 2014 Financial Markets Conference today; here’s a shorter version of what Stiglitz is saying.

Markets can be — and usually are — too active, and too volatile.

This is an idea which goes back to Keynes, if not earlier. Stiglitz says that in the specific area of international capital flows, “there is now a broad consensus that unfettered markets are welfare decreasing” — and certainly you won’t get much argument on that front from, say, Iceland, or Malaysia, or even Spain. As Stiglitz explains:

When countries do not impose capital controls and allow exchange rates to vary freely, this can give rise to high levels of exchange rate volatility. The consequence can be high levels of economic volatility, imposing great costs on workers and firms throughout the economy. Even if they can lay off some of the risk, there is a cost to doing so. The very existence of this volatility affects the structure of the economy and overall economic performance.

The question is: does the same logic, that traders seeking profit can ultimately cause more harm than good, apply equally to high-frequency trading, and other domestic markets? Stiglitz says yes: there’s every reason to believe that it does.

HFT is a negative-sum game.

In the algobot vs algobot world of HFT, the game is to capture profits which would otherwise have gone to someone else. Michael Lewis’s complaint is that if there weren’t any algobots at all, then those profits would have gone to real-money investors, rather than high-frequency traders, and that the algorithms are taking advantage of unfair levels of market access to rip off the rest of the participants in the stock market. But even if you’re agnostic about whether trade profits go to investors or robots, there are undeniably real-world costs to HFT — costs like drilling through Pennsylvania mountains. As a result, the net effect of the algorithms is negative: they reduce profits, for everybody, rather than increasing them.

In theory, HFT could bring with it societal benefits which more than offset all the costs involved. In practice, however, that seems unlikely. To see why, we’ll have to look at the two areas where such benefits might be found.

HFT does not improve price discovery.

Price discovery is the idea that markets create value by putting a price on certain assets. When a company’s securities rise in price, that company finds it easier to raise funds at cheaper rates. That way, capital flows to the places where it can be put to best use. Without the price-discovery mechanism of markets, society would waste more money than it does.

But is faster price discovery better than slower price discovery? Let’s say good news comes out about a company, and its share price moves as a result — does it matter how fast it moves? Is any particular purpose served to seeing the price move within a fraction of a millisecond, rather than over the course of, say, half a minute? It’s hard to think of a societal benefit to faster price discovery which is remotely commensurate with the costs involved in delivering those faster price moves.

What’s more, faster price discovery is generally associated with higher volatility, and higher volatility is in general a bad thing, from the point of view of the total benefit that an economy gets from markets.

HFT sends the rewards of price discovery to the wrong people.

Markets reward people who find out information about the real economy. Armed with that information, they can buy certain securities, sell other securities, and make money. But if robots are front-running the people with the information, says Stiglitz, then the robots “can be thought of as stealing the information rents that otherwise would have gone to those who had invested in information” — with the result that “the market will become less informative”. Prices do a very good job of reflect ignorant flows, but will do a relatively bad job of reflecting underlying fundamentals.

HFT reduces the incentive to find important information.

The less money that you can make by trading the markets, the less incentive you have to obtain the kind of information which would make you money and increase the stock of knowledge about the world. Right now, the stock market has never been better at reacting to information about short-term orders and flows. There’s a good example in Michael Lewis’s book: the president of a big hedge fund uses his online brokerage account to put in an order to buy a small ETF — and immediately the price on the Bloomberg terminal jumps, before he even hits “execute”. The price of stocks is ultra-sensitive to information about orders and flows. But that doesn’t mean the price of stocks does a great job of reflecting everything the world knows, or could theoretically find out, about any given company. Indeed, if investors think they’re just going to end up getting front-run by robots, they’re going to be less likely to do the hard and thankless work of finding out that information. As Stiglitz puts it: “HFT discourages the acquisition of information which would make the market more informative in a relevant sense.”

HFT increases the amount of information in the markets, but decreases the amount of useful information in the markets.

If markets produce a transparent view of all the bids and offers on a certain security at a certain time, that’s valuable information — both for investors and for the economy as a whole. But with the advent of HFT, they don’t. Instead, much of the activity in the stock market happens in dark pools, or never reaches any exchange at all. Today, the markets are overwhelmed with quote-stuffing. Orders are mostly fake, designed to trick rival robots, rather than being real attempts to buy or sell investments. The work involved in trying to understand what is really going on, behind all the noise, “is socially wasteful”, says Stiglitz — and results in a harmful “loss of confidence in markets”.

HFT does not improve the important type of liquidity.

If you’re a small retail investor, you have access to more stock market liquidity than ever. Whatever stock you want to buy or sell, you can do so immediately, at the best market price. But that’s not the kind of liquidity which is most valuable, societally speaking. That kind of liquidity is what you see when market makers step in with relatively patient balance sheets, willing to take a position off somebody else’s book and wait until they can find a counterparty to whom they can willingly offset it. Those market makers may or may not have been important in the past, but they’re certainly few and far between today.

HFT also reduces natural liquidity.

Let’s say I do a lot of homework on a stock, and I determine that it’s a good buy at $35 per share. So I put in a large order at $35 per share. If the stock ever drops to that price, I’ll be willing to buy there. I’m providing natural liquidity to the market at the $35 level. In the age of HFT, however, it’s silly to just post a big order and keep it there, since it’s likely that your entire order will be filled — within a blink of an eye, much faster than you can react — if and only if some information comes out which would be likely to change your fair-value calculation. As a result, you only place your order for a tiny fraction of a second yourself. And in turn, the market becomes less liquid.

It’s important to distinguish between socially useful markets and socially useless ones.

In general, just because somebody is winning and somebody else is losing, doesn’t mean that society as a whole is benefiting in any way. Stiglitz demonstrates this by talking about an umbrella:

If there is one umbrella, and there is a 50/50 chance of rain, if neither of us has any information, the price will reflect that risk. One of us will get the umbrella. If it rains, that person will be the winner. If it does not, the other person will be the winner. Ex ante, each has the same expected utility. If, now, one person finds out whether it’s going to rain, then he is always the winner: he gets the umbrella if and only if it rains. If the other person does not fully understand what is going on, he is always the loser. There is a large redistributive effect associated with the information (in particular, with the information asymmetry), but no real social benefit. And if it cost anything to gather the information, then there is a net social cost.

HFT is socially useless; indeed, most of finance does more harm than good.

As finance has taken over a greater and greater share of the economy, growth rates have slowed, volatility has risen, we’ve had a massive global financial crisis, and far too much talented human capital has found itself sucked into the financial sector rather than the real economy. Insofar as people are making massive amounts of money through short-term trading, or avoiding losses attributable to short-term volatility, those people are not making money by creating long-term value. And, says Stiglitz, “successful growth has to be based on long term investments”.

So let’s do something about it.

HFT shouldn’t be banned, but it should be discouraged. The tax system can help: a small tax on transactions, or on orders, would reduce HFT sharply. “A plausible case can be made for tapping the brakes,” concludes Stiglitz. “Less active markets can not only be safer markets, they can better serve the societal functions that they are intended to serve.”

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grayclhn
2420 days ago
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Now I need to watch a video of the talk. (Or, heavens forbid, read the paper)
Iowa State
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Advice for new Assistant Professors

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It’s a bit early for me to be giving advice (I’m only on the cusp of non-Assistant status), but I found myself asked for advice the other night by a table full of newly minted PhDs on to their first academic jobs. I also give advice, unasked, to my graduating students.

So, early or not, here’s what I passed on.

  1. Learn to say no to new projects. Opportunities will start crossing your desk faster than you expect. It’s tempting to take the first ones, even though they’re likely the worst. There’s a big opportunity cost here: every project you take on now crowds out a potentially better one in a year or two.
  2. Have a higher bar for projects with big exit costs. It’s one thing to start a historical data collection project or a new theoretical model. You can always stick it in a file drawer if it goes poorly. But if you commit to a field experiment or a project with an eminent person, you are stuck with it to the bitter end. Make sure they are worth it.
  3. Book chapters and reviews are a waste of time. David Romer told us this in my first macroeconomics class, and I have come to agree. Few people read these, especially when they are buried in a $200 book no library buys. Unless you’re invited to do a Handbook chapter or an especially high profile book, it’s almost always better to put your article in a field journal. If it doesn’t merit publication in a decent field journal, probably it’s crowding out something more important to you and the world.
  4. Get your dissertation papers or book out. I see so many people too busy starting new projects to finish the old ones. This is the kiss of tenure death. Send menuscipts out soon after the job market, and make revisions your first priority when they come back.
  5. Seek out mentorship. Ask your dissertation committee and colleagues in your new department to read your abstracts and introduction, and strategize about framing, titles, and generally how to sell your work to a general audience. This is an art that takes years to learn, and personal advice can make a big difference in where you publish your early work.

A word of caution: almost all professional advice is either “here’s the mistakes I made” or “how to be more like me” in disguise. In this instance, it’s more of the former than latter.

For someone with real experience, you should read Greg Mankiw’s advice. I agree with all, except for “do not start a blog”, as “that will only establish your lack of seriousness as a scholar”. This may have been good advice in 2007 (when I defied the advice to start this website). Maybe it is good advice still and I don’t realize it yet. But here’s my estimate of the impacts so far:

  • Blogging has made me a better writer
  • It has meant I and my papers are much better known and cited by colleagues than otherwise
  • Opportunities cross my desk more often than otherwise
  • And, maybe most of all, I hold this blog almost directly responsible for several million dollars in research and program funding so far (paying for a lot of serious scholarly stuff). This number is exaggerated by the fact that I typically need to raise large sums for interventions as well as the research, but the basic point holds–for me blogging has (unexpectedly) paid back a hundredfold in scholarly work.

Yes there are costs and risks, but I think social media is too important for young academics to ignore. Accordingly:

  1. If you want to tweet or blog under your research name, be serious. Let your research interests influence your blogging. Become a professional resource for people in your subfield. Be constructive and thoughtful not critical, and never use social media to attack colleagues. This will be a public good that pays back privately.

Colleagues: please add your advice below.

The post Advice for new Assistant Professors appeared first on Chris Blattman.

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grayclhn
2421 days ago
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Seems like decent advice. Read to the end, though; the research benefit he attributes to his blog is surprising. If I think of anything to add, I'll put it on my blog. (Which, unfortunately, has not helped me get millions of dollars of grant money.)
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ACA Insurance Coverage Cost Update from CBO

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Estimated insurance coverage costs revised downward.

From the CBO, Updated Estimates of the Effects of the Insurance Coverage Provisions of the Affordable Care Act, April 2014:

cbo_aca_newest_apr14

Figure 3 from CBO, Updated Estimates of the Effects of the Insurance Coverage Provisions of the Affordable Care Act, April 2014.

Relative to their previous projections, CBO and JCT now estimate that the ACA’s coverage provisions will result in lower net costs to the federal government: The agencies now project a net cost of $36 billion for 2014, $5 billion less than the previous projection for the year; and
$1,383 billion for the 2015–2024 period, $104 billion less than the previous projection.

The estimated net costs for 2014 stem almost entirely from spending for subsidies that are to be provided through insurance exchanges (often called marketplaces) and from an increase in spending for Medicaid…

Those estimates address only the insurance coverage provisions of the ACA, which do not generate all of the act’s budgetary effects. Many other provisions, on net, are expected to reduce budget deficits. Considering all of the provisions—including the coverage provisions—CBO and JCT estimated in July 2012 (their most recent comprehensive estimate) that the ACA’s overall effect would be to reduce federal deficits.

Note that the overall budgetary effect of the ACA is to reduce federal deficits. As indicated in CBO’s 2012 estimate, repeal of the ACA would have resulted in a ten year increase in budget deficits of over $100 billion.

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grayclhn
2421 days ago
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Iowa State
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