Introducing the Ddulites

I've got a new coinage I'll be referring to quite a bit in some upcoming posts so I thought I'd give it a link of its own rather than bringing it out in the middle of a longer post. (since the longer the post, the greater the chance of my saying something I'd just as well forget. This way I can always link back to this nice, short, neutral post.)


Ddulite (from Luddite):

A preference for higher tech solutions even in cases where lower tech alternatives have greater and more appropriate functionality; a person of ddulite tendencies.

Though Ddulites are the opposite of Luddites with respect to attitudes toward technology, they occupy more or less the same point with respect to functionality.

Is there an economist is the house? Casey Mulligan edition

After Christmas dinner, I did some web surfing and came across the following from Noah Smith:

Two posts back, I explained why the "Great Vacation" idea doesn't pass the smell test. If U.S. unemployment had been caused by a negative shock to labor supply, we should have expected to see an increase in real wages.

Casey Mulligan, one of the leading proponents of the Great Vacation story, responded on his blog:

A number of bloggers have recently discovered real wages as a labor market indicator. They are at least 3 years late to the party.

Three years ago I blogged about the effect of labor supply on real wages;

I noted how real wages had risen since 2007, and predicted that they would begin to decline in 2010.

I have continued to update this work, eg here, and here. The fact is that the real wage time series fits my recession narrative very well.*

Smith then pulls up a graph of real wages and uses it to argue that the data does not, in fact, fit Mulligan's narrative. It's definitely something you should check out, but right now there's something else I'd like you to take a look at. If you follow the link where Mulligan talks about blogging about the effect of labor supply on real wages, you get a column discussing the relationship between labor supply and productivity. This seems to be the relevant passage:

The second type of explanation is reduced labor supply.

Suppose, just for the moment, that people were less willing to work, with no change in the demand for their services. This means that employees would have to be more productive because they have to get by with fewer workers.

Of course, people have not suddenly become lazy, but the experiment gives similar results to the actual situation in which some employees face financial incentives that encourage them not to work and some employers face financial incentives not to create jobs.

Professor Douglas gave us a formula for determining how much output per work hour would increase as a result of a reduction in the aggregate supply of hours: For every percentage point that the labor supply declines, productivity would rise by 0.3 percentage points.

As mentioned earlier, in late 2008, labor hours were 4.7 percent below where trends from previous years would predict the number to be. According to Professor Douglas’s theory, this means productivity should rise 1.4 percent above its previous trend by the fourth quarter.

So let’s take a look at the numbers. Unlike in the severe recessions of the 1930s and early 1980s, productivity has been rising. Through the third quarter of 2008, productivity had risen six consecutive quarters, with an increase of 1.9 percent over the past three, or 0.7 percent above the trend for the previous 12 quarters.

Because productivity has been rising — almost as much as the Douglas formula predicts — the decreased employment is explained more by reductions in the supply of labor (the willingness of people to work) and less by the demand for labor (the number of workers that employers need to hire).

This way outside my field, so I could easily be missing the obvious here, but this post doesn't seem to support the claim that Mulligan was blogging on this question three years ago. That's not to say Mulligan's argument isn't valid or that it doesn't somehow imply his point about wages but if you're going to say "Three years ago I blogged about the effect of labor supply on real wages," you should probably mention wages in more than a passing way.

I can be sympathetic. Since I started blogging I've often recalled some prophetic observation I made in the past and started typing up a boastful post only to discover on review that I actually hadn't been that prophetic after all.

That's why I always reread old posts before I link to them; if I don't, someone else will.





* I had to remove a couple of reams of html formatting here. If I inadvertently removed something else. let me know.

Happy Holidays

Layoffs

Jeff Grubb has a very interesting window into how corporations act to try and create endless cycles of growth:

And part of it is that the corporation demands continued growth and profit. It can defer some of its growth for long-term development, or keep on an unsuccessful project that someone really likes, but really it boils down to guaranteed growth. And if you attain that growth, then they need to increase that rate of growth. And lord help you if you have a very good year - that very good year becomes the baseline for further calculations. In short, it is a vicious cycle.So they pass out the budgets for next year and now the departments have to plan. Yeah, some of that planning involves going back and telling the guys with the budgets that this makes no sense and sometimes that works. More often it involves figuring out what goes overboard in order to jack up profitability.Sometimes it is a new process that saves times or lowers cost of materials. Sometimes it is a new market that has been opened. Sometimes it is that "big hit" that suddenly arrives and surprises everyone (businesses actually don't like the "big hit" - it really screws up their planning. If they say you are going to lose 3 million this year and you instead MAKE 3 million, you make them look like idiots, and you will be punished accordingly).

There are two chilling comments here. One, is the idea that a good year can become the baseline for future expectations. So it makes sense to ensure that you don;t have any unexpected surprises. Two, which is the icing on the cake, is the idea that an unexpected burst of profitability will actually be punished. How this can actually be an efficient system is astonishing.

The standard explanation of "creative destruction" (badly run firms fade to be replaced with better run firms) presumes that we actually let large corporations fail. But there has been a general reluctance to do this in fields ranging from automobile manufacture to banking. Without that safety valve, this approach is going to be very dangerous to efficiency. In a later post, Jeff Grubb notes the CEO compensation for Hasbro (the subject of the first post) is pretty decent:

For those not linking, it is an announcement that the CEO of Hasbro is getting paid $23 Million this year. And yeah, it is like pouring oil on troubled water, then tossing in a match.Now, doing the digging in the article, the CEO gets a raise in salary from $1 Mill to $1.2 Mill (hardly chump change), and the rest being common stock. And to the best of my knowledge (the Internet will correct, of course), this means that it comes out of the company till - they are reassigning stock held by the company to the individual. And this assignment may have other strings attached - the stock cannot be sold except back to the company, it may only be sold at a particular price, it must be sold on leaving the company. So it is a fuzzy number, but a very large fuzzy number.The article also makes clear that this is a retention payment, negotiated last year, to keep the CEO around. It also notes that Hasbro had a weak 2010 in sales (stock prices went up, though). 2011 is nothing to write home about (stock prices have since deflated) and 2012 is not shaping up to be any better (Upcoming big movie: Battleship). So this is not about performance, but rather about stability. This is payment for showing up.

What is fascinating about part two is that this is the same company that just laid off two popular and productive long term employees in the Wizard's of the Coast division. So I googled game developer salaries and found this:

Game designers who work for a big company such as Hasbro or White Wolf Publishing can expect a more reliable salary, usually averaging between $30,000 and $50,000 per year.

Now let us presume fringe and overhead double the salary, and that both of the senior developers were at the very top of this range. The retention bonus portion of the CEO retention payment was enough to pay 400 developer-years of salary )both have fringe and overhead, it's unclear how this would work out in the details but this is a good starting estimate). Seriously, keeping the CEO around for another year was worth hundreds of experienced employees. What is ironic, is the base salary of the CEO is that of twenty senior developers (raised to that of twenty-four this year). That is actually a credible ratio of the benefit of a good CEO for a company (they have about as much influence as a couple of seasoned design teams). The additional $22 million is hard to understand. No wonder companies don't like comparisons between executive compensation and line worker compensation.

I do not really have a good idea about how to handle this issue in a more global sense, but I am deeply worried that this pattern could be playing out in corporations that we simply are unwilling to let go under.

That is a scary thought.

Do copyright extensions drive innovation? -- Hollywood blockbuster edition

After all this time on patents, I thought we'd give copyrights a turn.

One of the standard arguments for stronger intellectual property laws is that they encourage innovation. Now let's think about how this is supposed to work. Stronger protection for intellectual property makes those properties more valuable. Greater value causes the market to generate more and better properties, particularly those specific properties that best capitalize on the new profit potential.

In the case of copyright protection, the properties that make the best use of these extensions are franchisable stories and characters. I'm specifically using franchise in the sense of selling the right to use a business model. Just as McDonald's can sell one person the right to run a restaurant in one neighborhood and then sell a different person the right to run one in a different neighborhood, the company that owns the rights to, say, Batman can allow one creative team to produce a series of properties based on the character, then turn around a few years later and allow another team a shot.

This interchangeability of talent is essential given the lengths of time we're talking about here. For most of the Twentieth Century, copyright protection was effectively capped at fifty-six years, but major extensions were passed in 1976 and 1998 which extended protection of corporate works up to ninety-five years and left the possibility open of essentially unlimited future extensions.

In order to reach their full potential, franchises have to repeatedly replace all of their creative personnel. Bond and Batman are arguably the good examples, both having gone through numerous incarnations with completely different creative teams, but there's an important difference in the business model. Bond was an ongoing series with considerable continuity both in front of and behind the camera; Batman pattern since the Sixties has been successful run, fallow period, relaunch with new team. The second model, with its long cycles, takes better advantage of the long copyrights.

We would expect 1976 and 1998 to produce major upticks in the creation of properties that could support Batman style franchises because at those points the profit potential of that type of property greatly increased. We would also expect newer properties generally to be more valuable than older properties both because of freshness and because of changing tastes.

That means by now if we look at films that are either part of a franchise or an attempt to launch or relaunch one, we should expect to see a very large share from the past decade (both because of the 1998 Act and because of recency) then a decent showing from the the Eighties and Nineties and little if anything from before the mid-seventies. With that in mind, let's look at the medium to large budget franchisable movies from 2011 and their creation decade:



The Adventures of Tintin -- Twenties


Alvin and the Chipmunks: Chipwrecked -- Fifties


The Twilight Saga: Breaking Dawn - Part 1 -- 00s


Captain America: The First Avenger -- Forties


Conan the Barbarian -- Thirties


Cowboys & Aliens -- 00s


Diary of a Wimpy Kid: Rodrick Rules -- 00s


The Green Hornet -- Thirties


Green Lantern -- Sixties*


Harry Potter and the Deathly Hallows: Part 2 -- Nineties


I Am Number Four -- 00s


Mission Impossible -- Sixties


The Muppets -- Fifties


Pirates of the Caribbean: On Stranger Tides -- Sixties (part of Disney's movies based on rides series)


Rise of the Planet of the Apes -- Sixties


Sherlock Holmes -- Nineteenth Century


The Smurfs -- Fifties


Spy Kids: All the Time in the World -- 00s


Thor -- Sixties


Transformers: Revenge of the Fallen -- Eighties


X-Men: First Class -- Sixties


You can quibble with some of my calls here. I quibbled with myself quite a bit, going back and forth on the Adjustment Bureau (old), Cars (new), Puss-in-boots (old) and Diary of a Wimpy Kid among others, but no matter what standards you use, it's almost impossible to see anything in the data that supports the idea that these extremely long copyrights have increased the production of highly marketable properties.

At best you could argue that the extensions might have had a positive effect but it was small enough to be swamped by other technological, economic and demographic factors. At worst, you could make the case that copyright laws were approximately optimal in the middle of the Twentieth Century and that the extensions have actually inhibited innovation.

Like patents, copyrights are necessary, but highly intrusive regulations. Taken to an extreme, they distort markets, divert resources from creators to legal departments, encourage consolidation and set up onerous barriers to entry for small companies and start-ups.

For another layer of irony here, take a look at how Disney approached intellectual property in its early days.

* Technically very late Fifties (or even Forties if you count earlier character with the same name)

Also posted at MippyvilleTV.

Two telling quotes from Bill Adair of PolitiFact

Politifact has come in for a lot of criticism recently, some of it from surprising sources. Ramesh Ponnuru of the conservative National Review suggested that, rather than being the "Lie of the Year," the Democrats statements about Medicare were legitimate, while Jonathan Chait, then of the the liberal New Republic, has called the organization on unfair attacks on Republicans.

Without getting into the pros and cons of this most recent debate, I did want to share a couple of quotes from PolitiFact editor-in-chief Bill Adair:

From NPR:

"We're going to make the best calls we can in a pretty gutsy form of journalism," he says. "When we do, I think it's natural that the people on one side or other of this very partisan world we live in are going to be unhappy."

And from PolitiFact itself:

The most over-the-top response (was it tongue-in-cheek?) was a rant from Jim Newell in Gawker under the headline "Why PolitiFact is bad for you." He conveniently ignored the fact that our fact-checks are based on hours of journalistic research and portrayed them as the work of rogue bloggers with a gimmicky meter.

We've mentioned concerns about the decline of journalism and how various factors compound the problem. This is another one of those compounding factors: the strange obliviousness of many journalists. Adair, on the record, describes his own work as "gutsy." He holds up "hours of journalistic research" as an impressively high standard. He seems incapable of thinking of criticism as being based on anything but partisan bitterness. (If you think I'm cherry-picking here, follow the link above. The whole piece is like this.)

Even if you put aside the many criticisms of PolitiFact (spelled out cogently and with crushing thoroughness by Chait) and view them in the best (and I do mean best) possible light, the most you can say for the organization is that it's doing what we used to think of as standard due diligence from journalists.

Intellectual property: the story that never ends

More on intellectual property rights from Matt Yglesias, who is worried about Google patenting basic features of driverless cars:

If you look at the cars we have, they're all of course different but they have a lot of really profound similarities. You almost always turn a key in the ignition. You have your gas pedal and your break, and you push them both with your right foot. You steer them with a wheel. There's a spedometer and a fuel indicator in more-or-less the same place. They use mirrors so you can see where you're going without constantly turning your head. Would it be a better world if for twenty years someone had held a patent on a Using Mirrors To Allow Drivers To See Behind Them Without Turning Their Head? I say, no. Absent the inability of new entrants into the automobile market to copy some of the basic concepts of what a usable car looks like, we would have had much less competition and much less innovation around the real cutting edge of the automobile industry.

This was not the most interesting thing that was on Moneybox today, but it fit really well into an an evolving theme that we have been seeing recently about how the patent industry is formalizing rent-seeking.  This cannot be good in the long run.

Now, it is true that I think that the driverless car is an over-rated concept.  Like the jetpack, it is a neat idea that has a lot of very difficult implementation issues.  In the case of the driverless car, the main issues, in my opinion, are rethinking the complex web of liability we have constructed around vehicles and smoothly integrating them into mixed use roadways.

The risk of bicycle commuting has been an extremely favorable development, despite the occasional tension between cars and bikers.  But I wonder if driverless cars will be able to handle treating cyclists as other vehicles or might the smaller profile of the bike make it harder for the car to account for them?  The same concerns come up with pedestrians, especially in large cities.

Still more adventures in intellectual property

From the LA Times (comment would be superfluous):

The patent war between Apple Inc. and smartphone rival Samsung Electronics continues to escalate, and there's only one way to describe the latest vicious salvo:

:)

That's right, it appears that Samsung has initiated a lawsuit against Apple governing the company's use of emoticons.

According to a report from patent observer Florian Mueller, who has been dependably covering the worldwide patent wrestling match between Apple and Android manufacturers, one of four new patent lawsuits filed by Samsung in German court is over, once again, yes, emoticons.

Believe it or not, Samsung does indeed own a patent on smartphone use of emoticons. It won the European rights to that "technology" in 2000, and interested readers can see the actual patent here.

A few more thoughts on journalistic conformity

I complained in an earlier post that journalists have recently shown an alarming tendency to converge on a small set of standard stories when covering a major topic -- small sets that more often than not leave out things that we readers really ought to know about. Here's another example.

There are at least two potentially serious consequences to the amount of carbon we've been pumping into the atmosphere. The first is global warming. The second is the chemical and biological changes in the oceans.

Though it's difficult to compare the likely impact of phenomena this big and complex, the second problem is arguably on a level with the first, a point driven home in the LA Times' Pulitzer-winning series on the subject:

As industrial activity pumps massive amounts of carbon dioxide into the environment, more of the gas is being absorbed by the oceans. As a result, seawater is becoming more acidic, and a variety of sea creatures await the same dismal fate as Fabry's pteropods.

The greenhouse gas, best known for accumulating in the atmosphere and heating the planet, is entering the ocean at a rate of nearly 1 million tons per hour — 10 times the natural rate.

Scientists report that the seas are more acidic today than they have been in at least 650,000 years. At the current rate of increase, ocean acidity is expected, by the end of this century, to be 2 1/2 times what it was before the Industrial Revolution began 200 years ago. Such a change would devastate many species of fish and other animals that have thrived in chemically stable seawater for millions of years.

Less likely to be harmed are algae, bacteria and other primitive forms of life that are already proliferating at the expense of fish, marine mammals and corals.

In a matter of decades, the world's remaining coral reefs could be too brittle to withstand pounding waves. Shells could become too fragile to protect their occupants. By the end of the century, much of the polar ocean is expected to be as acidified as the water that did such damage to the pteropods aboard the Discoverer.

Some marine biologists predict that altered acid levels will disrupt fisheries by melting away the bottom rungs of the food chain — tiny planktonic plants and animals that provide the basic nutrition for all living things in the sea.

And we haven't even gotten to the primeval toxic slime (you really do need to read the whole series).

Given their common origin, comparable severity and potential for synergistic effects, topics like acidification should show up frequently in stories about global warming. Not all the time, but I would expect to see it in at least fifteen or twenty percent of the stories. It is simply a pairing that journalists to make on a fairly regular basis, but while a search of the last twelve months of the New York Times for "climate change" produces 10,509 hits, a search on '"climate change" acidification' over the same period produces 15.

(If we do a quick, back-of-the-envelope hypothesis test on the null that most journalists are well-informed, hard-working, independent thinkers...)

The specific tragedy here is that, for all the ink that's been spilled on the impacts of carbon emissions, all we really get in the vast majority of cases are simply the same handful of stories endlessly recycled. We read dozens of articles but since the writers have converged on a tiny number of narratives we remain ill-informed.

The general tragedy is that this is the way almost all journalism works these days. Through a lack of independent thinking (often augmented by laziness and a lack of rigor), journalists quickly settle on a small number of templates which they seldom stray from, even though these templates leave out important aspect of the larger story. Stories on the environmental impacts of carbon leave out the oceans; stories on the economics of cable don't mention broadcast television; stories about the free spending ways of countries like Greece and Spain omit the fact that Spain was running a surplus before the crisis.

It would be easy to find more examples. Finding counter-examples is the tough one.

Prediction is difficult

There is a really thoughtful post in the Economist. The gist:

In a nutshell: I've become far less confident about our ability to accurately describe possible outcomes more than a decade out. Correspondingly, I've become increasingly sceptical of the value of analyses of decisions now that attempt to assess the costs and benefits of action over horizons any longer than a decade.

I think that this was a very good complement to yesterday's discussion of inference from observational medical research.  Models are hard.  The more complicated the model is, the more likely something is to go wrong.  Future predictions suffer from these sorts of complications -- we honestly do not know what the circumstances will be like in the future or how many unlikely events will actually happen.  Over the short run, predictions can bank on it being unlikely that a lot of "low event rate but high impact" events will happen.  We can also neglect the slow (but incremental variables) that are currently unnoticed but which will make a huge difference in the future.

In the same sense, looking at low event rate outcomes in incomplete data (most of pharmacovigilence), leads to a lot of innate uncertainty.  In both cases, I think it makes a lot of sense to be humble about what our models can tell us and to focus on policy that accepts that there is a lot of innate uncertainty in some forms of prediction.

Hat-tip: Marginal Revolutions

Can we do observational medical research?

Andrew Gelman has a really nice post on observational medical research.  How could I not respond?

In the post he quotes David Madigan who has a fairly strong opinion on the matter:

I’ve been involved in a large-scale drug safety signal detection project for the last two or three years (http://omop.fnih.org). We have shown empirically that for any given safety issue, by judicious choice of observational database (we looked at 10 big ones), method (we looked at about a dozen), and method setup, you can get *any* answer you want – big positive and highly significant RR or big negative and highly significant RR and everything in between. Generally I don’t think there is any way to say definitively that any one of these analysis is a priori obviously stupid (although “experts” will happily concoct an attack on any approach that does not produce the result they like!). The medical journals are full of conflicting analyses and I’ve come to the belief that, at least in the medical arena, the idea human experts *know* the *right* analysis for a particular estimand is false.

This seems overly harsh to me.  Dr. Madigan (who I think is an amazing statistician) is working with OMAP, which I recall as being comprised of data sets of fairly low quality data (prescriptions claims for Medicare/MedicAid, GPRD and other clinical databases, and these sorts of databases).  It is a necessary evil to get the power to detect rare (but serious) adverse drug outcomes.  But these databases are often problematic when extended beyond extremely clear signal detection issues.  

The clearest example of high quality medical data is likely to be randomized controlled double-blinded clinical trials.  But there is a whole layer of data between these two extremes of data quality (prospective cohort studies, for example) that has also generated a lot of important findings in medicine.

Sure, it is true that the prospective cohort studies tend to be underpowered to detect rare adverse drug side effects (for precisely the same reason that RCTs are).  But there is a lot of interesting observational medical research that does not generate conflicting results or where the experts really seem to have a good grasp on the problem.  The links between serum cholesterol levels and cardiovascular events, for example, seems relatively solid and widely replicated.  So do the links between smoking and lung cancer (or cardiovascular disease) in North American and European populations.  There is a lot that we can learn with observational work.

So I would be careful to generalize to all of medical research.

That being said, I have a great deal of frustration with medical database research for a lot of the same reasons as David Madigan does.  I think the issues with trying to do research in medical claims data would be an excellent series of posts as the topic is way too broad for a single post.

How to read Megan McArdle part 46 -- the quotes

Via Joseph via Karl Smith, Megan McArdle (in a post entitled, "When it Comes to Taxes on the Poor, the Supply Siders are Right") quotes the following passage from Jeff Liebman:

"Despite the EITC and child credit, the poverty trap is still very much a reality in the U.S. A woman called me out of the blue last week and told me her self-sufficiency counselor had suggested she get in touch with me. She had moved from a $25,000 a year job to a $35,000 a year job, and suddenly she couldn't make ends meet any more. I told her I didn't know what I could do for her, but agreed to meet with her. She showed me all her pay stubs etc. She really did come out behind by several hundred dollars a month. She lost free health insurance and instead had to pay $230 a month for her employer-provided health insurance. Her rent associated with her section 8 voucher went up by 30% of the income gain (which is the rule). She lost the ($280 a month) subsidized child care voucher she had for after-school care for her child. She lost around $1600 a year of the EITC. She paid payroll tax on the additional income. Finally, the new job was in Boston, and she lived in a suburb. So now she has $300 a month of additional gas and parking charges. She asked me if she should go back to earning $25,000. I told her that she should first try to find a $35k job closer to home. Also, she apparently can't fully reverse her decision to take the higher paying job because she can't get the child care voucher back (the waiting list is several years long she thinks). She is really stuck. She tried taking an additional weekend job, but the combination of losing 30 percent in increased rent and paying for someone to take care of her child meant it didn't help much either.

The question is what is the policy solution here. Means-tested transfers have to be phased out at some point, so there is no easy answer.

Notice strangely brief second paragraph and the missing quotation mark at the end? Statisticians tend to be suspicious people, particularly when it comes to odd cut-offs for data ranges so I clicked through the link to the Jeff Frankels post that provided the original quote and saw a possible reason why McArdle had stopped so abruptly. Here's the very next sentence:

I think there are three things we might be able to do — all of which would, as you say, be a better use of revenue than tax cuts for the rich.

The whole paragraph is worth reading:

The question is what is the policy solution here. Means-tested transfers have to be phased out at some point, so there is no easy answer. I think there are three things we might be able to do — all of which would, as you say, be a better use of revenue than tax cuts for the rich. First, make child-related tax benefits equal for all families (now they are high at the bottom because of the EITC and high at the top because the dependent exemption is more valuable the higher the tax bracket you are in, and the dip in the middle raises marginal tax rates by 21 percent for a family with two kids — so eliminating the dip would get rid of this 21 percent portion of the effective marginal tax rate). David Ellwood and I analyze this first idea. Also Sawicky and Cherry have put forth a similar idea. Second, in designing universal health insurance, we need to be very careful not to phase out income-related premium subsidies over the same income range where all of these other benefits are being phased out. Third, implement a delay between income increases and rent increases in section 8 — allow people to save up a bit before they are hit with the rent increase (I believe I read that some states have been trying out something like this recently, but I am not up to date on these policies). There are some excellent papers that carefully model how the cumulative effects of the welfare system create a poverty trap. But I don’t think either of these papers includes all of the factors facing the woman above — so they would probably indicate that she faced a 60 percent marginal tax rate rather than the 130% (or whatever it really is) rate that she actually faces.”

I not entirely convinced that Liebman has made the case for counting personal expenses required for a new job as a tax increase, but it's a coherent and honest argument that's certainly persuasive on the reality of a poverty trap.

As for the rest of McArdle's post, after having spent a great deal of time arguing that a situation exists where supply siders predict a strong effect, her whole defense of her central thesis consists of this:

Note two things: first, that in this case, at least, the supply siders seem to be completely right. Everyone I've spoken to about the problem seems to agree that the poor respond to these high marginal tax rates by either taking lower-paying jobs than they could, or working less--not in every individual case, but in aggregate.

And second, that this is not a problem that supply siders seem to be applying much brain power or political capital to fixing.

The everyone-I've-spoken-to standard leaves something to be desired, particularly given the fact that the woman in the anecdote did the exact opposite of what supply side theory predicted; rather than "taking lower-paying jobs than [she] could, or working less," she "tried taking an additional weekend job."

(and to put way too fine a point on this, I don't see the predicted big dip for affected families in these numbers either)

On the bright side, this still isn't the worst thing to come out of the Atlantic recently.

When a model simply doesn't match reality

Karl Smith relates a story from Megan McArdle:

A woman called me out of the blue last week and told me her self-sufficiency counselor had suggested she get in touch with me. She had moved from a $25,000 a year job to a $35,000 a year job, and suddenly she couldn't make ends meet any more. I told her I didn't know what I could do for her, but agreed to meet with her. She showed me all her pay stubs etc. She really did come out behind by several hundred dollars a month. She lost free health insurance and instead had to pay $230 a month for her employer-provided health insurance. Her rent associated with her section 8 voucher went up by 30% of the income gain (which is the rule). She lost the ($280 a month) subsidized child care voucher she had for after-school care for her child. She lost around $1600 a year of the EITC. She paid payroll tax on the additional income. Finally, the new job was in Boston, and she lived in a suburb. So now she has $300 a month of additional gas and parking charges. She asked me if she should go back to earning $25,000. I told her that she should first try to find a $35k job closer to home. Also, she apparently can't fully reverse her decision to take the higher paying job because she can't get the child care voucher back (the waiting list is several years long she thinks). She is really stuck. She tried taking an additional weekend job, but the combination of losing 30 percent in increased rent and paying for someone to take care of her child meant it didn't help much either.

Ms, McArdle tries to make a supply side argument here, where she points out that we are failing to create policies to incentive work among the poor (who can suffer a marginal tax rate of > 100% in many circumstances). It is a really interesting question why we focus on the top marginal tax rate and not the marginal tax rate for people in lower income brackets (where there is less of a competition effect). However, Karl Smith notices the really interesting behavioral issue here:

She faced a marginal tax rate in excess of 100%. This meant as her earned income went up she got poorer. What did she do? She tried to earn even more income. It was only we she failed at the attempt to make ends meet by supplying ever more labor to the free market that she try to go back to making less money.

So, not only do we have evidence from Matt Yglesias and Felix Salmon that top income earners don't necessarily even know their marginal rate, but we see low income people (facing a > 100% marginal rate of taxes) desperately trying to get more income and not less. It is not the case that the woman in this heartbreaking story decides that she would prefer to spend more time in leisure (so we can't intice her into working more). It is that working actually costs her money.

And her response is to get a second job!

Is it really too late to put supply side economics into the "special circumstances only" bin and leave it there? It may influence the odd movie producer, consultant, or freelancer (who have the ability to take on work in discrete projects and who have income sufficiency already). But this conceptual model seems to be absolutely dreadful at making predictions about how real people will act in most employment situations.

A really nice article by Andrew Gelman and Kaiser Fung

Andrew Gelman and Kaiser Fung have an article on Freakonomics in American Scientist. My favorite part was the story of Emily Oster and her theory of Hepatitis B:

Monica Das Gupta is a World Bank researcher who, along with others in her field, has attributed the abnormally high ratio of boy-to-girl births in Asian countries to a preference for sons, which manifests in selective abortion and, possibly, infanticide. As a graduate student in economics, Emily Oster (now a professor at the University of Chicago) attacked this conventional wisdom. In an essay in Slate, Dubner and Levitt praised Oster and her study, which was published in the Journal of Political Economy during Levitt’s tenure as editor:

[Oster] measured the incidence of hepatitis B in the populations of China, India, Pakistan, Egypt, Bangladesh, and other countries where mothers gave birth to an unnaturally high number of boys. Sure enough, the regions with the most hepatitis B were the regions with the most “missing” women. Except the women weren’t really missing at all, for they had never been born.

Oster’s work stirred debate for a few years in the epidemiological literature, but eventually she admitted that the subject-matter experts had been right all along. One of Das Gupta’s many convincing counterpoints was a graph showing that in Taiwan, the ratio of boys to girls was near the natural rate for first and second babies (106:100) but not for third babies (112:100); this pattern held up with or without hepatitis B. In a follow-up blog post, Levitt applauded Oster for bravery in admitting her mistake, but he never credited Das Gupta for her superior work. Our point is not that Das Gupta had to be right and Oster wrong, but that Levitt and Dubner, in their celebration of economics and economists, suspended their critical thinking.

I think that this story actually has two elements. One is the dangers of a convincing explanation. There are a lot of associations that can appear and would be extremely exciting if they were true. Just consider the recent article on statins reducing mortality due to pneumonia: it is an amazing result that would be extremely exciting if it were true. I worry that these kinds of exciting results get a lot of press instead of being seen a signposts towards needing to examine the problem more carefully. After all, it was a good thing that Das Gupta had a chance to look at her data and control for an additional predictive variable. What is concerning is not raising the idea -- it is the strength of the language: "Except the women weren’t really missing at all, for they had never been born" which implied a lot more certainty than seemed warranted. But putting that point aside, the real interesting thing (to me) is considering likely effect sizes. When you look at the population level infection rates (incremental on the infection rates in countries without this gender imbalance) then you quickly conclude that the effect of infection has to be high. After all, the rate in India appears to be about 3% (versus less than 1% in the United States). At the same time, the sex ratio in India was 1.10 (these are approximate numbers). So if the natural sex ratio is 105 and India has 110 we can do a calculation. Assume that the Hep B rate among reproductive age women is triple the population average (say 9%). So 0.91 x 105 + 0.09 x [RATE] = 110. That suggests that the sex ratio among infected women is 160 (it gets a lot worse if you merely assume double). That means we could prove this hypothesis by following a very small cohort of Hep B infected pregnant women, since the effect size is so large. Now this is a simplistic way to look at the problem, and I am sure that more nuanced approaches make sense. But isn't this the sort of data you'd look for before suggesting that the experts completely missed the explanatory variable? After all, you are positing an enormous effect size for the influence of the virus on sex ratios. This would be observed in routine clinical practice. So, not to give anybody a hard time. We all have challenges in our research and it is really hard to tackle these types of problems. People should have credit for putting their necks out and proposing testable hypotheses that can enhance our understanding of the world. But I think we should rethink just how certain we are when we make these proposals. Maybe we need to learn to say "this is a possible explanation for some of the observed variation".

Remember, it no longer counts as plagiarism unless you use exactly the same words

I had started out to write a post about the cable executive who described the rising cost of ESPN as a "tax on every American household," but when I went looking for source articles I noticed something strange. The Atlantic, the Wall Street Journal, and the rest all told the story in the same way, right down to the same omission of the role of over-the-air television (which is particularly relevant to a story about threats to cable's business model).

Don't worry, this is not another rabbit-ears story. What's significant here is that in a story about cable losing cost-conscious customers, none of the writers mentioned the tens of millions of people who were getting full digital television for free. Not only do journalists now tend to cover the stories from the same angles, they even omit the same important details.

This group-think is bad enough on its own, but when you combine it with an increasingly nonchalant attitude toward accuracy and fact-checking (here's one of many examples), the results can be dangerous.

Look at the debate over the Euro-crisis. Any number of virtually identical stories have appeared claiming that the crisis was started by the wild deficit spending of southern countries, implicitly or explicitly including Spain, despite the fact that Spain had been running a surplus before the crisis.

If journalists aren't bothering to think independently or check their facts when reporting on the Euro-crisis, what stories are important enough to justify their A-game?