One of the cool things about about Andrew Gelman's blog is the quality of discussions you'll see in his comment section. The observations are almost always well-informed and the tone strikes a nice balance between spirited and civil.
Prof. Gelman's recent post on homework (which responded to this post we did earlier on OE) prompted one of these excellent discussions. Joseph has already built a post around one particularly interesting comment, but all of them are worth reading.
Sunday, January 30, 2011
Hotel pricing enigma
(that may not be that enigmatic)
Has anyone else noticed that the higher the price of the hotel, the more likely it is to charge for internet access? I do quite a bit of travelling on my own decidedly thin dime so I usually stay in one of the bargain chains but occasionally I find myself in a nice, corporate-booked hotel. Free internet is almost universal in the cheap places but it's likely to run you $10 a night in a place with valet parking and a fitness center.
I assume this is another case of prices being driven by expense accounts, but does anyone else have an alternative explanation?
Has anyone else noticed that the higher the price of the hotel, the more likely it is to charge for internet access? I do quite a bit of travelling on my own decidedly thin dime so I usually stay in one of the bargain chains but occasionally I find myself in a nice, corporate-booked hotel. Free internet is almost universal in the cheap places but it's likely to run you $10 a night in a place with valet parking and a fitness center.
I assume this is another case of prices being driven by expense accounts, but does anyone else have an alternative explanation?
Saturday, January 29, 2011
Educational Lotteries
Hoisted from the comments on Andrew Gelman's web site, Steve Sailor claims:
This is a very good point. There have been some very good comments on the use of charter school lotteries as a gold standard. I think there are persuasive reasons to be concerned, even if the lotteries are fair. However, it would be in the self interest of charter schools to accept a few "star students" outright rather than lave their selection to chance. Insofar as this happens at all, we would no longer have randomization (and thus would be unable to use these lotteries to estimate causal effects, even if the other concerns were not present).
So it seems increasingly hard to treatment there lotteries as a valid instrumental variable.
In my one experience with a charter school lottery, the charter school made it quite difficult to enter the lottery; and to find out if your kid was selected, you had to go there and ask them. And, it appeared, it wasn't a random lottery at all. My son was known to the founders of the school as a star student, so when I showed up and nervously asked if his name had been picked, I was told, Don't worry about it, of course he's in.
This is a very good point. There have been some very good comments on the use of charter school lotteries as a gold standard. I think there are persuasive reasons to be concerned, even if the lotteries are fair. However, it would be in the self interest of charter schools to accept a few "star students" outright rather than lave their selection to chance. Insofar as this happens at all, we would no longer have randomization (and thus would be unable to use these lotteries to estimate causal effects, even if the other concerns were not present).
So it seems increasingly hard to treatment there lotteries as a valid instrumental variable.
Weekend Gaming -- The Blue and the Gray
[If you missed it, check out last week's game as well.]
The famous game designer,* Sid Sackson, had over eighteen thousand games in his personal collection so making his short list was quite an accomplishment, particularly for a game that almost nobody has ever heard of.
On this alone, the Blue and the Gray would be worth a look, but the game also has a number of other points to recommend it: it only takes about three minutes to learn (you can find a complete set of rules here); it is, as far as I know, unique; it raises a number of interesting and unusual strategic questions; and for the educators out there, its Turn-of-the-Century** origins provide some opportunities for teaching across the curriculum. My only major complaint is that it requires a dedicated board, but making your own shouldn't take more than a few minutes.
The object of the game is to be the first to get your general to the center by moving along the designated path while using your soldiers to block your opponent's progress. Since soldiers can capture each other, the game has two offensive options (capturing and advancing) compared to one defensive option (blocking). (Something I learned from developing my own game was the more the designer can shift the focus to offense, the better and faster the game will play.)
I don't know of any attempt to do a serious analysis of the Blue and the Gray. Might be fun to look into. If someone out there finds anything interesting, make sure to let us know.
* Yes, I did just use the phrase, 'famous game designer.'
** I'm going off memory here about the age of the game. You should probably double check before building a lesson plan around this. (see update)
UPDATE:
Via the good people at the University of Maryland, here's the original patent from 1903.
The famous game designer,* Sid Sackson, had over eighteen thousand games in his personal collection so making his short list was quite an accomplishment, particularly for a game that almost nobody has ever heard of.
On this alone, the Blue and the Gray would be worth a look, but the game also has a number of other points to recommend it: it only takes about three minutes to learn (you can find a complete set of rules here); it is, as far as I know, unique; it raises a number of interesting and unusual strategic questions; and for the educators out there, its Turn-of-the-Century** origins provide some opportunities for teaching across the curriculum. My only major complaint is that it requires a dedicated board, but making your own shouldn't take more than a few minutes.
The object of the game is to be the first to get your general to the center by moving along the designated path while using your soldiers to block your opponent's progress. Since soldiers can capture each other, the game has two offensive options (capturing and advancing) compared to one defensive option (blocking). (Something I learned from developing my own game was the more the designer can shift the focus to offense, the better and faster the game will play.)
I don't know of any attempt to do a serious analysis of the Blue and the Gray. Might be fun to look into. If someone out there finds anything interesting, make sure to let us know.
* Yes, I did just use the phrase, 'famous game designer.'
** I'm going off memory here about the age of the game. You should probably double check before building a lesson plan around this. (see update)
UPDATE:
Via the good people at the University of Maryland, here's the original patent from 1903.
Thursday, January 27, 2011
A new post by James Kwak, an old rant by me
James Kwak has an excellent post on rational maximizing, but while the whole thing is worth reading, this passage jumped out at me:
I say this is interesting because, on the one hand, I accept the random walk studies (and I personally believe I have no ability to predict where any security price is going tomorrow), but on the other hand I think that any idea that markets have fundamental levels is flawed. For example, housing prices are still falling. Some people try to predict how far they will fall by looking at the Case-Shiller Index and figuring out where the long-term trend line will be. But how do you look at a chart and figure out what the right value is? What if there has been something different about the market over the last one hundred years from the market today? It’s really a fool’s errand.Kwak's objection reminded me of a similar problem I had with the book, "Lifecyle Investing," by Ian Ayres and Barry Nalebuff, one that finally made my head explode:
No one can possibly know what's going on here! We can get some smart people making good guesses about long term stock performance, but these guesses are based on data from a century's worth of secular upheavals. A list that includes the Great Depression, two world wars, a post-war reconstruction, the cold war, China becoming a major player, boomers entering the market, boomers leaving the market and huge changes in regulation, technology and business practices.I have great respect for economists, but, more so than any other field I can think of, they are shooting at moving targets and sometimes I get a bit nervous about their aim.
What's happening now never happened before. What happened before never happened before. What happened before what happened before never happened before. We have no precedents. People are recommending forty-year investment strategies using models based on data from markets that haven't gone twenty years without a major secular change.
One more exchange on Mankiw's assumptions
More from the ongoing debate.
Here's David (pulled from a longer comment):
David,
It's easy to get lost in the weeds here, so I'll try to get a few specific points out of the way then address the bigger issue of of the way we treat assumptions in the economic debate.
First, when it comes to robustness, it is sufficient to show that deviating from an assumption would cause the model to fail. There is no need to show that a particular deviation (such as the possible plateaus I suggested) occurs, only that if it occurs problems will follow. The world is full of perfectly good models that are not robust. As long as the real world lines up closely enough with the model's assumptions, the lack of robustness is not an issue.
Robustness is, however, an issue when we go out of the range of data, and, given these unique times, every policy proposal goes outside our range of data. At this point the burden falls on the proposer to be explicit with assumptions and make some kind of case that they are being met.
We also need to be carefully to distinguish between individual and aggregate relationships. We know that raises and promotions occur at discrete points and bonuses are frequently capped. That means, for many workers, the relationship between wages and productivity can't be linear. It is, however, possible that when aggregated that relationship is linear (or at least close enough for our purposes). The problem here is that proposals that assume individual level linearity can sound a lot like proposal that assumes aggregate linearity. Once again, we need more caution and clarity than we've been seeing.
All of which lead to the main point: much of the economic debate (particularly Greg Mankiw's corner of it) has been based on arguments that aren't all that robust and assumptions that aren't immediately self-evident. Many of these arguments reach conclusions that are difficult to reconcile with the historical record (such as Mankiw's prediction that a return to Clinton era taxes would have dire effects on the nation). Under these circumstances, assumptions should not be left implicit and they certainly should not be depicted as broad and obvious when they are highly specialized and non-intuitive (Freakonomics being the best known example with Levitt's go-to "people respond to incentives." formulation).
In other words, in this situation, I'd probably argue that the burden of proof is on Mankiw; I'd certainly insist the burden of clarity is.
Here's David (pulled from a longer comment):
I think where we disagree (assuming that we do disagree) is on where the burden of proof should lie. As an economist, and based on my reading of the theoretical and empirical literatures, the burden is on the individual who claims there are important plateaus and such. This requires showing empirically that they exist, and not in a general sense, but on the relevant margin of choice for those individuals. My general sense is that most economists would agree with this placing of the burden of proof, and your suggestion of the consensus of various economists is consistent with my impression as well. In other words, to assume that there are important plateaus on the margin requires empirical justification, and substantial justification because its very difficult to understand labor markets if we deviate generally even moderately from this productivity/wages relationship. So while you agree that “…if pundits' arguments are sufficiently robust or their assumptions are obviously true, they can do what Mankiw does.” I’d say that the consensus to me amongst economists supports the arguments and broader type of assumptions that I discussed previously. I suppose that’s an empirical question, for which I have not yet looked for data.
David,
It's easy to get lost in the weeds here, so I'll try to get a few specific points out of the way then address the bigger issue of of the way we treat assumptions in the economic debate.
First, when it comes to robustness, it is sufficient to show that deviating from an assumption would cause the model to fail. There is no need to show that a particular deviation (such as the possible plateaus I suggested) occurs, only that if it occurs problems will follow. The world is full of perfectly good models that are not robust. As long as the real world lines up closely enough with the model's assumptions, the lack of robustness is not an issue.
Robustness is, however, an issue when we go out of the range of data, and, given these unique times, every policy proposal goes outside our range of data. At this point the burden falls on the proposer to be explicit with assumptions and make some kind of case that they are being met.
We also need to be carefully to distinguish between individual and aggregate relationships. We know that raises and promotions occur at discrete points and bonuses are frequently capped. That means, for many workers, the relationship between wages and productivity can't be linear. It is, however, possible that when aggregated that relationship is linear (or at least close enough for our purposes). The problem here is that proposals that assume individual level linearity can sound a lot like proposal that assumes aggregate linearity. Once again, we need more caution and clarity than we've been seeing.
All of which lead to the main point: much of the economic debate (particularly Greg Mankiw's corner of it) has been based on arguments that aren't all that robust and assumptions that aren't immediately self-evident. Many of these arguments reach conclusions that are difficult to reconcile with the historical record (such as Mankiw's prediction that a return to Clinton era taxes would have dire effects on the nation). Under these circumstances, assumptions should not be left implicit and they certainly should not be depicted as broad and obvious when they are highly specialized and non-intuitive (Freakonomics being the best known example with Levitt's go-to "people respond to incentives." formulation).
In other words, in this situation, I'd probably argue that the burden of proof is on Mankiw; I'd certainly insist the burden of clarity is.
Wednesday, January 26, 2011
Evaluating the evaluations
Busy morning so I don't have time to do more than provide some links and the abstract for this paper on the effectiveness of college teachers.
Here's Andrew Gelman's reaction.
In primary and secondary education, measures of teacher quality are often based on contemporaneous student performance on standard-ized achievement tests. In the postsecondary environment, scores on student evaluations of professors are typically used to measure teaching quality. We possess unique data that allow us to measure relative student performance in mandatory follow-on classes. We compare metrics that capture these three different notions of instructional quality and present evidence that professors who excel at promoting contemporaneous student achievement teach in ways that improve their student evaluations but harm the follow-on achievement of their students in more advanced classes.Here's the ungated version via Tyler Cowen. May not be quite the same as the published one.
Here's Andrew Gelman's reaction.
Repost -- Fitness Landscapes, Ozark Style
[I'm working on a long post that uses fitness landscapes, so I thought I'd rerun some previous posts to get the conversation going.]
I grew up with a mountain in my backyard... literally. It wasn't that big (here in California we'd call it a hill) but back in the Ozarks it was a legitimate mountain and we owned about ten acres of it. Not the most usable of land but a lovely sight.
That Ozark terrain is also a great example of a fitness landscape because, depending on which side you look at, it illustrates the two serious challenges for optimization algorithms. Think about a mountainous area at least partially carved out by streams and rivers. Now remove all of the rocks, water and vegetation drop a blindfolded man somewhere in the middle, lost but equipped with a walking stick and a cell phone that can get a signal if he can get to a point with a clear line of sight to a cell tower.
With the use of his walking stick, the man has a reach of about six feet so he feels around in a circle, finds the highest point, takes two paces that direction then repeats the process (in other words, performs a gradient search). He quickly reaches a high point. That's the good news; the bad news is that he hasn't reached one of the five or six peaks that rise above the terrain. Instead, he has found the top of one of the countless hills and small mountains in the area.
Realizing the futility of repeating this process, the man remembers that an engineer friend (who was more accustomed to thinking in terms of landscape minima) suggested that if they became separated he should go to the lowest point in the area so the friend would know where to look for him. The man follows his friend's advice only to run into the opposite problem. This time his process is likely to lead to his desired destination (if he crosses the bed of a stream or a creek he's pretty much set) but it's going to be a long trip (waterways have a tendency to meander).
And there you have the two great curses of the gradient searcher, numerous small local optima and long, circuitous paths. This particular combination -- multiple maxima and a single minimum associated with indirect search paths -- is typical of fluvial geomorphology and isn't something you'd generally expect to see in other areas, but the general problems of local optima and slow convergence show up all the time.
There are, fortunately, a few things we can do that might make the situation better (not what you'd call realistic things but we aren't exactly going for verisimilitude here). We could tilt the landscape a little or slightly bend or stretch or twist it, maybe add some ridges to some patches to give it that stylish corduroy look. (in other words, we could perturb the landscape.)
Hopefully, these changes shouldn't have much effect on the size and position of the of the major optima,* but they could have a big effect on the search behavior, changing the likelihood of ending up on a particular optima and the average time to optimize. That's the reason we perturb landscapes; we're hoping for something that will give us a better optima in a reasonable time. Of course, we have no way of knowing if our bending and twisting will make things better (it could just as easily make them worse), but if we do get good results from our search of the new landscape, we should get similar results from the corresponding point on the old landscape.
In the next post in the series, I'll try to make the jump from mountain climbing to planning randomized trials.
* I showed this post to an engineer who strongly suggested I add two caveats here. First, we are working under the assumption that the major optima are large relative to the changes produced by the perturbation. Second our interest in each optima is based on its size, not whether it is global. Going back to our original example, let's say that the largest peak on our original landscape was 1,005 feet tall and the second largest was 1,000 feet even but after perturbation their heights were reversed. If we were interested in finding the global max, this would be be a big deal, but to us the difference between the two landscapes is trivial.
These assumptions will be easier to justify when start applying these concepts in the next post in the series. For now, though, just be warned that these are big assumptions that can't be made that often.
I grew up with a mountain in my backyard... literally. It wasn't that big (here in California we'd call it a hill) but back in the Ozarks it was a legitimate mountain and we owned about ten acres of it. Not the most usable of land but a lovely sight.
That Ozark terrain is also a great example of a fitness landscape because, depending on which side you look at, it illustrates the two serious challenges for optimization algorithms. Think about a mountainous area at least partially carved out by streams and rivers. Now remove all of the rocks, water and vegetation drop a blindfolded man somewhere in the middle, lost but equipped with a walking stick and a cell phone that can get a signal if he can get to a point with a clear line of sight to a cell tower.
With the use of his walking stick, the man has a reach of about six feet so he feels around in a circle, finds the highest point, takes two paces that direction then repeats the process (in other words, performs a gradient search). He quickly reaches a high point. That's the good news; the bad news is that he hasn't reached one of the five or six peaks that rise above the terrain. Instead, he has found the top of one of the countless hills and small mountains in the area.
Realizing the futility of repeating this process, the man remembers that an engineer friend (who was more accustomed to thinking in terms of landscape minima) suggested that if they became separated he should go to the lowest point in the area so the friend would know where to look for him. The man follows his friend's advice only to run into the opposite problem. This time his process is likely to lead to his desired destination (if he crosses the bed of a stream or a creek he's pretty much set) but it's going to be a long trip (waterways have a tendency to meander).
And there you have the two great curses of the gradient searcher, numerous small local optima and long, circuitous paths. This particular combination -- multiple maxima and a single minimum associated with indirect search paths -- is typical of fluvial geomorphology and isn't something you'd generally expect to see in other areas, but the general problems of local optima and slow convergence show up all the time.
There are, fortunately, a few things we can do that might make the situation better (not what you'd call realistic things but we aren't exactly going for verisimilitude here). We could tilt the landscape a little or slightly bend or stretch or twist it, maybe add some ridges to some patches to give it that stylish corduroy look. (in other words, we could perturb the landscape.)
Hopefully, these changes shouldn't have much effect on the size and position of the of the major optima,* but they could have a big effect on the search behavior, changing the likelihood of ending up on a particular optima and the average time to optimize. That's the reason we perturb landscapes; we're hoping for something that will give us a better optima in a reasonable time. Of course, we have no way of knowing if our bending and twisting will make things better (it could just as easily make them worse), but if we do get good results from our search of the new landscape, we should get similar results from the corresponding point on the old landscape.
In the next post in the series, I'll try to make the jump from mountain climbing to planning randomized trials.
* I showed this post to an engineer who strongly suggested I add two caveats here. First, we are working under the assumption that the major optima are large relative to the changes produced by the perturbation. Second our interest in each optima is based on its size, not whether it is global. Going back to our original example, let's say that the largest peak on our original landscape was 1,005 feet tall and the second largest was 1,000 feet even but after perturbation their heights were reversed. If we were interested in finding the global max, this would be be a big deal, but to us the difference between the two landscapes is trivial.
These assumptions will be easier to justify when start applying these concepts in the next post in the series. For now, though, just be warned that these are big assumptions that can't be made that often.
Tuesday, January 25, 2011
They may be anecdotal...
...but as recent events drive the mental health debate, cases like this take on an added significance.
"Why 3D doesn't work and never will. Case closed."
According to Roger Ebert (who should know), Walter Murch is "the most respected film editor and sound designer in the modern cinema" and, according to Murch, 3-D movies are still a bad technology.
Here's his main objection (from an open letter to Ebert):
As far as I can tell, it's been over seventy years since a customer-facing innovation (Technicolor) has revolutionized the cinema industry (distinguished here from home entertainment where the story has been entirely different). There have been customer-facing innovations but they've failed to catch on (Cinerama, color-based 3-D, Sensurround -- Imax has managed to stick around, but with less than 500 theaters after about four decades, it hasn't really been a game changer).
The innovations that actually had a major impact on the industry have been primarily focused on making films faster and quicker to make and easier to market (multiplexes, 'opening big,' digital production, post-production and projection, even CGI).
And yet studio executives continue to dream of the next Vitaphone.
*I'm not sure about the 600 million years -- how far back does stereoscopic vision go?
Here's his main objection (from an open letter to Ebert):
The biggest problem with 3D, though, is the "convergence/focus" issue. A couple of the other issues -- darkness and "smallness" -- are at least theoretically solvable. But the deeper problem is that the audience must focus their eyes at the plane of the screen -- say it is 80 feet away. This is constant no matter what.Murch also makes important points about the editing and aesthetics of 3-D cinema, none of which are likely to make you rush out and invest your money in the technology, but that's just what the film industry has been doing.
But their eyes must converge at perhaps 10 feet away, then 60 feet, then 120 feet, and so on, depending on what the illusion is. So 3D films require us to focus at one distance and converge at another. And 600 million years of evolution* has never presented this problem before. All living things with eyes have always focused and converged at the same point.
If we look at the salt shaker on the table, close to us, we focus at six feet and our eyeballs converge (tilt in) at six feet. Imagine the base of a triangle between your eyes and the apex of the triangle resting on the thing you are looking at. But then look out the window and you focus at sixty feet and converge also at sixty feet. That imaginary triangle has now "opened up" so that your lines of sight are almost -- almost -- parallel to each other.
We can do this. 3D films would not work if we couldn't. But it is like tapping your head and rubbing your stomach at the same time, difficult. So the "CPU" of our perceptual brain has to work extra hard, which is why after 20 minutes or so many people get headaches. They are doing something that 600 million years of evolution never prepared them for. This is a deep problem, which no amount of technical tweaking can fix. Nothing will fix it short of producing true "holographic" images.
As far as I can tell, it's been over seventy years since a customer-facing innovation (Technicolor) has revolutionized the cinema industry (distinguished here from home entertainment where the story has been entirely different). There have been customer-facing innovations but they've failed to catch on (Cinerama, color-based 3-D, Sensurround -- Imax has managed to stick around, but with less than 500 theaters after about four decades, it hasn't really been a game changer).
The innovations that actually had a major impact on the industry have been primarily focused on making films faster and quicker to make and easier to market (multiplexes, 'opening big,' digital production, post-production and projection, even CGI).
And yet studio executives continue to dream of the next Vitaphone.
*I'm not sure about the 600 million years -- how far back does stereoscopic vision go?
Monday, January 24, 2011
What's French for spam?
A few days ago, Seyward Darby posted a good piece of analysis on publishing teacher scores. Having been critical of Darby's previous writing on the subject, I entitled my response "Credit where credit is due." This morning I found the following comment complete with hyperlink:
Creadit - Vous cherchez crédit, credit d'impot, banque et bancaire [redacted] est une entreprise de courtage offrant les meilleures solutions pour pret relais et Credit en ligne au meilleur prix.Or (according to Google Translate):
Cread - Looking for credit, tax credit, bank and banking [redacted] is a brokerage firm offering the best solutions for bridging loan and Credit online at the best price.This should have been an easy catch for the spam filter. Was this just a random slip-up or does language make a difference?
I could not agree more
From Matt Yglesias:
I have been enjoying Matt's comments on pain medication. The ability to relieve pain is one of the miracles of modern medicine and one that should not be squandered. There are always going to be limitations to any system but it is odd that we don't focus on those in need of pain relief first and abuse second.
After all, we don't ban driving just because some driver's are reckless or irresponsible.
Opioid addiction is bad, and it’s perfectly reasonable for policymakers to try to minimize its incidence. But short of dying, experiencing chronic pain is one of the worst things that can happen to someone. The correct ordering of priorities is to try to make sure that nobody suffering from treatable chronic pain goes untreated, and then try to minimize addiction risks within that framework. The view that people suffering pain should get relief subject to the binding constraint that we need to fight addiction has a nice Puritan logic to it, but it doesn’t make any real sense.
I have been enjoying Matt's comments on pain medication. The ability to relieve pain is one of the miracles of modern medicine and one that should not be squandered. There are always going to be limitations to any system but it is odd that we don't focus on those in need of pain relief first and abuse second.
After all, we don't ban driving just because some driver's are reckless or irresponsible.
Sunday, January 23, 2011
Health care and economies of scale
As mentioned before, I always like to be cautious when drawing conclusions from different countries, cultures and hemispheres. With that caveat out of the way, this Marketplace story about an Indian health insurance program is definitely interesting and possibly important as well.
For another story of medical developments coming from unlikely places, check out this story on battlefield medicine (this time from NPR).
Shetty and his team of 40 cardiac surgeons at Narayana Hrudayalaya Hospital are used to conversations like this one. They perform many more operations each year than comparable U.S. hospitals.Shetty: This is a thousand-bed heart hospital. We do about 33 to 35 heart surgeries a day.
About a third of all of the patients at Shetty's hospital are farmers from rural villages. They're here because they have something called Yeshaswini insurance. It doesn't cover routine doctors visits for, say, a cough or a cold, but the insurance does cover all surgical procedures. The farmer pays approximately three cents a month; the government puts in one and a half cents and farmers cooperatives operate the program. Shetty believes there's strength in numbers.
For another story of medical developments coming from unlikely places, check out this story on battlefield medicine (this time from NPR).
Saturday, January 22, 2011
Damned, pinko entrepreneurs
Whether in business, education, or any other field, what works there might not work here. With that caveat in mind, take a look at "In Norway, Start-ups Say Ja to Socialism" by Max Chafkin in Inc. magazine (or, if you're in a hurry, you can go to Felix Salmon's pithy analysis of the article and get much of the meat without the local color).
Here's the keystone of the piece:
According to much of the conventional economic wisdom, we should be leaving all of these countries behind in terms of entrepreneurs and new businesses. Their progressive taxes and extensive social safety nets should leave people with little incentive to work hard while their restrictive regulations (in Norway "firing an employee for cause typically takes months, and employers generally end up paying at least three months’ severance.") should make running a nimble and efficient business virtually impossible, but what should happen clearly isn't.
It would be interesting to see Greg Mankiw's explanation for this.
Here's the keystone of the piece:
Norway is also full of entrepreneurs like Wiggo Dalmo. Rates of start-up creation here are among the highest in the developed world, and Norway has more entrepreneurs per capita than the United States, according to the latest report by the Global Entrepreneurship Monitor, a Boston-based research consortium. A 2010 study released by the U.S. Small Business Administration reported a similar result: Although America remains near the top of the world in terms of entrepreneurial aspirations -- that is, the percentage of people who want to start new things—in terms of actual start-up activity, our country has fallen behind not just Norway but also Canada, Denmark, and Switzerland.I tend to be distrustful of international comparisons, but, as I've mentioned before, if you're going to do it, Canada is probably where to start. "Demographically, economically, culturally and historically, Canada would seem to be the obvious country to look to when trying to determine the effectiveness of potential U.S. policies..." Having our northern neighbor on the list makes me more inclined to give its obvious implications some weight and those implications conflict with a lot of what we've been told about business-friendly policies.
According to much of the conventional economic wisdom, we should be leaving all of these countries behind in terms of entrepreneurs and new businesses. Their progressive taxes and extensive social safety nets should leave people with little incentive to work hard while their restrictive regulations (in Norway "firing an employee for cause typically takes months, and employers generally end up paying at least three months’ severance.") should make running a nimble and efficient business virtually impossible, but what should happen clearly isn't.
It would be interesting to see Greg Mankiw's explanation for this.
Subscribe to:
Posts (Atom)