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This is an excellent policy brief that is a well-written, fast, easy read. You can still see it here. Alex Tabarrok flagged it here. And Matthew Yglesias has a great discussion of the politics and the economic merits in his post “The Case of the Vanishing Policy Memo.” But on the economic merits, the policy brief speaks well for itself.
I have always thought the actions of men the best interpreters of their thoughts.
Essay Concerning Human Understanding (1689)
Jonathan Haidt, in The Righteous Mind: Why Good People Are Divided by Politics and Religion, pp. 303, 304:
The next time you go to the supermarket, look closely at a can of peas. Think about all the work that went into it–the farmers, truckers, and supermarket employees, the miners and metalworkers who made the can–and think how miraculous it is that you can buy this can for under a dollar. At every step of the way, competition among suppliers rewarded those whose innovations shaved a penny off the cost of getting that can to you. If God is commonly thought to have created the world and then arranged it for our benefit, then the free market (and its invisible hand) is a pretty good candidate for being a god. You can begin to understand why libertarians sometimes have a quasi-religious faith in free markets.
Now let’s do the devil’s work and spread chaos throughout the marketplace. Suppose that one day all prices are removed from all products in the supermarket. All labels too, beyond a simple description of the contents, so you can’t compare products from different companies. You just take whatever you want, as much as you want, and bring it up to the register. The checkout clerk scans in your food insurance card and helps you fill out your itemized claim. You pay a flat fee of $10 and go home with your groceries. A month later you get a bill informing you that your food insurance company will pay the supermarket for most of the remaining cost, but you’ll have to send in a check for an additional $15. It might sound like a bargain to get a cartload of food for $25, but you’re really paying your grocery bill every month when you fork over $2000 for your food insurance premium.
Under such a system, there is little incentive for anyone to find innovative ways to reduce the cost of food or increase its quality. The supermarkets get paid by the insurers, and the insurers get their premiums from you. The cost of food insurance begins to rise as supermarkets stock only the foods that net them the highest insurance payments, not the foods that deliver value to you.
As the cost of food insurance rises, many people can no longer afford it. Liberals (motivated by Care) push for a new government program to buy food insurance for the poor and the elderly. But once the government becomes the major purchaser of food, then success in the supermarket and food insurance industries depends primarily on maximizing yield from government payouts. Before you know it, that can of peas costs the government $30, and all of us are paying 25% of our paychecks in taxes just to cover the cost of buying groceries for each other at hugely inflated costs.
In 2009, [David] Goldhill published a provocative essay in the Atlantic titled “How American Health Care Killed My Father”: One of his main points was the absurdity of using insurance to pay for routine purchases. Normally we buy insurance to cover the risk of a catastrophic loss. We enter an insurance pool with other people to spread the risk around, and we hope never to collect a penny. We handle routine expenses ourselves, seeking out the highest quality for the lowest price. We would never file a claim on our car insurance to pay for an oil change.
Miles gives a delayed response to Jean-Paul Sartre on Twitter
Jean-Paul Sartre said:
The best work is not what is most difficult for you, it is what you do best.
From my own observation, of others as well as myself, let me say this:
When you are good at something, the way it looks to you is that you are OK at it, but everyone around you is messing up.
When things look that way, be patient with those around you and realize that you may have found your comparative advantage–a comparative advantage that might help you go far.
Here is a highly recommended link to Matt O'Brien’s post “The Scariest Jobs Chart, Private Sector Edition.” Matt’s job charts are beautifully laid out. His concise discussion of the Fed’s changing pattern of response to recessions is also excellent.
I found Noah’s argument in his post “Japanese Poverty: Who’s to Blame” intriguing. For comparison, see what Bill Dickens has to say about the poor in the U.S. in “Bill Dickens on Helping the Poor.”
This post of Noah’s rings true to me from the time I have spent in Japan.
I thought you might be interested in this question Evan Soltas posed to me (as he started thinking about what became his post “An Alternate View of Markets”) and my answer. I share this with his permission.
Question: I’m thinking about a question which might become a blog post, but before I go anywhere with it, I wanted to put my thoughts out there to someone who will be more knowledeagble on these questions.
Do you know / have read anything about supply-and-demand equilibriums which are made unstable by certain conditions – in particular, I’m thinking about a stylized micro model in which demand is determined to a significant extent by recent changes in price, and another in which supply is determined similarly by demand, or rather the nominal expenditure level, averaged over a long period of time.
That probably sounds absurdly vague or basic… Where I suppose I’m going with this is the first model appears to character some asset markets, particularly housing. The second is about hysteresis, particularly as it pertains to labor.
I understand those specific stories pretty well as a qualitative matter, but what I’m interested in here is the abstracted version of unstable systems, and general implication that in a very broad class of markets, the vanilla supply-and-demand story irons out too many wrinkles. Those wrinkles, in sum, point to a rather different model – one which exhibits significant path-dependent behavior, tends not to a single equilibrium but to multiple equilibria or just instability.
Maybe one way to phrase the question is: to what extent does the emphasis upon supply-and-demand blind economists? Are these portentous footnotes on the supply-and-demand really more than footnotes? Are they the “real story”? Thinking about exchange rates, we know that PPP doesn’t explain everything, and that forecasting based on fundamentals does a pretty poor job of things – are economists pretending to see equilibrating systems in realities which are more brittle, fragile, and chaotic?
Answer: This sounds like a great topic for a post. The main thing I would advise would be to preface things as what can happen when there are behavioral (=psychological, non-neoclassical) things going on in people’s behavior. If you do that, you don’t have to worry too much about being wrong if you have good intuition for a result. But when everyone in sight is optimizing from here to the end of time, there are some very powerful, and subtle, stabilizing influences. What multiple equilibria there are in fully optimizing models don’t usually seem very plausible to me: they require extreme parameter values. There are economists who study that kind of thing, but it usually degenerates into mathematical fun and games rather than serious economics. If your story is based on someone’s non-optimizing behavior, on the other hand, it could be very robust. Though even then, you have to worry about whether a minority of fully optimizing people could stabilize things. (The noise trader literature worries about that.)
A few years back, economists and other social scientists and technical experts at RAND and the University of Michigan put together a grant proposal focused on seeing what can be done with web surveys. Thanks to funding provided by the National Institute on Aging (part of the National Institute of Health), we were able to find out the answer. Leaving out many details, the basic answer is that, except for a few things that have to be done in person, web surveys are at least as good, and usually better, than other survey methods. RAND’s American Life Panel arose out of that collaboration (though it is now an independent RAND survey that has a wide range of clients other than government research agencies). I can’t pretend to be objective about the American Life Panel. As part of a large team, I have been involved in it from the beginning and I love it.
An important distinction has to be made between commercial web surveys, which use samples of convenience (often trying to match certain broad demographic frequencies to the population as a whole) and scientific web surveys that make great efforts to get as close to a representative sample as possible–even on characteristics that are unmeasured. The American Life Panel is just such a scientific web survey. Every effort is made not only to draw respondents randomly from the population as a whole, but also to give web access to those randomly chosen who don’t already have web access.
By contrast to most surveys, which fairly soon became calcified under the weight of a standard set of questions that are asked again and again, taking up most of the available survey time, under Arie Kapteyn’s leadership, the American Life Panel (ALP) has grown in power and reach under a unique philosophy of experimental modules initiated in a relatively decentralized way that over time add up to much more than the sum of the parts. At this point, data from a huge variety of experimental modules can now be compared to data on ALP respondents that duplicates most of what is collected from respondents to Michigan’s Health and Retirement Study and data that duplicates a big subset of what is collected from respondents to Michigan's Cognitive Economics Study. Arie’s commitment to supporting “bold, persistent experimentation” in surveys augurs well for the future of the American Life Panel.
Because the American Life Panel has only recently come into its own, most economists don’t realize what is there, what can be done with the existing data on the ALP, and what can be done by collecting new experimental data to combine with the ALP’s existing data. For young economists in particular, I am confident there are many, many dissertations hiding in the data already collected, aside from everything that is coming.
Just for fun, I have put a link under the illustration to the ALP’s election forecast webpage, based on survey questions that probe for probabilities as opposed to discrete answers–a style of survey question that has been advocated most forcefully by Chuck Manski and his coauthors. Also, unlike typical election polls, the results you see above and at the election forecast webpage are based on panel data: the same people are asked the questions repeatedly, so that the changes you see are more likely to be genuine changes in opinion, instead of random fluctuations in the set of people surveyed. (Note: the election polling behind the picture above is not supported by any government agency.)
Update: Brad DeLong tweeted to me this interesting comment:
RAND’s reinterview method is a treatment that over time turns low-info voters into high info voters. That’s a powerful bias…
My reaction is that if Brad is right, the views of a high-information sample of otherwise typical voters from a representative sample is itself very interesting. The question that Brad raises is a good example of the value of an experimental survey–to be able to discover and investigate, or rule out, effects such as that.
The end of rent control is very good for housing values, even for never controlled property. Here is Owen Zidar’s post that clued me in to this paper, with the abstract, and here is the academic paper by David Autor, Christopher Palmer and Parag Pathak.
Instead of thinking of rich countries and poor countries, rich regions an poor regions, this article by Enrico Moretti recommends thinking about rich cities and poor cities. Here are some of the highlights–the striking outcomes and the paradox that distance still matters in a wired world. One element of the story, at least in the U.S., is the rise of industries in which human capital is more important than physical capital. Highly educated people–who are the key resource for those industries–often want to congregate in interesting cities. (That claim is the main point of Richard Florida’s book The Rise of the Creative Class.)
The economic map of America today does not show just one country – it shows three increasingly different countries. At one extreme are America’s brain hubs – cities like Seattle, Raleigh-Durham, Austin, Boston, New York and Washington DC – with a thriving innovation-driven economy and a labor force among the most creative and best paid on the planet. The most striking example is San Francisco, where the labor market for tech workers is the strongest it has been in a decade. At the other extreme are cities once dominated by traditional manufacturing – Detroit, Flint, Cleveland – with shrinking labor force and salaries.
In 1980, the salary of a college educated worker in Austin was lower than in Flint. Today it is 45 percent higher in Austin, and the gap keeps expanding with every passing year. The gap for workers with a high school degree is a staggering 70 percent by some estimates. It is not that workers in Austin have higher IQ than those in Flint, or work harder. The ecosystem that surrounds them is different.
In China, Shanghai has reached a per capita income close to that of a rich nation. Its students outperform American and European students in standardized tests by a wide margin. Its public infrastructure is better than that of many American cities. But agricultural communities in western China have made much less progress.
Despite all the hype about exploding connectivity and the death of distance, economic research shows our salary, productivity and creativity increasingly depends on the place where we live.
Video conferencing, e-mail, and Skype have not made a dent in the need for innovative people to work side by side. In fact, that is more important than ever. Thousands of well-educated innovative workers are now moving to San Francisco and Silicon Valley, many attracted by jobs in social networking. They will produce software intended to create virtual communities that erase distance and allow us to share ideas and information from any corner of the world. Ironically, in order to do that successfully, all this talent must concentrate into a single location. Research shows that our best ideas still reflect the daily, unpredictable stimuli that we receive from the people we come across and our immediate social environment.
This op/ed by Nicholas Kristof is a classic that Greg Mankiw links to. I use it in my class to make two points:
A number of policies recommended by those who say they care about the poor have the common element of saying, in effect:
If you can’t or won’t create a good job, don’t create a job at all.
For some people, a “bad job” is a lifeline. And if we insist that only good jobs should exist, they will have no job.
I think there is another element behind opposition to sweatshops. When people in poor countries are suffering before the arrival of an American company in their backyard, that hideous suffering from poverty is out of sight for us in America. But as soon as the American company arrives to give the opportunity of taking what look like bad jobs to us, if they choose to, the somewhat lesser suffering of their poverty after taking the “bad job” seems like the fault of the American company for not making the jobs nicer. In fact the company has helped them, but we only see the suffering from poverty after, not the hideous suffering from worse poverty before.
One factor that can make it easier to blame the American company for the suffering left after providing the job is that some of the corporate executives involved in setting up and running the new factory in a poor country may, in fact, be uncaring, unfeeling people (though I doubt this is true anywhere near as often as people suppose). But even if many of the corporate executives involved in setting up and running the new factory are uncaring, unfeeling people, it doesn’t change the fact that, by their actions of setting up and running the factory, they have made people’s lives better. They could have made people’s lives better still if they had taken a bigger fraction of their personal earnings and donated it to helping the poor than they actually did, but that is something that can be said for almost every American.
One policy change that could increase what Americans do to help the desperately poor in other countries is the program of “public contributions” I recommend in my post “No Tax Increase Without Recompense.” That program of public contributions would dramatically increase the amount of assistance American give to the desperately poor in other countries. Government-funded foreign aid is very unpopular–and often is relatively ineffective because much of it is channeled through corrupt foreign governments. But many individuals (with whatever money they have set aside to donate to good causes) are attracted by the idea of helping the desperately poor.
Economists use utility functions to represent many aspects of people’s preferences. Even when an economic model has been simplified to (in some sense) have only one good–let’s call it “consumption”–the curved, concave shape of a utility function like the one above can be used to represent any of the following:
If there are two goods–lets call them “consumption” and “leisure,” the curved, concave shape of the part of the utility function that depends on consumption can be used to represent how the need to work to be able to afford more consumption changes as the amount of consumption one is doing already increases–whether that increase in consumption occurs from the passage of time or because of luck. I mention the many things that concave utility functions are used to represent because it is not at all clear that the utility function one should use to represent one of these things should look the same as the utility function one should use to represent another. In this post, I want to focus on just one thing a concave utility function can be used to represent: how people feel about inequality.
I want to emphasize that finding a good utility function to represent how people feel about inequality requires asking about people how they feel about the situation of the rich and the poor. There is no guarantee, for example, that you could ask about someone’s attitudes toward risk and get a good read on how they feel about inequality.
Yoshiro Tsutsui, Fumio Ohtake (both of the University of Osaka) and I arranged to collect data on a rider to the February, 2005 University of Michigan Survey of Consumers that asked directly about people’s feelings about the situation of the rich and the poor. The sample was the same sample as that used for the University of Michigan Consumer Confidence numbers–a sample intended to be representative of the adult U.S. population. This post gives a preview of some of the results from an academic paper we are working on, ably assisted by Daniel Reck and Fudong Zhang. It follows up on what I said about the poor and the rich in my first post “What is a Supply-Side Liberal?” In this post, I am taking the overall philosophical perspective is that of Utilitarianism, as developed by modern welfare economics using a social welfare function.
Yoshiro, Fumio and I wanted to ask questions that got at the key issues while minimizing reactions based in a shallow way on political ideology. To the extent these questions are about redistribution, the intent is to get at only the benefits of redistribution, as distinct from the costs of redistribution (say through tax distortions).
We began by asking
It is often said that one thousand dollars is worth more to a poor family than to a rich family. Do you agree?
90% of all respondents agreed. Then we went on to ask questions to probe how much more $1000 is worth to a poor family than a rich family. I won’t give the whole sequence of questions here. Let me just choose two questions that are especially revealing about what the typical adult American thinks. When we asked
Think of two families like yours, one with half the income of your family, the other with the same income as your family. Which would make a bigger difference, one thousand dollars to the family with half your family’s income or four thousand dollars to the family with an income like yours?
66% of all respondents thought the $1000 to the poorer family with half the income would make a bigger difference than $4000 to the richer family. (Everyone who had disagreed from the outset with the idea that $1000 is worth more to a poor family than to a rich family was counted as thinking the $4000 to the rich family would make a bigger difference.) When we asked
Think of two families like yours, one with half the income of your family, the other with the same income as your family. Which would make a bigger difference, one thousand dollars to the family with half your family’s income or eight thousand dollars to the family with an income like yours?
66% of all respondents though the $8000 to the richer family would make a bigger difference than $1000 to the poorer family with half the income. Focusing on the middle opinion, I read this evidence as saying that the median adult American thinks that $1000 to a poorer family with half the income would have about the same impact on that family’s life as an amount of money somewhere between $4000 and $8000 to the richer family. Stretching the interpretation a little more, I am going to take the utilitarian perspective and talk about this median view as “inequality aversion” and as an indication that most people think there would be some benefit to redistribution, though the costs might sometimes–or even often–outweigh the benefits. I do think that view represents the views of those in the middle of the political spectrum.
How can we represent these views in an inequality-aversion utility function? To make the numbers a little easier, let me lowball the degree of inequality aversion a little, and act as if $1000 to the poorer family with half the income had exactly the same life-impact as $4000 to the richer family. Let me also simplify by assuming that those ratios hold regardless of the initial income level. With those simplifications, some moderately advanced mathematics implies that the utility function must be of the form
U© = A - B/C
where A and B are some positive numbers and C is the level of consumption spending of an individual or family of a given size. The reason A and B are not determined is that we need some yardstick. It is easy to forget, but almost all measurement requires the choice of some arbitrary yardstick. The exact length of an Earth day is an accident of how our solar system formed and the geological era we are in, but we used it to develop units of time. Similarly, a kilometer was originally intended to by a 1/40,000 of the circumference of the Earth. In addition to the size of units of measurement, we also often need arbitrary starting points. Our measures of longitude start at 0 at Greenwich, England, which has to do with historical accidents of geopolitical and scientific power and influence at the time the system of latitude and longitude was chosen.
Fortunately, no economic logic depends on the values of A and B. The value of A doesn’t matter because for economic decisions because in any decision it is the comparison of how well-off one is under two or more possible situations that matters. When comparing any pair of options, the difference in utility between those two choices will leave “A” cancelled out. This is analogous to the fact that the path from Ann Arbor to the Detroit Metro Airport would be the same even if, in an egocentric change, Ann Arbor were the starting point for longitude instead of Greenwich, England. And the path from Ann Arbor to the Detroit Metro Airport would also be the same if Kabul, Afghanistan were the starting point for longitude. The value of B doesn’t matter because using one value of B rather than another is like the choice to measure distances in miles rather than kilometers, or in inches rather than yards. The real-world answers are going to come out the same.
For convenience–and only for convenience, since it doesn’t matter–I have chosen A=0 and B=1 for the graph at the top of this post. It may seem odd that utility is then always negative for this functional form, but utility being represented by a negative number is literally meaningless except in relation to what 0 utility means. With A=0, a utility of zero is material bliss–the maximum utility possible. So negative utility simply means that one has fallen short of material bliss.
Marginal utility is the slope of the utility function. It tells how much extra utility there is from a little more consumption. Even before choosing A=0 and B = 1, we can say that marginal utility here is
Marginal Utility = U’© = B/[C squared]
Notice how A has already dropped out. After choosing B=1, marginal utility becomes
Marginal Utility = U’© = 1/[C squared]
This means that doubling consumption C will reduce marginal utility to one quarter of what it would have been at the lower level of consumption, so $4000 at that higher level of consumption means only as much as $1000 at a consumption level half as big. What this shows is only that the utility function (with its associated slope, marginal utility) is doing OK at representing what we designed the utility function to represent: $1000 to a poorer family with half the income meaning the same as $4000 to a richer family.
It is my contention that bringing the discipline of mathematics to discussions of redistribution is useful in informing the debate about redistribution. Let me give just one example. Looking at the utility function at the top of the post, the slope shows how much a little extra money means to someone at each level of consumption. The difference between the slope at different levels of consumption shows how much benefit there is from redistributing from a richer to a poorer individual or family–a benefit that then needs to be weighed against the costs–for example costs to freedom from the compulsion of taxes, or costs from people’s efforts to evade and avoid taxes. If one thinks of a consumption of 1 as representing the middle class, a consumption of 4 as representing the rich and a consumption of ¼ as representing the poor, one can see that there is a much bigger difference in the slope for the poor minus the slope for the middle class than the difference in the slope for the middle class minus the slope for the rich. So with a utility function that has the slope depend inversely on the square of consumption as here, there are much bigger gains from redistributing dollars from the middle class to the poor than there are from redistributing dollars from the rich to the middle class.
Screen shot of the illustration for my column “More Muscle than QE3: With an Extra $2000 in their pockets, could Americans restart the U.S. economy?” on the Quartz website.
I am one of the columnists on the Atlantic’s new world business website Quartz (qz.com). I expect to have columns appear there approximately weekly, plus some quick reactions to breaking economic events.
At Quartz, I am working with Mitra Kalita and Lauren Brown.
Question. Professor Kimball - Former student here. Question. With QE3 recently announced, conversation about monetary policy and the Federal Reserve is picking up once again. I just got done watching one of those Institute for Humane Studies LearnLiberty videos explaining why we should end the Fed. It seems like most mainstream economists don’t take this view. Could you tell us your thoughts?
Answer. It is good to have a stable track of prices and output at its natural level. The Fed’s adjustments of the money supply make that possible. Without the Fed we would be at the mercy of other monetary winds–which could be anything from gold supply and demand to the vagaries of free banking. We would be particularly vulnerable to financial crises like the one we suffered in 2008. Without the Fed’s decisive action, the Great Recession would have been much worse. David Wessel’s book “In Fed We Trust: Ben Bernanke’s War on the Great Panic” is a good account. Unfortunately, that decisive action had to include bailing out big banks, which is a big part of why the Fed is unpopular now.
Economists have emphasized for some time now how important it is to have an independent central bank such as the Fed when inflation is too high to be able in order to be able to do the unpopular things necessary to bring inflation down. In the last few years, we have seen how important it is to have an independent central bank such as the Fed when inflation is too low in order to be able to do the unpopular things (such as bank bailouts and quantitative easing) necessary to bring inflation up–and in particular to avoid getting too close to negative territory. The Fed doesn’t always make the right decisions, but in general it is responsive to good economics in a way that other institutions often are not.
Ireland is in trouble. But outside Ireland, many economists think it is doing fine. Why? Stephen Donnelly argues that part of the answer turns on the difference between Gross Domestic Product and Gross National Product. Gross Domestic Product (GDP) is the value of goods and services produced within a country each year or quarter. Gross National Product (GNP) is the value of goods and services produced by the labor, capital and other resources owned by citizens of a country each year or quarter. For most countries, GDP and GNP are close to each other, but Ireland has attracted so much foreign investment that a large share of its capital stock in owned by foreigners. Thus, Ireland’s GNP is much lower than its GDP.
The presence of the foreign-owned capital raises wages in Ireland, so it is a good thing. But the income from the foreign-owned capital itself does not belong to Irish citizens, and so is not much help when it comes to handling the debt of the Irish government–especially since the Irish government needs to keep the promise to tax foreign-owned capital lightly that it made in order to attract foreign investment.
Much is written and said about the impact of energy imports and natural resources on output. But a basic fact makes it hard for energy imports and natural resources to matter as much as people seem to think they do: natural resources account for a small share of GDP–on the order of 1% = .01, and energy imports measured as a fraction of GDP are also on the order of 1% = .01. Even a 20% increase in the price of imported oil, for example, should make overall prices go up something like a .01 * 20% = .2%. It should take a huge increase in the price of oil to make overall prices go up by even 1%. Am I missing something?
It is a little dated, but here is what I found online about oil imports as a percentage of GDP. (I’ll gladly link to a more recent graph instead if there is one.) 2% of U.S. GDP is near the high end for the value of our oil imports in the past. And here are World Bank numbers for factor payments to natural resources as a percentage of GDP.
