Month: July 2013
Chen and Rey show an additional intuitive reason for loss leading: screening. Imagine there are two goods, A and B. Large stores sell both, while specialty or discount retailers sell only B, with unit costs cLA, cLB and cSB; the specialty retailer has a cost (or quality) advantage in B. Let consumers dislike shopping, with a heterogeneous cost of shopping for shopper i of s(i) for each store they patronize. Let consumers have homogeneous unit demand (vA>cLA and vB>cLB) for both A and B. If only the large store exists, it can’t screen by shopping cost, so it just sets a uniform price for the bundle of goods A and B to maximize profit; this means that those with low shopping costs will earn some rents since I keep the price low enough that even high shopping cost folks buy. If, on the other hand, the specialty retailers exist, the large store can sell B at below cost, keeping the combined price of A+B the same as before. This ensures that the large store continues to extract full rent from the high shopping cost buyers, and allows full extraction of willingness to pay for good A from low shopping cost buyers (who now visit both stores).
The authors prove that whenever the large retailer finds it worthwhile to price such that at least some shoppers buy both A and B at the large store, then that store will loss lead with B. As long as the distribution of shopping costs is sufficiently high, the large store earns higher profits when they face small store competition than under monopoly, since the small store can be used to screen for shopping costs, and hence for willingness to pay. This flavor of result is general to having only one competitor rather than a competitive fringe of small firms, as well as other loosened assumptions. Banning loss leading increases total social welfare as well as consumer surplus; those who shop at both venues are made better off, as are those who have shopping costs just too high to make shopping at both venues worthwhile, while every other consumer and the large firm earn the same surplus.
Iceland’s expanded debt relief programme in Iceland is targeting too broad a demographic, the OECD has warned.
By the end of 2013, Iceland’s banks will have forgiven almost €250 billion kronur (€1.6 billion) in consumer debt, equal to more than 14 per cent of gross domestic product, according to estimates from the Icelandic Financial Services Association.
Here is a bit more.
1. Saga: First choice goes to Njal’s Saga. It’s the clearest and crispest of the lot.
2. Novel, modern: How about Audur Ava Olafsdottir’s The Greenhouse? This is a boom area. There are one hundred twenty Icelandic novels translated into German each year [correction of earlier estimate].
3. Popular music: Sigur Ros, Agaetis Byrjun. This CD has a transcendental and also anthemic sound, even if the group never quite lived up to their initial promise. Bjork albums I usually find pretentious and I would rather listen to her earlier group The Sugar Cubes.
4. Annual tournament: Ram groping.
5. Sea bird: The puffin, followed by the guillemot.
6. Video: Daniel Tammet learns how to speak Icelandic in a week. That’s hard.
7. Economist: Erik Brynjolfsson, although I do not believe he was born in Iceland.
9. Movie, set in: Die Another Day, an underrated Bond movie in my view.
10. Vista: How about Höfn?
I am excited that we are arriving this morning. And as for the food, don’t forget the glories of skyr.
In Japan, where palm reading remains one of the most popular means of fortune-telling, some people have figured out a way to change their fate. It’s a simple idea: change your palm, change the reading, and change your future. All you need is a competent plastic surgeon with an electric scalpel who has a basic knowledge of palmistry. Or you can draw the lines on your hand with a marker and let him work the magic you want.
Re: my post immediately below on signaling, Bryan thinks I haven’t answered his question about the importance of signalling. But I have, he is just confused because I don’t use the exact same normalization as he does. In any case, I postulate the wage return to signalling as going away within five years, in say a career of forty years, then with the measure adjusted for the presence of capital and resource income. You can express that in terms of totals, variations, percentages, as you wish but the point remains that signaling is only a temporary factor, and overall only somewhat of a marginal factor (5-10%?) in explaining the overall evolution of wages. That is why it has lost ground to human capital approaches, all the more so with increasing inequality. (One can believe all of that and still think, as I do, that we could organize current education more efficiently and at lower cost.) I also stand by my points that insisting on the break down is missing the more important points about indeterminacy and nestedness and those points too can be applied to any normalization of the units. It would be more useful if Bryan would outline where he disagrees with my assessment, as the entire chain of reasoning is laid out pretty explicitly.
By the way, the easiest way to boost the contribution of signaling is to invoke the “you got your first job by signaling and then from that job quickly gained persistent extra human capital” argument, but even then that increment can, under traditional measures, be assigned to human capital. (You don’t want to rule out all human capital influences, on the grounds that signaling helped create them, any more than you wish to classify gains from signaling as human capital, if the human capital helped you get into the position to signal. But if that doesn’t convince you, revisit the earlier point about indeterminacy, as you can see that the marginal products for human capital and signaling will sum to well over one hundred percent.)
On Twitter Bryan asks me:
Would you state your human capital/ability bias/signaling point estimates using my typology?
He refers to this blog post of his, though he does not clearly define the denominator there: is it percentage of what you spend on education or explaining what percentage of the variation in lifetime earnings? I’ll choose the latter and also I’ll focus on signaling rather than trying to separate out which parts of human capital are from birth and which are later learned. My calculations are thus:
1. I don’t wish to count “credentialed” occupations, where you need a degree and/or license, but you are reaping rents due to monopoly privilege. It’s neither human capital nor signaling (it’s not about intrinsic talent), though you could argue it is a kind of human capital in rent-seeking. In any case, let’s focus on private labor markets without such barriers.
2. Most capital and resource income is due to factors better explained by human capital theories or due to inheritance. That is more than a third of earnings right there. Note that the higher is inequality, the less the signaling model will end up explaining. That is one reason why the signaling model has become less relevant.
3. Depending on job and sector, what you’ve signaled, as opposed to what you know, explains a big chunk of wages in the first three to five years of employment. Within five years (often less), most individuals are earning based on what they can do, setting aside credentialism as discussed under #1. Here is my earlier post on speed of employer learning.
Keep in mind that everyone’s wages change quite a bit over their lifetime and that is mostly not due to retraining (i.e., changes in the educational signal) in the formal sense, as most people stop formal retraining after some point. The changes are due to employer estimates of skill, modified by bargaining power. In this sense all theories are predominantly human capital theories, whether they admit it or not.
To be generous, let’s give Bryan the full first five years of income based on signaling alone, out of a forty year career. And let’s say that on average wages rise at the rate of time discount (not true as of late, but a simplifying assumption and I think Bryan believes in a claim like this anyway.)
How much of income is explained by signaling? I’m coming up with “1/8 of 2/3,” the latter fraction referring generously to labor’s share in national income. That will fall clearly under ten percent, but recall I’ve inserted some generous assumptions here.
Bryan wants to call me “a signaling denialist,” yet I see signaling as still very important for understanding some aspects of the labor market. But it’s far from the main story for the labor market as a whole, especially as you move into the out years.
That all said, this “decomposition” approach may obscure more than it illuminates. Let’s consider two parables.
First, imagine a setting where you need the signal to be in the game at all, but after that your ingenuity and your personal connections explain all of the subsequent variation in income. Depending what margin you choose, the contribution of signaling to later income can be seen as either zero percent or one hundred percent. Signaling won’t explain any of the variation of income across people with the same signal, yet people will compete intensely to get the signal in the first place.
Second, in a basic signaling model there are two groups and one dimension of signaling. That’s too simple. A signaling model implies that a worker is paid some kind of average product throughout many years, but of course the reference class for defining this average product is changing all the time and is not, over time, based on the original reference class of contemporaneous graduating peers. For the purposes of calculating your wage based on a signal, is your relevant peer group a) all those people who got out of bed this morning, b) all those people in the Yale class of 2012, or c) all those who have been mid-level managers at IBM for twenty years? This will change as your life passes.
So there’s usually a signaling model nested within a human capital model, with the human capital model determining the broader parameters of pay, especially changes in pay. The employer’s (reasonably good but not perfect) estimate of your marginal product determines which peer group you get put into, if you choose to invest in additional signals (or not). The epiphenomena are those of a signaling model, but the peer group reshufflings over time are ruled by something else. Everything will look like signaling but again over time signaling won’t explain much about the variation or evolution in wages.
Seeing the relevance of those “indeterminacy” and “nested” perspectives is more important than whatever decomposition you might cite to answer Bryan’s query.
Instead of trying to ban new drugs as fast as they are
created, New Zealand has taken a different
approach, it will allow synthetic drugs to be sold so long
as they pass safety trials.
It’s the first nation
to take a dramatically different approach to psychoactive
substances like party pills and synthetic marijuana… [that] go by names like bath salts, spice or
In a 119-to-1 vote on Thursday, the country’s parliament
passed the Psychoactive Substances Bill, establishing a framework
for testing, manufacturing and selling such recreational
The law does not overturn existing bans
such as on marijuana although that issue is likely to be revisited.
File this sentence under the culture that is New Zealand:
The drug law enjoyed broad support although there
was debate over whether animal testing would be required in the
1. Derek Sayer, Prague, Capital of the Twentieth Century: A Surrealist History. There needs to be a single word for “excellent if read in conjunction with other books on the same topic, though a quality but wasted effort if read alone.” This book is that.
2. Tom Miller, China’s Urban Billion: The Story Behind the Biggest Migration in Human History. Excellent on land use but also one of the very best books on the Chinese economy, as seen through the lens of land. Interesting on almost every page.
3. Kate Christensen, Blue Plate Special: An Autobiography of My Appetites. More a memoir than a food memoir (which is how it is being marketed), the subtitle is thus better than the title. This is an excellent example of the “read smart books by people who are totally unlike you” principle. I finished it in one sitting, and it takes a place with The Great Man as one of my two favorite Christensen books.
4. John C. Williams (not the composer), “A Defense of Moderation in Monetary Policy” (pdf). A beautiful title and full of truth.
5. Reiner Stach, Kafka: The Years of Insight. Brings the author and his milieu to life to a remarkable degree and shows Kafka was a comic author after all.
New from The Guardian:
Microsoft has collaborated closely with US intelligence services to allow users’ communications to be intercepted, including helping the National Security Agency to circumvent the company’s own encryption, according to top-secret documents obtained by the Guardian.
…The NSA has devoted substantial efforts in the last two years to work with Microsoft to ensure increased access to Skype, which has an estimated 663 million global users.
One document boasts that Prism monitoring of Skype video production has roughly tripled since a new capability was added on 14 July 2012. “The audio portions of these sessions have been processed correctly all along, but without the accompanying video. Now, analysts will have the complete ‘picture’,” it says.
In a new paper, Robert Higgs reports:
Until World War II and the postwar years, when the federal bureaucracy institutionalized the government’s preferred method for calculating national income, economists offered sound arguments for excluding government spending from estimates of gross domestic product. Using their general approach reveals that the private economy’s performance for the past thirteen years has been only somewhat better than complete stagnation.
I don’t think that zero counting of government consumption is the correct approach here, but this is nonetheless an interesting exercise. Keep in mind that even if government outputs are highly useful, many of them are closer to intermediate than final products. In other cases the output may be useful, and a final product, but not valued at actual market prices. There is then still something to be learned by considering and segregating, if only temporarily, those parts of gdp which are sold at true market prices.
For the pointer I thank Daniel B. Klein.
I cannot recall if I have linked to this Ricardo Reis paper (pdf) before, but it is the place to start reading on this topic. Here is the abstract:
The Portuguese Slump and Crash and the Euro CrisisBetween 2000 and 2012, the Portuguese economy grew less than the United States during the Great Depression or than Japan during the Lost Decade. This paper asks why this happened. It makes four contributions. First, it describes the main facts between 2000 and 2007, proposing a narrative for why the country did not grow. Second, it puts forward a model of credit frictions where capital inflows are misallocated, so that more integrated capital markets can lead to losses in productivity and an expansion of unproductive nontradables at the expense of productive tradables. Third, it argues that this model can account for the Portuguese slump, as a result of misallocated capital inflows and increases in taxes. Fourth, it shows that the crash after 2010 came with a sudden stop of capital flows, combined with fiscal austerity, downward nominal rigidities, and a diabolic loop between banks and sovereigns.
4. You are not an artisan. A bit meandering but interesting and multi-faceted and with some depth. I liked this sentence: “In other words, we’re more afraid of machines taking away our social status than our jobs.” And here is the al Qaeda vacuum cleaner.
5. Japanese markets in everything, yakuza magazine: “…it actually boasts of a poetry page and even fishing diaries from its senior members.”