There is a new paper from Andrew M. Francis and Hugo M. Mialon:
In this paper, we evaluate the association between wedding spending and marriage duration using data from a survey of over 3,000 ever-married persons in the United States. Controlling for a number of demographic and relationship characteristics, we find evidence that marriage duration is inversely associated with spending on the engagement ring and wedding ceremony.
What is the mechanism? Are signal-requiring and financial commitment-requiring marriages more likely to be fragile? Or, to put forward a politically incorrect interpretation, do the high expenditures indicate the wife has too much bargaining power in the relationship? That hardly seems like a plausible explanation. By the way, weddings with a large number of attendees are likely to last longer, as are weddings accompanied by honeymoons. Those correlations are easier to understand.
This piece is by a factor of more than five the most frequently downloaded SSRN paper over the last two months.
There is a new NBER paper by Campbell R. Harvey, Yan Liu, and Heqing Zhu, and it is a startler though perhaps not a surprise:
Hundreds of papers and hundreds of factors attempt to explain the cross-section of expected returns. Given this extensive data mining, it does not make any economic or statistical sense to use the usual significance criteria for a newly discovered factor, e.g., a t-ratio greater than 2.0. However, what hurdle should be used for current research? Our paper introduces a multiple testing framework and provides a time series of historical significance cutoffs from the first empirical tests in 1967 to today. Our new method allows for correlation among the tests as well as missing data. We also project forward 20 years assuming the rate of factor production remains similar to the experience of the last few years. The estimation of our model suggests that a newly discovered factor needs to clear a much higher hurdle, with a t-ratio greater than 3.0. Echoing a recent disturbing conclusion in the medical literature, we argue that most claimed research findings in financial economics are likely false.
The emphasis is added by me. There are ungated versions of the paper here.
For the pointer I thank John Eckstein.
This is from Larry Summers and Lant Pritchett:
…knowing the current growth rate only modestly improves the prediction of future growth rates over just guessing it will be the (future realized) world average. The R-squared of decade-ahead predictions of decade growth varies from 0.056 (for the most recent decade) to 0.13. Past growth is just not that informative about future growth and its predictive ability is generally lower over longer horizons.
The main point of this paper is to argue that Chinese growth rates will become much lower, perhaps in the near future, here is a summary of that point from Quartz:
Summer and Pritchett’s calculations, using global historical trends, suggest China will grow an average of only 3.9% a year for the next two decades. And though it’s certainly possible China will defy historical trends, they argue that looming changes to its authoritarian system increase the likelihood of an even sharper slowdown.
The piece, “Asiaphoria Meets Regression Toward the Mean,” is one of the best and most important economics papers I have seen all year. There is an ungated version here (pdf). I liked this sentence from the piece:
Table 5 shows that whether or not China and India will maintain their current growth or be subject to regression to the global mean growth rate is a $42 trillion dollar question.
And don’t forget this:
…nearly every country that experienced a large democratic transition after a period of above-average growth…experienced a sharp deceleration in growth in the 10 years following the democratizing transition.
As Arnold Kling would say, have a nice day.
From 1973 to 1985 German inflation was most of the time over two percent a year, sometimes much over two percent. In 1973 it hit eight percent and in the early eighties it exceeded six percent a year. Source here (pdf), see p.6.
From 1951-1973, the Germans seemed happy with roughly the same inflation rate as what Americans had. Source here (pdf), see p.9, and also p.13, passim. In the early 1970s, the rate averaged almost seven percent a year for a few years (p.15). It is fine to note the role of oil shocks here, and in the earlier period Bretton Woods, but still Germans tolerated the higher inflation rates. They expected the alternatives would be worse and probably they were right.
The claim that the current German dislike of inflation dates back to unique memories of Weimar hyperinflation is dubious. Rightly or wrongly, today’s Germans associate high rates of inflation with wealth transfers away from Germany and toward other nations. More broadly, Germany is a more flexible country than outsiders often think, not always to the better of course.
I have supported the various QEs from the beginning, while seeing them as limited in their efficacy. At the time, and still, I feared deflationary pressures more than high inflation. Still, recently the question has arisen whether those QEs boosted the risk of high inflation. Ashok Rao looks at options data to pull out the best answer I have seen so far:
…did the risk of high inflation increase after the Fed engaged in QE2? (Note this establishes a correlation, not causation)…
And you see two very interesting trends: the probability of high inflation (that above 6%, which is the largest traded strike) sharply increased over the latter half of 2010 and early 2011, the time period over which the effects of QE2 were priced in. This is a general trend across all maturities. While the 3, 5, and 10 year option follow a similar path afterwards, the 1-year cap is much more volatile (largely because immediate sentiments are more acute). Still, you see the probability of high inflation pic up through 2012, as QE3 is expanded.
The takeaway message from this is hard to parse. This market doesn’t exist in the United States before 2008, and isn’t liquid till a bit after that, so it’s tough to compare this with normal times. While the sharp increase in the probability of high inflation would seem to corroborate the Hoover Institution letter, that wouldn’t mean much if it simply implied a return to normalcy. That’s just a question we’ll have to leave for a later day.
What about the probability of deflation? We’ll the interesting point is that for the three higher maturity options, the probability for high inflation and probability of deflation were increasing at the same time. This was a time of relatively anchored 5 year implied inflation, but the underlying dynamics were much more explosive, as can be seen in the above charts.
There are some very useful pictures in the post, and do note the variety of caveats which Ashok wisely (and characteristically) offers. He notes also that for the United States deflationary risk was never seen as very likely, but the QEs lowered that risk even further.
Greg Mankiw refers us to this graph (there is further explanation here), which of course can be interpreted in a variety of ways, with causation running either way or perhaps not at all:
He has a new paper (pdf) on this topic, with Jorda and Schularick, based on data from seventeen advanced economies since 1870. In an email he summarizes the main results as follows:
1. Mortgage lending was 1/3 of bank balance sheets about 100 years ago, but in the postwar era mortgage lending has now risen to 2/3, and rapidly so in recent decades.
2. Credit buildup is predictive of financial crisis events, but in the postwar era it is mortgage lending that is the strongest predictor of this outcome.
3. Credit buildup in expansions is predictive of deeper recessions, but in the postwar era it is mortgage lending that is the strongest predictor of this outcome as well.
Here is VoxEU coverage of the work. On a related topic, here is a new paper by Rognlie, Shleifer, and Simsek (pdf), on the hangover theory of investment, part of which is applied to real estate. It has some Austrian overtones but the main argument is combined with the zero lower bound idea as well.
Neil Cummins has a new paper of interest, the abstract is this:
I analyze the age at death of 121,524 European nobles from 800 to 1800. Longevity began increasing long before 1800 and the Industrial Revolution, with marked increases around 1400 and again around 1650. Declines in violence contributed to some of this increase, but the majority must reflect other changes in individual behavior. The areas of North-West Europe which later witnessed the Industrial Revolution achieved greater longevity than the rest of Europe even by 1000 AD. The data suggest that the ‘Rise of the West’ originates before the Black Death.
For the pointer I thank the excellent Kevin Lewis.
I Quant NY reports:
…there on the map lies the farthest residential building from a subway entrance in Manhattan according to my analysis: 10 Gracie Square, located at the end of 84th street at the FDR Drive. It is 0.7 miles from the subway station as the crow flies, or 0.8 miles using the grid. My favorite part about the finding is that the Penthouse, which I guess is literally the farthest place you can live from the subway due to the longer ride down in the elevator, is currently on the market for $18.9 million, down from $23 million last year. That’s right, you can pay $18.9 million dollars to have the longest walk to the subway in all of Manhattan! But fear not power walkers, there is also a two bedroom with a the same walk but a slightly shorter elevator ride… for $3.75 million.
For the pointer I thank Craig Richardson.
Peer-to-peer file sharing of movies, television shows, music, books and other files over the Internet has grown rapidly worldwide as an alternative approach for people to get the digital content they want — often illicitly. But, unlike the users of Amazon, Netflix and other commercial providers, little is known about users of peer-to-peer (P2P) systems because data is lacking.
Now, armed with an unprecedented amount of data on users of BitTorrent, a popular file-sharing system, a Northwestern University research team has discovered two interesting behavior patterns: most BitTorrent users are content specialists — sharing music but not movies, for example; and users in countries with similar economies tend to download similar types of content — those living in poorer countries such as Lithuania and Spain, for example, download primarily large files, such as movies.
“Looking into this world of Internet traffic, we see a close interaction between computing systems and our everyday lives,” said Luís A. Nunes Amaral, a senior author of the study. “People in a given country display preferences for certain content — content that might not be readily available because of an authoritarian government or inferior communication infrastructure. This study can provide a great deal of insight into how things are working in a country.”
Amaral, a professor of chemical and biological engineering in the McCormick School of Engineering and Applied Science, and Fabián E. Bustamante, professor of electrical engineering and computer science, also at McCormick, co-led the interdisciplinary research team with colleagues from Universitat Rovira i Virgili in Spain.
Their study, published this week by the Proceedings of the National Academy of Sciences…reports BitTorrent users in countries with a small gross domestic product (GDP) per capita were more likely to share large files, such as high-definition movies, than users in countries with a large GDP per capita, where small files such as music were shared.
Also, more than 50 percent of users’ downloaded content fell into their top two downloaded content types, putting them in the content specialist, not generalist, category.
The full article is here, the paper and data are here, and for the pointer I thank Charles Klingman. Can you explain the rich-poor, music vs. movies difference using economic theory?
On average, students in 2014 in every income bracket outscored students in a lower bracket on every section of the test, according to calculations from the National Center for Fair & Open Testing (also known as FairTest), using data provided by the College Board, which administers the test.
Students from the wealthiest families outscored those from the poorest by just shy of 400 points.
From Josh Zumbrun, there is more here.
I double-checked these figures with [Philip] Cook, just to make sure I wasn’t reading them wrong. “I agree that it’s hard to imagine consuming 10 drinks a day,” he told me. But, “there are a remarkable number of people who drink a couple of six packs a day, or a pint of whiskey.”
As Cook notes in his book, the top 10 percent of drinkers account for well over half of the alcohol consumed in any given year. On the other hand, people in the bottom three deciles don’t drink at all, and even the median consumption among those who do drink is just three beverages per week.
The piece, by Christopher Ingraham, is interesting throughout. Here is my earlier post on “The culture of guns, the culture of alcohol”, one of my favorites.
Addendum: Via Robert Wiblin, Trevor Butterworth offers a good critique of the data.
Maybe so. Let’s hear from Mounir Karadja, Johanna Möllerström (my new colleague), and David Seim:
We study the extent to which people are misinformed about their relative position in the income distribution and the effects on preferences for redistribution of correcting faulty beliefs. We implement a tailor-made survey in Sweden and document that a vast majority of Swedes believe that they are poorer, relative to others, than they actually are. This is true across groups, but younger, poorer, less cognitively able and less educated individuals have perceptions that are further from reality. Using a second survey, we conduct an experiment by randomly informing a subsample about their true relative income position. Respondents who learn that they are richer than they thought demand less redistribution and increase their support for the Conservative party.
This result is entirely driven by prior right-of-center political preferences and not by altruism or moral values about redistribution. Moreover, the effect can be reconciled by people with political preferences to the right-of-center being more likely to view taxes as distortive and to believe that it is personal effort rather than luck that is most influential for individual economic success.
The paper (pdf) is here, and the pointer is from Gabriel Sahlgren.
Renee B. Adams, Matti Keloharju, and Samuli Knüpfer have a new paper:
This paper analyzes the role three personal traits — cognitive and non-cognitive ability, and height — play in the market for CEOs. We merge data on the traits of more than one million Swedish males, measured at age 18 in a mandatory military enlistment test, with comprehensive data on their income, education, profession, and service as a CEO of any Swedish company. We find that the traits of large-company CEOs are at par or higher than those of other high-caliber professions. For example, large-company CEOs have about the same cognitive ability, and about one-half of a standard deviation higher non-cognitive ability and height than medical doctors. Their traits compare even more favorably with those of lawyers. The traits contribute to pay in two ways. First, higher-caliber CEOs are assigned to larger companies, which tend to pay more. Second, the traits contribute to pay over and above that driven by firm size. We estimate that 27-58% of the effect of traits on pay comes from CEO’s assignment to larger companies. Our results are consistent with models where the labor market allocates higher-caliber CEOs to more productive positions.
In other words, Swedish CEOs are a pretty impressive lot. Scott Sumner offers some related remarks on American CEOs.
Christopher Buccafusco and Chris Sprigman report:
…we ran an experiment to measure how much people value the ability to recline compared to extra knee and laptop room.
In an online survey, we asked people to imagine that they were about to take a six-hour flight from New York to Los Angeles. We told them that the airline had created a new policy that would allow people to pay those seated in front of them to not recline their seats. We asked one group of subjects to tell us the least amount of money that they would be willing to accept to not recline during the flight. And we asked another group of subjects to tell us the most amount of money that they would pay to prevent the person in front of them from not reclining.
It turns out that Barro was right: Recliners wanted on average $41 to refrain from reclining, while reclinees were willing to pay only $18 on average. Only about 21 percent of the time would ownership of the 4 inches change hands.
But it also turns out that Barro was wrong and Marron was right. When we flipped the default—that is, when we made the rule that people did not have an automatic right to recline, but would have to negotiate to get it—then people’s values suddenly reversed. Now, recliners were only willing to pay about $12 to recline while reclinees were unwilling to sell their knee room for less than $39. Recliners would have ended up purchasing the right to recline only about 28 percent of the time—the same right that they valued so highly in the other condition.
Wait … what? How is it possible that people’s valuation of reclining vs. not being reclined upon depended so completely on which party (recliner or reclinee) held initial ownership of the property right? Shouldn’t the right to recline be worth the same to you whether you initially have it or not?
It is fair to call this an endowment effect, but I also view it as evidence for my earlier view that people do not want to bargain over this right.
For the pointer I thank Tim Harford.