Data Source

Catherine Rampell reports:

While engineers, mathematicians and scientists today are (unfairly) stereotyped as awkward nerds who don’t know how to interact with the opposite sex, in 1950 they were among the occupations most likely to be married. Today, the most commonly conjugated occupations are instead more often medical professionals with doctorates, starting with dentists (81 percent of whom are hitched)…

The top of the list looks like this:

1) Dentist
2) Chief executive
3) Sales engineer
4) Physician
5) Podiatrist
6) Optometrist
7) Farm product buyer
8) Precision grinder
9) Religious worker
10) Tool and die maker

We also learn this:

Turns out that in 1950, many of the occupations whose members were most likely to end up divorced were creative or artistic ones (artist, writer/director, dancer, designer, writer), which perhaps reflects the communities that were most accepting of divorce at the time. In 2010, the occupations with the highest divorce rates were predominantly in manufacturing or other areas that have been subject to downsizing (drilling machine operator, knitter textile operative, force operator, winding machine operative, postal clerk). This seems to support the idea that economic stability is a good predictor of marital status.

Do read the whole thing.

Supreet Kaur has a new NBER paper on this:

This paper tests for downward nominal wage rigidity in markets for casual daily agricultural labor in a developing country context. I examine transitory shifts in labor demand, generated by rainfall shocks, in 600 Indian districts from 1956-2009. First, there is asymmetric adjustment: nominal wages rise in response to positive shocks but do not fall during droughts. Second, transitory positive shocks generate ratcheting: after they have dissipated, nominal wages do not adjust back down. Third, inflation moderates these effects, enabling downward real wage adjustments both during droughts and after positive shocks. Fourth, wage distortions generate employment distortions, creating boom and bust cycles: employment is 9% lower in the year after a transitory positive shock than if the positive shock had not occurred. Fifth, consistent with the misallocation of labor across farms, households with small landholdings increase labor supply to their own farms when they are rationed out of the external labor market. The results are not consistent with other transmission mechanisms, such as migration or capital accumulation. These findings indicate the presence of rigidities in a setting with few institutional constraints. Survey evidence suggests that workers and employers believe that nominal wage cuts are unfair and lead to effort reductions.

There are ungated versions here.  I am often puzzled, by the way, that we do not spend much more time studying nominal rigidities, which are the source of rather considerable deadweight losses.   We do not find nominal rigidities everywhere.  Salespeople working on commission often have flexible wages, as do (some) people working in high-trust, high morale organizations.  What exactly accounts for these differences and how much can they be replicated?  What are their psychological costs?  Are there personality types which can deal with nominal flexibility of wages and types who cannot?  How frequent is one type relative to the other?  How do the psychological costs of a wage cut compare to the psychological costs of suffering losses when running your own business?  Questions such as these should be much higher on the list of research priorities.

Everyone is up in arms over the list supplied by The Economist.  I won’t go through those debates.  Let me just note that for all the talk of wonk this, data that, and Generalized Method of Moments this that and the other, every now and then the best algorithm is simply Asking Tyler Cowen.  So here are, in no particular order, the most influential economists circa 2014:

1. Thomas Piketty

2. Paul Krugman

3. Joseph Stiglitz

4. Jeffrey Sachs

5. Amartya Sen

Basta.  Of course Yellen and Draghi are extremely influential as central bankers, but in the way Paul Volcker was, so that is a different list, albeit a more important one.

I would add several comments:

a. Piketty does very very well for marginal impact in 2014, but probably would/will do less well over broader time spans, even if you think his work will hold up.

b. Krugman is a clear winner for the United States.

c. Stiglitz, Sachs, and Sen have most of their influence outside of the United States.

d. Larry Summers is influential among economists and the intelligentsia and is one possible choice for number six, with Dani Rodrik as another, or maybe drum up the leading Islamic theorist on sukuk.  But Summers is not so influential with casual observers, which in some ways puts him as the opposite of Stiglitz (in his current incarnation).

e. There is no right-wing or center-right economist on the list.  See the EJW symposium on why there is no Milton Friedman today.  Krugman is probably the most politically conservative figure among the top five.

f. Behavioral economics as a whole is quite influential, but with no single dominant figure of influence.  In actuality Cass Sunstein (not formally an economist) and Richard Thaler might globally be #1 in the behavioral area, followed by Daniel Kahneman.

In particular, about 57% of the papers accepted by the first committee were rejected by the second one and vice versa. In other words, most papers at NIPS would be rejected if one reran the conference review process (with a 95% confidence interval of 40-75%)

Here is another framing:

If the committees were purely random, at a 22.5% acceptance rate they would disagree on 77.5% of their acceptance lists on average.

That is from Eric Price on the NIPS experiment, there is more here.

For the pointer I thank a loyal MR reader.


by on December 12, 2014 at 12:20 am in Data Source, Science | Permalink

David Keith, a climate scientist at Harvard University, and author of  A Case for Climate Engineering, is interviewed at re/code.

There’s no question it reduces the global average temperatures; even the people who hate it agree you could reduce average global temperatures. The question is: How does it do on a regional basis?

By far the single most important thing to look at on a region-by-region basis is the impact on rainfall and temperature.

And the answer is, it works a lot better than I expected. It’s really stunning.

A lot of us thought that, in fact, geoengineering would do a lousy job on a regional basis — and there’s lots of talk on the inequalities — but in fact, when you actually look at the climate models, the results show they’re strikingly even.

Now, it’s not perfect and there are some things it won’t do. Turning down the sun does nothing for ocean acidification.

But it looks like it can cut, like, 80 percent of the total variation in climate, which is really stunning.

In some ways we should be singing it from the rooftops. But the scientific community is so painfully scared of talking about it. These papers come out, and people find the best ways to say, well, it sort of works, but it’s really awful.

The fact is, people really appear to have found a way to significantly reduce the climate risk — by more than half, which is a big deal.

Hat tip: Mark Frazier.

Scott Sumner writes:

Here’s one thought experiment. Get a department store catalog from today, and compare it to a catalog from 1964. (I recently saw Don Boudreaux do something similar at a conference.) Almost any millennial would rather shop out of the modern catalog, even with the same nominal amount of money to spend. Of course that’s just goods; there is also services, which have risen much faster in price. OK, so ask a millennial whether they’d rather live today on $100,000/year, or back in 1964 with the same nominal income. Recall the rotary phones and bulky cameras. The cars that rusted out frequently. Cars that you couldn’t count on to start on a cold morning. I recall getting cavities filled in 1964, without Novocaine. Not fun. No internet. Crappy TVs, where you have to constantly move the rabbit ears on top to get a decent picture. Lame black and white sitcoms, with 3 channels to choose from. Shorter life expectancy, even for the affluent. No Thai restaurants, sushi places or Starbucks. It’s steak and potatoes. Now against all that is the fact that someone making $100,000/year in 1964 was pretty rich, so your social standing was much higher than that income today. So it’s a close call, maybe living standards have risen for people making $100,000/year, maybe not. Zero inflation in the past 50 years may not be right, but it’s a reasonable estimate for a millennial, grounding in utility theory. In which period does $100,000 buy more happiness? We don’t know.

I say I prefer $100k today to $100k in 1964, that being a nominal rather than a real comparison.  If you are not convinced, try comparing $1 million or $1 billion (nominal) today to 1964.  For some income level, we have seen net deflation.

But here’s the catch: would you rather have net nominal 20k today or in 1964?  I would opt for 1964, where you would be quite prosperous and could track the career of Miles Davis and hear the Horowitz comeback concert at Carnegie Hall.  (To push along the scale a bit, $5 nominal in 1964 is clearly worth much more than $5 today nominal.  Back then you might eat the world’s best piece of fish for that much.)

So for people in the 20k a year income range, there has been net inflation.

Think about it: significant net deflation for the millionaires, but significant net inflation for those earning 20k a year.  In real terms income inequality has gone up much more than most of our numbers indicate.

Here is the video of my panel at the Cato Conference on Growth (other videos at the link). John Haltiwanger leads off with a very good talk summarizing some of his work on declining business dynamism (see also his important paper with Decker, Jarmin and Miranda.) Amar Bhide follows with some skepticism about productivity statistics. My talk begins at 50:26. I discuss regulation and dynamism, why less-developed economies are more entrepreneurial than the United States, Japan’s Ise Grand Shrine and its lessons for entrepreneurship, how Zara is internalizing creative destruction and more.

This is from Wojciech Kopczuk in his recent NBER paper:

The methods that rely on direct measurement of wealth — that is, those based on the Survey of Consumer Finance and on the estate tax — show at best a small increase in the share of wealth held by the top 1 percent, while the capitalization methods show a steep increase.

These methods start diverging in their estimates in the 1980s, and the paper has a very useful discussion of their strengths and weaknesses.  This is a notable paragraph:

The most striking feature of the estimates for 2000s is a huge run-up of fixed income-generating wealth in the capitalization series. In fact, this run-up accounts for virtually all of the increase in the share of the top 0.1% between 2000 and 2012 and most of the increase since 2003. The underlying change in taxable capital income (reported by Saez and Zucman, 2014, in their Figure 3) is nowhere as dramatic. The fixed income actually falls in relative terms, as would be expected when yields fall. Instead, the (almost) tripling of the fixed income component on Figure 3 (from 3.3% of total wealth in 2000 to 9.5% in 2012) is driven by an increase in the underlying capitalization factor from 24 to 96.6. This is precisely what the method is intended to do: as yields have declined, the capitalization method should weight the remaining income much more heavily. This increase – if real – would correspond to enormous re-balancing of the underlying portfolios of the wealthy throughout the 2000s. An alternative possibility is simply that the capitalization factors are difficult to estimate during periods of very low rates of return resulting in a systematic bias.

Overall Kopczuk does not favor the capitalization method and thus there seems to be a very real possibility that U.S. wealth inequality has gone up by only a modest amount.

For the pointer I thank Allison Schraeger.

The number of women in the United States who gave birth dropped last year, according to federal statistics released Thursday, extending the decline for a sixth year.

The National Center for Health Statistics reported Thursday that there were 3.93 million births in the United States in 2013, down slightly from 3.95 million in 2012, but 9 percent below the high in 2007.

According to the report, the general fertility rate in the United States — the average number of babies women from 15 to 44 bear over their lifetime — dropped to a record low last year, to 1.86 babies, well below the 2.1 needed for a stable population. For every 1,000 women ages 15 to 44, there were 62.5 births in 2013, compared with 63 the previous year.

From Tamar Lewin, there is more here.  Here is Clive Crook on the importance of demography.

From Rhia Catapano,

…Using a capuchin population previously trained in a token market, we explored whether monkeys used price as an indicator of value across four experiments. Although monkeys demonstrated an understanding of which goods had which prices (consistently shifting preferences to cheaper goods when prices were increased), we observed no evidence that such price information affected their valuation of different kinds of goods.

In other words, the monkeys don’t think that the more expensive goods are more valuable per se.  Yet the monkeys are judged cognitively deficient for getting the problem right!:

These results suggest that human pricing effects may involve more sophisticated human-unique cognitive capacities, such as an understanding of market forces and signaling.

Hat tip goes to Diane Coyle.

In 2006, the year after the storm, wage and salary income for the average Katrina victim in our sample is roughly $2,200 lower than their matched counterparts.  Remarkably, the earnings gap is erased the following year, and by 2008, the hurricane victims actually have higher wage income and total income than control households.

That is from a new NBER working paper by Tatyana Deryugina, Laura Kawano, and Steven Levitt.  I agree with this claim:

…strong ties to a place, especially a place with limited economic opportunities such as New Orleans, have adverse economic consequences.  When forced by an exogenous shock to migrate, people are able to choose from a wide range of possible locations to move to, and they seem to choose places that offer them better economic opportunities.

You will find an ungated version here.

The economics of Uber

by on November 28, 2014 at 7:16 am in Data Source, Economics, Travel | Permalink

We were talking about this at lunch the other day, and now Josh Barro steps forward with the numbers:

The average price of an individual New York City taxi medallion fell to $872,000 in October, down 17 percent from a peak reached in the spring of 2013, according to an analysis of sales data. Previous figures published by the city’s Taxi and Limousine Commission — showing flat prices — appear to have been incorrect, and the commission removed them from its website after an inquiry from The New York Times.

In other big cities, medallion prices are also falling, often in conjunction with a sharp decline in sales volume. In Chicago, prices are down 17 percent. In Boston, they’re down at least 20 percent, though it’s hard to establish an exact market price because there have been only five trades since July. In Philadelphia, the taxi authority recently scrapped a planned medallion auction.

There is more here.  I learn also that Nevada just banned Uber.

…of those in middle-skill occupations who remain in a full-time job, about 83 percent are still working in a middle-skill job one year later. … What types of jobs are the other 17 percent getting? Mostly high-skill jobs; and that transition rate has been rising. The percent going from a middle-skill job to a high-skill job is close to 13 percent: up about 1 percent relative to before the recession. The percent transitioning into low-skill positions is lower: about 3.4 percent, up about 0.3 percentage point compared to before the recession. This transition to a high-skill occupation tends to translate to an average wage increase of about 27 percent (compared to those who stayed in middle-skill jobs). In contrast, those who transition into lower-skill occupations earned an average of around 24 percent less.

That is Ellie Terry and John Robertson via Mark Thoma.

Session 16M, Economics and Chess


“Thinking Outside the Game Tree: Game Preparation at Chess World Championship”
Doru Cojoc, Columbia University

“Do Rational Agents Make Rational Decisions? Evidence from Chess Data”
Alexander Matros, University of South Carolina
Irina Murtazashvili, Drexel University

“Human and Computer Preference Divergences at Chess”
Kenneth Regan, University at Buffalo
Tamal Tanu Biswas, University at Buffalo
Jason Zhou, SUNYIT

The link to the program is here.  Here is Cojoc’s earlier paper on mixed strategies in chess.

Carlsen played an imperfect match, by the way, especially in the second half, but won on the grounds of age and stamina.  For the next cycle, I see Grischuk as the most likely challenger, as Aronian tends to choke at key moments and Caruana does not yet have a good enough positional understanding of the middle game and end game.  Carlsen will hold the title still for some while to come.

The pointer is from Daniel Klein, here is his earlier paper on why don’t government officials seem like villains (pdf).

David E. Kalist and Daniel Y. Lee report:

This article investigates the effects of National Football League (NFL) games on crime. Using a panel data set that includes daily crime incidences in eight large cities with NFL teams, we examine how various measurements of criminal activities change on game day compared with nongame days. Our findings from both ordinary least squares and negative binomial regressions indicate that NFL home games are associated with a 2.6% increase in total crimes, while financially motivated crimes such as larceny and motor vehicle theft increase by 4.1% and 6.7%, respectively, on game days. However, we observe that play-off games are associated with a decrease in financially motivated crimes. The effects of game time (afternoon vs. evening) and upset wins and losses on crime are also considered.

Is it that a game works up everyone’s excitement, but the playoff games the criminals actually watch?  That is via the excellent Kevin Lewis.