Results for “cohort” 290 found
Tuesday assorted links
The incompetence of thieves
I investigate self-reported theft data in the NLSY 1997 Cohort for the years 1997–2011. Several striking patterns emerge. First, individuals appear to be active thieves for extremely short periods – in most cases in only one year, and fewer than 5% of thieves for more than three years out of the 15 years of data. Second, self-reported earnings from theft are generally very low and there is little evidence of “successful” criminals or consistent earnings from theft. Third, measures that proxy impatience (smoking, for example) are highly correlated with theft. Fourthly, thieves and non-thieves have similar earnings during the years of peak theft activity, but thieves have lower earnings in their late 20s (after most have long since stopped committing theft). Attrition of survey respondents, underreporting and incapacitation effects do not appear to explain this. There may be “professional thieves” too rare to show up in even large samples such as the NLSY. Theft in the United States thus appears to be substantially a phenomenon of individuals entering a temporary period of intensified risk-taking in adolescence.
That is from a new Geoffrey Fain Williams paper in JEBO, via the excellent Kevin Lewis. Kevin also links to new evidence that concealed carry laws are orthogonal to crime rates.
Are tenure track professors better teachers?
At least at Northwestern University, the answer seems to be no. Figlio, Schapiro, and Soter report:
This study makes use of detailed student-level data from eight cohorts of first-year students at Northwestern University to investigate the relative effects of tenure track/tenured versus contingent faculty on student learning. We focus on classes taken during a student’s first term at Northwestern and employ an identification strategy in which we control for both student-level fixed effects and next-class-taken fixed effects to measure the degree to which contingent faculty contribute more or less to lasting student learning than do other faculty. We find consistent evidence that students learn relatively more from contingent faculty in their first-term courses. This result is driven by the fact that the bottom quarter of tenure track/tenured faculty (as indicted by our measure of teaching effectiveness) has lower “value added” than their contingent counterparts. Differences between contingent and tenure track/tenured faculty are present across a wide variety of subject areas and are particularly pronounced for Northwestern’s averages and less-qualified students.
Emphasis is added by me. I wonder how much of the problem is that the bottom quarter of the tenure track instructors are more likely not to have English as a first language?
The pointer is from Ben Southwood.
Is the Great Reset coming first to immigrants?
Casey Warman and Christopher Worswick have a new and interesting NBER paper on Canadian immigrants. Apparently even the better-educated ones are not reaping real gains from (supposedly) skill-enhancing technical change:
The earnings and occupational task requirements of immigrants to Canada are analyzed. The growing education levels of immigrants in the 1990s have not led to a large improvement in earnings as one might expect if growing computerization and the resulting technological change was leading to a rising return to non-routine cognitive skills and a greater wage return to university education. Controlling for education, we find a pronounced cross-arrival cohort decline in earnings that coincided with cross-cohort declines in cognitive occupational task requirements and cross-cohort increases in manual occupational task requirements. The immigrant earnings outcomes had only a small effect on overall Canadian earnings inequality.
Immigrants of course are rarely labor market insiders, so, when structural change is occurring, they step into the new world of labor markets before the natives do. You will find non-gated versions of the paper here.
Will U.S. demographics be improving?
For just a while? Keep in mind that an aging population still can be moving more people into prime working age:
Changes in demographics are an important determinant of economic growth, and although most people focus on the aging of the “baby boomer” generation, the movement of younger cohorts into the prime working age is another key story in coming years…
The prime working age population peaked in 2007, and appears to have bottomed at the end of 2012. The good news is the prime working age group has started to grow again, and should be growing solidly by 2020 – and this should boost economic activity in the years ahead.
That is from Bill McBride at Calculated Risk. Check out this St. Louis Fed graph, via Conor Sen.
How love conquered (arranged) marriage
Gabriela Rubio of UC Merced has a very interesting paper (pdf) on this topic:
Using a large number of sources, this paper documents the sharp and continuous decline of arranged marriages (AM) around the world during the past century, and describes the factors associated with this transition. To understand these patterns, I construct and empirically test a model of marital choices that assumes that AM serve as a form of informal insurance for parents and children, whereas other forms of marriage do not. In this model, children accepting the AM will have access to insurance but might give up higher family income by constraining their geographic and social mobility. Children in love marriages (LM) are not geographically/socially constrained, so they can look for the partner with higher labor market returns, and they can have access to better remunerated occupations. The model predicts that arranged marriages disappear when the net benefits of the insurance arrangement decrease relative to the (unconstrained) returns outside of the social network. Using consumption and income panel data from the Indonesia Family Life Survey (IFLS), I show that consumption of AM households does not vary with household income (while consumption of LM households does), consistent with the model’s assumption that AM provides insurance. I then empirically test the main predictions of the model. I use the introduction of the Green Revolution (GR) in Indonesia as a quasi-experiment. First, I show that the GR increased the returns to schooling and lowered the variance of agricultural income. Then, I use a difference-in-difference identification strategy to show that cohorts exposed to the GR experienced a faster decline in AM as predicted by the theoretical framework. Second, I show the existence of increasing divorce rates among couples with AM as their insurance gains vanish. Finally, using the exogenous variation of the GR, I find that couples having an AM and exposed to the program were more likely to divorce, consistent with the hypothesis of declining relative gains of AM.
MR referenced this paper in an addendum some while ago, Michael Clemens on Twitter recently reminded me of its existence. One question of course is to what extent the arranged marriage is the only marriage form which provides these insurance benefits. In other words, the arranged marriage might go away, but without the love marriage triumphing. Perhaps one key change is that the parents are no longer the best producers of those financial insurance benefits, but that is distinct from the triumph of love.
Is hypergamy fading?
Here is a new paper from Christine R. Schwartz and Hongyun Han, and here is the key part of the abstract:
…marriages in which wives have the educational advantage were once more likely to dissolve, but this association has disappeared in more recent marriage cohorts. Another key finding is that the relative stability of marriages between educational equals has increased. These results are consistent with a shift away from rigid gender specialization toward more flexible, egalitarian partnerships, and they provide an important counterpoint to claims that progress toward gender equality in heterosexual relationships has stalled.
There are ungated versions here, and for the pointer I thank the excellent Kevin Lewis.
Has the religion-education gradient turned positive?
For those born in much of the 20th century, it was true that college graduates of all ages were significantly less likely than others to report any religious affiliation.
But research just published in the journal Social Forces (abstract available here) finds that, starting for those born in the 1970s, there was a reversal in this historic trend. For that cohort, a college degree increases the chances that someone will report a religious affiliation.
“College education is no longer a faith-killer,” said Philip Schwadel, author of the paper and associate professor of sociology at the University of Nebraska at Lincoln.
That is for belief, observance was not tested. The full story is here.
Will the recent decline in entrepreneurship be reversed by demographic forces?
Annie Lowrey documents that decline, Matt Yglesias offers a partially optimistic hypothesis:
…people are founding fewer new businesses. But why?
One possibility is that the link to population aging is quite literal. A study by Vivek Wadhwa, Raj Aggarwal, Krisztina Holly, and Alex Salkever that looked specifically at “high-growth” industries found that the typical successful founder is 40. Not someone who’s at the tail-end of his career, but not someone who’s fresh out of school either. That’s in part because “professional networks were important to the success of their current business for 73 percent of the entrepreneur,” and it takes time to achieve that success. Mark Zuckerberg founded a great company when he was in college, but that kind of super-young founder is the exception not the rule — most people need some practical experience and contacts to succeed.
And back in the early 1990s, there were a lot of people in their late-thirties and early forties…
Nowadays that cohort of people’s prime founding years are behind them. There is another large cohort of people coming up, but right now they’re too young to be peak entrepreneurs. This cool CNN graphic shows that the most common age in the United States right now is 22 and 23, and that’s followed by 53 and 52.
The story about aging is so well-known that people tend to neglect this sub-trend of the youth bulge. But right now we’re at a moment where a lot of inexperienced workers are entering the labor market, and 10 to 20 years from now we’ll be in a moment when a lot of experienced workers are founding new businesses. But for the past 10 years, we’ve been seeing a demographic trend that’s unfavorable to entrepreneurship.
There are a few relevant questions:
1. At any point in time, are there external benefits or external costs to having more new businesses founded?
2. As organizational capabilities increase with progress, does market equilibrium serve up larger and older firms? It seems so.
3. What are the external social costs and benefits of that progression?
In poor, developing economies, I think of high levels of petty entrepreneurship as a negative, rather than a positive. Might the United States be a bit the same way? Yet the continuation of The Great Stagnation makes that a hard line to buy into enthusiastically.
I thank Robin Hanson for a useful conversation related to this blog post.
The Declining Fortunes of the Young Since 2000
That is a new piece in the May AER by Paul Beaudry, David A. Green, and Benjamin M. Sand, here is the clincher scary paragraph:
The data reveal a clear break in 2000. Between 1992 and 2000, each successive entry cohort has a higher share in cognitive occupations at the outset of their working lives, with the proportion increasing by 0.1 between the 1994 and 1998 cohorts. After 2000, with the exception of the difference between the 2004 and 2006 entry cohorts, each successive cohort has a lower share in these occupations, with the share at entry for the 2010 cohort being approximately the same as for the 1990 cohort. Given all the attention that has been paid to growing demand for cognitive skills, this complete reversal is striking.
Do you know of an ungated version? Here is a related Brookings piece of research (pdf). Here is a related piece by Acemoglu, Auor, Dorn, Hanson, and Price.
Score one for the signaling model of education
In the new AER there is a paper by Melvin Stephens Jr. and Dou-Yan Yang, the abstract is this:
Causal estimates of the benefits of increased schooling using US state schooling laws as instruments typically rely on specifications which assume common trends across states in the factors affecting different birth cohorts. Differential changes across states during this period, such as relative school quality improvements, suggest that this assumption may fail to hold. Across a number of outcomes including wages, unemployment, and divorce, we find that statistically significant causal estimates become insignificant and, in many instances, wrong-signed when allowing year of birth effects to vary across regions.
In other words, those semi-natural experiments for the return to education, when some regions move with extra doses of compulsory schooling before others and we estimate differential wage effects, maybe don’t show as much as we used to think. As I’ve remarked to Bryan Caplan, if there is a criticism of a famous or politically correct result (or better yet both) getting published in the AER, you can up your Bayesian priors on that criticism being on the mark.
There are ungated copies of the paper here.
The Son Also Rises
Economist and Australian politician Andrew Leigh has a very informative review of Gregory Clark’s The Son Also Rises:
If you want to know who made up Australia’s elite in the nineteenth century, a useful place to look is the Australian Dictionary of Biography. In its many volumes, you’ll find business leaders, scientists, media barons and politicians who have featured among the upper echelons of Australian society.
Now, suppose we take the first cohort of significant Australians – those who died before 1880 – and identify those with unusual surnames like Ebden or Maconochie. People with those names were overrepresented among the elite in the nineteenth century. Are they still at the top of society, or are they mixed through?
The answer to this question will depend on the level of social mobility we have in Australia.
…For Australia, it turns out that if we look at the register of modern-day medical practitioners, we find the privileged names of the nineteenth century overrepresented by a factor of nearly three. In other words, if your ancestor was at the top of Australian society six generations ago, you are three times more likely to be a doctor today than the average Australian.
…if we accept Gregory Clark’s methodology, his results imply a very static society. For Britain, the United States, India, Japan, Korea, China, Taiwan, Chile and even Sweden, he concludes that the intergenerational elasticity is between 0.7 and 0.9. This would mean that social status is at least as hereditable as height. It suggests that while the ruling class and the underclass are not permanent, they are extremely long-lasting. Erasing privilege takes not two or three generations, but ten to fifteen generations.
Read the whole thing.
Will raising the minimum wage boost crime?
There is a recent 2013 paper on this topic by Andrew Beauchamp and Stacey Chan, the abstract is here:
Does crime respond to changes in the minimum wage? A growing body of empirical evidence indicates that increases in the minimum wage have a displacement effect on low-skilled workers. Economic reasoning provides the possibility that disemployment may cause youth to substitute from legal work to crime. However, there is also the countervailing effect of a higher wage raising the opportunity cost of crime for those who remain employed. We use the National Longitudinal Survey of Youth 1997 cohort to measure the effect of increases in the minimum wage on self-reported criminal activity and examine employment–crime substitution. Exploiting changes in state and federal minimum wage laws from 1997 to 2010, we find that workers who are affected by a change in the minimum wage are more likely to commit crime, become idle, and lose employment. Individuals experiencing a binding minimum wage change were more likely to commit crime and work only part time. Analyzing heterogeneity shows those with past criminal connections are especially likely to see decreased employment and increased crime following a policy change, suggesting that reduced employment effects dominate any wage effects. The findings have implications for policy regarding both the low-wage labor market and efforts to deter criminal activity.
For the pointer I thank Kevin Lewis. And there is an ungated version here (pdf). And via Gordon, here is a profile behind one of the forces behind the campaign to raise the minimum wage. Here is a good recent article on minimum wages and cross-state mobility.
From the comments, on being a government economist
DC Economist writes:
I am in this cohort of economists (although ashamedly a non-responder to the NSF SED survey – I filled it out but neglected to mail it). And I did chose a government job over an academic offer and I’ve never been sorry that I did.
All my academic offers (2002) were from public institutions, mostly on the west coast and mid-west. For the next five years of my career, almost all of those departments had pay freezes. Meanwhile, I was quickly promoted in my government job. While the cost of living in DC eats a comfortable share of that salary differential, it was decidedly better financial move in retrospect to take the federal job. (I did not know that ex ante; my federal starting salary was actually lower than the starting pay for my best academic offer, and I assumed I was making a financial sacrifice to take a job I genuinely preferred.)
You can make even more money in consulting, but it’s a different world, and I’ve known a fair number of economists who move back and forth between consulting and government, depending on their relative preference for money vs. interesting work. Colleagues that have moved back and forth between academia and government have often voiced to me their extreme surprise how interesting and rewarding the work can be.
I just got back from recruiting at the AEAs and as always, I remain truly surprised how strongly candidates prefer academic jobs to government work. Academic jobs often have serious drawbacks — geography, teaching, collegiality (the incentives are stronger for us to all get along on this side of the market), the gut-wrenching uncertainty of the tenure track. Government jobs often offer better opportunities to do research (especially empirical work) and find similar co-authors. DC is also a great place to be an economist – lots of jobs, lots of interesting work – and the policy work is often more rewarding than teaching can often be. The one serious drawback is a lack of sabbaticals and summer research time. I often groan at the inevitable co-author email flood in May – let’s get back to our paper! – while I’m still working as hard in June as I was in March. But that’s not enough to tempt me back to academia – I’m much, much happier here.
But every year I offer a job to a junior candidate who turns me down for a really marginal academic job. I understand being turned down for a good-to-great academic offer, but turning this job down for a really marginal academic department makes no sense at all to me. And yet so many junior candidates can’t seem to imagine themselves in another line of work that they torpedo their own research opportunities to take a lower-paying, high-teaching load, academic job. Maybe they are just not that into research, and would rather have their summers off than be placed somewhere where they will work harder but have better opportunities for research. Or maybe they worry that all government jobs are being some boring government bureaucrat and they can’t see past that initial bias (those jobs do exist, but those agencies aren’t often looking for Ph.D. economists at AEAs to fill them).
Graduate students really should be more strongly considering some of the great government jobs in the DC area. You really can have a great, rewarding career here.
Should economists aspire to be academics or to work in government?
From Scott Jaschik at InsideHigherEd:
The study was based on data from the National Science Foundation’s Survey of Earned Doctorates, and also on surveys of economics Ph.D.s who entered or left programs in certain years. The work was conducted by Wendy Stock, professor of economics at Montana State University, and John Siegfried, professor of economics at Vanderbilt University.
Comparing four cohorts of economics Ph.D.s by year graduated (from 1997 through 2011), the study found that while a majority still enter academe, that share is going down. And while salaries for those in business and industry exceeded those in academe throughout the period studied, the time span saw salaries in government grow such that they too now exceed those in academe.
In 1997 63.7% of new economics Ph.d.s went into academia, as of 2011 it is 56.3%. The government to academia salary over that same time went from 0.87 to 1.17, see the chart at the initial link. For instance:
…for those who earned Ph.D.s in 1997, the average annual salary increase was 8.2 percent. But for academics that was 5.7 percent, while for non-academics it was 15.0 percent.
You can earn more if you were hired later:
“Indeed, the median salaries of graduates of full-time permanent 9-10 month academic economists hired in 2002-3 actually exceeded the median 2003 salaries of their counterparts initially hired in 1997-98,” the paper says.
There is a marriage penalty for women but not for men, and the paper reports this:
The surveys of new Ph.D.s also asked them about the doctoral education they received. Among the findings:
- Most said that the overall emphasis in their programs was “about right.”
- Most also reported too little emphasis on “applying economic theory to real-world problems,” “understanding economic institutions and history” and “the history of economic ideas.”
- Mathematics was viewed by most as more important in graduate school than in their careers.
- Skills in application, instruction and communication were more important in their careers than in graduate school.
Here are related thoughts from Megan McArdle and from Bryan Caplan. Can any of you find a link to the actual paper on-line (try this: http://www.aeaweb.org/aea/2014conference/program/retrieve.php?pdfid=305#sthash.Avt8kMpt.dpuf)?