Data Source

Via Ben Schmidt, the term becomes common only in the 1970s:

I’d like to see a detailed look at actual journal practices, but my personal sense is that editorial review was the norm until fairly recently, not review by a team of outside referees.  In 1956, for instance, the American Historical Review asked for only one submission copy, and it seems the same was true as late as 1970.  I doubt they made the photocopies themselves. Schmidt seems to suggest that the practices of government funders nudged the academic professions into more formal peer review with multiple referee reports.

Further research is needed (how about we ask some really old people?), at least if peer review decides it is worthy of publication.  Frankly I suspect such work would stand a better chance under editorial review.

In the meantime, here is a tweet from the I didn’t know she was on Twitter Judy Chevalier:

I have just produced a 28-page “responses to reviewer and editor questions” for a 39-page paper.

I’d rather have another paper from Judy.

By the way, scientific papers are getting less readable.

This is from a job market paper at Stockholm University, by Sirus Dehdari:

This paper studies the effects of economic distress on support for far-right parties. Using Swedish election data, I show that shocks to unemployment risk among unskilled native-born workers account for 5 to 7 percent of the increased vote share for the Swedish far-right party Sweden Democrats. In areas with an influx of unskilled immigrants equal to a one standard deviation larger than the average influx, the effect of the unemployment risk shock to unskilled native-born workers is exacerbated by almost 140 percent. These findings are in line with theories suggesting that voters attribute their impaired economic status to immigration. Furthermore, I find no effects on voting for other anti-EU and anti-globalization parties, challenging the notion that economic distress increases anti-globalization sentiment. Using detailed survey data, I present suggestive evidence of how increased salience of political issues related to immigration channels economic distress into support for far-right parties, consistent with theories on political opportunity structure and salience of sociocultural political issues.

Here is Dehdari’s cv, all via Matt Yglesias.

There is a hot hand after all

by on September 16, 2017 at 11:21 am in Data Source, Sports | Permalink

This paper, “The Hot-Hand Fallacy: Cognitive Mistakes or Equilibrium Adjustments? Evidence from Major League Baseball,” delivers on both the theory and the empirics:

We test for a “hot hand” (i.e., short-term predictability in performance) in Major League Baseball using panel data. We find strong evidence for its existence in all 10 statistical categories we consider. The magnitudes are significant; being “hot” corresponds to between one-half and one standard deviation in the distribution of player abilities. Our results are in notable contrast to the majority of the hot-hand literature, which has generally found either no hot hand or a very weak hot hand in sports, often employing basketball shooting data. We argue that this difference is attributable to endogenous defensive responses: basketball presents sufficient opportunity for transferring defensive resources to equate shooting probabilities across players, whereas baseball does not. We then develop a method to test whether baseball teams do respond appropriately to hot opponents. Our results suggest teams respond in a manner consistent with drawing correct inference about the magnitude of the hot hand except for a tendency to overreact to very recent performance (i.e., the last five attempts).

That is from Brett Green and Jeffrey Zwiebel, via Rolf Degen.  Here are ungated versions.

We find that staggering SNAP benefits throughout the month leads to a 32 percent decrease in grocery store theft and reduces monthly cyclicity in grocery store crimes.

That is by Jillian B. Carr and Analisa Packham (pdf), via Alexander Berger.

Possibly so, though some more good years would be nice, to say the least.  To some extent this could be noise, or delayed catch-up growth.  Still, there seems to be a break in the previous trend:

In 2015, median household incomes rose by 5.2 percent. That was the fastest surge in percentage terms since the Census Bureau began keeping records in the 1960s. Women living alone saw their incomes rise by 8.7 percent. Median incomes for Hispanics rose by 6.1 percent. Immigrants’ incomes, excluding naturalized citizens, jumped by over 10 percent.

The news was especially good for the poor. The share of overall income that went to the poorest fifth increased by 3 percent, while the share that went to the affluent groups did not change. In that year, the poverty rate fell by 1.2 percentage points, the steepest decline since 1999.

…The numbers for 2016 have just been released by the Census Bureau, and the trends are pretty much the same. Median household income rose another 3.2 percent, after inflation, to its highest level ever. The poverty rate fell some more. The share of national income going to labor is now rising, while the share going to capital is falling.

That is from the new David Brooks column.

That topic has been knocking around for some time, with varying opinions.  I’ve now seen the clearest and most thorough treatment to date, namely from Gerald Auten and David Splinter.  It hasn’t received that much attention, perhaps because the results don’t have such a strong built-in constituency, but here goes:

Previous studies using U.S. tax return data conclude that the top one percent income share increased substantially since 1960. This study re-estimates the long-term trend in inequality after accounting for changes in the tax base, income sources missing from individual tax returns and changes in marriage rates. This more consistent estimate suggests that top one percent income shares increased by only about a quarter as much as unadjusted shares. Further, accounting for government transfers suggests that top one percent shares increased a tenth as much. These results show that unadjusted tax return based measures present a distorted view of inequality trends, as incomes reported on tax returns are sensitive to changes in tax laws and ignore income sources outside the individual tax system.

You’ll find the paper at the first link here.

In a new NBER working paper David Card and Abigail Payne have a stunning new explanation of the gender gap in STEM at universities. The conventional wisdom is that the gender gap is about women and the forces–discrimination, sexism, parenting, aptitudes, choices; take your pick–that make women less likely to study in STEM fields. Card and Payne are saying that the great bulk of the gap is actually about men and their problems. At least that is my interpretation of their results, the authors, to my mind, don’t clearly state just how much their results run against the conventional wisdom. (Have I misunderstood their paper? We shall see.)

The authors are using a large data set on Canadian high school students that includes data on grade 12 (level 4) high school classes and grades and initial university program. Using this data, the authors find that females are STEM ready:

…At the end of high school, females have nearly the same overall rate of STEM readiness as males, and
slightly higher average grades in the prerequisite math and science courses.  The mix of STEM related courses taken by men and women is different, however, with a higher concentration of women in biology and chemistry and a lower concentration in physics and calculus.

Since females are STEM-ready when leaving high school you are probably thinking that the gender gap must be a result either of different entry choices conditional on STEM-readiness or different attrition rates. No. Card and Payne say that entry rates and attrition rates are similar for males and females. So what explains why males are more likely to take a STEM degree than females?

The main driver of the gender gap is the fact that many more females (44%) than males (32%) enter university.  Simply assuming that non‐STEM ready females had the same university entry rate as non‐STEM ready males would
narrow the gender gap in the fraction of university entrants who are STEM ready from 14
percentage points to less than 2 percentage points.


On average, females have about the same average grades in UP (“University Preparation”, AT) math and sciences courses as males, but higher grades in English/French and other qualifying courses that count toward the top 6 scores that determine their university rankings. This comparative advantage explains a substantial share of the gender difference in the probability of pursing a STEM major, conditional on being STEM ready at the end of high school.

Put (too) simply the only men who are good enough to get into university are men who are good at STEM. Women are good enough to get into non-STEM and STEM fields. Thus, among university students, women dominate in the non-STEM fields and men survive in the STEM fields. (The former is mathematically certain while the latter is true only given current absolute numbers of male students. If fewer men went to college, women would dominate both fields). I don’t know whether this story will hold up but one attractive feature, as a theory, is that it is consistent with the worrying exit from the labor market of men at the bottom.

If we accept these results, the gender gap industry is focused on the wrong thing. The real gender gap is that men are having trouble competing everywhere except in STEM.

Hat tip: Scott Cunningham.

I haven’t had a chance to look at this one, but here is the headline summary from Brookings:

The new paper, published in the Fall 2017 edition of the Brookings Papers on Economic Activity, makes a strong case for looking at the opioid epidemic as one driver of declining labor force participation rates.

In fact, Krueger suggests that the increase in opioid prescriptions from 1999 to 2015 could account for about 20 percent of the observed decline in men’s labor force participation during that same period, and 25 percent of the observed decline in women’s labor force participation.

Here is the Brookings link.

Our findings indicate that premiums as a percentage of coverage purchased are regressive: premium shares are larger than income shares for lower-income zip codes. Payouts, however, also as a percentage of coverage purchased, are progressive, meaning lower-income zip codes receive a larger portion of claims paid. Overall net premiums (premiums – payouts) divided by coverage are also regressive.

That is from a recent paper by Bin, Bishop, and Kousky, via the excellent Kevin Lewis.  Here is Politico on the fight to thwart flood insurance reform.

The formal title of this important paper is “The Wind of Change: Maritime Technology , Trade , and Economic Development.”  One of the major findings is that if you consider 1850-1905, using conservative estimates, the introduction of the faster and more reliable steam ships was responsible for least half of the world trade boom during those years.

That was just published in the AER by Luigi Pascali.  Here is the abstract:

The 1870–1913 period marked the birth of the first era of trade globalization. How did this tremendous increase in trade affect economic development? This work isolates a causality channel by exploiting the fact that the introduction of the steamship in the shipping industry produced an asymmetric change in trade distances among countries. Before this invention, trade routes depended on wind patterns. The steamship reduced shipping costs and time in a disproportionate manner across countries and trade routes. Using this source of variation and novel data on shipping, trade, and development, I find that (i) the adoption of the steamship had a major impact on patterns of trade worldwide; (ii) only a small number of countries, characterized by more inclusive institutions, benefited from trade integration; and (iii) globalization was the major driver of the economic divergence between the rich and the poor portions of the world in the years 1850–1900.

Here are ungated copies.

Flooded Cities

by on September 1, 2017 at 12:35 am in Data Source, History, Science, Uncategorized | Permalink

That is the title of a recent research paper (pdf) by Adriana Kocornik-Mina, Thomas K.J. McDermott, Guy Michaels, and Ferdinand Rauch.  Here is the abstract:

Does economic activity relocate away from areas that are at high risk of recurring shocks? We examine this question in the context of floods, which are among the costliest and most common natural disasters. Over the past thirty years, floods worldwide killed more than 500,000 people and displaced over 650,000,000 people. This paper analyzes the effect of large scale floods, which displaced at least 100,000 people each, in over 1,800 cities in 40 countries, from 2003-2008. We conduct our analysis using spatially detailed inundation maps and night lights data spanning the globe’s urban areas. We find that low elevation areas are about 3-4 times more likely to be hit by large floods than other areas, and yet they concentrate more economic activity per square kilometer. When cities are hit by large floods, the low elevation areas also sustain more damage, but like the rest of the flooded cities they recover rapidly, and economic activity does not move to safer areas. Only in more recently populated urban areas, flooded areas show a larger and more persistent decline in economic activity. Our findings have important policy implications for aid, development and urban planning in a world with rapid urbanization and rising sea levels.

One possible implication of these strong results is that, better pricing of flood insurance, which I favor, still probably won’t get most population centers out of those low-lying, relatively vulnerable areas.

On a global level, the University of Colorado’s Roger Pielke Jr. notes that disaster losses as a percentage of the world’s G.D.P., at just 0.3 percent, have remained constant since 1990. That’s despite the dollar cost of disasters having nearly doubled over the same time — at just about the same rate as the growth in the global economy. (Pielke is yet another victim of the climate lobby’s hyperactive smear machine, but that doesn’t make his data any less valid.)

Climate activists often claim that unchecked economic growth and the things that go with are principal causes of environmental destruction. In reality, growth is the great offset. It’s a big part of the reason why, despite our warming planet, mortality rates from storms have declined from .11 per 100,000 in the 1900s to .04 per 100,000 in the 2010s, according to data compiled by Hannah Ritchie and Max Roser. Death rates from other natural disasters such as floods and droughts have fallen by even more staggering percentages over the last century.

That is from Bret Stephens at the NYT.

…competitive conduct changes quickly as the number of incumbents increases.  In markets with five or fewer incumbents, almost all variation in competitive conduct occurs with the entry of the second or third firm…once the market has between three and five firms, the next entrant has little effect on competitive conduct.

That is from Bresnahan and Reiss, “Entry and Competition in Concentrated Markets.

Part of their method is to compare doctor and dentist pricing practices across towns of different size, and thus across different numbers of providers.  Then they see where bigger numbers makes a difference in terms of pricing.  Plumbers and tire dealers are considered too.  One lesson seems to be that market concentration has to rise to very high levels to make a big difference in outcomes.

If you are wondering, the “sweet spot” for a town to have a single dentist or doctor is population between 700 and 900, at least circa the early 1990s.

Russia fact of the day

by on August 21, 2017 at 3:13 pm in Data Source, Economics, History, Law | Permalink

…the wealth held offshore by rich Russians is about three times larger than official net foreign reserves, and is comparable in magnitude to total household financial assets held in Russia.

That is from Novokmet, Piketty, and Zucman.