That is the column subtitle, the actual title is “The Lesson of Bretton Woods.” Note that yesterday was the 75th anniversary of the signing of the final agreement. Here is one excerpt:
The Bretton Woods arrangements also seemed highly unlikely until they were in place. They involved a complicated system of exchange rate pegs, capital controls and a “gold pool” (and other methods) to control gold prices and redemption ratios. What’s more, the whole thing was dependent on America’s role as global hegemon, both politically and economically. The dollar still was tied to gold, and the other major currencies tied to the dollar, but as the system evolved it required that no one was too keen to redeem dollars for gold (the French unwillingness to abide by this stricture was one proximate cause of the collapse of Bretton Woods).
I don’t think a monetary economist from, say, 1890 could have imagined that such an arrangement would prove possible, much less successful. Yet the Bretton Woods arrangements had a wonderful track record, as the 1950s and 1960s generated strong economic growth for both the U.S. and Western Europe.
At the same time, once Bretton Woods ended in the early 1970s, few people thought it was possible to turn back the clock. The system required the U.S. to be a creditor nation, to hold much of the world’s gold stock, and for countries such as France to defer to American wishes on gold convertibility. Once again, the line between an “imaginable” and “unimaginable” monetary arrangement proved to be a thin one.
As I point out in the piece, today’s arrangements of fiat currencies and (mostly) floating rates were unimaginable to most previous thinkers, including Keynes. Here is the column’s closing bit:
So as you consider the legacy of Bretton Woods this week, remember that core lesson: There will be major changes in monetary and institutional arrangements that no one can even imagine right now. Assume the permanency of the status quo at your peril.
That is the title of a new and important paper by Andrea L. Eisfeldt, Antonio Falato, and Mindy Z. Xiaolan. It seems that perhaps the share of labor in gdp has not fallen much after all:
The widespread and growing practice of equity-based compensation has transformed high-skilled labor from a pure labor input into a class of “human capitalists”. We show that high-skilled labor income in the form of equity claims to firms’ future dividends and capital gains has dramatically increased since the 1980s. Indeed, in recent years, equity-based compensation represents almost 45% of total compensation to high-skilled labor. Ignoring such income results in incorrect measurement of the returns to high-skilled labor, with important implications for macroeconomics. Including equity-based compensation to high-skilled labor cuts the total decline in the labor share since the 1980’s by over 60%, and completely reverses the decline in the high skilled labor share to an increase of almost 1%. Correctly measuring the return to high-skilled labor can thus resolve the puzzling lack of a skill premium in recent data, as well as the corresponding lack of evidence of complementarity between high-skilled labor and new-economy physical capital. Moreover, tackling the capital structure question of who owns firms’ profits is necessary to provide a link between changing factor shares and changing income and wealth shares. We use an estimated model to understand the rise of human capitalists in an economy with declining capital goods prices. Finally, we present corroborating cross section and time series evidence for complementarity between high-skilled labor and physical capital using our corrected measure of the total return to human capitalists.
Since smart people are bearing more and more risk, this may be another reason why income inequality is rising.
Via the excellent Kevin Lewis.
It is rare that anyone wishes to broach this general topic, on either side of the debate. This is from a new working paper by Geoffrey Heal and Wolfam Schlenker:
We highlight important dynamic aspects of a global carbon tax, which will reallocate consumption through time: some of the initial reduction in consumption will be offset through higher consumption later on. Only reserves with high enough extraction cost will be priced out of the market. Using data from a large proprietary database of field-level oil data, we show that carbon prices even as high as 200 dollars per ton of CO2 will only reduce cumulative emissions from oil by 4% as the supply curve is very steep for high oil prices and few reserves drop out. The supply curve flattens out for lower price, and the effect of an increased carbon tax becomes larger. For example, a carbon price of 600 dollars would reduce cumulative emissions by 60%. On the flip side, a global cap and trade system that limits global extraction by a modest amount like 4% expropriates a large fraction of scarcity rents and would imply a high permit price of $200. The tax incidence varies over time: initially, about 75% of the carbon price will be passed on to consumers, but this share declines through time and even becomes negative as oil prices will drop in future years relative to a case of no carbon tax. The net present value of producer and consumer surplus decrease by roughly equal amounts, which are almost entirely offset by increased tax revenues.
Here is an earlier MR post on the same topic, and it gives more of the theoretical intuition.
In recent years I have substantially increased my estimate of the deadly nature of air pollution. It’s not that I had a contrary opinion earlier but the number and range of studies showing surprisingly large effects has raised this issue in relative importance in my mind. I would not have guessed, for example, that the introduction of EZ Pass could reduce pollution near toll booths enough to reduce the number of premature and low birth weight babies. I also find the following result hard to believe yet also hard to dismiss given the the accumulating body of evidence. Diane Alexander and Hannes Schwandt find that Volkswagen’s cheating diesel cars increased the number of low birth weight babies and asthma rates. Here are some details:
In 2008, a new generation of supposedly clean diesel passenger cars was introduced to the U.S. market.These new diesel cars were marketed to environmentally conscious consumers, with advertising emphasizing the power and mileage typical for diesel engines in combination with unprecedented low emissions levels. Clean diesel cars won the Green Car of the Year Award in 2009 and 2010 and quickly gained market share. By 2015, over 600,000 cars with clean diesel technology were sold in the United States. In the fall of 2015, however, it was discovered that these cars covertly activated equipment during emissions tests that reduced emissions below official thresholds, and then reversed course after testing. In street use, a single “clean diesel” car could pollute as much nitrogen oxide as 150 equivalent gasoline cars.Hereafter, we refer to cars with “clean diesel” technology as cheating diesel cars.
We exploit the dispersion of these cheating diesel cars across the United States as a natural experiment to measure the effect of car pollution on infant and child health. This natural experiment provides several unique features. First, it is typically difficult to infer causal effects from observed correlations of health and car pollution, as wealthier individuals tend to sort into less-polluted areas and drive newer, less-polluting cars. The fast roll-out of cheating diesel cars provides us with plausibly exogenous variation in car pollution exposure across the entire socio-economic spectrum of the United States. Second, it is well established that people avoid known pollution, which can mute estimated impacts of air pollution on health (Neidell, 2009). Moderate pollution increases stemming from cheating diesel cars, a source unknown to the population, are less likely to induce avoidance behaviors, allowing us to cleanly estimate the full impact of pollution. Third, air pollution comes from a multitude of sources, making it difficult to identify contributions from cars, and it is measured coarsely with pollution monitors stationed only in a minority of U.S. counties. This implies low statistical power and potential attenuation bias for correlational studies of pollution (Lleras-Muney, 2010). We use the universe of car registrations to track how cheating diesel cars spread across the country and link these data to detailed information on each birth conceived between 2007 and 2015. This setting provides rich and spatially detailed variation in car pollution.
We find that counties with increasing shares of cheating diesel cars experienced large increases both in air pollution and in the share of infants born with poor birth outcomes. We show that for each additional cheating diesel car per 1,000 cars—approximately equivalent to a 10 percent cheating-induced increase in car exhaust—there is a 2.0 percent increase in air quality indices for fine particulate matter (PM2:5) and a 1.9 percent increase in the rate of low birth weight. We find similar effects on larger particulates (PM10; 2.2 percent) and ozone (1.3 percent), as well as reductions in average birth weight (-6.2 grams) and gestation length (-0.016 weeks). Effects are observed across the entire socio-economic spectrum, and are particularly pronounced among advantaged groups, such as non-Hispanic white mothers with a college degree. Effects on pollution and health outcomes are approximately linear and not affected by baseline pollution levels. Overall, we estimate that the 607,781 cheating diesel cars sold from 2008 to 2015 led to an additional 38,611 infants born with low birth weight. Finally, we also find an 8.0 percent increase in asthma emergency department (ED) visits among young children for each additional cheating diesel car per 1,000 cars in a subsample of five states.
Another surprising result is that on a global scale air pollution reduces life expectancy more than smoking. In part, because a single individual can’t quit air pollution.
Globally, the AQLI reveals that particulate pollution reduces average life expectancy by 1.8 years, making it the greatest global threat to human health. By comparison, first-hand cigarette smoke leads to a reduction in global average life expectancy of about 1.6 years. Other risks to human health have even smaller effects: alcohol and drugs reduce life expectancy by 11 months; unsafe water and sanitation take off 7 months; and HIV/AIDS, 4 months. Conflict and terrorism take off 22 days. So, the impact of particulate pollution on life expectancy is comparable to that of smoking, twice that of alcohol and drug use, three times that of unsafe water, five times that of HIV/AIDS, and more than 25 times that of conflict and terrorism.
One in five U.S. high-technology firms are led by CEOs with hands-on innovation experience as inventors. Firms led by “Inventor CEOs” are associated with higher quality innovation, especially when the CEO is a high-impact inventor. During an Inventor CEO’s tenure, firms file a greater number of patents and more valuable patents in technology classes where the CEO’s hands-on experience lies. Utilizing plausibly exogenous CEO turnovers to address the matching of CEOs to firms suggests these effects are causal. The results can be explained by an Inventor CEO’s superior ability to evaluate, select, and execute innovative investment projects related to their own hands-on experience.
He spent a bunch of weeks there, there are many good observations, here is one of them:
17. Big question: Why is Spain so much richer now than almost any country in Spanish America? Before you answer with great confidence, ponder this: According to Angus Maddison’s data on per-capita GDP in 1950, Spain was poorer than Argentina, Chile, Mexico, Peru, Uruguay, and Venezuela, and roughly equal to Colombia, Bolivia, Costa Rica, Cuba, Ecuador, Guatemala, and Panama. This is 11 years after the end of the Spanish Civil War, and Spain of course stayed out of World War II.
The worst grocery store I saw in Spain offered higher quality, more variety, and lower prices than the best grocery store I saw in Denmark, Sweden, or Norway.
Do read the whole thing.
I had never heard about this before:
The controversial practice of picking corporate sponsors for the European Union‘s rotating presidency is to continue, despite an outcry from MEPs.
EU countries have been raising eyebrows by doing deals with increasingly controversial multinational corporations during their stints overseeing debates at the EU council.
Romania’s presidency in the first half of 2019 was sponsored by Coca-Cola, with the US drinks giant’s logo plastered over banners and signs at meetings. One council summit in Bucharest featured Coca-Cola branded bean bag chairs, and a fridge of free drinks plastered with statistics about the company’s contribution to the economy.
Other sponsors of the council presidency have included car manufacturers, software companies, and other firms with vested interests in influencing EU policy.
But hopes that the incoming Finnish presidency, which took the helm this summer, might end the practice, were dashed after it picked German car manufacturer BMW as a sponsor – despite the firm being hit with a fine over its cars’ diesel emissions earlier this year.
By Gareth Cook, interesting and excellent throughout, here is one good bit of many:
For example, the strongest correlation is the number of intact families. The explanation seems obvious: A second parent usually means higher family income as well as more stability, a broader social network, additional emotional support, and many other intangibles. Yet children’s upward mobility was strongly correlated with two-parent families only in the neighborhood, not necessarily in their home. There are so many things the data might be trying to say. Maybe fathers in a neighborhood serve as mentors and role models? Or maybe there is no causal connection at all. Perhaps, for example, places with strong church communities help kids while also fostering strong marriages. The same kinds of questions flow from every correlation; each one may mean many things. What is cause, what is effect, and what are we missing? Chetty’s microscope has revealed a new world, but not what animates it—or how to change it.
Here is the full piece.
The AEA has long had a data repository but no one was responsible for examining the data or replicating a paper’s results and confidential data was treated as an exception. All that is about to change. The AEA has hired a Data Editor, Lars Vilhuber. Vilhuber will be responsible for verifying that the author’s code produces the claimed results from the given data. In some cases Vilhuber will even verify results from raw data all the way to table output.
The new data policy is a significant increase in the requirements to publish in an AEA journal. It takes an immense amount of work to document in a replicable way every step of the empirical process. It’s all to the good, of course, but it is remarkable how little economists train our students in these techniques and make no mistake writing code to be replicable from day one is an art and a science and it needs to be part of the econometrics sequence. All hail Gentzkow and Shapiro!
Here’s more information:
On July 10, 2019, the Association adopted an updated Data and Code Availability Policy, which can be found at https://www.aeaweb.org/journals/policies/data-code. The goal of the new policy is to improve the reproducibility and transparency of materials supporting research published in the AEA journals by providing improved guidance on the types of materials required, increased quality control, and more review earlier in the publication process.
What’s new in the policy? Several items of note:
A central role for the AEA Data Editor. The inaugural Data Editor was appointed in January 2018 and will oversee the implementation of the new policy.
The policy now clearly applies to code as well as data and explains how to proceed when data cannot be shared by an author. The Data Editor will regularly ask for the raw data associated with a paper, not just the analysis files, and for all programs that transform raw data into those from which the paper’s results are computed. Replication archives will now be requested prior to acceptance, rather than during the publication process after acceptance, providing more time for the Data Editor to review materials.
Will the Data Editor’s team run authors’ code prior to acceptance? Yes, to the extent that it is feasible. The code will need to produce the reported results, given the data provided. Authors can consult a generic checklist, as well as the template used by the replicating teams.
Will code be run even when the data cannot be posted? This was once an exemption, but the Data Editor will now attempt to conduct a reproducibility check of these materials through a third party who has access to the (confidential or restricted) data. Such checks have already been successfully conducted using the protocol outlined here.
What are the best things to read on this topic? How does it work? Why is it difficult and expensive (to the extent it is)? How might current institutions be improved? And what determines bid-ask spreads in the relevant trading markets?
I thank you all in advance for your wisdom and counsel.
That is the subject of my latest Bloomberg column, and here are the closing bits:
So that means the trade war is really all about Huawei and Taiwan. If the U.S. persists in trying to eliminate Huawei as a major company, by cutting off its American-supplied inputs and intimidating foreign customers and suppliers for Huawei equipment, it will be difficult for the Chinese to accept. In this case, the reluctance to make a deal will be on the Chinese side, and the structure and relative power of the various American interest groups are not essential to understanding the outcome.
The question, then, is whether the U.S. national security establishment, and in turn Congress (which has been heavily influenced on this question), will accept a compromise on Huawei. Maybe that means no Huawei communications technologies for the U.S. and its closest intelligence-sharing allies, but otherwise no war against the company. That is the first critical question to watch in the unfolding of this trade war. The answer is not yet known, though it seems Trump is willing to deal.
The second major question, equally important but less commented upon, is Taiwan. China has long professed a desire to reunite Taiwan with the mainland, using force if necessary. If you belong to the U.S. national security establishment, and you think a confrontation with China is necessary sooner or later, if only because of Taiwan, you would prefer sooner, before China gains in relative strength. And that militates in favor of the trade war continuing and possibly even escalating, as the U.S. continues to push against China and there is simply no bargain to be had.
It is far from clear what a U.S.-China deal over the status of Taiwan could look like. How much Americans actually care about Taiwan is debatable, but the U.S. is unlikely to abandon a commitment that would weaken its value as an ally around the world. And unlike with Huawei, it is difficult to see what a de-escalation of this issue might look like.
So: If the Huawei and Taiwan questions can be resolved, then the trade war should be eminently manageable. Now, does that make you optimistic or pessimistic?
There is much more at the link.
The FT writes about the bust in India’s construction sector:
It was meant to be the tallest building in India, with luxury flats, a swimming pool and cinema where billionaires and Bollywood stars could enjoy a life of perfect splendour looking down over the Mumbai skyline.
But the Palais Royale complex now sits unfinished alongside other partially built structures tangled in the megacity’s traffic-choked downtown streets, an apt symbol of a crisis that threatens a key part of India’s financial system.
Part of the problem is cyclic, a shadow banking system that overextended credit and is now having to deleverage. India’s construction sector, however, is also plagued by systematic issues including the fact that major construction projects are invariably sued and thus become entangled with India’s notoriously slow legal system. Drawing on a Brookings India working paper by Gandhi, Tandel, Tabarrok and Ravi the FT notes:
But progress was soon slowed by legal challenges over allegedly unauthorised features, sparking a series of delays….However grand the planned building, Palais Royale’s woes fit a familiar pattern: 30 per cent of real estate projects and half of all built-up space in Mumbai is under litigation, according to a 2019 Brookings India report, with projects taking an average of eight and a half years to complete.
Here is the opening of a Jacob M. Schlesinger Wall Street Journal piece:
For decades, William Darity Jr. and Darrick Hamilton toiled in obscurity. They criticized mainstream economists and politicians for failing to address racial inequality, and touted more radical remedies of their own.
Now, with the 2020 presidential campaign under way and liberal Democrats ascendant, the two economists are in the spotlight, thrust into the middle of an intraparty debate over how much to embrace big government and a race-oriented message.
Their signature ideas—guaranteed jobs for all adult Americans seeking them, government-backed trust funds for American babies and reparations for slave descendants—are being talked about on the campaign trail and, in the case of reparations, during a raucous congressional hearing in June.
The two African-American economists’ theories on “stratification economics,” which focuses on economic gaps between whites and blacks, have helped shape the rhetoric and platforms of several candidates.
At a conference earlier this year for liberal activists, New Jersey Sen. Cory Booker told Mr. Hamilton he had “laid the foundation for a lot of things that we’re doing,” including “baby bonds.” Former Texas Rep. Beto O’Rourke name-checks Mr. Hamilton in television interviews, calling him an “extraordinary economist” who “talks about a more conscious capitalism.”
Mr. Hamilton, an Ohio State University professor, has advised the campaigns of California Sen. Kamala Harris on middle-class tax cuts, Vermont Sen. Bernie Sanders on job guarantees and Massachusetts Sen. Elizabeth Warren on student-debt relief.
And this section:
They have teamed up to write more than 50 articles for academic and popular journals and books, and pioneered what they consider a new field of scholarship they branded stratification economics. They contend that mainstream economists tend to regard racial discrimination as a short-term market glitch that market forces will correct eventually. That logic, they say, leads to the conclusion that persistent African-American woes result mainly from their own failings, such as inadequate education or poor financial choices.
Policy makers, they contend, focus too much on employment, income and education and not enough on family wealth across generations. They say wealth is a better measure of household economic security—the ability to weather emergencies, pay for education, afford homes in good neighborhoods and take risks.
I hope you subscribe or can get through the gate, as there are many meaty sections. One interesting angle, of course, is whether their claims and theories are true. But most of all this piece, and their role as advisers, marks the end of an era, namely that of mainstream consensus technocracy. The range of ideas being considered in politics today is remarkably wider than just a few years ago, for better or worse. And, whether we like to admit it or not, the academic world also will follow rather than just lead this process. If a plausible candidate pops up and starts making claims, especially on the Democratic side, the academic research supporting those claims will rise in status.
Fasten your seatbelts.