Month: March 2020
Recent influential work finds large increases in inequality in the U.S., based on measures of wealth concentration that notably exclude the value of social insurance programs. This paper revisits this conclusion by incorporating Social Security retirement benefits into measures of wealth inequality. Wealth inequality has not increased in the last three decades when Social Security is accounted for. When discounted at the risk-free rate, real Social Security wealth increased substantially from $5.6 trillion in 1989 to just over $42.0 trillion in 2016. When we adjust for systematic risk coming from the covariance of Social Security returns with the market portfolio, this increase remains sizable, growing from over $4.6 trillion in 1989 to $34.0 trillion in 2016. Consequently, by 2016, Social Security wealth represented 58% of the wealth of the bottom 90% of the wealth distribution. Redistribution through programs like Social Security increases the progressivity of the economy, and it is important that our estimates of wealth concentration reflect this.
That is from a new paper by Sylvain Catherine, Max Miller, and Natasha Sarin, I look forward to reading it soon. It is at least possible that the Saez-Zucman results are coming under further question.
Just to repeat part of the abstract, I find this sentence striking: “When discounted at the risk-free rate, real Social Security wealth increased substantially from $5.6 trillion in 1989 to just over $42.0 trillion in 2016.” That’s a lot.
And this one: “Consequently, by 2016, Social Security wealth represented 58% of the wealth of the bottom 90% of the wealth distribution.” Wow.
We develop a new method to measure CEO behavior in large samples via a survey that collects high-frequency, high-dimensional diary data and a machine learning algorithm that estimates behavioral types. Applying this method to 1,114 CEOs in six countries reveals two types: “leaders,” who do multifunction, high-level meetings, and “managers,” who do individual meetings with core functions. Firms that hire leaders perform better, and it takes three years for a new CEO to make a difference. Structural estimates indicate that productivity differentials are due to mismatches rather than to leaders being better for all firms.
The double oral auction was one of the first experiments that Vernon Smith ran. He was expecting to find that the supply and demand model didn’t work. Instead, the results changed his life and led to a Nobel prize:
I am still recovering from the shock of the experimental results. The outcome was unbelievably consistent with competitive price theory. … But the result can’t be believed, I thought. It must be an accident, so I will take another class and do a new experiment with different supply and demand schedules. (Smith 1991)
I’ve run similar experiments in my principles class. The exercise is fun for the students and it’s always amazing to see how quickly the equilibrium is attained even though none of the participants has any idea what the equilibrium price and quantity are. The experiment can be run with paper and pencil or a laptop in a small class but that gets cumbersome for a larger class. Fortunately, there are some free tools.
Here’s Hampton and Johnson describing Kiviq.us.
Kiviq.us provides an online version of the double oral auction that works on all student Internet-enabled devices, including smartphones and iPads, without requiring students or instructors to download any special software. Results can be projected on a screen for debriefing. Instructors can set key parameters. A version with price controls can be setup. The use of the experiment is free for instructors and students. Students do not have to give their email address to play.
The design is the classic market experiment for introducing students to demand and supply. Joseph (1970) makes a strong case for the benefits of the “market experiment” in teaching based on experience with high school and undergraduate students. The original experiment was created by Smith (1962).
….After a trading session, instructors can debrief showing dynamically the history of bids, asks, trades, individual attribution of bids/asks (by clicking the chart), individual total earnings, and the underlying demand and supply curves.
Modern Principles of Economics introduces the supply and demand model and Smith’s classic experiment and thus is an ideal accompaniment.
New reports suggest that the coronavirus has been spreading in Washington state for at least six weeks, infecting hundreds or maybe more. At the same time, other reports suggest a high “R0 value,” sometimes 3 or more, reflecting that the coronavirus is highly contagious and it spreads very quickly.
It is then possible to have hundreds of cases in Washington state if most cases are asymptomatic, or with only slight symptoms. Yet when we look at the experiences of the coronavirus cruise ships, it seems a reasonable number of cases have symptoms of distress. For instance, on the Diamond Princess six people died and only about half are listed as having the virus but asymptomatic (see the previous link on the rhs). So many others seem to have reported being sick or requiring treatment.
So what gives? I see a few options, none of them obviously convincing:
1. People on the cruise ship were hit especially hard.
2. Significantly different strains of the virus are circulating (all of the sequence that has been done seems to run counter to this).
3. Washington state local public health infrastructure has in fact been overwhelmed as of late, we just thought it was all a very bad flu season.
4. Many of the people on the cruise ship who showed symptoms “thought they were supposed to” but were not actually so sick.
5. Most of the detected cases on the cruise ship in fact were asymptomatic, but the media has been misreporting the extent of actual illness among the passengers.
Any other suggestions? It is quite likely the cruise ship people are older than usual, but will that make up for the entire difference? People, what do you think is going on here?
Please restrict your comments to attempting to resolve this particular issue, as you can put your more general coronavirus observations on other posts.
That is from Jon Hartley, and here is his closely related new paper “Recession Prediction Markets and Macroeconomic Risk in Asset Prices.” Here is the prediction market page, at 47 as I am writing.
That is the topic of my latest Bloomberg column, note first of all that the virus is a kind of referendum on global response capabilities, and so far we have been failing (with Singapore as a possible exception). Here is another bit:
…investors now have a better sense of what other investors think about risk. Before Covid-19, investors did not have much direct information about what other investors thought about the robustness of the global economy. Their expectations were not seriously being tested.
When a new shock to the system comes along, however, everyone gets to observe everyone else’s selling behavior. And investors have learned that the faith of their fellow investors is not as strong as they had thought. That raises the risk premium on holding stocks, and in turn causes share prices to fall more. Given how much this pandemic is a truly new event, and that the process of trading itself generates information about the forecasts of other investors, price volatility can be expected to continue.
The stock market is scared by the fact that it took so long for the stock market to be scared.
2. Cowen’s Second Law: “How the Avengers assemble: Ecological modelling of effective cast sizes for movies.”
4. “The Oxford lexicographers have updated the dictionary with 29 Nigerian words, recognising the “unique and distinctive contribution to English as a global language” of Africa’s most populous country.”
My neologism for: The act of seeing a public library under renovation/expansion, and rightfully fearing that upon reopening the book collection will be smaller rather than larger.
This time it is Mary Riley Styles Library in Falls Church City.
Nicholas Whitaker of Brown, general career development grant in the area of Progress Studies.
Coleman Hughes, travel and career development grant.
Michael T. Foster, career development grant to study machine learning to predict which politicians will succeed and advance their careers.
John Strider, a Progress Studies grant on how to reinvent the integrated corporate research lab.
Dryden Brown, to help build institutions and a financial center in Ghana, through his company Bluebook Cities.
Adaobi Adibe, to restructure credentialing, and build infrastructure for a more meritocratic world, helping workers create property rights in the evaluation of their own talent.
Jassi Pannu, medical student at Stanford, to study best policy responses to pandemics.
Vasco Queirós, for his work on a Twitter browser app for superior threading and on-line communication.