The latest Nobel Prize in economics

Timothy Taylor has coverage

The award announcements says that one-half of the award is given to David Card “for his empirical contributions to labour economics,” while the other half is given jointly to Joshua D. Angrist and Guido W. Imbens “for their methodological contributions to the analysis of causal relationships.”

All three are involved in what Angrist and Jörn-Steffen Pischke dubbed the “credibility revolution” in empirical economics. As Alex Tabarrok puts it,

Almost all of the empirical work in economics that you read in the popular press (and plenty that doesn’t make the popular press) is due to analyzing natural experiments using techniques such as difference in differences, instrumental variables and regression discontinuity.

Last year, I suggested that a Nobel should go to Edward Leamer, the economist who set off the credibility revolution.

The Leamer critique caused economists to largely abandon ordinary multiple regression and to instead employ more credible research designs, such as natural experiments.

Leamer in 2010 pointed out that the newer methods also come with limitations. But, alas, he was bypassed by the Nobel committee.

Noah Smith goes way overboard in praise of the new laureates. He makes it sound as though the results that David Card and Alan Krueger claimed about the minimum wage were only controversial because they were surprising. But they were also controversial because they were wrong.

PSST watch

Timothy Taylor writes,

Every recession involves a reorganization and restructuring of the economy. In a standard recession, this involves a larger-than-usual number of companies going broke, and workers needing to scramble for different jobs. But the restructuring in the pandemic recession–and in continuing restructuring in the pandemic that has continued even though the pandemic recession ended back in April 2020–is of a different sort. There are new dividing lines across the labor force like who can work from home, and what sectors of the economy have been more affected by the pandemic on an ongoing basis, and whether parents can rely on sending their children physically off to school. There are concerns about what working environments are more or less safe.

And every recovery involves discovering new patterns of sustainable specialization and trade, requiriing entrepreneurial trial and error.

Shareholders vs. stakeholders

Timothy Taylor writes,

if a focus on stakeholders always or usually benefited shareholders, then there would be no reason to argue for a focus on stakeholders. Thus, one can reasonably assume that those who advocate a focus on “stakeholders” believe that such actions would make shareholders worse off, but that this social tradeoff is worthwhile.

I doubt that anyone says this out loud. In any case, Taylor links to a paper by Bebchuk, et al, that finds (as they and others have always found) that CEOs focus on shareholders.

Central bank digital currency

Timothy Taylor has helpful post. He cites the potential to lower the cost of making payments compared with using bank deposits. But then

At least to me, other advantages sometimes cited for a central bank digital currency often miss the point. For example, one will sometimes hear claims that the Fed needs a digital currency to compete with the cryptocurrencies like Bitcoin and Ethereum. But it’s not at all clear to me that these cryptocurrencies are anywhere near unseating the US dollar as a mechanism for payments, and it’s quite clear to me that competing with Bitcoin is not the Fed’s job. Or one will hear that because other central banks are trying digital currencies, the Fed needs to do so, also. My own sense is that it’s great for some other central banks to try it out, and for the Fed to wait and see what happens. There is a hope that zero-cost bank accounts at the Federal Reserve might help the unbanked to get bank accounts, but it’s not clear that this is an effective way to reach the unbanked (who are often disconnected from the financial sector and even the formal economy in many ways), and there are a number of policy tools to encourage banks to offer cheap or even zero-cost no-frills bank accounts that don’t involve creating a central bank digital currency.

For now, I file CBDC under “solutions in search of a problem.”

Road to sociology watch

M. V. Lee Badgett, Christopher S. Carpenter and Dario Sansone report,

Public attitudes and policies toward LGBTQ individuals have improved substantially in recent decades. Economists are actively shaping the discourse around these policies and contributing to our understanding of the economic lives of LGBTQ individuals.

From the Journal of Economic Perspectives (an important mainstream journal), as reported by Timothy Taylor, the long-time managing editor.

Let’s be clear. The Democratic Party was once the home of economists who, while rather too confident in their technocratic skills for my taste, at least understood how to add, subtract, and distinguish demand from supply. They would not have embarked on the dangerous, inflation-stoking efforts of the current Administration.

But contemporary economists are thriving. They are contributing to the study of LGBTQ! And the status of women in the profession is now a major concern!

The top 150 intellectuals, selected competitively

We held the Fantasy Intellectual Teams draft on Saturday. 10 owners competed. The owners came from the readership of this blog, and they themselves are not public figures in any way. The intellectuals they chose are shown below in the order they were selected. Because one owner arrived well after the draft had begun, the order in which teams picked was a bit mixed up.

Scoring for this season, which starts April 1 and ends June 30, is based on three categories:

(M) memes. These are phrases that are associated with a certain intellectual. For example, Black Swan is associated with Taleb (pick 31). If during the season the term Black Swan is used in at least three prominent places (well-known podcast or blog, newspaper, new book), that scores one M for Taleb. No more than one M per season for each catch-phrase. Richard Dawkins, who coined the term “meme,” was not chosen, although picking him would have guaranteed his owner at least one meme point.

(B) bets. An intellectual scores a B by expressing a belief in quantitative probabilistic terms. Oddly enough, Annie Duke, who would be credited with a meme if the phrase “Thinking in Bets” were to appear three times during the season, was not selected, either.

(S) steel-manning. The intellectual presents a point of view with which he or she disagrees in a way that someone who holds that point of view would consider to be representative. It is the opposite of straw-manning. I believe that Peter Thiel (pick 70) coined the term, or at least popularized it, and his owner is all but certain to pick up an M point. S’s are most likely to be earned by bloggers and podcasters and least likely to be earned by tweets or political speeches. They are more likely to be earned by centrists than by hard-core Red or Blue team members.

Tyler Cowen (pick 2) is a solid three-category player. He sometimes states beliefs in terms of probabilities, he tries to steel-man (although at times he can be too terse to earn a point), and he has meme candidates, such as Great Stagnation or “mood affiliation.”

Scott Alexander (pick 4) is likely to be a monster in the S and B categories.

I think that for next season I would add a category (R), for summarizing the research on two (or more) sides of a controversial issue. I would score one R for every 2 examples. I don’t want to give away an R to someone who just looks at research on a single topic during the season. Adding the (R) category would make Tyler and Scott even stronger candidates.

I will note that I thought that about a third of the picks reflected mood affiliation, and I would not have chosen them. I don’t want to pick on any owner in particular, but I’ll just say that I don’t think politicians will score points, and I will not be rooting for whoever took Oren Cass. By the end of this season, all of the picks will have track records, and those should inform owners who compete in a follow-up season.

I would caution the reader not to pay too much attention to relative ranking within this list. If there had been ten drafts, with ten different sets of owners, the average order would represent a consensus rank. But with only one iteration, the results reflect individual idiosyncrasies. In your comments, I am not interested in what picks you don’t like or what picks you think should have gone higher. I am interested in suggestions for intellectuals who seem likely to earn at least 3 points but who were not chosen.

Much as I poor-mouth my connections, I can brag by saying that in recent years I have had lunch and/or exchanged text messages with pick numbers 2, 5, 13, 32, 37, 38, 42, 95, 97, 132, and 147. I have met several others in person, but not recently. I believe that a social graph of the picks would show Tyler Cowen (2) and Marc Andreessen (97) as having the most dense connections with other picks.

Continue reading

The recent evolution of central banking in the U.S.

Timothy Taylor writes,

when I was teaching big classes in the late 1980s and into the 1990s, the textbooks all discussed three tools for conducting monetary policy: open market operations, changing the reserve requirement, or changing the discount rate.

Somewhat disconcertingly, when my son took AP economics in high school last year, he was still learning this lesson–even though it does not describe what the Fed has actually been doing for more than a decade since the Great Recession. Perhaps even more disconcertingly, when Ihrig and Wolla looked the latest revision of some prominent intro econ textbooks with publication dates 2021, like the widely used texts by Mankiw and by McConnell, Brue and Flynn, and found that they are still emphasizing open market operations as the main tool of Fed monetary policy.

I recommend the whole post. I think this is an important issue.

The way I see it, central bank practices moved away from the textbook story at least 40 years ago. There were three important steps.

1. Intervention via the market for repurchase agreements, commonly called the repo market.

2. The use of risk-based capital requirements (RBC) to steer the banking sector.

3. The expansion of bank reserves and the payment of interest on reserves (IOR).

I will discuss these in turn. Continue reading

Administrative data in economic research

Timothy Taylor writes,

economic research often goes well beyond these extremely well-known data sources. One big shift has been to the use of “administrative” data, which is a catch-all term to describe data that was not collected for research purposes, but instead developed for administrative reasons. Examples would include tax data from the Internal Revenue Service, data on earnings from the Social Security Administration, data on details of health care spending from Medicare and Medicaid, and education data on teachers and students collected by school districts. There is also private-sector administrative data about issues from financial markets to cell-phone data, credit card data, and “scanner” data generated by cash registers when you, say, buy groceries.

Vilhuber writes: “In 1960, 76% of empirical AER [American Economic Review- articles used public-use data. By 2010, 60% used administrative data, presumably none of which is public use …”

The quote is from a paper by Lars Vilhuber.

My thoughts:

1. The Census Bureau has procedures in place for allowing researchers to use administrative data while making sure that no individual record can be identified. I know this because one of my daughters worked at Census in this area for a few years.

2. The private firms that collect data as part of their business are not going to waste resources making sure that the data is free from coding mistakes and other errors. Researchers who are used to assuming that they are working with clean data are going to be surprised.

3. The data surrounding COVID are particularly treacherous. I found this out first-hand back when I was trying to follow the virus crisis closely.

4. This course should be taught more widely. As a point of trivia, the professor, Robert McDonald, was an undergraduate roommate of Russ Roberts (now the host of EconTalk) and also shared an apartment with me our first year of graduate school.

Extreme Wealth

Timothy Taylor writes,

the big story with US wealth is the growth in wealth/GDP ratio and the growing share of that wealth held by the top 1%. The share of wealth going to the top 1% shows occasional setbacks, like when the stock market fell in 2001 or in the aftermath of the Great Recession, but overall, the share of wealth going to this group has risen from about 24% of the total back in 1990 to above 30% of the total more recently.

Read the whole post.

Note that the ratio of wealth to GDP can be decomposed as the ratio of earnings of assets to GDP times the price/earnings ratio for assets. My impression, and I could check this, is that earnings of real estate have gone up a lot as a share of GDP, but corporate profits as a share of GDP have not gone up as fast. Instead, what has powered the stock market has been an increase in the price/earnings ratio, and/or the ratio of profits of firms on the stock exchange to profits of small businesses has gone up considerably.

As to “shares” of wealth, I bet that if you look at the actual households that were in the top 1 percent in 1990, their share of wealth did not go up over the past 30 years. What went up was an arithmetic measure of the share of the wealth in 2020 held by the top 1 percent of households as of 2020 relative to the share of the wealth in 1990 held by the top 1 percent of households as of 1990.

My guess is that the amount of churn at the top of the wealth distribution is higher than it was thirty years ago, although that is something that one could check. You could compare the turnover in a magazine’s list of the richest people from say, 1985-1990 to the turnover from 2015-2020.

Virus update

1. Timothy Taylor has a useful discussion and links regarding the issue of whether lockdowns have a large effect over and above voluntary changes in behavior.

2. The president told me [Marc Siegel] in a late July interview that he was more excited about therapeutics in the short term even than vaccines. Does that mean he reads my blog?

3. The average daily death rate has trended up recently.

4. Robin Hanson writes,

those virus harm estimates come from assuming a $7M value for each of these lives lost, and that I say does seem crazy.

He refers to estimates by David Cutler and Larry Summers of the direct harm caused by the virus vs. the indirect cost of prevention measures. The thrust of Robin’s post is that the cost of the prevention measures was probably higher than the cost of the virus, and that we are “over-preventing” COVID. I want to question that conclusion.

We should be cautious about employing the notion of “lost GDP.” There are two states of the world, one in which some activities have little or no perceived risk and the other in which those activities have a significant perceived risk. The value of “output” for those activities differs under those two states of the world.

Note that most of the prevention measures were voluntary. Many of us are making decisions to restrict travel, social activities, and in-person shopping. Our revealed preferences indicate that the GDP that we are thus giving up is worth less to us than the value of risk prevention.

Think of it as a relative price shift. Valuing today’s output at yesterday’s relative prices can be misleading.