Category: Data Source

Our aggregate demand shortfall?

From Ben Casselman: “…unlike with most measures of the economy, retail sales are actually ABOVE their prepandemic level. Up 2.6% from February, and 2.9% over the past year. So not a clean story like with jobs.”

And from Larry Summers: ” Total household income is 8% above what anybody thought it would be before Covid.”

There are very real macroeconomic problems right now, but please keep the following in mind while drawing up a “demand-based” stimulus plan.  Focus on public health!

Ireland fact of the day, coming soon to a state near you

Some experts estimate this could mean, if we do not accelerate the pace of vaccination, one million deaths for the United States.

Who Runs the AEA?

That is a new paper by Kevin D. Hoover and Andrej Svorenčík:

The leadership structure of the American Economics Association is documented using a biographical database covering every officer and losing candidate for AEA offices from 1950 to 2019. The analysis focuses on institutional affiliations by education and employment. The structure is strongly hierarchical. A few institutions dominate the leadership, and their dominance has become markedly stronger over time. Broadly two types of explanations are explored: that institutional dominance is based on academic merit or that it based on self-perpetuating privilege. Network effects that might explain the dynamic of increasing concentration are also investigated.

I wonder how the AEA budget will hold up now that interviews can be done by Zoom and meeting attendance is not required.

Via the excellent Kevin Lewis.

We are more risk-averse for other people

From Pavel D. Atanasov:

Are we more inclined to take risks for ourselves rather than on someone else’s behalf? The current study reviews and summarizes 28 effects from 18 studies (n=4,784). Across all studies, choices for others were significantly more risk-averse than choices for self (d=0.15, p=0.012). Two objective features of the choices moderated these effects: potential losses and reciprocal relationships. First, self-other differences in risk preferences were significant in the presence of potential losses (k=14, d=0.33, p<.001), and not significant (k=14, d=-0.06, p=0.473) in the gains-only domain (Q=12.56, p=<0.001). Choices for others were significantly more risk-averse when decision makers were reciprocally related to recipients (k=6, d=0.33, p=0.018) but no different in the absence of such a relationship (d=0.11, p=0.115). Reciprocal relationship was a marginally significant predictor (Q=2.02, p=0.155). Results are shown separately by publication status and by context (medical, economic game, hypothetical choice). A relational model of surrogate risk taking is proposed to explain the pattern of results, which emphasizes the importance of chooser-recipient relationships, and the tendency of choosers to minimize anticipated blame from losses, rather than maximizing credit for gains. Implications for benefits design, medical and managerial decision making are discussed.

At least that is what the science says.

How will we interpret data on the new strain?

Instead of exploding relative to a baseline of 0 cases (like in March), the new strain will be exploding relative to a baseline of around 200,000 cases per day. As a result, day-to-day random noise will completely mask any increase in infections from the new strain until it becomes dominant — around day 40 in the above chart. This means that if people use the overall numbers to guide their levels of precaution, our reaction time could lag by two or three weeks compared to March — as if we had locked down in early April instead of mid-March.

Now, this isn’t entirely a correct comparison because the rate of exponential growth will be much below 1.36; a reasonable guess might be 1.12. (You can get this by assuming R = 1.6 and assuming a generation time of 4 days.) But the overall point is the same: because any increase in the prevalence of the new strain will be masked by noise in current COVID levels, the new strain won’t be evident in overall numbers until it starts contributing hundreds of thousands of daily infections.

That is from Eric Neyman, good points thought note we will have independent measures of the spread of the new strain, with shorter lags than is currently the case.

Sudan estimate of the day

…researchers have just declared that there was a huge, hidden outbreak in the capital of Sudan. In the absence of a good death registration system, they used a molecular and serological survey and an online one distributed on Facebook, where people reported their symptoms and whether they’d had a test. The researchers calculated that Covid-19 killed 16,000 more people than the 477 deaths confirmed by mid-November in Khartoum, which has a population roughly the size of Wisconsin’s.

Here is the full NYT article by Ruth Maclean.  The main theme of the piece is that Africa may not have escaped Covid by nearly as much as we had thought.

The racialization of international trade preferences

…we find that white individuals have become less supportive of trade than minorities and that whites are more likely than minorities to favor trade with highly similar countries. We suggest that minority support for trade is due to four well‐documented differences in the psychological predispositions of whites and minorities in the United States. Minorities have lower levels of racial prejudice, are lower in social dominance, and express less nationalism than whites. At the same time, there is evidence of rising ingroup racial consciousness among whites. Each of these characteristics has been independently linked to trade support in a direction encouraging greater support for trade among minorities. As the United States grows ever closer to becoming a “majority minority” nation, the racialization of trade attitudes may stimulate shifts in the likely future of America’s trade relationships.

That is from a new paper by Diana Mutz, Edward D. Mansfield, and Eunij Kim.  Via the excellent Kevin Lewis.

Covid-19 is also not so great for young people

Young adults are dying at historic rates. In research published on Wednesday in the Journal of the American Medical Association, we found that among U.S. adults ages 25 to 44, from March through the end of July, there were almost 12,000 more deaths than were expected based on historical norms.

In fact, July appears to have been the deadliest month among this age group in modern American history. Over the past 20 years, an average of 11,000 young American adults died each July. This year that number swelled to over 16,000.

The trends continued this fall. Based on prior trends, around 154,000 in this demographic had been projected to die in 2020. We surpassed that total in mid-November. Even if death rates suddenly return to normal in December — and we know they have not — we would anticipate well over 170,000 deaths among U.S. adults in this demographic by the end of 2020.

That is from Jeremy Samuel Faust, Harlan M. Krumholz and at the NYT.  To be clear, this is not the main problem, but it is not a nothingburger either.  3,656 deaths per day right now, no matter what the ages how many other American catastrophes can rival that?  #1 cause of death in the country right now, bar none.

From David Splinter, from my email

This is all David:

A related paper by BEA came out today with their updated distributional estimates of personal income. Marina Gindelsky has done a lot of work to produce these estimates.

I have a couple new papers on tax progressivity and redistribution that may be of interest to you. Both used CBO data to avoid the PSZ-AS differences. Abstracts below.

The first paper is about the ends of the distribution: tax progressivity has increased significantly since 1979 (and steadily since 1986) due to more generous tax credits for the bottom, while average tax burdens of the top have been relatively unchanged because lower marginal rates were offset by decreased use of tax shelters. The online appendix shows why the CBO estimates differ from those of Saez and Zucman (see Fig. B7 at the end; it’s mostly due to refundable credits at the bottom and imputed income at the top) and the Heathcote et al. paper you blogged about a couple months ago (it’s technical differences and their inclusion of some transfers, but their most similar measure of tax progressivity was not flat—it increased 21 percent since 1979).

The second paper, with Adam Looney and Jeff Larrimore, is about the middle of the distribution. Since 1979, we found that non-elderly middle-class market income increased 39 percent in real per person terms. The increase was 57 percent when accounting for taxes and transfers. This seems to fit with the “updated” view of stagnation—expanding male wages to also look at untaxed compensation and including female compensation and taxes/transfers shows larger median growth. But there was a structural break in 2000. Before then, middle-class incomes grew at the same rate before and after taxes and transfers, and since then income after taxes and transfers grew three times faster (Fig. 6 on page 19). We don’t discuss the recent market income slowdown (maybe related to the debated labor share break around 2000), but we show that the additional fiscal support that filled the gap looks like an unsustainable way to boost middle-class disposable incomes going forward.”

Are the elites worse than you think?

Here is a new and important paper by Joshua D. Kertzer, noting that it mainly confirms what I observe every day (aren’t those the very best research studies?)  Here is part of the abstract:

…political scientists both overstate the magnitude of elite-public gaps in decision-making, and misunderstand the determinants of elite-public gaps in political attitudes, many of which are due to basic compositional differences rather than to elites’ domain-specific expertise.

My rewrite of his sentence is that elites are arguing from their class and demographic biases (a bias can be positive, to be clear), not from their expertise.  That lowers the marginal value of expertise, at least given how our world operates.  I recall earlier research blogged by Alex showing that if you are a French economist, your views are more influenced by being a French person than by being an economist.  And so on.

This is one of the very most fundamental facts about our world, and elites are among the people least likely to have internalized it.

Have a nice day.

How to build Haitian state capacity

Strengthening state capacity in low income countries requires raising tax revenue while maintaining political stability. The risk of inciting political unrest when attempting to increase taxes may trap governments in a low-tax equilibrium, but public goods provision may improve both tax compliance and political stability. To test these questions empirically, I partner with the national tax authority and a local mayor’s office in Haiti to cross-randomize both tax collection and public goods across one of the country’s largest cities. Effects are measured both via administrative data on tax revenue as well as through novel measures of political unrest. In the paper’s main result, I show that hand-delivering property tax invoices reduces individual tax compliance by 48%, and increases independently observed measures of localized political violence by 192%. In contrast, providing a valuable and visible public good (namely municipal garbage removal) increases tax compliance by 27%, and reduces localized political violence by 85%. Importantly, public goods provision significantly mitigates the adverse effects of tax collection in neighborhoods receiving both treatments. A cost accounting exercise suggests that providing the public good in this setting could pay for itself within the first year. These findings suggest that it may be possible to peacefully shift to a new equilibrium of higher tax compliance with a sufficient initial investment perhaps financed through foreign aid or other transfers.

That is a paper from Benjamin Krause, a job market candidate from UC Berkeley.  Here is his home page and CV.  He was also four years Chief of Staff to Sean Penn, check out the vita.

Youyang Gu will estimate vaccination numbers and herd immunity

  • We believe COVID-19 herd immunity (>60% of population immune) will be reached in the US by late summer/early fall 2021 (Sep-Nov 2021).
  • At the time herd immunity is reached, roughly half of the immunity will be achieved via natural infection, and the other half will be achieved via vaccination.
  • New COVID-19 infections may become negligible before herd immunity is reached. Our current best estimate of when daily community transmissions will drop below 1,000 per day is summer 2021 (Jul-Sep 2021).
  • Summarizing the above findings, our best estimate of a complete “return to normal” in the US is late summer 2021 (Aug-Oct 2021).
  • We estimate around 30% of the US population (~100 million) will have been infected by the SARS-CoV-2 virus by the end of 2021. This translates to a final US COVID-19 death toll of roughly 500,000 (+/-100k) reported deaths.

You can track the data here, his earlier forecasts of cases, hospitalizations, and the like were among the best.  He is here on Twitter.  For the pointer I thank CatintheHat.