Category: Data Source
How does engagement with markets affect socioeconomic values and political preferences? A long line of thinkers has debated the nature and direction of such effects, but claims are difficult to assess empirically because market engagement is endogenous. We designed a large field experiment to evaluate the impact of financial markets, which have grown dramatically in recent decades. Participants from a national sample in England received substantial sums they could invest over a 6‐week period. We assigned them into several treatments designed to distinguish between different theoretical channels of influence. Results show that investment in stocks led to a more right‐leaning outlook on issues such as merit and deservingness, personal responsibility, and equality. Subjects also shifted to the right on policy questions. These results appear to be driven by growing familiarity with, and decreasing distrust of markets. The spread of financial markets thus has important and underappreciated political ramifications.
By Patrick A. McLaughlin and Casey Mulligan, Patrick of course being from GMU/Mercatus:
Despite evidence to the contrary, three common myths persist about federal regulations. The first myth is that many regulations concern the environment, but in fact only a small minority of regulations are environmental. The second myth is that most regulations contain quantitative estimates of costs or benefits. However, these quantitative estimates appear rarely in published rules, contradicting the impression given by executive orders and Office of Management and Budget guidance, which require cost-benefit analysis (CBA) and clearly articulate sound economic principles for conducting CBA. Environmental rules have relatively higher-quality CBAs, at least by the low standards of other federal rules. The third myth, which is particularly relevant to the historic regulations promulgated during the COVID-19 pandemic, is the misperception that regulatory costs are primarily clerical, rather than opportunity or resource costs. If technocrats have triumphed in the regulatory arena, their victory has not been earned by the merits of their analysis.
Here is the link to the NBER working paper.
In Brazil, 15 percent of deaths have been people under 50 — a rate more than 10 times greater than in Italy or Spain. In Mexico, the trend is even more stark: Nearly one-fourth of the dead have been between 25 and 49. In India, officials reported this month that nearly half of the dead were younger than 60. In Rio de Janeiro state, more than two-thirds of hospitalizations are for people younger than 49.
And here are the speculations:
Because population density is so much higher in much of the developing world — and because so many people must keep working to survive — a far greater share of the population ends up being exposed to the virus.
The virus then spreads through a population that’s less resilient. People in the developing world grapple not only with the diseases that have long been associated with it — malaria, dengue, tuberculosis, HIV/AIDS — but increasingly with those more closely associated with wealthier countries. Rates of diabetes, obesity and hypertension are surging. But treatment for many such illnesses is lacking.
Fairfax County Health Department responded to my request for nursing home/longterm care facility deaths from COVID-19. As of May 22, there have been 249 coronavirus deaths in these facilities. That’s ***75 percent*** of all Fairfax County deaths from coronavirus as of today (330)
Here is the link, via Alex T. For epidemiology, shouldn’t those numbers be in a separate model altogether?
Also, it would be very interesting to test the performance of the private sector vs. public sector institutions here.
One in four low-wage workers face marginal net tax rates above 70 percent, effectively locking them into poverty. Over half face remaining lifetime marginal net tax rates above 45 percent. The richest 1 percent also face a high median lifetime marginal tax rate – roughly 50 percent.
That is from a new NBER paper by David Altig, Alan J. Auerbach, Laurence J. Kotlikoff, Elias Ilin, and Victor Ye.
Minton is the author of a newly released study showing just how far the CDC has strayed from its core mission. In addition to combating dangerous infectious diseases like HIV and malaria, the CDC now also studies alcohol and tobacco use, athletic injuries, traffic accidents, and gun violence. While those things can indeed be important factors to public health, Minton notes, they don’t seem to fall within the agency’s original mission.
They do, however, explain why the CDC’s budget has ballooned from $590 million in 1987 to more than $8 billion last year. If the agency had grown with inflation since 1987, it would have a budget of about $1.3 billion today. Total federal spending, meanwhile, has grown from a hair over $1 trillion in 1987 to $4.4 trillion last year—which means that the CDC’s budget has grown faster the government’s overall spending.
That is by Eric Boehm at Reason. Via J.
Workers in the bottom quintile of the wage distribution experienced a 35 percent employment decline while those in the top quintile experienced only a 9 percent decline. Large differences across the wage distribution persist even after conditioning on worker age, business industry, business size, and worker location. As a result, average base wages increased by over 5 percent, though this increase arose entirely through a composition effect. Overall, we document that the speed and magnitude of labor market deterioration during the early parts of the pandemic were unprecedented in the postwar period, particularly for the bottom of the earnings distribution.
From three economics Ph.D students at Harvard, namely Andrew Lilley, Matthew Lilley, and Gianluca Rinaldi:
Using data from 43 US cities, Correia, Luck, and Verner (2020) find that the 1918 Flu pandemic had strong negative effects on economic growth, but that Non Pharmaceutical Interventions (NPIs) mitigated these adverse economic effects. Their starting point is a striking positive correlation between 1914-1919 economic growth and the extent of NPIs adopted at the city level. We collect additional data which shows that those results are driven by population growth between 1910 to 1917, before the pandemic. We also extend their difference in differences analysis to earlier periods, and find that once we account for pre-existing differential trends, the estimated effect of NPIs on economic growth are a noisy zero; we can neither rule out substantial positive nor negative effects of NPIs on employment growth.
I am very willing to publish a response from the original authors on this one.
That is a new paper by Luís Cabral and Lei Xu, here is the abstract:
We test the theory that seller reputation moderates the effect of demand shocks on a seller’s propensity to price gouge. From mid January to mid March 2020, 3M masks were priced 2.72 times higher than Amazon sold them in 2019. However, the difference (in price ratios) between a post-COVID-19entrant and an established seller is estimated to be about 1.6 at times of maximum scarcity, that is, post-COVID-19entrants price at approximately twice the level of established sellers. Similar results are obtained for Purell hand sanitizer. We also consider cumulative reviews as a measure of what a seller has to lose from damaging its reputation and, again, obtain similar results. Finally, we explore policy implications of our results.
In other words, Amazon is afraid to raise its prices, presumably for a mix of reputational and regulatory reasons.
There are about 2.3 million prisoners in the United States, and so far the number of reported Covid-19 deaths is 251, or higher by the time you are reading this. If you know of a better data source, please let me know.
For purposes of contrast, Rhode Island has about a million people and currently 266 deaths (and rising). Connecticut has 2,339 Covid-19 deaths, and a population of about 3.5 million, or in other words almost ten times the deaths as the prisons without having even twice the population. In other words, at least nominally the prison system seems to be doing better against Covid-19 than either The Nutmeg State or The Ocean State.
And I read this kind of line quite frequently:
Ohio officials found that more than 80% of those inmates had the virus with the vast majority showing no symptoms.
Yet asymptomatic cases in non-prison samples are often in the 40-50% range, not higher. Furthermore, the Bureau of Prisons just tested 2000 prisoners (how random a sample?…but don’t forget the false negatives!) and 70% tested positive. Again, the death rate does not seem to be through the ceiling.
How can this heterogeneity be? I see a few options:
1. Actual Covid-19 deaths in prisons are much higher than reported. This is quite possible, though I don’t see the media coverage that might go along with this. At the very least, prisons might have longer death reporting and classification lags than does Connecticut.
2. Prison deaths are about to explode, due to exponential growth in the number of cases and their progression through time. Again, this is quite possible, but you know what? I thought of writing this post a few weeks ago and then figured I would be refuted by an explosion of the death total over the next few weeks. So far it hasn’t happened. It may yet.
3. Prisoners are younger. Here is data on inmate ages, they are not that much younger than the general U.S. population. But they are somewhat younger, and surely this is one factor.
4. Prisoners smoke a lot, and nicotine actually may have protective properties against Covid-19. And is obesity low in prison? I do not know. Still, I don’t think of prisoners as a group in perfect physical health.
5. Prisoners are…um…locked up. The superspreaders just aren’t that super, there are not many new entrants to the prison population, few tourists from Italy, and so on. Not only do they live in cells, but the prison system as a whole is like thousands of scattered islands.
I see 1-5 all as possible significant options, with #4 as the weakest candidate. What else might be playing a role here?
Those who grew up in East Germany seem to have a harder time cottoning to the realities of capitalism:
We analyze the long-term effects of living under communism and its anticapitalist doctrine on households’ financial investment decisions and attitudes towards financial markets. Utilizing comprehensive German brokerage data and bank data, we show that, decades after Reunification, East Germans still invest significantly less in the stock market than West Germans. Consistent with communist friends-and-foes propaganda, East Germans are more likely to hold stocks of companies from communist countries (China, Russia, Vietnam) and of state-owned companies, and are unlikely to invest in American companies and the financial industry. Effects are stronger for individuals exposed to positive “emotional tagging,” e.g., those living in celebrated showcase cities. Effects reverse for individuals with negative experiences, e.g., environmental pollution, religious oppression, or lack of (Western) TV entertainment. Election years trigger further divergence of East and West Germans. We provide evidence of negative welfare consequences due to less diversified portfolios, higher-fee products, and lower risk-adjusted returns.
That is from a new NBER paper by Christine Laudenbach, Ulrike Malmendier, and Alexandra Niessen-Ruenzi.
But if you are looking for a contrary point of view, consider this new paper by Sascha O. Becker, Lukas Mergele, and Ludger Woessmann:
German separation in 1949 into a communist East and a capitalist West and their reunification in 1990 are commonly described as a natural experiment to study the enduring effects of communism. We show in three steps that the populations in East and West Germany were far from being randomly selected treatment and control groups. First, the later border is already visible in many socio-economic characteristics in pre-World War II data. Second, World War II and the subsequent occupying forces affected East and West differently. Third, a selective fifth of the population fled from East to West Germany before the building of the Wall in 1961. In light of our findings, we propose a more cautious interpretation of the extensive literature on the enduring effects of communist systems on economic outcomes, political preferences, cultural traits, and gender roles
That said, I still believe that communism really matters, and durably so, even if the longer history matters all the more so. And now there is yet another paper on East Germany and political path dependence, by Luis R. Martinez, Jonas Jessen, and Guo Xu:
This paper studies costly political resistance in a non-democracy. When Nazi Germany surrendered in May 1945, 40% of the designated Soviet occupation zone was initially captured by the western Allied Expeditionary Force. This occupation was short-lived: Soviet forces took over after less than two months and installed an authoritarian regime in what became the German Democratic Republic (GDR). We exploit the idiosyncratic line of contact separating Allied and Soviet troops within the GDR to show that areas brieﬂy under Allied occupation had higher incidence of protests during the only major episode of political unrest in the GDR before its demise in 1989 – the East German Uprising of 1953. These areas also exhibited lower regime support during the last free elections in 1946. We argue that even a “glimpse of freedom” can foster civilian opposition to dictatorship.
I take the core overall lesson to be that the eastern parts of Germany will experience significant problems for some time to come.
And speaking of communist persistence, why is it again that Eastern Europe is doing so well against Covid-19? Belarus is an extreme case, with hardly any restrictions on activity, and about 14,000 cases and 89 deaths. You might think that is a cover-up, but the region as a whole has been quite robust and thus it is unlikely to be a complete illusion. And no, it doesn’t seem to be a BCG effect.
Does communism mean there is less of a culture of consumption and thus people find it easier to just stay at home voluntarily? Or have all those weird, old paranoid communist pandemic ministries persisted and helped with the planning? Or what?
Double credit on this one to both Kevin Lewis and Samir Varma, neither less excellent in his conjunction with the other.
By Jisung Park, Joshua Goodman, Michael Hurwitz and Jonathan Smith, in the latest issue of the AEA policy journal:
We demonstrate that heat inhibits learning and that school air conditioning may mitigate this effect. Student fixed effects models using 10 million students who retook the PSATs show that hotter school days in the years before the test was taken reduce scores, with extreme heat being particularly damaging. Weekend and summer temperatures have little impact, suggesting heat directly disrupts learning time. New nationwide, school-level measures of air conditioning penetration suggest patterns consistent with such infrastructure largely offsetting heat’s effects. Without air conditioning, a 1°F hotter school year reduces that year’s learning by 1 percent. Hot school days disproportionately impact minority students, accounting for roughly 5 percent of the racial achievement gap.
This is all from Michael A. Alcorn, from my email, no further indentation offered:
“Just to keep hammering on this nursing home point… I saw your Tweet about Eastern vs. Western Europe and decided to explore the nursing home angle there too. The WHO has data on the number of nursing and elderly home beds for different countries here. Unfortunately, the data only goes up to 2013-ish for many countries, but it’s suggestive nonetheless.
Italy and France were clearly trending up seven years ago in its number of beds… would be interesting to see if Italy had a similar jump to Spain at some point. The number of beds gives us a proxy for the number of people who are highly vulnerable to COVID-19. Obviously, these countries have different total populations, but I don’t think that should matter too much because I suspect nursing homes tend to be highly concentrated within countries (e.g., how many of France’s nursing homes are in the Paris metro?). Based on what I’ve read about nursing home staff often being low paid and so perhaps coming to work when sick and working at multiple facilities, I suspect nursing home density is nonlinearly related to the number of COVID-19 deaths in a country (especially when you account for some of the truly horrifying government decisions regarding nursing homes).
Here are those Nordic countries everyone likes to compare:
You can get exact numbers on the website, but Sweden had twice as many nursing home beds as Finland and three times as many as Norway. The ship might have sailed on what we can do to protect these vulnerable populations, but I would love to see a Fast Grant go towards investigating the COVID-19/nursing home tragedy.”
Want to know how many tuberculosis cases there were in the U.S. last year? Ask the CDC. Want to know about health-care-associated infections? Ask the CDC. It knows.
But ask how many Covid-19 tests have been done, and the CDC’s doesn’t have an answer. Want a daily update on how many people are getting hospitalized for Covid-19? The CDC isn’t tracking it. Want to know if social distancing is making a difference? The CDC doesn’t know.
During this pandemic, when accurate, timely, nationwide information is the lifeblood of our response, the CDC has largely disappeared.
The performance of the world’s leading public health agency has been surprising, and by that I mean surprisingly disappointing. When the outbreak began, the CDC decided to forgo using the World Health Organization’s testing kit for Covid-19 and build its own. The test it shipped out to states was faulty, creating problems that stretched for weeks and slowed response as states waited for replacement tests.
Here is more from Ashish K. Jha. As I’ve said before, our regulatory state has been failing us.