Category: Data Source
Evidence from 27 Thousand Economics Journal Articles on Africa
The first two decades of the 21st century have seen an increasing number of peer-reviewed journal articles on the 54 countries of Africa by both African and non-African economists. I document that the distribution of research across African countries is highly uneven: 45% of all economics journal articles and 65% of articles in the top five economics journals are about five countries accounting for just 16% of the continent’s population. I show that 91% of the variation in the number of articles across countries can be explained by a peacefulness index, the number of international tourist arrivals, having English as an official language, and population. The majority of research is context-specific, so the continued lack of research on many African countries means that the evidence base for local policy-makers is much smaller in these countries.
Here is the article by Obie Porteus, via David Evans.
New results on the housing boom and bust
We build a model of the US economy with multiple aggregate shocks that generate fluctuations in equilibrium house prices. Through counterfactual experiments, we study the housing boom-bust around the Great Recession, with three main results. First, the main driver of movements in house prices and rents was a shift in beliefs, not a change in credit conditions. Second, the boom-bust in house prices explains half of the corresponding swings in nondurable expenditures through a wealth effect. Third, a large-scale debt forgiveness program would have done little to temper the collapse of house prices and expenditures but would have dramatically reduced foreclosures and induced a small, but persistent, increase in consumption during the recovery.
That is from a recently published article by Greg Kaplan, Kurt Mitman, and Giovanni L. Violante in the Journal of Political Economy. Here are some less gated versions.
Are School Reopening Decisions Related to Union Influence?
Yes, in short. Here is a new paper from Corey Deangelis and Christos Makridis:
The COVID-19 pandemic led to widespread school closures affecting millions of K-12 students in the United States in the spring of 2020. Groups representing teachers have pushed to reopen public schools virtually in the fall because of concerns about the health risks associated with reopening in person. In theory, stronger teachers’ unions may more successfully influence public school districts to reopen without in-person instruction. Using data on the reopening decisions of 835 public school districts in the United States, we find that school districts in locations with stronger teachers’ unions are less likely to reopen in person even after we control semi-parametrically for differences in local demographic characteristics. These results are robust to four measures of union strength, various potential confounding characteristics, and a further disaggregation to the county level. We also do not find evidence to suggest that measures of COVID-19 risk are correlated with school reopening decisions.
And please do note that last sentence again:
We also do not find evidence to suggest that measures of COVID-19 risk are correlated with school reopening decisions (emphasis added).
Via the excellent Kevin Lewis.
Dark matter, second waves and epidemiological modelling
Here is a new paper from , , and :
Background Recent reports based on conventional SEIR models suggest that the next wave of the COVID-19 pandemic in the UK could overwhelm health services, with fatalities that far exceed the first wave. These models suggest non-pharmaceutical interventions would have limited impact without intermittent national lockdowns and consequent economic and health impacts. We used Bayesian model comparison to revisit these conclusions, when allowing for heterogeneity of exposure, susceptibility, and viral transmission. Methods We used dynamic causal modelling to estimate the parameters of epidemiological models and, crucially, the evidence for alternative models of the same data. We compared SEIR models of immune status that were equipped with latent factors generating data; namely, location, symptom, and testing status. We analysed daily cases and deaths from the US, UK, Brazil, Italy, France, Spain, Mexico, Belgium, Germany, and Canada over the period 25-Jan-20 to 15-Jun-20. These data were used to estimate the composition of each country’s population in terms of the proportions of people (i) not exposed to the virus, (ii) not susceptible to infection when exposed, and (iii) not infectious when susceptible to infection. Findings Bayesian model comparison found overwhelming evidence for heterogeneity of exposure, susceptibility, and transmission. Furthermore, both lockdown and the build-up of population immunity contributed to viral transmission in all but one country. Small variations in heterogeneity were sufficient to explain the large differences in mortality rates across countries. The best model of UK data predicts a second surge of fatalities will be much less than the first peak (31 vs. 998 deaths per day. 95% CI: 24-37)–substantially less than conventional model predictions. The size of the second wave depends sensitively upon the loss of immunity and the efficacy of find-test-trace-isolate-support (FTTIS) programmes. Interpretation A dynamic causal model that incorporates heterogeneity of exposure, susceptibility and transmission suggests that the next wave of the SARS-CoV-2 pandemic will be much smaller than conventional models predict, with less economic and health disruption. This heterogeneity means that seroprevalence underestimates effective herd immunity and, crucially, the potential of public health programmes.
This would appear to be one of the very best treatments so far, though I would stress I have not seen anyone with a good understanding of the potential rotation (or not) of super-spreaders, especially as winter comes and also as offices reopen. In that regard, at the very least, modeling a second wave is difficult.
Via Yaakov Saxon, who once came up with a scheme so clever I personally sent him money for nothing.
Covid-19 in Kenya
Let’s hope this is true!:
Policy makers in Africa need robust estimates of the current and future spread of SARS-CoV-2. Data suitable for this purpose are scant. We used national surveillance PCR test, serological survey and mobility data to develop and fit a county-specific transmission model for Kenya. We estimate that the SARS-CoV-2 pandemic peaked before the end of July 2020 in the major urban counties, with 34 – 41% of residents infected, and will peak elsewhere in the country within 2-3 months. Despite this penetration, reported severe cases and deaths are low. Our analysis suggests the COVID-19 disease burden in Kenya may be far less than initially feared. A similar scenario across sub-Saharan Africa would have implications for balancing the consequences of restrictions with those of COVID-19.
Here is the full paper.
The impact of economic regulation on growth: survey and synthesis
This study provides a survey of research that uses cross-country comparisons to examine how economic regulation affects growth. Studies in the peer-reviewed literature tend to rely on either World Bank or Organisation for Economic Co-operation and Development measures of regulation. Those studies seem to reflect a consensus that entry regulation and anticompetitive product and labor market regulations are generally harmful to growth. The results from this cross-country research, taken in conjunction with economic theory as well as other country-specific studies of economic regulation, support the hypothesis that economic regulation tends to reduce welfare in competitive markets. Given the continued use of certain types of economic regulation, the findings may offer important lessons for policymakers.
That is a new Mercatus working paper by James Broughel and Robert Hahn.
Four stylized facts about Covid-19
We document four facts about the COVID-19 pandemic worldwide relevant for those studying the impact of non-pharmaceutical interventions (NPIs) on COVID-19 transmission. First: across all countries and U.S. states that we study, the growth rates of daily deaths from COVID-19 fell from a wide range of initially high levels to levels close to zero within 20-30 days after each region experienced 25 cumulative deaths. Second: after this initial period, growth rates of daily deaths have hovered around zero or below everywhere in the world. Third: the cross section standard deviation of growth rates of daily deaths across locations fell very rapidly in the first 10 days of the epidemic and has remained at a relatively low level since then. Fourth: when interpreted through a range of epidemiological models, these first three facts about the growth rate of COVID deaths imply that both the effective reproduction numbers and transmission rates of COVID-19 fell from widely dispersed initial levels and the effective reproduction number has hovered around one after the first 30 days of the epidemic virtually everywhere in the world. We argue that failing to account for these four stylized facts may result in overstating the importance of policy mandated NPIs for shaping the progression of this deadly pandemic.
That is the abstract of a new NBER paper by Andrew Atkeson, Karen Kopecky, and Tao Zha. You will note that when it comes to Covid-19 cases, the superior performance Europe had enjoyed over the United States seems to be evaporating, see here on France and here on Europe more generally.
Differential occupational mortality in Sweden from Covid-19
We use data the Swedish authorities organized as an early release of all recorded COVID-19 deaths in Sweden up to May 7, 2020, which we link to administrative registers and occupational measures of exposure. Taxi and bus drivers had a higher risk of dying from COVID-19 than other workers, as did older individuals living with service workers. Our findings suggest however that these frontline workers and older individuals they live with are not at higher risk of dying from COVID-19 when adjusting the relationship for other individual characteristics. We also did not find evidence that being a frontline worker in terms of occupational exposure was linked to higher COVID-19 mortality. Our findings indicate no strong inequalities according to these occupational differences in Sweden and potentially other contexts that use a similar approach to managing COVID-19.
Overall I am quite surprised how large is the bus and taxi driver effect (even after adjusting for demographics), and how small are the other professional effects. Here is the paper, by Sunnee Billingsley, et.al., via Daniel B. Klein.
How bad was the Spanish Flu pandemic of 1918?
Yes it was a terrible tragedy, but many locales had much worse events fairly recently:
Between 1917 and 1918 New York City’s crude mortality rate increased by 3.173 deaths per 1000 persons. While tragic, the hollow circles in Figure 1 depict 12 other years where the year-over-year increase in mortality exceeded the magnitude of the 1917 to 1918 change. During the cholera epidemics of 1832, 1834, 1849, and 1854 the year-over-year increase in mortality was 3 to 5 times larger in magnitude than what occurred in 1918. As another comparison, the mortality rate in New York City was higher in nearly every year between 1800 and 1905 than the mortality rate in 1918.
The same is true for many other American cities, but here is a picture for NYC:
And this:
During the first half of the 20th century, Black Americans in urban areas died from infectious disease at a rate that was greater than what urban whites experienced during the 1918 flu pandemic every single year.
On a different but related topic:
…the evidence suggests that the 1918 pandemic was not a major determinant of U.S. stock market volatility.
That is all from the new and very interesting NBER paper by Brian Beach, Karen Clay, and Martin H. Saavedra, “The 1918 Influenza Pandemic and its Lessons for Covid-19.”
Mental Health and the Reluctance to Use Talk Therapy
I know very little about this area, but found these results of interest and worthy of further investigation:
Mounting evidence across disciplines shows that psychotherapy is more curative than antidepressants for mild-to-moderate depression and anxiety. Yet, few patients use it. This paper develops and estimates a structural model of dynamic decision-making to analyze mental health treatment choices in the context of depression and anxiety. The model incorporates myriad costs suggested in previous work as critical impediments to psychotherapy use. We also integrate links between mental health and labor outcomes to more fully capture the benefits of mental health improvements and the costs of psychotherapy. Finally, the model addresses measurement error in widely-used mental health variables. Using the estimated model, we find that mental health improvements are valuable, both directly through increased utility and indirectly through earnings. We also show that even though psychotherapy improves mental health, counterfactual policy changes, e.g., lowering the price or removing other costs, do very little to increase uptake. We highlight two conclusions. As patient reluctance to use psychotherapy is nearly impervious to a host of a priori reasonable policies, we need to look elsewhere to understand it (e.g., biases in beliefs about treatment effects, stigma, or other factors that are as yet unknown). More broadly, large benefits of psychotherapy estimated in randomized trials tell only half the story. If patients do not use the treatment outside of an experimental setting—and we fail to understand why or how to get them to—estimated treatment effects cannot be leveraged to improve population mental health or social welfare.
That is from a new NBER working paper by Christopher J. Cronin, Matthew P. Forsstrom, and Nicholas W. Papageorge.
The Covid cost of professional sports events
We compare COVID-19 case loads and mortality across geographic areas that hosted more vs fewer NHL hockey games, NBA basketball games, and NCAA basketball games during the early months of 2020, before any large outbreaks. We find that hosting one additional NHL/NBA game leads to an additional 783 COVID-19 cases during March-mid May and an additional 52 deaths. Similarly, we find that hosting an additional NCAA Division 1 men’s basketball games results in an additional 31 cases and an additional 2.4 deaths. Back of the envelope calculations suggest that the per-game fatality costs exceed consumption benefits by a wide margin.
That is from Coady Wing, Daniel H. Simon, and Patrick Carlin. I think we have not a good enough model of the heterogeneities of prevalence across regions for those to be reliable estimates. Still, I am happy to see more work on the question of what in particular causes Covid cases, and also whether sporting events play a significant role.
U.S.A. facts of the day
One in four young adults between the ages of 18 and 24 say they’ve considered suicide in the past month because of the pandemic, according to new CDC data that paints a bleak picture of the nation’s mental health during the crisis.
The data also flags a surge of anxiety and substance abuse, with more than 40 percent of those surveyed saying they experienced a mental or behavioral health condition connected to the Covid-19 emergency. The CDC study analyzed 5,412 survey respondents between June 24 and 30.
The toll is falling heaviest on young adults, caregivers, essential workers and minorities. While 10.7 percent of respondents overall reported considering suicide in the previous 30 days, 25.5 percent of those between 18 to 24 reported doing so. Almost 31 percent of self-reported unpaid caregivers and 22 percent of essential workers also said they harbored such thoughts. Hispanic and Black respondents similarly were well above the average.
Here is the full story, via the excellent Kevin Lewis.
Young “stars” in economics
I had not seen this paper before, by Kevin A. Bryan, here is the abstract:
We construct a data set of job flyouts for junior economists between 2013 and 2018 to investigate three aspects of the market for “stars.” First, what is the background of students who become stars? Second, what type of research does the top of the market demand? Third, where do these students take jobs? Among other results, we show that stars are more likely to be international and male than PhDs overall, that theoretical and semi-theoretical approaches remain dominant, that American programs both produce the most stars and hire even more, that almost none are hired by the private sector, and that there is a strong shift toward having pre-PhD full-time academic research jobs.
Is this good news or bad? The paper is interesting throughout, here is another bit:
…both Americans and women are nearly twice as likely to have Applied Micro as a primary field compared to non-Americans and men.
As for country of origin of these star students, see p.5, I was surprised to see Germany rank second after the United States, with Italy and France not far behind, China coming next, then Argentina (!).
Via Soumaya Keynes.
“Israel Versus Anyone”
That is the title of a new research paper by Kenneth S. Brower, focusing on the capabilities of the Israeli military against various potential adversaries. I do not myself have particular opinions on these questions, but I found this piece interesting throughout. Here is one excerpt:
The simple and unarguable truth is that for decades the US military has lacked the ability to quickly project conventional ground and air forces into the Middle East that would be able to successfully defend Israel. This has been true for about 50 years.
The US Army and US Marine Corps combined now have an active force structure of just 39 maneuver brigades, of which only about 13 are combat ready. It would require many weeks to bring a portion of the remaining 26 active maneuver brigades to combat ready status. Achieving this would require cannibalization of about 25% of the remaining active units in order to bring the others to full strength. US reserve National Guard maneuver brigades would each require about five months for mobilization, retraining, and deployment. These National Guard reserve units are thus irrelevant to any Israeli rescue scenario.
The ability of the US military to deploy forces over long distances has declined in the last 30 years because of a lack of investment in large specialized roll-on roll-off ships. Many of the existing US reserve merchant marine ships dedicated to military use are overage and have been poorly maintained. Based on the deployment times achieved during Operation Desert Storm, it is estimated that within about three weeks the US could project two light infantry paratroop brigades into Israel by air, plus one Marine infantry brigade transferred by forward deployed USN amphibious ships and pre-loaded forward-based maritime ships. Given about nine weeks, the US would likely be able to field nine maneuver brigades in the Middle East consisting of three paratroop, three Marine, and three heavy armored brigades. Consequently, it would require about nine weeks for the US military to generate roughly 15% of the IDF’s ground force mobilizable order of battle. These US forces would only deploy about 10% of the number of armored fighting vehicles the IDF can field.
The USAF has a very limited number of combat aircraft currently deployed in Europe. With air-to-air refueling, it is estimated that these aircraft might be able to sustain the generation of about 90 sorties a day in support of Israel. But these few sorties, which only 14 I Israel Versus Anyone: A Military Net Assessment of the Middle East represent 5% of Israeli wartime capability, could only be generated if the host country where these aircraft are based were to allow them to be operated in support of Israel. In the past, this approval has not always been provided. Neither the USN nor USMC currently have any operational combat aircraft based on aircraft carriers or large amphibious ships that are normally deployed in the Mediterranean within range of Israel.
Via Adam K.
From the comments, on coronavirus and humidity
I am not convinced by the humidity hypothesis, as I don’t see it having much macro explanatory power globally, but I find the questions very important. On New York City, I tend to blame all those cramped indoor spaces combined with bad ventilation systems, but that too is an unconfirmed hypothesis. Anyway, here are the words of Daniel Hess:
Here is Alex’s source post, and there are a few interesting responses in the ensuing discussion.