Month: May 2021

It seems obvious that the COVID-19 pandemic must be worse in lower-income countries. After all, it seems as if the opportunities for social  distancing must be lower in urban areas in those countries, and the resources for everything from protective gear to hospital care must be lower. There are certainly cases where the pandemic has hit some areas hard outside of  high-income countries: for example, the current situation in India, or the city of Manaus in Brazil that suffered a a first wave, and then suffered a second wave with a new variant of COVID.  

But that said, Angus Deaton (Nobel \’15) makes a case that the areas outside the high-income countries of the world have, as a group, been less affected by the pandemic in \”Covid-19 and Global Income Inequality\” (Milken Institute Review, Second Quarter 2021, pp. 24-35). As a starting point for his argument, consider this figure, which shows countries with higher per capita income have tended to have higher per capita COVID-19 deaths. 

Deaton discusses this figure from a variety of angles,  including the possibility that COVID-19 is less well-measured in lower-income countries. But he argues that a number of other factors may help to explain the pattern of higher COVID-19 deaths in higher-income countries. 

The low number in low-income countries has been linked by Pinelopi Goldberg and Tristan Reed to (the lack of) obesity, to the smaller fraction of the population over 70 and to the lower density of population in the largest urban centers.

Another alternative is to focus on demography. Patrick Heuveline and Michael Tzen provide age-adjusted mortality rates for each country by using country age-structures to predict what death rates would have been if the age-specific Covid-19 death rates had been the same as the U.S. The ratio of predicted deaths to actual deaths is then used to adjust each country’s crude mortality rate. This procedure scales up mortality rates for countries that are younger than the U.S. (Peru has the highest age- and sex-adjusted mortality rate) and scales down mortality rates for countries like Italy and Spain (which had the highest unadjusted rate) that are older than the U.S.

If Figure 1 were redrawn using the adjusted rates, the positive slope would remain, though the slope showing the relationship between death rates and income would be reduced from 0.99 to 0.47 — that is, the relationship would hold but would be less pronounced. …

[P]oor countries are also warmer countries, where much activity takes place outside, and there are relatively few large, dense cities with elevators and mass transit to spread the virus. It is also possible that Africa’s long-standing experience with infectious epidemics stood it in good stead during this one. People in countries with more-developed economies consume a higher fraction of income in the form of personal services, which makes infection easier.

Deaton further argues that countries with higher death rates, as shown in the figure above, have also tended to have worse economic outcomes. 

All analysis of the pandemic is, as yet, incomplete. Deaton\’s data goes through the end of 2020. Just as India has recently been clobbered by the pandemic, something similar could happen in other countries. Furthermore, in the poorest countries of the world, even a smaller loss of income may cause extreme human suffering. 

But other possible lessons here are that, just perhaps, the pandemic did not make the world a more economically unequal place. Moreover, having lower deaths from the pandemic appears to be a good way of bolstering a country\’s economy. asdj

For much of human history, a majority of people have worked in agriculture. In the countries of sub-Saharan Africa, about half of all workers are currently in agriculture–more in lower-income countries. The process of raising the overall standard of living requires a rise in agricultural productivity, so that a substantial share of workers can shift away from agriculture, and thus be able to work in other sectors of the economy. In turn, rises in agricultural productivity are typically driven by research and development, which has been lagging. Julian M. Alston, Philip G. Pardey, and Xudong Rao make the case in \”Rekindling the Slow Magic of Agricultural R&D\” (Issues in Science and Technology, May 3, 2021).

The authors discuss CGIAR, which stands for Consultative Group on International Agricultural Research. This system was started in 1971. The authors note: \”The CGIAR was conceived to play a critical role, working in concert with national agricultural research systems of low- and middle-income countries, to develop and distribute farm technologies to help stave off a global food crisis. The resulting Green Revolution technologies were adapted and adopted throughout the world, first and foremost in South Asia and parts of sub-Saharan Africa and Latin America where the early centers of the CGIAR were located. In 2019 the CGIAR spent $805 million on agricultural R&D to serve the world’s poor, down by 30% (adjusted for inflation) from its peak of over $1 billion in 2014 … \”

For perspective, total public and private spending by low-income countries on agricultural R&D is roughly equal to what is spent through CGIAR. The payoff from this spending has been on the order of 10:1. 

The CGIAR research record has been much studied, but questions remain about the past and prospective payoffs to the investment. Similar questions have been raised about public investments in the agricultural research systems of various nations—particularly those of poor countries that receive substantial development aid from richer countries. To address those questions, we conducted a comprehensive meta-analysis of more than 400 studies published since 1978 that looked at rates of return on agricultural research conducted by public agencies in low- and middle-income countries. Of that total, 78 studies reported rates of return for CGIAR-related research and 341 studies reported rates of return for non-CGIAR agricultural research. (Full details of the meta-analysis are online at supportagresearch.org.) …

 Across 722 estimates, the median ratio of the estimated research benefits to the corresponding costs was approximately 10:1 for both the CGIAR (170 estimates) and national agricultural research systems of developing countries (522 estimates). In other words, $1 invested today yields, on average, a stream of benefits over future decades equivalent to $10 (in present value terms). …  Notably, all these estimated benefits accrued in developing countries, home to the preponderance of the world’s food poor. And yet, rich donor countries also reap benefits by adopting technologies developed by CGIAR research—“doing well by doing good.” For example, the yield- and quality-enhancing traits bred into new wheat and rice varieties destined for developing countries are also incorporated into most varieties used by rich-country farmers.

But as noted earlier, CGIAR funding is down 30% in the last few years. Also, I was surprised to notice that the Gates Foundation alone is more than one-eighth of then entire CGIAR budget. 

David A. Price does an \”Interview\” with Matthew Jackson, with the subheading \”On human networks, the friendship paradox, and the information economics of protest movements\” (Econ Focus: Federal Reserve Bank of Richmond, 2021, Q1, pp. 16-20). Here are a few snippets of the conversation, suggestive of the bigger themes.

Homophily

[O]ne key network phenomenon is known among sociologists and economists as homophily. It\’s the fact that friendships are overwhelmingly composed of people who are similar to each other. This is a natural phenomenon, but it\’s one that tends to fragment our society. When you put this together with other facts about social networks — for instance, their importance in finding jobs — it means many people end up in the same professions as their friends and most people end up in the communities they grew up in.

From an economic perspective, this is very important, because it not only leads to inequality, where getting into certain professions means you almost have to be born into that part of society, it also means that then there\’s immobility, because this transfers from one generation to another. It also leads to missed opportunities, so people\’s talents aren\’t best matched to jobs.

The Friendship Paradox

This concerns another network phenomenon, which is known as the friendship paradox. It refers to the fact that a person\’s friends are more popular, on average, than that person. That\’s because the people in a network who have the most friends are seen by more people than the people with the fewest friends.

On one level, this is obvious, but it\’s something that people tend to overlook. We often think of our friends as sort of a representative sample from the population, but we\’re oversampling the people who are really well connected and undersampling the people who are poorly connected. And the more popular people are not necessarily representative of the rest of the population.

So in middle school, for example, people who have more friends tend to have tried alcohol and drugs at higher rates and at earlier ages. And this distorted image is amplified by social media, because students don\’t see pictures of other students in the library but do tend to see pictures of friends partying. This distorts their assessment of normal behavior.

There have been instances where universities have been more successful in combating alcohol abuse by simply educating the students on what the actual consumption rates are at the university rather than trying to get them to realize the dangers of alcohol abuse. It\’s powerful to tell them, \”Look, this is what normal behavior is, and your perceptions are actually distorted. You perceive more of a behavior than is actually going on.\”

Causality in Networks

In the aftermath of the Texas power failures in February, a number commenters found confirmation that, amazingly, they had been right about everything all along. Thus, those who were against wind power and renewable energy mandated in general blamed the wind farms. Those who are suspicious of competition in markets for generating electrical power blamed deregulation, although blaming \”the market\” for what happens in a heavily regulated industry seems peculiar to me. Some critics even blamed Enron, a company that has not existed for years. What actually happened seems simpler, if less reinforcing for various preconceptions: It got really cold. 

Michael Giberson provides an overview in \”Texas Power Failures: What happened in February 2021 and What Can be Done\” (Reason Foundation, April 2021). He describes the weather: 

The temperature in Dallas dipped to -2° F, the coldest it had been in Dallas for 70 years. Snow fell on the beaches on the Gulf Coast at Galveston, south of Houston. Temperatures in Austin remained below freezing for six days at a time of when temperatures usually average in the mid-50s. At Brownsville, near the most southern tip of Texas, February weather typically averages 65° F. High temperatures in Brownsville were in the mid-80s just days before the cold. The temperature in the city did not rise above freezing for nearly 48 hours once the cold settled in. For the first time in history all 254 counties in Texas were under a winter storm warning at the same time. The cold was not unprecedented at any particular location, but it was extreme, widespread, and long lasting in February 2021. …

The cold affected more than the ERCOT power system. Some power systems in Texas not within the ERCOT system also resorted to rolling outages. Natural gas production and distribution froze up. Municipal water mains froze in cities across the South. Ranchers in the Panhandle lost cattle to the cold. Citrus growers in South Texas saw damage to trees that may last for years. Roads were closed due to ice and storms. Failures were not solely an electric power industry concern or a natural gas failure. The cold was simply worse than almost anyone in Texas was prepared for. … Clearly, it was not negligent on ERCOT’s part—and maybe anyone’s part—to fail to anticipate such anomalous temperatures.

The  Texas power emergency lasted about four days: at its worst, about 4.5 million people were without power.

The black line shows the actual electricity load. The thin gray line shows the forecasted demand, if ERCOT had been able to deliver it. In general, electricity demand is typically  higher in Texas in the summer (air-conditioning) rather than the winter. But electricity demand during the cold snap would have broken the all-time summer records, as well as the winter ones. 

Pity China\’s statisticians, who seem caught in the middle between the facts of arithmetic and the demands of government. The recent kerfuffle started about a week ago when the Financial Times reported, \”China set to report first population decline in five decades\” (April 27, 2021).  The report was based on \”people familiar with the research,\” who presumably had some insight into the results of China\’s population census that was completed last December, with data schedule for released in April. 

But apparently this census data was too hot to handle. The FT quoted Huang Wenzheng, a fellow at the a Beijing-based think-tank, who said: \”The census results will have a huge impact on how the Chinese people see their country and how various government departments work. They need to be handled very carefully.” A few days later, China\’s National Bureau of Statistics released a one-sentence statement on its website: According to our understanding, in 2020, China’s population continued to grow.\” The actual numbers have not yet been released. 

I have no inside information about the details of China\’s population numbers for 2020. But I do know that demographic patterns can be inexorable. China made decisions a half-century in the early 1970s about pursuing an aggressive policy of population control, decisions that evolved into the stringently enforced \”one child\” policy adopted in 1979.  A common saying in China was that it takes six adults to raise one child: that is, the two sets of grandparents who had one child each, and whose offspring then produced a single grandchild. 

When low birthrates have been in motion for several generations, population growth will eventually drop below replacement rates.  Japan\’s population began shrinking about a decade ago. Russia\’s population peaked back in the 1990s. A group of demographers looking at global population forecasts predicted in the Lancet that by 2100: \”In 23 countries, including Japan, Thailand, Spain, and Ukraine, populations are expected to decline by 50% or more. Another 34 countries will probably decline by 25–50%, including China, with a forecasted 48.0% decline.\”

In short, it\’s not clear if China\’s population peaked last year, or if the peak will happen in the next few years, but at some point, the fact of the peak will be undeniable. Indeed, China\’s National Bureau of Statistics has already been reporting for several years that the size of China\’s working-age population aged between 15-64 peaked back in 2014. It has been apparent for some years now that China faces a challenge as to whether the country will become old before it becomes rich. 

There are multiple ironies here. One is that after decades of pushing hard for population control, China\’s government has now apparently decided that a declining population would be an undesirable outcome. Another irony is that China\’s repressive and draconian one-child policy may had relatively little effect.  Countries around the world and in east Asia have experienced rapidly falling birthrates in recent decades without anything like China\’s one-child policy. Several academic studies suggest that if China\’s birthrates had just declined in the same way as in other countries that had similar birthrates back in in 1970, China\’s population would have come out in at about the same level.   

I know that I am naive and foolish in the ways of public relations. But I learned long ago when a government is faced with an embarrassing admission, a politically useful approach can be to declare victory and move ahead. Thus, it seems obvious to me that from a public relations point of view, China\’s government should declare victory in its long-standing population-control campaign, point to the level or declining population level as evidence of the great success, and then say the time has come when such constraints are no longer needed–and in fact that higher birthrates can now be welcomed because of the sacrifices in the past. But attempts to deny that China\’s population either has peaked, or is about to peak, will need to fly in the face of both evidence and demographic logic. 

I am now in my 35th year as Managing Editor of the Journal of Economic Perspectives. The JEP is published by the American Economic Association, which decided about a decade ago–to my delight–that the journal would be freely available on-line, from the current issue all the way back to the first issue. You can download individual articles or the entire issue, and it is available in various e-reader formats, too. Here, I\’ll start with the Table of Contents for the just-released Spring 2021 issue, which in the Taylor household is known as issue #136. Below that are abstracts and direct links for all of the papers. I will probably blog more specifically about some of the papers in the next week or two, as well.