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The National Advisory Commission on Civil Disorders was appointed by President Lyndon Johnson in the summer of 1967 and issued its report in February 1968. US cities had been experiencing sporadic but severe riots for three years. The report became known as the Kerner Commission after its chair, Governor Otto Kerner, Jr. of Illinois. I’m not seeing a place online where the full report is freely available online, which is a bit of a surprise to me, although the intro and first 70 pages or so are available here. For the tone, here is some of the introduction: 

The authors of this Economic Policy Institute aren’t arguing over causes and reasons–at least not here–just putting some facts out there. But I’ll add a few words.

The patterns mentioned here are of course intertwined. The fact that whites have far higher college graduation rates affects wages, income, poverty rates, and wealth. Lower education and income are also correlated with infant mortality rates and crime.  Differences in education level between groups can take a long time to play out. Someone who didn’t finish high school back around 1970 has probably just retired in the last few years. Someone who didn’t go to college in the 1970s or the 1980s or the 1990s has been probably been working for decades in lower-paying jobs. When parents have less education, their children tend to have less education, too. And while racial discrimination in America doesn’t operate with the same brute force as 50 years ago, it surely continues to play a role in patterns of housing, employment, and what society is willing to tolerate in terms of educational results.

The racial disparities in 2018 aren’t happening in the same society as in 1968, or from the same causes, or against the same backdrop of urban rioting. But black/white racial disparities remain very large. Very large indeed. 

Analysis in economics and other social sciences often uses a combination of words and mathematics. There is an ongoing critique by those who argue that while the math may sometimes be useful, it is too often deployed with insufficient regard for whether it captures the underlying economic reality. In such cases, the argument goes, math is used as a way of pretending that an argument about the real-world economy has been definitely made, or settled, when in reality only an equation of limited application has been solved.

Paul Romer recently offered a pithy commentary on this longstanding dispute on his blog. Romer quotes from an earlier post by Dani Rodrik, who in some lists of advice for economists and non-economists, includes the following:

“Make your model simple enough to isolate specific causes and how they work, but not so simple that it leaves out key interactions among causes. … Unrealistic assumptions are OK; unrealistic critical assumptions are not OK. …  Do not criticize an economist�s model because of its assumptions; ask how the results would change if certain problematic assumptions were more realistic. … Analysis requires simplicity; beware of incoherence that passes itself off as complexity. … Do not let math scare you; economists use math not because they are smart, but because they are not smart enough.”

Romer has in recent years expressed concerns over “mathiness,” in which predetermined conclusions masquerade behind what looks like an “objective” mathematical model.  As he wrote in a 2015 paper:

The Council of Economic Advisers was established by the Employment Act of 1946 as a separate office in the White House. Along with an ongoing stream of stream of reports and advice, the CEA also produces an annual report, and the 2018 Economic Report of the President  is now available. The CEA is headed by three political appointees, which is fine by me. I expect every president to choose appointees who are broadly in agreement with administration policies. My (often unrequited) hope is that the president will then actually listen to such experts on the dangers of likely tradeoffs and the details of policy design.

If you want to read the reasonable person’s defense of Trump’s economic policies–either because you want to support these policies or you want to rebut them–the Economic Report thus offers a useful starting point. For example, the first chapter is a defense of the Tax Cuts and Jobs Act (TCJA) passed in December 2017, and the second chapter is a defense of the Trump’s regulatory policy efforts.  I tend to skim over such partisan arguments, but I still appreciate the figures and tables surrounding these arguments. They often describe facts and patterns worthy of note, whatever one’s policy beliefs about the appropriate reaction to them.

In that spirit, I’ll offer a grasshopper view of the report, leaping with no particular rhyme or reason between figures that caught my eye, with a few sentences quoted from the report about about each. Topics include: geographic mobility, road infrastructure, the US balance of trade since 1790, the fall in US manufacturing employment after 2000, the opioid epidemic, firms are investing less while paying out more to shareholders, and there is an international decline in labor productivity in the last decade or so.

The Fall of Geographic Mobility 

“High levels of unemployment concentrated in particular locations may amplify exit from the labor force, especially when workers are unwilling or unable to move to a location with a stronger job market. People move to improve their life circumstances, but the share of Americans moving has been declining, and is currently at its lowest value on record (figure 3-21).

“In addition to family and social connections, deterrents to moving include (1) search time, (2) State-specific occupational licensing requirements, (3) local land use regulations that raise housing costs in places with the greatest potential growth, and (4) homeowners� limited ability to sell their homes. Such obstacles to finding better employment opportunities, coupled with high local unemployment rates, may lead employees to ultimately exit the workforce. More research is needed to determine the direct relationship between geographic immobility and labor force participation, specifically exploring whether obstacles to moving have increased over time, and how prime-age workers in particular have been affected.”

More Driving on the Same Roads

“For example, between 1980 and 2016, vehicle miles traveled in the United States more than doubled, while public road mileage and lane miles rose by only 7 and 10 percent, respectively (figure 4-1). Unsurprisingly, queuing caused by traffic congestion has risen, imposing both direct and indirect costs on business and leisure travelers alike …”

Swings in the US balance of trade since 1790

“Figure 5-7 illustrates the U.S. trade balance from 1790 to the present, expressed as a share of GDP. From 1790 through 1873, the U.S. trade balance was volatile, in part due to the low trade volumes (Lipsey 1994). The trade balance swung back and forth between surplus and deficit, but was mostly in deficit. From 1873 through the 1960s, the trade balance was mostly in surplus. The largest historic surpluses were during the years 1916�17 and 1943�44, as wartime production and trade with allies predominated. Since 1976, the trade balance has been continually in deficit. The largest deficit as a share of GDP was nearly 6 percent in 2006, a share exceeded in only six other years in U.S. history and not seen since 1816.”

The sharp fall in manufacturing employment after 2000

“Although employment in the sector has long exhibited procyclicality, it has seen changes since 2000. In the expansionary period from the end of 2000 through 2007, the economy failed to recover the manufacturing job losses it experienced during the previous recession years.”

The Opioid Epidemic

“And since 1999, over 350,000 people have died of opioid-involved drug overdoses, which is 87 percent of the 405,399 Americans killed in World War II (DeBruyne 2017). The staggering opioid death toll has pushed drug overdoses to the top of the list of leading causes of death for Americans under the age of 50 and has cut 2.5 months from the average American�s life expectancy (Dowell et al. 2017). … 

“The opioid epidemic evolved with three successive waves of rising deaths due to different types of opioids, with each wave building on the earlier one (Ciccarone 2017). In the late 1990s, in response to claims that pain was undertreated and assurances from manufacturers that new opioid formulations were safe, the number of opioid prescriptions skyrocketed (CDC 2017b). What followed was an increase in the misuse of and deaths related to these prescriptions (figure 6-2). As providers became aware of the abuse potential and addictive nature of these drugs, prescription rates fell, after peaking in 2011. Deaths involving prescription opioids leveled off, but were followed by a rise in deaths from illicit opioids: heroin and fentanyl. Heroin deaths rose first, followed by a rise in deaths involving fentanyl�a synthetic opioid that is 30 to 50 times more potent than heroin and has legitimate medical uses but is increasingly being illicitly produced abroad (primarily in Mexico and China) and distributed in the U.S., alone or mixed with heroin. In 2015, males age 25 to 44 (a core group of the prime-age workers whose ages range from 25 to 54) had the highest heroin death rate, 13 per 100,000. Fentanyl-related deaths surpassed other opioid-related deaths in 2016.”

Investment is down, while firms pay out more to shareholders

“It is a matter of concern that net investment has been generally falling as a share of the capital stock during the past 10 years, which limits the economy�s productive capacity. In 2016, net investment as a share of the capital stock fell to a level previously seen only during recessions (figure 8-10). The Tax Cuts and Jobs Act is designed to increase the pace of net investment. As discussed further below, the slowdown in investment has also exacerbated the slowdown in labor productivity growth. …

“The rate of payouts to shareholders by nonfinancial firms, in the form of dividends together with net share buybacks, has been gradually trending higher for several decades, although it fell in 2017 (figure 8-11). Nonfinancial corporations returned nearly half the funds that could be used for investment to stockholders in 2017. In a well-functioning capital market, when mature firms do not have good investment opportunities, they should return funds to their stockholders, so the stockholders can invest these funds in young and growing firms. Although it may be admirable for individual firms to thus return funds to their shareholders, the rising share of paybacks to shareholders suggests that investable funds are not being adequately recycled to young and dynamic firms. Guti�rrez and Philippon (2016) find that firms in industries with more concentration and more common ownership invest less.”

The International Decline in Labor Productivity

“Labor productivity growth has been slowing in the major advanced economies (figure 8-41), driven by an estimated decline of 0.3 percent in annual multifactor productivity growth relative to average precrisis growth of 1 percent a year. This slowdown is broad-based, also affecting developing and emerging market economies. Although the causes of this productivity slowdown are unclear, a number of hypotheses have been offered�including financial crisis legacies, such as weak demand and lower capital investment; the trade slowdown; the aging of the post�World War II Baby Boom generation in its various forms around the world; the rising share of low-productivity firms; and a widening gap between high- and low-productivity firms. The Organization for Economic Cooperation and Development (OECD) finds that the survival of abnormally low-productivity firms may have contributed to the slowdown in productivity growth.” 

There are legitimate concerns about how the poverty line is set. It was set back in the early 1960s and adjusted for inflation since then, but without regard for other changes in the economy. It doestn’t vary according to regional differences in the cost of living and it doesn’t include in-kind benefits like Medicaid and food stamps. It is based on income levels, rather than consumption levels (or see also  here). At least for a bloodless social scientist, it’s possible to become focused on these conceptual issues to such an extent that basic empathy for those living with very low income levels gets crowded out. But just as one should remember that the poverty line is an arbitrary but useful convention, one should also remember that households living with very low income levels have a hard time.

Thus, it seems to me a  profoundly useful exercise, every now and then, to set aside the questions of how to measure poverty and instead to focus on what might be done about it. In that spirit, the Russell Sage Foundation Journal for the Social Sciences has put together a special double issue on the theme of  “Anti-poverty Policy Initiatives for the United States” (February 2018, vol 4, issues 2-3). After an overview essay by Lawrence M. Berger, Maria Cancian, and Katherine Magnuson, the two issues include 15 papers with a wide range of concrete proposals: focused on children in low-income families, the elderly, renters, food stamps, the earned income tax credit, the minimum wage, subsidizing or guaranteeing jobs, postsecondary training and higher education, contraception, and more.

There’s a lot to contemplate in these issues, and I’ll list the table of contents, with links to specific papers, below. A number of the papers are focused on how to adjust existing programs at a moderate cost. Here, I’ll just sketch a couple of proposals that think much bigger. 

For example, a “universal child allowance” means that any household with children, regardless of income level, would receive a per child payment from the government. . Luke Shaefer, Sophie Collyer, Greg Duncan, Kathryn Edin, Irwin Garfinkel, David Harris, Timothy M. Smeeding, Jane Waldfogel, Christopher Wimer, Hirokazu Yoshikawa  lay out what such a proposal might look like in “A Universal Child Allowance: A Plan to Reduce Poverty and Income Instability Among Children in the United States.”

The point out that the US has oriented much of it social safety net toward work, with the result that children in families where the adults don’t work much can be very badly off. Their baseline proposal is to that every US family with a child  would be about $250 per month ($3,000 per year).  Because the allowance doesn’t depend on income or hours worked, it is not reduced if an adult works more hours or gets higher pay. There is no need for a large bureaucracy to monitor eligibility and sliding-scale reductions in benefits.

Lots of other countries have enacted policies along these lines. They write (citations omitted):

Part of the reason that other nations have fewer poor children than the United States is that they provide what the OECD terms a universal child benefit�a cash grant that goes to all families with children. Austria, Canada, Denmark, Finland, France, Germany, Ireland, Luxembourg, the Netherlands, Norway, Sweden, and the UK have all implemented a version of a child benefit. Some call their measures child allowances (CA). Others implement their CA through the tax code as universal child tax credits. A notable feature of these universal child benefit plans is that they are accessible to all: families with children receive them regardless of whether parents work and whatever their income. The level of these child benefits varies by country. The benefit in U.S. dollars for two children in Belgium and Germany is about $5,600 per year; in Ireland $4,000, and in the Netherlands $2,400 (. Canada has a base child allowance, in U.S. dollars, of roughly $5,000 per child under six and $4,300 per child age six to seventeen …  

To pay for the allowances, they would start by scrapping the existing “$1,000 per child per year Child Tax Credit and a $4,000 per child per year tax exemption (often referred to as the child deduction),” which as they point out mostly go to families with incomes well above the poverty line.” This saves $97 billion.  The total estimated cost of the baseline proposal about $190 billion, so the additional spending needed would be $93 billion. For those who are skeptical about whether the money would actually benefit children, the author point to a body of evidence that for low-income families in particular, available cash seems to make a real difference in many measures of well-being. 

Another aggressive proposal is that the federal government should guarantee a job to everyone who wants one. Mark Paul, William Darity Jr., Darrick Hamilton, and Khaing Zaw sketch a proposal long these lines, and respond to some of the common concerns, in “A Path to Ending Poverty by Way of Ending Unemployment: A Federal Job Guarantee.” Their proposal is: “Any American wanting a job, at any time, would be able to obtain one through the public employment program.”

Their proposal is that local, state and federal governments would “conduct an inventory of their needs and develop a jobs bank. … At the federal level, we anticipate a wide array of major public investment activities, which may include fostering a transition to a green energy economy, extending access to high-speed rail, improvements in our public park service, revival and product diversification for the postal service, and an increase in general services across the economy. At the state level, we anticipate the states to undertake major infrastructure investment projects, as well as projects to improve the services they offer to their citizens. At the local level, we expect communities to undertake community development projects, provide universal daycare, maintain and upgrade their public school facilities, and improve and expand the services provided by their libraries.”

Most countries of the world tax oil products, especially the gasoline used in the road sector, but impose only very low taxes on other fossil fuels.  The OECD compiles a Taxing Energy Use Database that includes energy use and energy taxes for 42 countries that make up 80% of global energy use, and not coincidentally, 80% of global carbon emissions. For the latest iteration of this database, the OECD has also published Taxing Energy Use 2018: Companion to the Taxing Energy Use Database (February 2018), which pulls together some of the overall patterns. Here are a couple of the figures that caught my eye.

This figures shows energy taxes on a country-by-country basis. The energy taxes are measured in terms of euros per ton of carbon dioxide emitted. The little horizontal notches show the total tax on carbon emissions from energy use. Switzerland, Luxembourg, Germany, and Norway have the highest taxes, while the US and China are down at the low end,along with Brazil, Indonesia, and Russia. The variation across countries is considerable.

The dark blue balls show the tax on oil products, including gasoline. As is quickly apparent, the effective tax rate on carbon emissions from oil is higher than the tax rate on carbon emissions from other sources of energy. In particular, coal goes essentially untaxed in most countries. As a result, the OECD finds that 81% of carbon emissions are not taxed at all.

Here’s a similar story, but told in terms of sectors of the economy. The first section of the table on the left shows taxing of energy in the road sector, and the blue lines show carbon taxes on diesel and gasoline. But the next sections show energy taxes in industrial uses, in residential/commercial, and in electricity generation. From a global perspective, energy pollution arising from these other sources is largely untaxed.

If burning fossil fuels is enough of an environment problem that it justifies taxes on oil products in the road sector, then it seems quite peculiar to have burning of fossil fuel from other sectors going essentially untaxed. Indeed, there is a literature on the “co-benefits” of reducing air pollution, which points out that there are immediate short-term health gains to doing so, as well as a longer-term reduction  in the risks posed by carbon emissions.

• “Short-Term Benefits of a Climate Change Policy” (September 22, 2014)
• “The Immediate Global Costs of Pollution” (October 25, 2017)
• “Costs of Air Pollution in the U.S.” (November 7, 2011)

A couple of decades back, it was  hard to find systematic and reliable information on the economic and family characteristics of same-sex couples. However, the US Census has been collecting baseline data for some years now, and just released an annual report, Characteristics of Same-Sex Couple Households: 2005 to Present. The report is just a few statistical tables. I’ve taken one of the tables, cut some of the rows, left out the columns showing statistical significance, and cut the footnotes. But there’s enough left to note some patterns.

A table like this one is useful for showing some factual patterns, but it would be extremely unwise to draw any conclusions about causality from it. For example, it is certainly not true that if the unmarried couples were to marry, they would immediately become older, better educated, and with higher paychecks.

[Note added 3/1/18: Those interested in this topic might also want to check this Research Report from the Tax Policy Center: “Same-Sex Married Tax Filers After Windsor and Obergefell,” by Robin Fisher, Geoff Gee, and Adam Looney (February 28, 2018) It looks at evidence on same-sex married couples from tax returns, and how the patterns shifted after key Supreme Court rulings affecting same-sex marriage in 2013 and 2015.]

A decade ago, Dan A. Black, Seth G. Sanders, and Lowell J. Taylor. wrote about “The Economics of Lesbian and Gay Families.” in the Spring 20017 issue of the Journal of Economic Perspectives (21:2,  53-70). They noted that many of the observed patterns of same-sex couples are consistent with economic reasoning. For example, if a smaller share of same-sex couples are likely to have children, this will influence patterns of work, willingness to live in urban areas, and other factors. They wrote:

“The economic approach to thinking about families�with its focus on deliberative choices made by people with reasonably stable preferences�stresses the importance of constraints. That is, when economists seeks to understand systematic differences in the behavior of gays, lesbians, and heterosexuals, we do not start with a hypothesis of innate differences in preferences, but instead seek to understand how differences in constraints systematically alter incentives faced by gay, lesbian, and heterosexual people. This paper uses the economic approach to organize our thinking about gay and lesbian families, and thus implicitly assumes that, aside from sexual preference, other preferences do not systematically differ by sexual orientation. Based on that approach we provide evidence pertaining to some initial questions. 

“For example, do differing biological constraints faced by gay, lesbian, and heterosexual couples affect choices over children? Clearly they do; there are far fewer children in lesbian and gay families than heterosexual-partnered families. Gays and lesbians also face higher costs for adoption, which further reduces opportunities to raise children. 

“Do differences in fertility (or anticipated fertility), again owing to differences in constraints, influence where people live? We argue that because gay couples face a relatively high price for children, they will consume more non-child goods, and this increased consumption often takes the form of locating in expensive highamenity locations like San Francisco or New York. 

“Do same-sex couples have patterns of household specialization that differ in predictable fashion from heterosexual couples? Available evidence indicates that lesbian women have higher wages and greater labor force attachment than heterosexual women, while the opposite situation pertains for gay men relative to heterosexual men. A variant of Becker�s (1991) model of household specialization would predict this pattern. 

“Of course, many other interesting and fundamental questions await analysis, from economics and other social science disciplines, as better data sources become available.”

Why is it that the United States (or democracies in general) can in many cases pass foolish bad laws or make a  misguided selection of leaders–but nonetheless continue over time to flourish over a sustained time? Alexis de Tocqueville tackles that question in this passage from his 1840 work Democracy in America (Chapter XIV: Advantages American Society Derive From Democracy � Part I, available various places on the web like here and here).  It’s food for thought for today’s President’s Day holiday.

Cotton pickers. Shelf-scanners at Walmart. Quality control at building sites. Radiologists. These are just four examples of jobs that are being transformed and even sometime eliminated by the newest wave of automated and programmable machinery. Here are four short stories from various sources, which of course represent a much broader transformation happening across the global economy.
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Before settling into my sofa for a couple of weeks of watching the athletes slip and slide through Winter Olympics from PyeongChang, I need to confess that the Games are a highly questionable economic proposition. One vivid illustration is that the $100 million new stadium in which the opening ceremonies will be held is going to be used four times in total–opening and closing of the Winter Olympics, opening and closing the Paralympics next month–and then it will torn down. Andrew Zimbalist goes through the issues in more detail in “Tarnished Gold: Popping the Olympics Bubble,” which appears in the Milken Institute Review (First Quarter 2018).

Building new facilities (or dramatically refurbishing older ones) is a major cost for the Games. Zimbalist notes that the previous Winter Games in 2014, “the IOC embraced an ostentatious bid from Sochi for the 2014 Winter Olympics where almost none of the required venues or infrastructure were in place. It became the most expensive Olympics in history, with Russia ponying up between $50 billion and $67 billion � though how much of that actually went into construction and operations is unclear.”

As it has become abundantly clear that that direct revenues that a host city receives from the Olympics–for example, revenues related to tickets and television rights–typically cover only about one-third of the costs of hosting, fewer cities are bidding  to host the Games.  The 2022 Winter Games came down to two bidders, Beijing in China and Almaty in Kazakhstan. Beijing “won,” as Zimbalist describes:

“The Beijing organizing committee pitched its bid to the IOC by noting that it would use some venues left over from the 2008 summer Olympics. But China went along with the IOC�s penchant for creative accounting by excluding the cost of the high-speed railroad that will link Beijing to the downhill and cross-country ski areas (54 miles and 118 miles from the capital, respectively). That project will run to about $5 billion and have little value to the region after the Games are over.

“Also excluded from the Beijing budget will be the substantial expense of new water diversion and desalination programs necessary for hosting Winter Games in China�s water- (and snow-) starved northern cities. North China has only 25 percent of the country�s water resources to supply nearly 50 percent of the population. Accordingly, China launched an $80 billion water-diversion program from the south before the 2008 summer Olympics.

“But the north’s water availability still remains below what the United Nations deems to be the critical level for health � let alone for an Olympics extravaganza. Zhangjiakou, the site of the Nordic skiing competition, gets fewer than eight inches of snow per year. Yanqing, the site of the Alpine skiing events, gets less than 15 inches of precipitation annually.

“Both areas will thus require copious water for artificial snowmaking. But even if China manages to complete the necessary infrastructure for water diversion, it will amount to robbing Peter to pay Paul: Beijing, Zhangjiakou and Yanqing lie in one of China’s most important agricultural regions, producing sorghum, corn, winter wheat, vegetables and cotton.

“The government, moreover, is apparently counting on lasting value from the construction of the Winter Games, creating permanent ski resorts in the mountains bordering Inner Mongolia and the Gobi Desert. If the ski resorts survive, only China’s richest residents will be able to afford them, while food supplies � and the incomes of the growers � will suffer.

“Another strike against Beijing 2022 is that winter is one of the worst times for air pollution in this horribly polluted city. Deforestation of the northern mountains needed for Games infrastructure will only compound the problem.

“One might wonder why, in light of the daunting complications of hosting the Winter Games in northern China, Beijing got the nod in the first place. The answer is simple: thanks to the prospect of big deficits, the only other city bidding was Almaty, capital of oildrenched Kazakhstan, which has been ruled with an iron fist by the kleptocrat Nursultan Nazarbayev since independence in 1991.”

Zimbalist doesn’t offer parallel estimates for the PyeongChang games. The standard estimate floating round seems to be that South Korea will spend about $13 billion on facilities for the Winter Games, but such estimates turn out to be too low. Also, this amount doesn’t include infrastructure like a high-speed rail line over the 80 miles between Seoul and PyeongChang. A few years ago, analysts from the Hyundai Research Institute pegged these additional infrastructure costs at $43.8 billion.

The economic case for hosting the Olympics thus needs to rely on indirect benefits: short-term construction jobs before the Games, tourist spending during the Games, infrastructure and recognition that could last after the Games. Looking at past Olympics, such benefits are quite uncertain. The best-case economic scenario for the  PyeongChang Games may be the Salt Lake City Winter Games of 2002. The underlying reason is that this area was an attractive and reachable destination for winter sports, but somewhat underappreciated before the Games. It’s visibility and tourism seemed to get a long-term boost from the Games. Indeed, Salt Lake City has just announced that it would be interested in hosting the Games again in 2026 or 2030.

However, other homes for the Winter Games in recent decades have not succeeded in the same way: either the destination was already fairly popular for winter activities, and thus didn’t receive a long-term tourism boost, or the area just didn’t get a long-term boost. Here’s the roll call of locations for the last 10 Winter Games: Sochi (2014), Vancouver (2010), Turin (2006), Salt Lake City (2002), Nagano (1998), Lillehammer (1994), Albertville (1992), Calgary (1988), Sarajevo (1984), Lake Placid (1980).

For the PyeongChang Games, ticket sales have not been brisk. Television ratings seem likely to be fine, but with the big time difference and people who access their media in other ways, they may not be great. Spending on facilities seems to have been kept under control, although this may also mean that the details of cost overruns haven’t yet filtered out. Even the International Olympic Committee, not known for encouraging parsimony, has warned publicly that many of the new venues may become useless after the Games.

The ultimate economic payoff is likely to depend on whether PyeongChang becomes a considerably more prominent destination for winter tourist activities in the years after the Games. On the downside, PyeongChang at present has a small population (about 44,000), and it’s night life,  restaurants, and hotels are correspondingly limited. It also about 40 miles from the demilitarized zone separating South and North Korea, which might make potential tourists uncertain about plunking down money for reservations. On the upside, income levels have been growing rapidly in east Asia, especially in China. The demand for tourist destinations is rising. There are a number of successful South Korean ski resorts already. PyeongChang will almost have economic costs far exceeding the benefits. But it has a reasonable chance of less red ink than other recent Winter Games, and seems likely to do far better on a cost-benefit calculation than either its predecessor in Sochi or its successor in Beijing.

For more on economics and the Olympics, here’s a discussion from Zimbalist of why Boston opted out of even trying to host the 2024 Summer Games, and here’s a discussion of an n article Robert A. Baade and Victor A. Matheson that appeared in the Spring 2016 issue of the Journal of Economic Perspectives, “Going for the Gold: The Economics ofthe Olympics,”

If you’re interested in how K-12 schools might improve their performance, charter schools can be viewed as a laboratory experiment. Sarah Cohodes discusses the lessons they have to teach in “Charter Schools and the Achievement Gap,” written as a Policy Issue paper for Future of Children (Winter 2018). From a social science view, charter schools have two especially useful properties: there are enough of them to have a reasonable sample size, and a number of them are required to admit students through a lottery process–which means that those randomly selected to attend the charter can be compared with those randomly not selected to do so. Cohodes notes:

“The first charter schools were created in Minnesota in 1993. Forty-three states and Washington, DC, now have laws that permit the operation of charter schools, and around 7,000 charter schools now serve more than 5 percent of students in the United States.1 They�ve grown steadily over the past 10 years, adding about 300 or 400 schools each year. To put this in perspective, about 10 percent of US students attend a private school, and 3 percent are homeschooled. …

“Because charter schools are required by law to admit students by a random lottery if they�re oversubscribed, charter school admissions are analogous to an experiment in which participants are randomly assigned to a treatment group or a control group (a randomized controlled trial). After accounting for important details that arise from operating a lottery in the real world versus doing so purely for research purposes, such as sibling preferences and late applicants, a random lottery assigns the seats for charter schools that are oversubscribed. This allows researchers to compare the outcomes of a treatment group of students who were offered a seat in the lottery to a control group of those who were not.”

Of course, it’s also possible to study the effects of attending charter schools by finding a good comparison group outside the school, in what is called an “observational” study, but choosing an  appropriate comparison group necessarily adds an element of uncertainty. The research on charter schools finds that on average, they perform about the same as K-12 schools. But charter schools  vary considerably: some do worse than K-12 schools, but some do better.

“The best estimates find that attending a charter school has no impact compared to attending a traditional public school. That might surprise you if you were expecting negative or positive impacts based on the political debate around charter schools. But using both lottery-based and observational estimates of charter school effectiveness in samples that include a diverse group of charter schools, the evidence shows, on average, no difference between students who attend a charter and those who attend a traditional public school. However, much of the same research also finds that a subset of charter schools has significant positive impacts on student outcomes. These are typically urban charter schools serving minority and low-income students that use a no excuses curriculum.”

 Here’s how the “no escuses approach” is defined in a couple of the lottery-based studies: