Conversable Economist

Africa\’s cities are growing rapidly, which presents both an environmental problem and a policy opportunity. The problem is that many of these cities already have severe environmental issues. The opportunity is that because these cities are much smaller than they will be in a few decades, there are opportunities now to guide and shape their growth in ways that can be much more cost-effective than trying to clean up the mess after it has already happened. Roland White, Jane Turpie, and Gwyneth Letley explore these issues in a World Bank report, Greening Africa\’s Cities : Enhancing the Relationship between Urbanization, Environmental Assets, and Ecosystem Services (May 2017).

On the patterns of urbanization in Africa, they write:

\”Urbanization in Africa began later than in any other global region and, at a level of about approximately 40%, Africa remains the least urbanized region in the world. However, as indicated in Figure 3, this is rapidly changing: SSA’s cities have grown at an average rate of close to 4.0% per year over the past twenty years, and are projected to grow between 2.5% and 3.5% annually from 2015 to 2055 (Figure 3). By contrast, globally the average annual urban population growth rate is projected to be between 1.44% and 1.84% from 2015 to 2030 (WHO 2015). From an environmental perspective, this has two important implications. On the one hand, most of Africa’s urban space has yet to emerge. Much of the area which will eventually be covered by the built environment has not yet been constructed and populated. Crucial natural assets – and significant biodiversity – thus remain intact in areas to which cities will eventually spread. On the other hand, this is changing quickly: pressures on the natural environment in and around cities are escalating steadily and these assets are increasingly under serious threat.\”

The existing environmental hazards levels in many African cities are often severe. They write: \”For the entire region the proportion of urban residents with access to sanitation was estimated to be only 37% in 2010. Solid waste coverage also remains very limited with collection rates for many African cities at below 50% …\” 

Just because corporate executives pay hundreds of visits to the White House doesn\’t prove that their firms are benefiting from White House connections. Perhaps it\’s just a useful way for the White House to gather information and input about economic effects of real-world policies. Perhaps it\’s a useful way for the White House to get a little reflected glory from those who run successful companies. Perhaps it\’s a way of rewarding diehard supporters who would have been supporting you anyway. But Jeffrey R. Brown and Jiekun Huang actually take a look at how corporate stocks perform right around the time of White House visits. Their evidence appears in All the President’s Friends: Political Access and Firm Value,\” which appears as a National Bureau of Economic Working Paper (#23356, April 2017, not freely available on-line, but many academics will have access through library subscriptions.

The Brown/Huang approach is fairly straightforward. They look at the stock market returns of companies in the 10 days before and the 120 days after the visit of a top executive to the White House between 2009 and 2015. According to the White House logs, there were 2,286 visits by top executives to officials at the White House during these seven years, which includes more than 100 visits apiece with Barack Obama, Valerie Jarrett, and Jeffrey Zients. Brown and Huang adjust for how the overall stock market is doing, so they are looking at \”abnormal\” returns that differ from the average for the market as a whole. Here\’s a figure showing the pattern they find.

Within about 30 days of the visit of a top executive to the White House, on average a company sees its stock rise by nearly 1% more than the market as a whole–and then remain near that higher level at least through the 120-day horizon. When the authors break down the statistics by year, they find that the \”cumulative abnormal returns,\” as they refer to these calculations, \”are significantly positive during the election year (2012), the first years post-election (2009 and 2013) as well as 2014, suggesting that access to influential government officials is particularly beneficial during those years.\”

Of course, the pattern shown here doesn\’t prove that companies are benefiting from their White House connections. Perhaps stock market investors mistakenly perceive a White House visit means good news for the company. Perhaps top executives are more likely to get a White House invitation when good news is about to arrive for their company. But it\’s an interesting tidbit of actual evidence.

Here are some snippets from Trotsky, which include a number of phrases and sentences that could have been written by a fierce critic of socialism like Friedrich Hayek. Trotsky\’s concerns include: the large costs of mistakes in centralized decision-making, problems in which quality of output is sacrificed in the drive for greater quantity, lack of coordination across production chains in the economy, how bureaucrats lack a \”universal mind\” and thus need to rely on supply and demand and \”commercial relations.\” Of course, for Trotsky, all of this just proves that socialism is working.

\”Even though the first five-year plan took into consideration all possible aspects, by the very nature of things it could not be anything but a first and rough hypothesis, destined beforehand to fundamental reconstruction in the process of the work. It is impossible to create a priori a complete system of economic harmony. The planning hypothesis could not but include old disproportions and the inevitability of the development of new ones. Centralized management implies not only great advantages but also the danger of centralizing mistakes, that is, of elevating them to an excessively high degree. … 

\”The administrative hue and cry for quantity leads to a frightful lowering of quality; low quality undermines at the next stage the struggle for quantity; the ultimate cost of economically irrational “successes” surpasses as a rule many times the value of these same successes. Every advanced worker is acquainted with this dialectic, not through the books of the Communist academy (alas! more inferior goods), but in practice, through experience in their own mines, factories, railroads, fuel stations, etc. … If we were to introduce a corrective coefficient for quality into the official data, then the indices of the fulfilment of the plan would immediately suffer substantial drops. …

\”The problem of the proportionality of the elements of production and the branches of the economy constitutes the very heart of socialist economy. The tortuous roads that lead to the solution of this problem are not charted on any map. To discover them, or more correctly to lay them, is the work of a lengthy and arduous future. All of industry groans from the lack of spare parts. Weavers’ looms remain inactive because a bolt is not to be had. “The assortment of articles produced,” writes EZ, “in the line of commodities of widespread consumption is haphazard and does not correspond to … the demand.” …

\”If a universal mind existed, of the kind that projected itself into the scientific fancy of Laplace – a mind that could register simultaneously all the processes of nature and society, that could measure the dynamics of their motion, that could forecast the results of their inter-reactions – such a mind, of course, could a priori draw up a faultless and exhaustive economic plan, beginning with the number of acres of wheat down to the last button for a vest. The bureaucracy often imagines that just such a mind is at its disposal; that is why it so easily frees itself from the control of the market and of Soviet democracy. But, in reality, the bureaucracy errs frightfully in its estimate of its spiritual resources. In its projections it is necessarily obliged, in actual performance, to depend upon the proportions (and with equal justice one may say the disproportions) it has inherited from capitalist Russia, upon the data of the economic structure of contemporary capitalist nations, and finally upon the experience of successes and mistakes of the Soviet economy itself. But even the most correct combination of all these elements will allow only a most imperfect framework of a plan, not more.

\”The innumerable living participants in the economy, state and private, collective and individual, must serve notice of their needs and of their relative strength not only through the statistical determinations of plan commissions but by the direct pressure of supply and demand. The plan is checked and, to a considerable degree, realized through the market. The regulation of the market itself must depend upon the tendencies that are brought out through its mechanism. The blueprints produced by the departments must demonstrate their economic efficacy through commercial calculation. …

\”Within the scope of this brief pamphlet I have deemed it necessary to present in all their acuteness the contradictions of the Soviet economy, the incompleteness and the precariousness of many of its conquests, the gross errors of the leadership, and the dangers that stand in the path of socialism. … One who accepts the proletarian revolution only when it is accompanied by all conveniences and lifelong guarantees cannot continue on the road with us. We accept the workers’ state as it is and we assert, “This is our state.” Despite its heritage of backwardness, despite starvation and sluggishness, despite the bureaucratic mistakes and even abominations, the workers of the entire world must defend tooth and nail their future socialist fatherland which this state represents. …\”

Around the world, life expectancy is rising, birthrates are either falling or stable, and populations are aging. But Mauricio Soto offers some eye-opening calculations about what this means for those relying on government pensions in \”Pension Shock,\” which appears in the June 2017 issue of Finance & Development.

In the chart, the left-hand panel shows government spending on old-age pensions across OECD countries. The level has basically doubled from over 4% in 1970 to roughly 9% at present. But at least given current projections, and after various steps that governments have taken, government spending on pensions as a share of GDP isn\’t scheduled to rise much more in the next few decades.

The difficulty arises because if government keeps spending the same share of GDP on pensions at a time when the share of the population who are elderly keeps rising, then the average government pensions will cover a smaller share of income. Thus, the right-hand panel shows that while the \”economic replacement rate\” for an average individual over the age of 65 has been around one-third of per capita GDP for the last few decades, it\’s projected to fall to about 20% of per capita GDP by 2040 and later.

What\’s are some of the  possible responses here? One set of reactions could happen within the  political system. For example, the elderly could vote for dramatic increases in taxes on the working generation to support higher pensions. Or government pensions could be redesigned to provide only a basic income support, and nothing much higher, even if you paid much more in payroll taxes throughout your life.

Another set of reactions could happen with the actions of individuals. Soto\’s calculations suggest that if people worked about five years longer before retirement, it would offset about half of the predicted decline in the \”economic replacement rate.\” If everyone also saved at least 6 percent of their income during their working life, this would offset the other half of the fall in the \”economic replacement rate.\” Again, these changes are just what is necessary to offset the expected decline in what government pensions are currently scheduled to pay.

The needs and expectations of an aging population are a tectonic shift under our current political and economic understandings, and will cause some earthquakes before it\’s done.

US coal output and coal jobs have dropped in recent years. In \”What Is Killing the US Coal Industry?\”, Charles D. Kolstad names and investigates the suspects. The essay is a March 2017 Policy Brief for the Stanford Institute for Economic Policy Research. Here is Kolstad\’s list of suspects:

• \”Environmental regulations — the primary suspect for some — killed coal. 
• \”Deregulating railroads in the 1970s allowed cheap Western coal to displace more costly Eastern coal, resulting in major job losses in the labor-intensive Eastern coal industry. 
• \”The fracking revolution has driven down natural gas prices, making coal less competitive in electricity production. 
• \”Coal mining jobs are going away because of the same productivity gains that have led to fewer manufacturing jobs across the country — workers can produce more coal per hour, meaning fewer workers are needed to maintain steady coal output. 
• \”Other reasons include financial markets, which may see the future of coal as risky (for a variety of reasons) and thus a poor investment.\” 

Kolstead\’s conclusion: \”[E]nvironmental regulations did not kill coal. Progress is the culprit.\” Here\’s some additional detail, starting with the big-picture overview of US coal output and jobs.

Total US coal output rose fairly steadily from 1950 up to about 2010. However, the graph shows that all of the rise was in western coal, like the Powder River Basin in Montana and Wyoming, rather than eastern coal like West Virginia and Pennsylvania. Railroad deregulation in the 1970s made it much more cost-effective for western coal to be shipped around the country.

Employment in the coal industry first fell sharply in the 1950s with the agreement between the United Mineworkers union to pursue automation in the coal industry in exchange for better wages. There is another long decline in coal miner jobs starting around 1980, but it is mostly in eastern mines. Remember, the output of eastern mines wasn\’t changing much during most of this time, which implies that the productivity of coal miners was rising substantially.

More recently, the rise of natural gas production has taken market share from coal: for example, coal has traditionally been the main fuel for generating electricity, even into the early 2000s. However, the share of electricity generated by natural gas now exceeds that from coal.

What about environmental regulations as a reason for decline in the coal industry? Kolsted points out two ironies here.

First, it\’s true that air pollution rules passed back in 1970 to reduce sulfur emissions tended to hurt high-sulfur eastern coal. But then those rules were given exceptions to help offset the harms to eastern coal. The result was that coal-fired power plants in the east ended up holding on to old and inefficient facilities much longer–and in recent years the age of those facilities has caught up with them. Kolsted explains:

\”The easiest way to meet the 1970 sulfur emissions regulations was to burn low-sulfur coal, which set off  a dramatic expansion of low-sulfur coal mining, primarily in Wyoming. The strong demand for low-sulfur coal threatened high-sulfur coal producers, primarily in the East. 

\”In order to save coal-mining jobs in the East, the Clean Air Act was amended in 1977 to require equipment on all new coal-fired power plants to physically remove sulfur from the smokestacks after combustion, reducing the attractiveness of low-sulfur coal (all coal becoming “compliance coal”). This reduced the competitive threat to Eastern mines.

\”Another feature of the 1970 Clean Air Act had more subtle and delayed effects. That is the exemption of existing (as of 1970) power plants from sulfur reduction rules. This “grandfathering” was done for political reasons to facilitate passage of the Act. But it was also viewed as fair and without long-term consequences since those older plants were expected to retire at the end of their 40- or 50-year lives anyway. But as Revesz and Lienke (2016) detail, this exemption provided an incentive to keep old and dirty power plants operating rather than retire, despite the higher operating costs of old plants. To protect health and welfare, this necessitated the EPA’s imposition of more restrictions on old power plants over the years, including the acid rain provisions instituted in 1990 during the Bush administration. Additional rules were put in place during the next three presidential administrations to deal with the problems caused by old plants operating long after their assumed retirement date.

\”Now, nearly 50 years after the 1970 Act, shuttering of old power plants has finally begun. … [T]he coal plants retired in 2015 were quite old (the oldest began operation in 1944, the year the Allies landed in Normandy). … This suggests that the decline in coal-fired electricity generation is largely the result of an aging fleet of power plants, which may well have been retired years ago absent the Clean Air Act’s grandfathering clause.\”

Second, if environmental regulations are loosened for all types of energy production–that is, for natural gas as well as for coal–it\’s quite plausible that natural gas will continue to gain relative to coal.

So yes, environmental rules affected eastern coal production. But the big stories for the fall of coal are productivity growth among coal miners and the rise of natural gas. demand for eastern coal might well be larger today if instead of favoring aging coal-fired electrical power plants through grandfathering rules, those plants had been updated and replaced over the decades.  

Douglas Clement offers yet another of his excellent interviews, this one with Hilary Hoynes, in The Region, published by the Federal Reserve Bank of Minneapolis (June 1, 2017).  Here are some tidbits.

Long-Term Returns to Food Stamps

\”Food stamps are a central part of the U.S. social safety net, and it’s a means-tested program—meaning that you have to have low income to participate. And, remarkably, it has remained fairly intact over the past 20, 30, 40 years while other parts of the safety net for low-income families have been restricted and reformed. Also, it’s federal—run out of the USDA—so it doesn’t vary a lot geographically. That’s helpful because it really provides a uniform floor across the United States. In very poor areas, even in states that don’t tend to provide a lot of assistance for the poor, food stamps create a kind of universal minimum across all places. It does, however, create challenges for doing evaluation because it doesn’t vary much across space, and it also hasn’t varied much over time. …

\”Food stamps started under President Kennedy. His first executive action was to start some pilot programs for food stamps. … Those pilot programs eventually led to passage of the Food Stamp Act in 1964. But it wasn’t until 1974, 10 years later, that subsequent legislation compelled all areas to implement food stamps. In that 10-year interim, Congress essentially said to U.S. counties, “We’re going to appropriate these funds for this program. If you’re interested in implementing this program, please apply and we will fund them, subject to our appropriation.” … This resulted in gradual rollout of food stamps across the almost 3,200 U.S. counties. …

\”The “rollout design” is one of the tools in our tool bag for doing evaluation. And, of course, we need to convince ourselves that that rollout was as good as random, that it wasn’t systematic, that certain areas had the rollout earlier than others. In our first paper on this, my co-author Diane Schanzenbach and I really dug into the nature of the rollout and the political economy behind it. At the end of the day, we were convinced that it was as good as random which places got food stamps earlier rather than later. …

\”In the paper in last year’s AER with Douglas Almond and Diane Schanzenbach, we took a long-term evaluation lens to this program. Food stamps rolled out in the ’60s and ’70s, so the cohorts affected, or not, in early or late childhood are in their early 50s today. This presented an opportunity to address a question that no one has ever looked at before in the context of food stamps: What are their long-run benefits? …

\”We couldn’t in our data know precisely which families were on food stamps, so it’s sort of an indirect estimate. But we know whether food stamps were implemented when these individuals were 2 or 4 or 14 or 20 years old. We essentially analyzed the data within that lens: How old were you when food stamps were rolled out in your county?

\”The headline finding was about health. We measured metabolic syndrome, which is essentially a range of conditions including high blood pressure, diabetes, heart disease and obesity. … And we found that the more exposure to food stamps that a person had, the lower their risk of metabolic syndrome in adulthood. In particular, the gains were greatest if the food stamps program was implemented before an individual was 3 or 4 years old. That period between in utero exposure—prebirth—to those first three or four years of life, was the age range where having more exposure to food stamps available led to a more dramatic reduction in the incidence of metabolic syndrome in adulthood. … Then we also looked at effects on human capital outcomes. …  In short, we found that better nutrition in early childhood leads to human capital improvement and better outcomes in adulthood, but that finding was limited to women.\”

On the Earned Income Tax Credit

\”The EITC is the most important anti-poverty program for families with children in America. It removes the most children from poverty, and it’s organized as an in-work benefit rather than an out-of-work benefit. Welfare, for instance, is an out-of-work benefit …  The whole idea of in-work programs like EITC is to respond to that and say, “Well, American voters would rather have a program that redistributes while encouraging work, not discouraging work.” The EITC operates as an earning subsidy on incomes up to about $14,000. For every dollar that you earn, if you’re a single mother with two children or a married couple with two children, for every dollar that you earn up to about $14,000, you get 40 cents added to that dollar through the EITC. It’s a quite powerful increase in your after-tax wage.

\”It still needs to phase out or everybody would get it, so there are some negative work incentives that are faced by higher-income workers at levels where the EITC phases out: between about $15,000 and $40,000—or $18,000 and $45,000, depending on your family size. And it’s phased out at a rate of about 21 cents on the dollar. So, if you earn an additional dollar, your EITC is reduced by 21 cents, a gradual phase-out.

\”Research shows that this program design has a dramatic effect on employment. When the EITC expands, you see more low-skilled workers, particularly single mothers, in the labor market. It has a very powerful effect on transitioning people from out-of-work to in-work. And in so doing, it lowers poverty rates, not just because you’re giving households a tax refund at the end of the year—and of course, if you give someone money, you’re going to reduce poverty—but just as important is the fact that by encouraging work, earnings go up in the household, and that also reduces poverty. It generates a roughly 2-for-1 reduction in poverty for every dollar of federal spending, and that’s every efficient. … It does redistribution within the tax code, rather than a sort of brick-and-mortar social welfare operation that is the model of the state-based social safety net.\”

Head Start Doesn\’t Fade for All Groups 

\”[M]any studies that look at the effects of Head Start (and, to some extent, of programs like Perry Preschool and others) have found that increases in cognitive test scores for children in the years they’re in Head Start seem to fade out once they enter school. … Is it possible that this fadeout is masking the fact that there are gains for some groups that somehow, in the global mean, seem to disappear?

\”It turns out that the story isn’t quite that simple; but we did discover that, yes, Head Start increases cognitive test scores, but those global mean results mask the fact that the gains are very concentrated at the bottom of the skill distribution. The test scores at the bottom of the distribution went up by a lot; whereas, test scores in the middle and the top of the distribution didn’t go up by very much. …

\”Fast forward in this Head Start impact study, and observe kids through grade 1. We found that overall, the fadeout occurs throughout the distribution for the full population. But by looking across groups based on maternal education, race, ethnicity and other characteristics, we uncovered this finding of much larger gains for a specific group: kids who enter Head Start as English language learners—that is, English is not the primarily language at home. And in this experiment, that turned out to mostly be Spanish speakers because of the population in the experiment. These results were contemporaneous when the kids are still in Head Start, but they also persisted through transition to elementary school. Fadeout didn’t occur.\”

Hoynes has written for the Journal of Economic Perspectives, where I work as Managing Editor, a couple of times. For those who would like to sample her work up close, the articles are:

• \”Poverty in America: Trends and Explanations,\” by Hilary W. Hoynes, Marianne E. Page, and Ann Huff Stevens, Journal of Economic Perspectives, Winter 2006, 20:1, pp. 47-68.
• \”Who Suffers During Recessions?\” by Hilary Hoynes, Douglas L. Miller, and Jessamyn Schaller, Journal of Economic Perspectives, Summer 2012, 26:3, pp. 27-48. 

It is a fact of nature that all countries have the same electromagnetic spectrum of radio frequencies. It is a fact of politics that countries have different rules for allocating these frequencies. And it is a fact of economics that people in different countries pay very different rates for their use of spectrum. Mara Faccio and Luigi Zingales ask: \”Why does the price of the same basket of mobile phone services vary around the world from $10.07 to $47.25? Why does the price of a 1GB mobile-broadband internet plan vary from $11.24 to $100.28?\” They investigate the question in a January 2017 working paper \”Political Determinants of Competition in the MobileTelecommunication Industry,\” available from the Stigler Center for the Study of the Economy and the State at the University of Chicago Booth School of Business.  For those who prefer to get their economics via cartoon, the most recent issue of the Chicago Booth Review has you covered with on this topic.

Countries can affect the competitive situation of telecommunications industries in many ways, including the rules that govern entry, the extent of price regulation, whether phone numbers are easily portable when shifting between carriers, whether voice-over-internet calls are permitted, and so on. These rules vary substantially across countries. Faccio and Zingales write: \”[E]very time one crosses a national border in Europe the roaming company of the mobile phone changes. In spite of the European integration process, the mobile communication industry remains segmented at the national level. This is not unique to Europe: throughout the world, the mobile communication industry remains very much segmented by country.\” Another reason to focus on mobile phone and broadband is because the availability and quality of these services can be readily across users in different countries.

Indeed, they have data from the International Telecommunications Union available for 148 countries that includes dozens of variables in They have data on five main categories of variables in each country: regulatory climate; competitive structure; quality of service; spectrum auctions; and broad institutional characteristics (democracy, unions, tax rates and more). Thus, they offer a lot of statistical tables to make their case: \”We show that the way a government designs the rules of the game has an impact on concentration, competition, and prices. Pro-competition regulation reduces prices, but does not hurt quality of services or investments. More democratic governments tend to design more competitive rules, while more politically connected operators are able to distort the rules in their favor, restricting competition.

But beyond the statistics, they offer a comparison between the United States and \”the two EU countries with the level of regulation closest to the Unites States,\” namely Germany and Denmark. They write:

\”The United States exhibits much higher monthly revenues per unique subscriber ($67.6 in 2015:3 vs $23.48 Germany and $31.01 for Denmark), which implies U.S. cellular phone companies have annual revenues per customers $530 higher than their German counterparts, and $439 higher than their Danish counterparts. One reason for the large difference could be that the U.S. carriers tend to subsidize the headsets, while the European carriers do not. The typical subsidy for an iPhone is $500 dollars (they charge $199 for a phone worth $699). Even factoring in this difference, each U.S. customer pays $280 a year more than a German customer and $189 a year more than a Danish one. Given the number of U.S. customers (233.2 million in 2015), this implies that U.S. operators enjoy a transfer of $65.2bn ($44.1bn) vis-à-vis the German (Danish)
benchmark.

\”Not all of this difference is a pure transfer. We do find better quality of service in the
United States, where in 2013 4G connections represented 23.1% of the total and 4G coverage was 95.1%. In Germany, 4G connections represented 2.7% of the total 4G coverage was 64.54%, while for Denmark, 4G connections represented 9.31% of the total and 4G coverage was 92.37%.\”

However, the authors go on to argue that the relatively small differences in quality cannot explain the relatively large differences in prices paid by consumers; indeed, the higher prices paid by consumers help to explain the high stock prices for major US carriers like AT&T, Verizon, T-Mobile, and Sprint. In looking at their overall data set, the authors write: \”We test this hypothesis and we find no evidence that a higher degree of competition leads to lower quality of service or less investments. If anything, the results go in the opposite direction.\”

In the United States, the Federal Communications Commission just completed in March 2017 its first \”incentive\” auction, in which the broadcast TV companies that were allocated huge chunks of spectrum decades ago, but now deliver most of their content via cables, have an chance to sell off that spectrum to mobile services. As the FCC writes: \”In the auction, TV broadcasters could voluntarily give up their current broadcast channel in exchange for a share of the proceeds from an auction of their channel to commercial wireless service providers to provide expanded mobile broadband services.\” This is a step in the right direction. But American consumers have every reason to keep comparing their mobile bills to those in Germany, Denmark, and elsewhere, and to get an answer from their government on why the electromagnetic spectrum that is naturally available everywhere should cost more in the United States.

Life and work is more than reading and writing and arithmetic. Being able to function well with others in a wide range of situations is extraordinarily important–for many jobs, at least as important–as explicitly cognitive skills. The Future of Children has devoted is Spring 2017 issue to nine articles about \”Social and Emotional Learning.\” After reading through the articles, my sense is that the subject is of potentially enormous importance, and that the state of current knowledge and practice is  fragmented and incomplete, with difficulties in deciding what traits to study, at what ages, and how to measure them.  Here are a few snippets.

From the the introductory essay by Stephanie M. Jones and Emily J. Doolittle, called \”Social and Emotional Learning: Introducing the Issue:\”

\”Research increasingly suggests that social and emotional learning (SEL) matters a great deal for important life outcomes like success in school, college entry and completion, and later earnings. This research also tells us that SEL can be taught and nurtured in schools so that students increase their ability to integrate thinking, emotions, and behavior in ways that lead to positive school and life outcomes. Although the term social and emotional learning has been around for 20 years, we’ve recently seen a rapid surge in interest in SEL among parents, educators, and policymakers. … All 50 states have SEL standards in place at the preschool level, and four (Illinois, Kansas, West Virginia, and Pennsylvania) have SEL standards for kindergarten through 12th grade. …  We also know that teachers believe SEL skills can be taught, although they may not always know the best way to do so in their classrooms. … SEL goes by many other names. Common terms for this set of skills include character education, personality, 21st-century skills, soft skills, and noncognitive skills, just to name a few. …

\”But what are we talking about when it comes to SEL? Researchers, educators, and policymakers alike have trouble pinning down exactly what’s included in this broad domain—and what isn’t. The popular press has highlighted a wide array of skills, such as grit, empathy, growth mindset, social skills, and more. At its core, SEL involves children’s ability to learn about and manage their own emotions and interactions in ways that benefit themselves and others, and that help children and youth succeed in schooling, the workplace, relationships, and citizenship. To effectively manage emotions and social interactions requires a complex interplay of cognitive skills, such as attention and the ability to solve problems; beliefs about the self, such as perceptions of competence and autonomy; and social awareness, including empathy for others and the ability to resolve conflicts. …

\”Decades’ worth of research suggests that something other than academic skills and content knowledge strongly influences success in school and beyond. Indeed, SEL skills may be just as important as academic or purely cognitive skills for understanding how people succeed in school, college, and careers. In addition, preliminary evidence suggests that SEL skills could be central to understanding and remediating stubbornly persistent gaps in achievement defined by income and racial/ethnic differences. …\”

From the abstract of the article called \”SEL Interventions in Early Childhood,\” by Megan M. McClelland, Shauna L. Tominey, Sara A. Schmitt, and Robert Duncan:

\”Three strategies appear to make interventions more successful, the authors write. First, many effective SEL interventions include training or professional development for early childhood teachers; some also emphasize building teachers’ own SEL skills. Second, effective interventions embed direct instruction and practice of targeted skills into daily activities, giving children repeated opportunities to practice SEL skills in different contexts; it’s best if these activities grow more complex over time. Third, effective interventions engage children’s families, so that kids have a chance to work on their SEL skills both at school and at home. Family components may include teaching adults how to help children build SEL skills or teaching adults themselves how to practice and model such skills. 

\”Are early childhood SEL interventions cost-effective? The short answer is that it’s too soon to be sure. We won’t know how the costs and benefits stack up without further research that follows participants into later childhood and adulthood. In this context, we particularly need to understand how the long-term benefits of shorter, less intensive, and less costly programs compare to the benefits of more intensive and costlier ones.\”

From the abstract for \”Promoting Social and Emotional Competencies in Elementary School,\” by  Stephanie M. Jones, Sophie P. Barnes, Rebecca Bailey, and Emily J. Doolittle:

\”But evidence from the most rigorous studies of elementary-school SEL programs is ambiguous. Some studies find few or no effects, while others find important and meaningful effects. Or studies find effects for some groups of students but not for others. What causes such variation isn’t clear, making it hard to interpret and act on the evidence. What are the sources of variation in the impacts of SEL programs designed for the elementary years? To find out, Stephanie Jones, Sophie Barnes, Rebecca Bailey, and Emily Doolittle examine how the theories of change behind 11 widely used school-based SEL interventions align with the way those interventions measure outcomes. Their central conclusion is that what appears to be variation in impacts may instead stem from imprecise program targets misaligned with too-general measures of outcomes. That is to say, program evaluations often fail to measure whether students have mastered the precise skills the programs seek to impart.\”

From the abstract for \” Social and Emotional Learning Programs for Adolescents,\” by David S. Yeager:

\”On the positive side, Yeager finds that effective universal SEL can transform adolescents’ lives for the better. Less encouragingly, typical SEL programs—which directly teach skills and invite participants to rehearse those skills over the course of many classroom lessons—have a poor track record with middle adolescents (roughly age 14 to 17), even though they work well with children. But some programs stand out for their effectiveness with adolescents. Rather than teaching them skills, Yeager finds, effective programs for adolescents focus on mindsets and climate. Harnessing adolescents’ developmental motivations, such programs aim to make them feel respected by adults and peers and offer them the chance to gain status and admiration in the eyes of people whose opinions they value.\”

Those interested in this subject might also look back at my post on \”The Economics of Noncognitive Skills\” (October 14, 2016).

Erik Brynjolfsson and Tom M. Mitchell serves as co-chairs of a \”Committee on Information Technology, Automation, and the U.S. Workforce,\” which produced the report \”Information Technology and the U.S. Workforce: Where Are We and Where Do We Go from Here?\”  (March 2017). The report offers a nice overview of the extremely widespread adoption and application of information technology across the economy (which I\’ll skip over here) as well as discussion of the effects of information technology on productivity, employment, and inequality. Here, I\’ll just pass along a few comments on these themes. The emphasis of the report is on summarizing the various views and providing links to research, rather than on trying to draw hard bottom lines.

Technology isn\’t Destiny

\”[E]conomic and societal changes occasioned by technological developments are shaped, not just by the availability of new technologies and their features, but also by ideologies, power structures, and human aspirations and agendas. Technologies are not exogenous forces that roll over societies like tsunamis with predetermined results. Rather, our skills, organizations, institutions, and values shape how we develop technologies and how we deploy them once created, along with their final impact.\”

Productivity Measures Output/Inputs, not Technological Progress or Welfare

\”A related, but more fundamental, issue is that productivity is neither a measure of technological progress nor welfare. Productivity is based on gross domestic product (GDP), which is in turn a measure of production or output. However, technological progress can increase welfare without increasing output. For instance, if Wikipedia replaces a paper encyclopedia or a free GPS mapping app replaces a stand-alone GPS device, then consumers can be better off even if output is stagnant or declining.\”

[In passing, I\’ll note that the Spring 2017 issue of the Journal of Economic Perspectives, where I toil in the fields as Managing Editor, has a three-paper symposium bearing on the issue of how or how much the measures of economic growth and productivity are biased by the arrival of new digital technologies. The three papers are \”Underestimating the Real Growth of GDP, Personal Income, and Productivity,\” by Martin Feldstein; \”Challenges to Mismeasurement Explanations for the US Productivity Slowdown,\” by Chad Syverson; and \”How Government Statistics Adjust for Potential Biases from Quality Change and New Goods in an Age of Digital Technologies: A View from the Trenches,\” by Erica L. Groshen, Brian C. Moyer, Ana M. Aizcorbe, Ralph Bradley and David M. Friedman.]

Information Technology is Shifting Employment with Occupational Categories

\”There have also been substantial shifts in employment in various occupational categories. For instance, the employment rate in clerical and sales jobs has fallen sharply, while employment in professional jobs has grown, as shown in Figure 3.1.\”

Technology Certainly Makes Some Jobs Obsolete, But Despite Centuries of Dire Predictions, It Has Not Led to Collapsing Demand for Labor

\”Predictions that new technologies will make workers largely or almost entirely redundant are as old as technological change itself. Although the story might be apocryphal, the famous Roman historian Pliny the Elder recounts how the Roman Emperor Tiberius killed an inventor who had supposedly invented unbreakable glass for fear of what this would do to the glassmaking trade. Queen Elizabeth I similarly refused to grant William Lee a patent for his mechanical knitting machine, arguing, “Consider thou what the invention could do to my poor subjects.” … 

\”However, predictions of widespread, technologically induced unemployment have not come to pass, at least so far. Technological changes over the last 200 years (and presumably many of those that came before) stimulated demand, created new markets, and fueled wage growth with few adverse consequences for aggregate employment. To be sure, technologies did and will continue to decimate particular occupations. As the Luddites feared, artisans lost their jobs in spinning and then weaving
as new technologies automated tasks they had previously performed. Similarly, the replacement of horses by automobiles eliminated the need for blacksmiths. But as these jobs disappeared, new ones sprang up to operate, manage, and service the new technologies. For instance, in the late 1800s, the replacement of the stagecoach by the railroad went hand in hand with the creation of new work for managers, engineers, machinists, repairmen, and conductors. Simultaneously, there was a boom in a range of new service occupations, from teaching to entertainment to sales. Nonetheless, simultaneous automation of a broader range of tasks could create unemployment or perhaps reduce aggregate levels of employment for an extended period of time.\”

Technology Contributes to Wage Inequality, but How Much is Uncertain

\”There is a debate in the research literature, and indeed, among committee members, about how much of the increase in inequality should be attributed to technology. There are three prominent narratives implicating technological change as a force toward greater inequality over the last several decades. First, many new technologies have replaced labor-intensive, routine, and physical tasks and expanded demand for labor in jobs that require social skills, numeracy, abstract thinking, and flexibility. This shift is often said to be responsible for higher returns to a college education and the widening income gap between skilled and less skilled workers. Second, as labor-intensive tasks are automated, the share of income going to capital relative to labor can increase, which may also help to explain the falling share of labor in overall GDP … Third, improvements in communication technologies have contributed to what has been termed the “superstar phenomenon” whereby the most successful performers in any occupation can now command a larger share of the global market. This in part reflects their improved ability to sell to not only customers in local markets, but also with greater ease to those in regional, national, and even global markets as improved communications technologies reduce the costs of reaching a broader audience. … 

\”It bears repeating that this discussion of technology and inequality should not be read to imply that all aspects of inequality and its recent increase in much of the Western world can simply be attributed to technological change: one must also consider the role played by the demise of unions, concessions on wages and job structures, the offshoring of work to places with lower wage rates, tax policy, and the increasing contribution played by financial investments in the accumulation of wealth. Indeed, increasing inequality in the United States has a political dimension, a phenomenon that is, of course, not new.\”

Technology is Altering the Nature of Work and Career Relationships

\”IT is enabling new work relationships, including a new form of on-demand employment. Although current digital platforms for on-demand work directly involve less than 1 percent of the workforce, they display significant growth potential. Many employers are increasingly viewing their relationship with employees as a short-term commitment rather than a lifelong investment. As Manpower Group CEO Jonas Prising recently put it, `Employers have gone from being builders of talent to consumers of work.\’\”