Month: July 2018

There\’s an saying along these general lines \”If you’re not a liberal when you’re 25, you have no heart. If you’re not a conservative by the time you’re 35, you have no brain.\” Who said it? One blessing of the web is that I can fiddle around with such questions without needing to spend three days in the library.

\”In a conversation between Dr. Ewen and the President, the former said one of his sons was an aristocrat, the other a democrat. The President asked if it was not the youngest who was the democrat. Yes, said Ewen. Well, said the President, a boy of 15 who is not a democrat is good for nothing, and he is no better who is a democrat at 20. Ewen told Hurt, and Hurt told me.\”

\”Every human—not excepting scientists—bears the whole stamp of the human condition. This includes evolved neural programs specialized for navigating the world of coalitions—teams, not groups.  … These programs enable us and induce us to form, maintain, join, support, recognize, defend, defect from, factionalize, exploit, resist, subordinate, distrust, dislike, oppose, and attack coalitions. …

\”Why do we see the world this way? Most species do not and cannot. … Among elephant seals, for example, an alpha can reproductively exclude other males, even though beta and gamma are physically capable of beating alpha—if only they could cognitively coordinate. The fitness payoff is enormous for solving the thorny array of cognitive and motivational computational problems inherent in acting in groups: Two can beat one, three can beat two, and so on, propelling an arms race of numbers, effective mobilization, coordination, and cohesion.

\”Ancestrally, evolving the neural code to crack these problems supercharged the ability to successfully compete for access to reproductively limiting resources. Fatefully, we are descended solely from those better equipped with coalitional instincts. In this new world, power shifted from solitary alphas to the effectively coordinated down-alphabet, giving rise to a new, larger landscape of political threat and opportunity: rival groups or factions expanding at your expense or shrinking as a result of your dominance.

\”And so a daunting new augmented reality was neurally kindled, overlying the older individual one. It is important to realize that this reality is constructed by and runs on our coalitional programs and has no independent existence. You are a member of a coalition only if someone (such as you) interprets you as being one, and you are not if no one does. We project coalitions onto everything, even where they have no place, such as in science. We are identity-crazed.

\”The primary function that drove the evolution of coalitions is the amplification of the power of its members in conflicts with non-members. This function explains a number of otherwise puzzling phenomena. For example, ancestrally, if you had no coalition you were nakedly at the mercy of everyone else, so the instinct to belong to a coalition has urgency, preexisting and superseding any policy-driven basis for membership. This is why group beliefs are free to be so weird. Since coalitional programs evolved to promote the self-interest of the coalition’s membership (in dominance, status, legitimacy, resources, moral force, etc.), even coalitions whose organizing ideology originates (ostensibly) to promote human welfare often slide into the most extreme forms of oppression, in complete contradiction to the putative values of the group. … 

\”Moreover, to earn membership in a group you must send signals that clearly indicate that you differentially support it, compared to rival groups. Hence, optimal weighting of beliefs and communications in the individual mind will make it feel good to think and express content conforming to and flattering to one’s group’s shared beliefs and to attack and misrepresent rival groups. The more biased away from neutral truth, the better the communication functions to affirm coalitional identity, generating polarization in excess of actual policy disagreements. Communications of practical and functional truths are generally useless as differential signals, because any honest person might say them regardless of coalitional loyalty. In contrast, unusual, exaggerated beliefs—such as supernatural beliefs (e.g., god is three persons but also one person), alarmism, conspiracies, or hyperbolic comparisons—are unlikely to be said except as expressive of identity, because there is no external reality to motivate nonmembers to speak absurdities.

\”This raises a problem for scientists: Coalition-mindedness makes everyone, including scientists, far stupider in coalitional collectivities than as individuals. Paradoxically, a political party united by supernatural beliefs can revise its beliefs about economics or climate without revisers being bad coalition members. But people whose coalitional membership is constituted by their shared adherence to “rational,” scientific propositions have a problem when—as is generally the case—new information arises which requires belief revision. To question or disagree with coalitional precepts, even for rational reasons, makes one a bad and immoral coalition member—at risk of losing job offers, one\’s friends, and one\’s cherished group identity. This freezes belief revision.

\”Forming coalitions around scientific or factual questions is disastrous, because it pits our urge for scientific truth-seeking against the nearly insuperable human appetite to be a good coalition member. \”

The lesson I draw here is although we all feel a strong need to join groups, we do have some degree of choice and agency over what groups we end up joining. Even within larger groups, like a certain religion or political party, there will be smaller groups with which one can have a primary affiliation. It may be wise to give an outlet to our coalitional nature by joining several different groups, or by pushing oneself to occasionally phase out one membership and join another.

In addition, we all feel a need to do something a little whacky and extreme to show our group affiliation, but again, we have some degree of choice and agency over what actions and messages define our group. Wearing the colors of a professional sports team, for example, is a different kind of whackiness than sending vitriolic social media  messages. Humans want to join coalitional groups, but we can at least consider whether the way a group expresses solidarity is a good fit with who we want to be.

Making predictions is hard, especially about the future. It\’s a comment that seems to have been attributed to everyone from Nostradamus to Niels Bohr to Yogi Berra. But it\’s deeply true. Most of us have a tendency to make statements about the future with a high level of self-belief, avoid later reconsidering how wrong we were, and then make more statements.

Here\’s a nice vivid example from back in 2001. The Bush administration has just taken office, and a Department of Defense Linville Wells at the US Department of Defense was reflecting on the then-forthcoming \”Quadrennial Defense Review.\” He wanted offer a pungent reminder that the entire exercise of looking ahead even just 10 years has often been profoundly incorrect. Thus, Wells wrote this memo (dated April 12, 2001):

• If you had been a security policy-maker in the world\’s greatest power in 1900, you would have been a Brit, looking warily at your age-old enemy, France. 
• By 1910, you would be allied with France and your enemy would be Germany. 
• By 1920, World War I would have been fought and won, and you\’d be engaged in a naval arms race with your erstwhile allies, the U.S. and Japan. 
• By 1930, naval arms limitation treaties were in effect, the Great Depression was underway, and the defense planning standard said \”no war for ten years.\” 
• Nine years later World War II had begun. 
• By 1950, Britain no longer was the world\’s greatest power, the Atomic Age had dawned, and a \”police action\” was underway in Korea. 
• Ten years later the political focus was on the \”missile gap,\” the strategic paradigm was shifting from massive retaliation to flexible response, and few people had heard of Vietnam.
• By 1970, the peak of our involvement in Vietnam had come and gone, we were beginning détente with the Soviets, and we were anointing the Shah as our protégé in the Gulf region.
• By 1980, the Soviets were in Afghanistan, Iran was in the throes of revolution, there was talk of our \”hollow forces\” and a \”window of vulnerability,\” and the U.S. was the greatest creditor nation the world had ever seen. 
• By 1990, the Soviet Union was within a year of dissolution, American forces in the Desert were on the verge of showing they were anything but hollow, the U.S. had become the greatest debtor nation the world had ever known, and almost no one had heard of the internet. 
• Ten years later, Warsaw was the capital of a NATO nation, asymmetric threats transcended geography, and the parallel revolutions of information, biotechnology, robotics, nanotechnology, and high density energy sources foreshadowed changes almost beyond forecasting. 
• All of which is to say that I\’m not sure what 2010 will look like, but I\’m sure that it will be very little like we expect, so we should plan accordingly.

One can make a reasonable argument that the concept of an economy and the study of economics begins with the idea of specialization, in the sense that those who function within an economy specialize in one kind of production, but then trade with others to consume a broader array of good. Along these lines, the first chapter of Adam Smith\’s 1776 Wealth of Nations is titled, \”On the Division of Labor.\” But in the push for specialization, there can be a danger of neglecting the virtues of generalists. Even when it comes to assembly lines, specialization of tasks can be pushed so far that it becomes unproductive (as Smith recognized). In a broad array of jobs, including managers, journalists, legislators and politicians, and even editors of academic journals, there is a need for generalists who can synthesize and put in context the work of a range of specialists.

The need for generalists is not at all new, of course. Here\’s a commentary from 80 years on \”The Need for Generalists\” from AG Black, who was Chief of the Bureau of Agricultural Economics at the US Department of Agriculture, \” published in the Journal of Farm Economics (November 1936, 18:4, pp. 657-661, and available vis JSTOR). Black is writing in particular about specialization within what is already a specialty of agricultural economics, but his point applies more broadly.

\”The past generation, like several generations before it, has indeed been one of greater and greater specialization. This has resulted in great advances in agricultural economics. Our specialists have developed new technics of analysis, they have discovered new relationships, they have been able to give close attention to important facts and factors that might otherwise have escaped attention and by such escape might have led to wrong conclusions. Without this specialized attention our discipline in agricultural economics could not have attained the position it has reached today.

\”This advance has not been attained without cost. The price has been the loss of minds, or the neglect to develop minds, trained to cope with the complex problems of today in the comprehensive, overall manner called for by such problems. Our specialists are splendidly equipped to solve a problem concerning the price of wheat, or of corn, or of cotton, or a technical question in cooperative marketing, farm management, taxation or international trade. But the more important problems almost never present themselves in those narrow terms; rather they may involve elements of all the above and perhaps several more. …

\”Increased specialization itself tends to raise barriers between fields. It tends to create a system of professional jealousies that is not conducive to the development of generalists. The specialist who burrows deeper and deeper into a narrower and narrower hole becomes convinced that no one who has been sapping in a neighboring tunnel can possibly know as much about the peculiar twists and turns of his burrow as he, himself. And he is right. He knows that he can readily confound and confuse a neighboring specialist if the latter strays from his own confines, and what is more, he will. One of the greatest joys of the specialist is to make an associate appear infantile and ridiculous on the occasions when the latter appears to be getting out of his field.

\”The specialist stakes out his claim and guards it as jealously as ever did a prospector of the \’40s, and woe to the unwary trespasser. As the specialist knows how he looks upon intruders, he knows how he would be treated if he had the temerity to wander outside his main field. Consequently he is usually quite willing to leave outside fields to other specialists.

\”The development of the whole field takes on a honeycomb appearance with series upon series of well-marked and almost wholly isolated cells. These cell walls need to be broken down. There is need of men who can correlate and coordinate the specialized knowledge in the separate cells–men who can bring to bear on the larger problems the findings of the different specialists and who have sufficient perspective and sense of proportion to apply just the correct shade of emphasis to the contribution of each particular specialist. …

\”Our whole organization has developed on the assumption that the generalizing function is not important, that it does not require quite the ability and training of the specialist, that it can be satisfactorily done by almost anyone and that certainly there is nothing about it that demands the attention of really first class men. If generalizing be done at all, it can safely be committed to the specialist who can play with it as relaxation from the really serious and important demands of his specialty, or to the administrator who can give it all of the attention it requires between telephone calls and committee meetings.

\”All of this, I suppose, leads to the conclusion that in agricultural economics we need another specialist, that is a \”specialist\” who is a \”generalist.\” We need to make a place for the trained economist of highest ability who will be free from administrative demands as well as free from the tyranny of specialization, who will have the job of keeping abreast of the results of the various specialists and who can spend a good deal of time in analyzing findings having a bearing upon the ultimate solution of these same problems. … In other words, students need training in analysis and in synthesis. Today the ability to synthesize facts, research results and partial solutions into a well rounded whole, is too infrequently available.\”

One of the many political cliches that makes me die a little bit inside is when someone claims that all we need to address a certain problem (health care, poverty, transportation, the Middle East, whatever) is to bring together a group of experts who will provide the common-sense solution that we have all been ignoring. But while bringing together a group of specialist experts can provide a great deal of information and insight, they are often not especially good at melding their specific insights into a general policy.

Homage: I ran across a mention of this article at Carola Binder\’s always-useful \”Quantitative Ease\” website  last summer, and left myself a note to track it down. But given my time constraints and organizational skills, it took awhile for me to do so.

There\’s an old rueful line from firms that advertise: \”We know that half of all we spend on advertising is wasted, but we don\’t know which half.\” It\’s not clear who originally coined the phrase. But we do know that the effects of advertising have changed dramatically in a digital age. Half of all advertising spending may still be wasted, but now it\’s for a very different reason.

I was raised with the folklore that John Wanamaker, founder of the eponymous department stores, was the originator of the phrase at hand. But the attribution gets pretty shaky, pretty fast. David Ogilvy, the head of the famous Ogilvy & Mather advertising agency, wrote in his 1963 book Confessions of an Advertising Man (pp. 86-87): \”As Lord Leverhulme (and John Wanamaker after  him) complained, `Half the money I spend on advertising is wasted, and the trouble is I don\’t know which half.\”

So how about William Lever, Lord Leverhulme, who built a fortune in the soap business (with Sunlight Soap, and eventually Unilever)? Career advertising executive Jeremy Bullmore has looked into it, and wrote in the 2013 annual report of the British advertising and public relations firm WPP:

\”There are at least a dozen minor variations of this sentiment that are confidently quoted and variously attributed but they all have in common the words ‘advertising’, ‘half’ and ‘waste’. Google the line and you’ll get about nine million results. … As it happens, there’s little hard evidence that either William Lever or John Wanamaker (or indeed Ford or Penney) ever made such a remark. Certainly, neither the Wanamaker nor the Unilever archives contains any such reference. Yet for a hundred years or so, with no accredited source and no data to support it, this piece of folklore has survived and prospered.\” 

Bullmore makes some compelling points. One is that even 100 years ago, it was widely believed tha advertising could be usefully shaped and targeted. He writes:

\”Retail advertising in the days of John Wanamaker was mostly placed in local newspapers and was mainly used to shift specific stock. An ad for neckties read, ‘They’re not as good as they look, but they’re good enough. 25 cents.’ The neckties sold out by closing time and so weren’t advertised again. Waste, zero. Experiment was commonplace. Every element of an advertisement – size, headline, position in paper – was tested for efficacy and discarded if found wanting. Waste, if not eliminated, was ruthlessly hounded.

\”Claude Hopkins published Scientific Advertising in 1923. In it, he writes, “Advertising, once a gamble, has… become… one of the safest of business ventures. Certainly no other enterprise with comparable possibilities need involve so little risk.” Even allowing for adman’s exuberance, it strongly suggests that, within Wanamaker’s lifetime, there were very few advertisers who would have agreed that half their advertising money was wasted.\”

Further, Bullmore points out that people are more comfortable buying certain products because \”everyone knows\” about them, and \”everyone knows\” because even those who don\’t purchase the product have seen the ads.

\”A common attribute of all successful, mass-market, repeat-purchase consumer brands is a kind of fame. And the kind of fame they enjoy is not targeted, circumscribed fame but a curiously indiscriminate fame that transcends its particular market sector. Coca-Cola is not just a famous soft drink. Dove is not just a famous soap. Ford is not just a famous car manufacturer. In all these cases, their fame depends on their being known to just about everyone in the world: even if they neither buy nor use. Show-biz publicists have understood this for ever. When The Beatles invaded America in 1964, their manager Brian Epstein didn’t arrange a series of targeted interviews in fan magazines; he brokered three appearances on the Ed Sullivan Show with an audience for each estimated at 70 million. Far fewer than half of that 70 million will have subsequently bought a Beatles record or a Beatles ticket; but it seems unlikely that Epstein thought this extended exposure in any way wasted.\”

And of course, if large amounts of advertising are literally wasted, it seems as we should be able to observe a substantial number of companies who cut their advertising budget in half and suffered no measurable decline in sales. (In fact, if  half of advertising is always wasted, shouldn\’t the firm then keep cutting the advertising budget by half, and half again, and half again, and so down to zero? Seems as if there must be a flaw in this logic!)

Of course, one of the major changes in advertising during the last decade or two is that print advertising has plummeted, while digital advertising has soared. More generally, digital technology has made it much more straightforward to create systematic variations in the quantity and qualities of advertising– and to track the results. Bullmore writes: \”And given modern measurements and the growth of digital channels, it’s easier than ever for advertising to be held accountable; to be seen to be more investment than cost.\”

But Bullmore is probably too optimistic here about how easy it is to hold advertising accountable, for a couple of reasons.

One problem is that the idea of targeting specific audiences for digital advertising is a lot more complicated in practice than it may seem at first. Judy Unger Franks of Medill School of Journalism, Media, Integrated Market Communications at Northwestern University explained the issues in a short essay late last summer: She wrote:

\”Programmatic Advertising enables marketers to make advertising investments to select individuals in a media audience as opposed to having to buy the entire audience. Advertisers use a wealth of Big Data to learn about each audience member to then determine whether that audience member should be served with an advertisement and at what price. This all happens in near real-time and advertisers can therefore make near real-time adjustments to their approach to optimize the return-on-investment of its advertising expenditures.

\”In theory, Programmatic Advertising should solve the issue of waste. However, in our attempt to eliminate waste from the advertising value chain, we may have made things worse. We have unleashed a dark side to Programmatic Advertising that comes at a significant cost. Now, we know exactly which half of the money spent on advertising is wasted: it’s the half that marketers must now spend on third parties who have inserted themselves into the Programmatic Advertising ecosystem just to keep our investments clean. … 

\”How bad is it? How much money are advertisers spending on this murky supply chain? The IAB (Interactive Advertising Bureau) answered this for us when they released their White Paper, “The Programmatic Supply Chain: Deconstructing the Anatomy of a Programmatic CPM” in March of 2016. The IAB identified ten different value layers in the Programmatic ecosystem. I believe they are being overly generous by calling each a “value” layer. When you need an ad blocking service to avoid buying questionable content and a separate verification service to make sure that the ad was viewable by a human, how is this valuable? When you add up all the costs associated with the ten different layers, they account for 55% of the cpm (cost-per-thousand) that an advertiser pays for a programmatic ad. This means that for every dollar an advertiser spends in Programmatic Advertising over half (55%) of that dollar never reaches the publisher. It falls into the hands of all the third parties that are required to feed the beast that is the overly complex Programmatic Advertising ecosystem. We now know which half of an advertising investment is wasted. It’s wasted on infrastructure to prop up all those opportunities to buy individual audiences across the entire Programmatic Advertising supply chain.\”

In other words, by the time an advertiser has spent the money to do the targeting, and to make sure that the mechanisms to do the targeting work, and to follow up on the targeting, the costs can be so high that the reason for targeting in the first place is in danger of being lost.

The other interesting problem is that academic studies that have tried to measure the returns to targeted online advertising have run into severe problems. For a discussion, see \”The Unfavorable Economics of Measuring the Returns to Advertising,\” by Randall A. Lewis and Justin M. Rao

(Quarterly Journal of Economics, 130:4, November 2015, pp. 1941–1973, available here). They describe the old \”half of what I spend in advertising is wasted\” slogan in these terms (citations omitted):

\”In the United States, firms annually spend about $500 per person on advertising. To break even, this expenditure implies that the universe of advertisers needs to casually affect $1,500–2,200 in annual sales per person, or about $3,500–5,500 per household. A question that has remained open over the years is whether advertising affects purchasing behavior to the degree implied by prevailing advertising prices and firms’ gross margins …\”

The authors look at 25 studies of digital advertising. They find that the variations in what people buy and how much they spend are very large. Thus, it\’s theoretically possible that if adverting causes even a small number of people to \”tip\” from spending only a little on a product to being big spender on a product, the advertising can pay off for the advertiser. But in statistical sense, given that people vary so much in their spending on products and change so much anyway,  it\’s really hard to disentangle the effects of advertising from the changes in buying patterns that happen anyway. As the authors write: \”[W]e are making the admittedly strong claim that most advertisers do not, and indeed some cannot, know the effectiveness of their advertising spend …\”

Thus, the economics of spending on advertising remain largely unresolved, even in the digital age. Those interested in more on the economics of advertising might want to check my post on \”The Case For and Against Advertising\” (November 15, 2012).

Randomization is one of the most persuasive techniques for determining cause and effect. Half of a certain group get a treatment; half don\’t. Compare. If the groups were truly chosen at random, and the treatment was truly the only difference between them, and the differences in outcomes are meaningful and the size of the samples are also large enough for drawing statistically meaningful conclusions, then the differences can tell you something about causes.

Economists have surged into randomized experimental work in the last few decades. From the 1970s, up into the 1990s, such work was often focused on social policies, with experiments on different kinds of health insurance, job training and job search, changes in welfare rules, early childhood education, and others. More recently, such work has become very prominent in the development economics literature, as well as on a variety of focused economics topics like how incentive pay affects work or how charitable contributions could be increased. Running experiments is now part of the common tool-kit (for a small taste, see here, here, here, and the three-paper symposium in the Fall 2017 issue of the Journal of Economic Perspectives on \”From Experiments to Economic Policy\”).

Thus, economists and other social scientists may find it useful to keep some historical examples of randomization near at hand. Julian C. Jamison provides a trove of such examples in \”The Entry of Randomized Assignment into the Social Sciences\”  (World Bank Policy Research Working Paper 8062, May 2017).

Jamison has a run-through of the classic examples of randomization over the centuries, which were often in a medical context. For example, he quotes the correspondence between poet/writers Petrarch and  Boccaccio in 1364, in which Petrarch wrote:

\”I solemnly affirm and believe, if a hundred or a thousand men of the same age, same temperament and habits, together with the same surroundings, were attacked at the same time by the same disease, that if one half followed the prescriptions of the doctors of the variety of those practicing at the present day, and that the other half took no medicine but relied on Nature’s instincts, I have no doubt as to which half would escape.\” 

Or Jan Baptist van Helmont, a doctor writing in the first half of the 1600s, proposed that the two \”cures\” of the day–bloodletting vs. induced vomiting/defecation–be tested in this way:

\”Let us take out of the Hospitals, out of the Camps, or from elsewhere, 200 or 500 poor People, that have Fevers, Pleurisies, etc. Let us divide them in halfes, let us cast lots, that one half of them may fall to my share, and the other to yours; I will cure them without bloodletting… we shall see how many Funerals both of us shall have.\”

There are cases from the 1600s, 1700s, and and 1800s of randomization as a way of testing for the effectiveness of  treatments for scurvy, or smallpox, salt-based homeopathic treatments. Perhaps one of the best-known experiments was done by Louis Pasteur in 1881 to test his vaccine for sheep anthrax. Jamison writes:

\”He was attempting to publicly prove that he had developed an animal anthrax vaccine (which may not have been his to begin with), so he asked for 60 sheep and split them into three groups: 10 would be left entirely alone; 25 would be given his vaccine and then exposed to a deadly strain of the disease; and 25 would be untreated but also exposed to the virus …. [A]ll of the exposed but untreated sheep died, while all of the vaccinated sheep survived healthily.\”

There are LOTS of examples. But in Jamison\’s telling, the earliest example of randomization in an experiment within a subject conventionally thought of as economics was actually done by two non-economists working on game theory, psychologist Richard Atkinson and polymath Patrick Suppes, in work published in 1957:

\”Atkinson and Suppes (1957), also not economists by training, analyzed different learning models in two-person zero-sum games, and they explicitly “randomly assigned” pairs of subjects into one of three different treatment groups. This is the earliest instance of random assignment in experimental economics, for purposes of comparing treatments, that has been found to date.\”

As to broader social experiments about the effects of policy interventions, the first one goes back to the 1940s:

\”The first clearly and individually randomized social experiment was the Cambridge-Somerville youth study. This was devised by Richard Clarke Cabot, a physician and pioneer in advancing the field of social work. Running from 1942-45, the study randomized approximately 500 young boys who were at risk for delinquency into either a control group or a treatment group, the latter receiving counseling, medical treatment, and tutoring. Results (Powers and Witmer 1951) were highly disappointing, with no differences reported.\” 

Back in high school, we had to design and carry out our own experiment in a psychology class. I wrote up the same message (a request for some saccharine and meaningless information) on two sets of postcards. One of the sets of postcards was typed; the other was handwritten. I chose the first 60 households in the local phone directory, and sent the postcards out at random. My working hypothesis was that the typewritten notes would get a higher response (perhaps because they would look more \”professional,\” but actually the handwritten notes got a much higher response (probably because they reeked of high school student). Even at the time, it felt like a silly little experiment to me. But the result felt powerful, nonetheless.

I\’m taking some family vacation the next 10 days or so. The lake country of northern Minnesota calls. My wife says that I get a distinctively blissful expression when I\’m sitting in the back of a canoe with a paddle in my hand. While I\’m gone, I\’ve prescheduled a string of posts that look at various things I\’ve been reading or have run across in the last few months that are at least loosely connected to my usual themes of economics and academia.

It’s not unusual to hear predictions that in the future, we will all have opportunities to run our own companies, or that jobs will become a series of freelance contracts. Here’s a representative comment from business school professor Arun Sundararajan (“The Future of Work,” Finance & Development, June 2017, p. 7-11):

Harald Uhlig delivered a talk on \”Money and Banking: Some DSGE Challenges\” (video here, slides here) at the Nobel Symposium on Money and Banking recently held in Stockholm. He introduces the \”Chicken Paper Conundrum,\” which he attributes to Ed Prescott.

 I\’ve definitely read academic papers, as well as listed to policy discussions, which follow this pattern.

Homage: I ran across this in the middle of two long blog posts by John Cochrane at his Grumpy Economist blog (here and here), which summarize and give links to many papers at this conference given by leading macroeconomists. Many have links to video, slides, and sometimes full papers. If you are interested in topics on the cutting edge of macroeocnomics, it\’s well worth your time.

The Tennessee Voluntary Pre-K Program offers support for families with low-income levels. In 2008-2009, the program only had sufficient funding to cover 42% of applicants. Admission to the program was thus decided by a lottery. This selection procedure makes the eyes of academic researchers light up, because it means that there was random selection of who was in the program (the \”treatment\” group) and those who were not (the \”control\” group). As these students continue into Tennessee public schools, there is follow-up information on how these two groups performed. The result was that that students in the pre-K program has a short-term boost in performance, which quickly faded. The abstract of the study says:

\”Low-income children (N = 2990) applying to oversubscribed programs were randomly assigned to receive offers of admission or remain on a waiting list. Data from pre-k through 3rd grade were obtained from state education records; additional data were collected for a subset of children with parental consent (N = 1076). At the end of pre-k, pre-k participants in the consented subsample performed better than control children on a battery of achievement tests, with non-native English speakers and children scoring lowest at base-line showing the greatest gains. During the kindergarten year and thereafter, the control children caught up with the pre-k participants on those tests and generally surpassed them. Similar results appeared on the 3rd grade state achievement tests for the full randomized sample – pre-k participants did not perform as well as the control children. Teacher ratings of classroom behavior did not favor either group overall, though some negative treatment effects were seen in 1st and 2nd grade.\”

The previous major randomized control trial study of an early childhood education program was done on the federal Head start program. I discussed it here. Lipsey, Farran and Durkin summarize the finding in this way:

\”This study [of Head Start] began in 2002 with a national sample of 5000 children who applied to 84 programs expected to have more applicants than spaces. Children were randomly selected for offers of admission with those not selected providing the control group.The 4-year-old children admitted to Head Start made greater gains across the pre-k year than nonparticipating children on measures of language and literacy, although not on math. However, by the  end of kindergarten the control children had caught up on most achievement outcomes; subsequent positive effects for Head Start participants were found on only one achievement measure at the end of 1st grade and another at the end of 3rd grade. There were no statistically significant effects on social–emotional measures at the end of the pre-k or kindergarten years. A few positive effects appeared in parent reports at the end of the 1st and 3rd grade years, but teacher and child reports in those years showed either null or negative effects.\”

Of course, the fact that the two major studies of publicly provided pre-K find near-zero results by third grade doesn\’t prove that such programs never or can\’t work. There are many studies of early childhood education programs. The results of the Tennessee and Head Start studies don\’t rule out the possibility of benefits from narrower programs specifically targeted at children with certain needs. Also, some studies with longer-term follow-up found that although measures of educational performance didn\’t move much. pre-K programs had longer-term effects on outcomes like high school graduation rates.

But the case for believing that publicly provided  pre-K programs will boost long-term educational outcomes for the disadvantaged is not very strong. If positive results were clear-cut and of meaningful size, it seems as if they should have shown up in these major studies.

Some researchers in this area have suggested that interventions earlier than pre-K might be needed to close achievement gaps. For example, some evidence suggests that the black-white educational achievement gap is apparent by age 2. It may be, although the evidence on this point isn\’t clear, that some of the funding now being spent on pre-K programs would have a bigger payoff if spent on home visits to the parents of very young children. Greater attention to the health status of pregnant women–including both personal health and exposure to environmental risks–might have a substantial payoff for the eventual educational performance of their children, too.

The cause seemed worthy, and the policy mild. Militia groups in the Democratic Republic of the Congo (DRC) were taxing and extorting revenue from those who mined like tin, tungsten, and tantalum. Thus, Section 1502 of the Dodd-Frank Act of 2010 required companies to disclose the source of their purchases of such minerals. The hope was to reduce funding for the militias, and thus to benefit people in the area. Human rights advocacy groups supported the idea. The Good Intentions Paving Company was up and running.

But tradeoffs are no respecters of good intentions. Dominic Parker describes some research on the tradeoffs that occurred in  \”Conflict Minerals or Conflict Policies? New research on the unintended consequences of conflict-mineral regulation\” (PERC Reports, Summer 2018, 37:1, pp. 36-40). Parker writes:

\”First, Section 1502 initially caused a widespread, de facto boycott on minerals from the eastern DRC. Rather than engaging in costly due diligence to identify the sources of minerals—and risking being considered a supporter of rebel violence—some U.S. companies simply stopped buying minerals from the region. This de facto boycott had the intended effect of reducing funding to militias, but its unintended effect was to undercut families who depended on mining for income and access to health care. The decreases in mineral production rocked an artisanal mining sector that had supported an estimated 785,000 miners prior to Dodd-Frank, with spillovers from their economic activity thought to affect millions.

\”Second, the legislation changed the relative value of controlling certain mining areas from the perspective of militias, who changed their tactics accordingly. Before the boycott, the militias could maximize revenue by taxing tin, tungsten, and tantalum at or near mining sites. They therefore had an interest in keeping mining areas productive and relatively safe for miners. After the legislation, the militias sought to make up for reduced revenue in other ways. According to the evidence, they started to loot civilians who were not necessarily involved in mining. They also started to fight for control over other commodities, including gold, which was in effect exempt from the regulation.\”

One result of the economic losses in the area was a sharp rise in infant mortality rates: \”The combined evidence suggests that Dodd-Frank increased the probability of infant deaths (that is, babies who died before reaching their first birthday) from 2010 to 2013 for children who lived part of or all of their first year in villages targeted by the legislation and mining ban. The most conservative estimate is that the legislation increased infant mortality from a baseline average of 60 deaths per 1,000 births to 146 deaths per 1,000 births over this period—a 143 percent increase.\”

The level of violent conflict affecting civilians actually seemed to rise, rather that fall: \”At the end of 2010, after the passage of Dodd-Frank, looting in the territories targeted by the mining policies became more common and remained that way through much of 2011 and 2012, when our study period ended. … The incidence of violence against civilians also increased in the policy regions after the legislation …\”

One economic insight here is the \”stationary bandit\” theory that when a bandit remains in one location, there are incentives for the bandit to keep local workers and companies safe and productive.

The political insights are fuzzier. One can\’t rule out that if the Dodd-Frank provisions had been better thought-out or better targeted, maybe the effects would have been better, too. Or maybe this is a case where long-run benefits of these provisions will outweigh short-run costs. But it\’s also possible that an alternative strategy for bolstering the economy and human rights in the area might have worked better. And it\’s quite clear that those who supported this particular conflict mineral policy did not predict or acknowledge that their good intentions could have these adverse consequences.