Russia Growth Diagnostics: Conclusions

After a week of writing about the Russian economy, I put together the pieces of its growth diagnostics. The conclusion follows.


  1. Getting Started
  2. Introduction to Russia
  3. Finance
  4. Infrastructure and Human Capital
  5. Uncertainty
  6. Taxes and Laws
  7. Market Structure and Competition

The Hausmann–Rodrik–Velasco framework (HRV) that I use throughout the series is explained in the first post. The replication files are available on GitHub.


I picked Russia’s industrial policy as the top issue. Economists rightfully reach for their revolvers when they hear this. Local barons use “industrial policy” to justify protection for their industries. Usually it ends badly, even backed by good historical examples. The United States, Germany, and South Korea protected their “infant industries” at some point of time. But the isolated impact of protectionism is unclear in these cases. It may have any sign. Besides, protection for the 19th-century manufacturing sectors says a little about what a country should promote now.

So what should a country promote with industrial policies? In Russia, less protection for losers and more benefits for winners. This rule is hard to follow when the government appoints losers and winners. The market just supports those who get government protection. It must be the other way around! Government may support companies that do well in competitive, often international, markets. Usually, it’s not about handpicking specific firms, but about simple rules for entire sectors. A good industrial policy for Russia would imply less discretion in industrial policy making.

Since this series concerns only diagnostics, I’m not commenting on actions that can make sense in this case. However, I hope this series shows well that for upper-middle income countries, like Russia, the HRV framework must go much deeper because constraints become less obvious as economic complexity increases.

Appendix: What deserves attention

Industrial policy is important, but overall I took four issues from the previous posts in the series. The table below ranks each of them on a scale from 1 to 5 according to:


  • How large is the possible impact of changes in this constraint on economic growth?
  • How far is the current situation from the optimal one?


  • How many evidences are available (or potentially available) for managing changes in this direction?
  • Confidence in normative recommendations that economics can offer here
  • Clarity of recommendations and their quantitative substance
  • The “distortion potential” for stakeholders in cherry picking or changing recommendations in their favor


  • Are there stakeholders who lose from changes in this direction?
  • Do these stakeholders have policy making power?
  • Are there stakeholders who win and can support changes in policies?

This is my arbitrary scale, and you may have your own. Now back to the list. The four constraints belong to “Taxes and Laws” (formal taxes, formal regulations) and “Market Structure and Competition” (industrial organization, industrial policy):


(More here means more potential for growth. The scale is for ranking only and doesn’t reflect the size of the gap between constraints.)

Formal taxes. As mentioned in the post, Russia combines its own idiosyncratic taxes with the same taxes that disincentivize accumulation of human capital in developed countries. Changing this situation could be technically easy because taxes are specific and quantitatively transparent mechanisms. However, taxes are vulnerable to politics (partly because of their transparency) and changes here are likely to face much opposition.

Formal regulations. Regulations constrain growth through two channels. First, they are direct and often not justifiable costs that always end in prices. So the citizen pays for them. Second, regulations grant power to corrupt officials. Corruption discredits both good and bad regulations, with more negative consequences for law enforcement and state capacity. That’s a quite conventional simplification, and the key nontrivial question is how large the distortions are (see rough estimates in this post). As for confidence, the burden of proof for regulations must be on the regulator and lawmakers. This is an idealistic picture for any country, but the point here is that many proofs don’t fit well what economics already knows.

Industrial organization. I put de-facto competition above de-jure regulations because competitive firms actually find ways to optimize regulatory costs, minimize corruption, and somehow do this without breaking the law. I would exemplify this with multinationals, which are more productive than domestic firms even in bad environments. For the entire range of issues that arise here, see the previous post.

Industrial policy. Like regulations, the policy of keeping weak firms afloat is paid by citizens, including workers who suffer poor management and lower wages. This part of low-performing firms can’t live without subsidies of some sort, but these subsidies are a bad form of job security. The key policy problem is how to relocate capital and labor to the best firms without unemployment and loss of physical capital. It’s technically difficult and economic knowledge here is limited. Why did I mark it as the most feasible then? Certain cases could have many winners, including powerful decision makers, and this is more important than administrative complexities.

This doesn’t say how much exactly the Russian economy could get from solving problems in these areas. The impact depends on the changes in question. But the exercise in growth diagnostics just organizes many issues in a single framework, which should ideally direct attention to more specific issues.

Public Policies and Persistence of Institutions

A fabulous series of works on institutional persistence emerged in the 2000s. To name a few:

This series has several things in common. First, the common narrative says that very old decisions influence current economic performance. Melissa Dell finds a 25% decline in current consumption due to forced labor in the 16-century mines. Nathan Nunn quantifies the impact of slavery on current output per capita in Africa. Abhijit Banerjee and Lakshmi Iyer report a 15% increase in current crop yields in territories owned by cultivators in the 19th century, compared to the territories of then-landlords:

Banerjee and Iyer, “History, Institutions, and Economic Performance.”
Banerjee and Iyer, “History, Institutions, and Economic Performance.”

A passerby may say that, of course, slavery and ownership last — that’s our history. This position is so general that it’s always true. The authors did much more than that. They showed by how much history matters — and the numbers are serious.

One unintended consequence, though. These results reassure the pessimists in developing countries. The problem is, of course, that developing countries aren’t developing much. The countries have some economic growth — often induced by commodity prices and imported technologies — and few successful fundamental reforms. People out there rarely see changes and don’t ask for them, so the past matters because it actually equals the present.

Let’s see how economists can encourage these people.

In a sense, any persistent connection between the past and the present is a public policy failure. If a 18th century earthquake destroyed a bridge and the local community didn’t rebuild it since then, the earthquake naturally worsens the current village performance. This happens due to the earthquake and the (absent) mitigation policies.

The earthquake stands for any lasting factor of development. A lasting factor (earthquake) determines policies (endure the loss of the bridge) and these policies affect current outcomes (village output). This is the standard line in the literature. The lasting factor can be anything. Institutions just happened to be the group large enough to be statistically significant in small samples, which always constrain research in economic growth. This group is a big bunch of laws and rules, which wouldn’t manifest itself in regressions if taken separately.

What do we know about such lasting factors?

Well, sometimes they last. Of course, there’s a publication bias favoring historical persistence. Imagine, instead, the flow of publications enumerating historical factors that do not affect the present. A lot of boring reading, for sure. Instead, we have a few dozens of highly cited papers with robust positive results. These citations signal two things. First, authors brilliantly did their job. Second, few results of this sort exist. Perhaps, citations would be diluted if results could be tested in different settings. Just look at randomized trials, which are very important but authors basically no longer seek publishing there as they test same policies across countries.

Secondly, historical factors leave many questions. Are they resistant to public policies? Are they resistant to informed public policies? To exogenous policies, like international aid programs? To a different set of institutions?

These questions hint at the idea that some societies respond to challenges and, therefore, flourish. But for the other societies, the data always shows persistence. Especially to large exogenous shocks, which dominate the literature because they are nearly the only way to measure the impact.

I mean, all the papers I mentioned exploit a very strong “treatment”: A well-armed army of foreigners attack an indigenous population and establish particular rules. Why is it common in publications? Because such a situation is accompanied by a suitable identification strategy: invaders grab whatever comes first (that’s randomization) and divide previously homogeneous regions (that’s discontinuity). Still, these invasions are only one part of history.

So we need to know more about the economic significance of this sort of persistence. We may discover that persistence vanishes. For example, the conflict between relatively equal France and Germany in the Napoleonic Wars (1803−1815):

The Consequences of Radical Reform: The French Revolution
The Consequences of Radical Reform: The French Revolution

The treatment group includes the German territories occupied by the French. The French induced growth-enhancing reforms, so the treatment group grows faster:

The Consequences of Radical Reform: The French Revolution
The Consequences of Radical Reform: The French Revolution

The difference is becoming unimportant as both groups develop. The control group reaches the same level of reforms with a 10-year lag, but it does reach the same level. The gap in urbanization is also closing relative to the level of urbanization.

History matters until you find solutions to very specific problems. Returning to Melissa Dell’s 25% consumption gap in Peru, what would happen to this gap if Peru got richer? What would happen with persistence in growing India and Africa, featured in the other articles? The good question is, therefore, what can we do about this persistence?

Government Resistance to Human Capital

James Heckman has a great paper called “Policies to foster human capital“. Apart from excellent integration of economics into government policies, this paper relentlessly reminds the reader about the lifetime aspects of investments in human capital:

Heckman and Carneiro - 2003 - Human Capital Policy
Heckman and Carneiro – 2003 – Human Capital Policy

Heckman refers to the evidences that late investments do not pay off. Late learning costs money, including foregone earnings, but it only modestly increases wage rates and generates less human capital, since investments are made closer to retirement.

Heckman also criticizes the excessive attention to formal education, which is all about a few narrow cognitive abilities and in any case just one of many ways to acquire skills.

This paper was published in 2000. To count how many of its insights made it into government policies, I looked into the 2013 Economic Report of the President. This report includes a chapter on human capital.

The chapter discusses three things. First, labor inputs of women and immigrants. Second, rising debt and enrollment bias in college education. Third, educational opportunities for adults. So, formal education and adult learning?

Why does this influential publication promote the exact policies that Heckman criticized fifteen years ago? Alan Krueger — who edited the 2013 report — is a brilliant labor economist himself. The entire Council of Economic Advisors is well staffed. So it’s not about competence.

The problem seems to be in the complexity of the policies that Heckman proposes. When economists remind the Congress about student debt, they have better chances of being heard than economists who suggest targeted programs in preschool education. Student debt is something that even US presidents had. Preschool education? TL;DR.

But rephrasing Neil deGrasse Tyson, science is true whether you read it or not. The complex stuff still explains well why policies fail when consensus is reached.

For the United States, this complex stuff is about fine-tuning the system that works well. For the middle-income countries, on the other hand, ignorance is costlier, not least because these countries tend to aggravate mistakes with more government intervention. Policy makers in these countries often frame human capital accumulation as another industrialization. Like, if we could raise savings-investments to 50% of GDP, we can accumulate human capital in the same way. Obviously, it doesn’t work this way; and for BRICS, it’s an important challenge.

As for the least developed countries, the major innovators out there are international organizations, which recently got an open letter from Chris Blattman asking to “stop hurting” poor people with skill training programs. For the same reason: the programs don’t work as intended; even if being accumulated, this human capital solves no important problem.

“Stop hurting” is a good suggestion because it encourages policy makers to do less, which is the idea they like. The second part is more difficult: stop hurting and accept better policies. Some of the better policies look unconventional but remain as simple as training programs. Their main disadvantage is that they are not invented here, that is, in government. And before anything happens, someone has to market these policies as if they were government’s genuine invention.

Impact and Implementation of Evidence Based Policies

Chris Blattman noted that economists lack evidences on important policies. That’s true for foreign aid programs, which Chris mentioned. But defined broadly, policy making in poor countries can source evidences from elsewhere. NBER alone supplies 20 policy-relevant papers each week. And so does the World Bank, which recently studied its own economy:

About 49 percent of the World Bank’s policy reports … have the stated objective of informing the public debate or influencing the development community. … About 13 percent of policy reports were downloaded at least 250 times while more than 31 percent of policy reports are never downloaded. Almost 87 percent of policy reports were never cited.

In an ideal world, policy makers would read more and adjust their economies to the models we already know thanks to the decades of thorough research. This is not happening because policy makers are managers, not researchers with well-defined problems. And, as Russell Ackoff said, managers do not solve problems they manage messes.

Governments have their own limits of the messes they can deal with. Economists in research, on the contrary, simplify messes to tractable models. Let’s take one of the most powerful ideas in development: structural changes. Illustrated by Dani Rodrik:

McMillan and Rodrik - 2011 - Globalization, Structural Change and Productivity Growth
McMillan and Rodrik – 2011 – Globalization, Structural Change and Productivity Growth

The negative slope of the fitted values says that people moved from more productive to less productive industries over time. Which, of course, is a bad structural change. We can blame politics for this or whatever, but it’s hard to separate politics and, say, incompetence.

Emerging (and not so emerging) economies love the idea of employment growing in productive sectors. Even reports on sub-Saharan Africa regularly refer to knowledge economies and high-value-added industries. But in the end, many nations have something like that picture. (Oh, those messes.)

Did economists learn to manage messes better than public officials? Well, that’s what development economics is trying to accomplish. While it doesn’t include “general equilibrium effects” (the key takeaway from Daron Acemoglu), the baseline for judging the effectiveness of assessment programs is way below this and other criticisms. The baseline is eventually the intuition of a local public official—and policies that he would otherwise enact, if there were no evidence based programs.

Instead, these assessment programs provide simple tools for clear objectives. NGOs and local governments can expect something specific.

What about big evidence based policies? They require capacity building. At the extreme, look at the healthcare reform in the United States. Before anything happened, the Affordable Care Act already contained 1,000 pages. Implementation was difficult. Could a government in Central Africa implement a comparable reform, even having abundant evidences on healthcare in the US or at home?

Economists start to ignore the problem of implementation as the potential impact of their insights increases. The connection is not direct, but if you simplify a complex problem, you get a solution for the simplified problem. Someone else must complete the solution, and that becomes the problem.

What If Germany Annexed Greece?

The obsession with Greek debt shadowed the whole point of borrowing—that is, helping Greece grow again. While the debt matters, it matters even more when it’s well spent on policies that would reverse the recession. And this genre is totally different from today’s media coverage.

What plans does Europe have for Greece?

Greece itself doesn’t stick to any long-term plan. That’s both good news and bad news. Having several years of economic decline in a row, people try to rotate the left and the right in power, and new elections introduce new policies. The Papandreou government prioritized the business climate. In the best-practice style, it committed itself to the 2012 bailout terms and Greece even earned 48 positions in the World Bank’s Doing Business ranking since 2010 (praise by St. Louis Fed’s economist). This is how GDP responded:


Getting rid of bureaucracy solved no urgent economic problem. Business can include red tape in the price, but it can’t escape the falling demand on its own. Eventually, Greece got a good business climate without business.

Syriza had tried to argue with the creditors, so in response, the ECB cut the Greek banks off liquidity. Surely, the ECB did so in compliance with the June 30 official deadline, but it could negotiate the extension. Such events shake the public opinion, and Greek governments change each other. So which plan of long-term growth should we assess?

The plan of the creditors, of course. They have a large impact on short-term economic stability, which is a lever for making long-term decisions. With a small abuse of democracy, the troika writes a detailed plan for Greece and waits till the Greek officials accept this plan as their own.

This plan escapes the debtor’s fluctuating politics, so the bottom line remains the same since 2012. It includes the “milestones” that unlock new tranches from the EU:


The full manual concerns just everything:


(Along with some alternatives by academics, this plan tells something about the contribution of economic growth theory to the current affairs, or, rather, the lack of thereof. While growth theory speaks esoteric ideas, like creative destruction and rule of law, practitioners reduce recommendations to straightforward cost-cutting.)

But isn’t there a conflict of interest in this plan? A creditor’s planning horizon ends where his bonds mature. The debtor hopefully lives a little longer. So, their plans don’t coincide. If the troika wants its interest from the Greek bonds (that mature in 5−10 years), then its plan may be short-termed, compared to the recovery cycle. For example, the US stimulus was opting out of the economy for six years:


Maybe Angela Merkel loves the Greek people as much as the German people who elected her. But if not, which system would provide a German plan consistent with the Greek interests? Perhaps, the one where the Greek and German people elect a single representative.

How would it happen if merely adopting a single European currency took fifty years? Through the crises like the current one. The troika pays Greece for being more like Germany. As the new agreement is getting closer, this crisis management team continues controlling Greece even after the ruling party has been replaced. Then, wouldn’t the Greek people have more power if they affected the German politics directly, in joint elections?

That would be possible if the Greeks couldn’t quit. But Germany can’t take over its neighbors like the Thirteen Colonies did. And there’s already much disagreement about voluntary unification:


Greece, Spain, and Italy don’t enjoy being a hostage of the euro, even if this allows them to borrow cheap. Whatever these countries get from being more like Germany, they get it after giving up independence. How much could they get? The local unifications of Italy and of Germany didn’t lead to the full convergence of the regions, so the prospects are unclear. Meanwhile, it’s not even clear what “being more like Germany” means because the north of Germany is poorer than some South European regions:

Income per capita in European regions (FT)

If the Greek people could affect German politics, this would lead to more consistent plans, but not necessarily effective. Again, we know some general things about taming GDP fluctuations, but too little about the impact of structural reforms. And after the troika switched from macro to structural reforms, it must explain well why their experts think they know Greece better than the Greeks do.

Thinking Like Lee Kuan Yew

This is Lee Kuan Yew’s miracle everybody’s talking about today:

Data from Maddison
Data: Maddison

The rising green line includes better healthcare, education, security, housing, and other benefits of economic growth. A distinctive feature of Singapore—compared to virtually all developed countries—it hasn’t closed its borders after becoming rich:

Data: WDI
Data: WDI

Which shows how good institutions adapt immigrants and the country continues to grow in per-capita terms. “They’re stealing our jobs” and other forms of intellectual racism never look for the examples like this.

How much did Lee contribute to this success? Scarce evidences on personal contributions to economic growth (like Jones and Olken, “Do Leaders Matter?” [ungated working paper]) leave some space to leaders to affect history. But in specific cases, impact evaluation is informal. In this case, endorsements are also overwhelmingly positive—for the last thirty years or so. Then how did he do it?

Lee shares his executive experience in his well-known book From Third World to First. Perhaps, it’s a bad guide to development because readers may screen it for confirmatory evidences that reenforce their own opinions about economic policies. But the book has two valuable qualities that rarely coincide. First, it’s written by a top politician. Second, it’s written by someone who thinks hard.

In the book, Lee explains his decisions and their reasonable foundations. Why is his reasoning important for others? Because economic development is all about context. When a policy maker copies a decision without reasoning, for a start, he doesn’t understand the decision. Then he applies it to a wrong situation. Industrial policies in developing countries are full of this misunderstanding.

A politician rarely explains himself, and when he does, he is torn between embarrassment and empty words. In contrast, Lee has the point and refutable defense. His colleagues also recall that he’s okay to change his opinion. It seems trivial with all sophisticated economic research on topic; but when leaders lack these qualities, it’s irrelevant how much we know about development (or anything else, for that matter).

So, unlike most commentators of the day, I’d pay tribute not to what Lee Kuan Yew has done but how he thought about these things. The book is a good source to learn it.

A Billion-Dollar Bill on the Sidewalk

A new $29 bn. stimulus announced by Japan reminds about how more effective the package could be if we knew more about the impact of fiscal spending. Christina Romer (2012) and Council of Economic Advisers (2014, Ch. 3, Appx. 2) update on traditional aggregate estimates, but any such spending is also an opportunity for randomized trials—that is, a missed opportunity.

The motivation for experiments in macro is, of course, omitted variable bias. Macro has natural experiments to handle it. That’s what you find in research like Romer and Romer, 1989; Card and Krueger on the minimum wage in New Jersey; Card on the Cuban immigrants in Miami. Natural experiments are pure luck in this sense: you need to look for pseudo-random assignments, which are rarely the case. In contrast, designed experiments make all kinds of random assignments at will, including those allowing for interactions between macro policies. Governments spend hundreds of billions on programs outside routine annual budgets. These programs have nice, open-minded goals of supporting specific sectors or people. However, a typical assignment is not random within target groups—and it greatly complicates estimation of how effectively the money has been spent.

The 2009 American Recovery and Reinvestment Act created arbitrary opportunities for a few evaluations to appear, but apart from these bottom-up initiatives, the stimulus was business as usual. Eventually, the 2014 Economic Report of the President recommended RCTs for microeconomic programs and grants (2014, Ch. 7). It was an important step with too little attention to macro RCTs, which will have to wait.

Waiting for randomized macro evaluations costs billions of dollars, as policy makers launch programs based on careful, but imprecise, expectations of the impact. That’s despite per-capita costs of evaluations in macro are lower than similar overheads of microeconomic programs. Assignment in macro is simpler; household and firm responses appear in regular statistical reports. Why not to run more evaluations? No sophisticated problems or conspiracies here. It just takes twenty years for any idea to travel from economists to policy makers. The stopwatch is somewhere in the middle right now.

That means yes, the joke about $10 bill on the sidewalk is actually not about economists.

Learning to Learn from Indonesia

The World Bank publishes its 2015 development report. Behavioral economics, which the report is about, already earned a Nobel and best-seller positions for popular books on topic. The Bank now politely reminds that nudges matter for public policies.

One literally illustrative case from the chapter on productivity:


Which is about this:

Seaweed farmers in Indonesia, for example, had no problem noticing that the spacing between pods determined the amount of seaweed they could grow, and they could accurately report the spacing on their own lines. They failed to notice, however, that the length of the pod also mattered; they did not even know the lengths of the pods that they used, even though farmers had an average of 18 years of experience and harvested multiple crop cycles per year and thus had plenty of opportunities for learning by doing.

Even when randomized controlled trials on their own plots demonstrated the importance of both length and spacing—at least for researchers analyzing the data—the farmers did not notice the relationship between length and yields simply from looking at their yields in the experimental plots. Only after researchers presented them with data from the trials on their own plots that explicitly pointed out the relationship between pod size and revenues did farmers begin to change their production method and vary the length of the pods.

At this point, some think “Oh, those stupid Indonesian farmers! This never happens to me.” Well, it does. Lawrence Summers suggests a good example: the airport elevator that takes more time to fix than the Empire State building to build.

Apart from the decline of social trust in the United States (which is Summers’ main point), slow construction has some behavioral roots. Why doesn’t the owner fix his elevator faster? The losses from this elevator are not on his books—they’re opportunity costs that few care about. If thousands of people have to make their route two minutes longer each day while the elevator stands still, the owner doesn’t notice the losses either. The people do, and not Harvard professors alone. Customers are less satisfied with service (walking around the place is a service, too) and less likely to leave their money around. It boomerangs on the elevator owner through the long chain of revenues and rents from airport shops.

Like the Indonesian farmers, managers would notice this “only after researchers presented them with data from the trials on their own plots airports that explicitly pointed out the relationship between” time to fix an elevator and revenue from operations.

And guess what? Managers wouldn’t agree to establish a proper trial to find this out empirically. It requires some elevators to work and some not to work in a random order—a thing totally unacceptable to managers. After all, they realize that dysfunctional infrastructure isn’t that great.

A single dysfunctional elevator ain’t great either. The math is embarrassingly simple. If ten elevators reduce revenues by 10%, then one elevator reduces revenues by 1% (actually, more than that; people don’t care much if nothing works, but they still notice those small flaws if things run somewhat smoothly).

If elevators still seem to be a small issue, big construction projects don’t. Repairing a road takes time but contractors rarely use this time wisely. Why should they? A daily 8-hour shift is a cheap way to complete the works in one year. Three shifts could do it in six months, but margins would be smaller. Meanwhile, drivers spend another six months in jams around roadblocks.

A private contractor need not to care about drivers, but government must. Naturally, by paying contractor more for completing the project fast. It may mean more taxes or debt; but if drivers realize how much slow roadworks add to communing, they would pay to avoid this waste.

Again, like the Indonesian farmers and airport managers, drivers rarely draw the connection between “downsizing the government” and personal time lost in jams. First, politicians rarely puts things this way; second, people routinely underestimate opportunity costs compared to direct expenses. So, they choose fewer taxes and more jams.

Where does behavioral economics lead to? Teaching yourself biases is an option. But it probably won’t help with elevators, bridges, and roads. These are problems that deserve routine attention, which governments may provide. If governments prevent crimes, shouldn’t they take control over things that kill our time?

Free Cheese, not in the Mousetrap

OECD has a nice cost-benefit analysis of returns to education. First, what a high school gives to students:


Okay, huge net benefits for a degree. Even more interesting is the “unemployment effect.” Here lies a monetary value of higher employment security. The degree holder spends less time unemployed due to job security during crises and later retirement. This component is especially high in Slovak and Czech Republic. These countries have one of the lowest wealth inequality in the world, but it looks like the effect of relatively low incomes in the top quantiles. Their labor markets need more highly educated employees, as the market quickly absorbs high skilled candidates and low-skilled workers remain jobless (unemployment rates of 14 and 7% for Slovakia and Czech Republic, respectively). You can compare it to Korea, which has a more balanced labor market: a degree holder earns more but not because she gets jobs faster.

Net lifetime gains from having Bachelor’s, Master’s, or PhD:


Eastern Europe could do a lot better given its middle-income status. Slovenia and Czech Republic would greatly benefit from more educated workers. A Hungarian with a tertiary degree creates more benefits for others than for herself, which makes a case for government support. It’s not necessarily support for education spending in this particular case. Free labor migration within the EU creates difficulties for public spending on education. Political support for these subsidies is low because students who get free education may migrate to high-income Germany and United Kingdom. High returns to tertiary education in Eastern Europe discourage this move, but they cannot fully offset the income gap between the West and the East.

So, it’s a case of the European Union without unity. Countries still have independent budgets (with exception of “stability and growth” rules), collect and spend their public revenues, but have to distort policies in response to other members stealing employment, demand, capital, or workforce. So, hypothetically, net beneficiaries from the brain drain should compensate losers for free public education.

But the point is, countries with fewer emigrants keep the returns to education and should invest in it more. Both by increasing public spending and by facilitating student loans. It’s not rocket science, just more care about people’s future.

Solving Big Problems by Breaking Them Into Smaller Ones

As Gallup reports, Americans worry most about economic issues:


That’s puzzling because the United States did best, compared to other developed countries, in recovering from the crisis:


David Wessel from Brookings suggests why this achievement isn’t encouraging and “economy in general” is still a concern. Now, look at developing countries:

PEW Research
PEW Research

These problems are more specific, partly because PEW’s questions are closed and Gallup’s are open-ended. Crime, health care, pollution, for example, appear in both polls. But it’s less evident that they’re important problems in the United States, too. The number of homicides is comparable to that of developing countries. K-12 education doesn’t catch up developed countries in international rankings. Or the results of the War on Poverty:


(The poor actually do slightly better because the measure excludes social transfers. Still, transfers are supposed to be a temporary relief when families fall below the poverty level. Instead, social mobility is low and the poverty is persistent among many specific families.)

Dissatisfaction with government and economy is a big, unsolvable complaint. But breaking big dissatisfaction into smaller problems helps recognize crimes, education, and poverty, which the government can solve. What does it takes? Usually, smarter, not necessarily expensive, policies. And it’s not like no one knows how to do better in this complex world (thousands of academic papers offer very feasible changes for better), but it seems too few want it after all got confused by big hopeless problems.