When East Asian countries grew at record rates, some articles attributed this to factor accumulation (eg Krugman 1994). Indeed, Japan and South Korea reinvested a lot of their output and also benefited from the growing working-age population. The data showed that factor accumulation actually went along with productivity growth, so these economies did have “genuine” improvements in the end.
Now, twenty years later, the same can be said about the United States. But this time, instead of capital, labor input drives economic growth. In 1950, the countries that would be called G7 looked this way (all data from PWT8, OECD):
US workers had relatively short working hours and much more equipment than their colleagues in other countries. In 2010, the picture looks different:
Hours declined rapidly in all countries but the United States. To feel the difference:
With the typical disclaimer about comparing hours across economies, I’d rather emphasize the dynamics of changes, instead of comparing countries directly. The growth paths for regional leaders:
These lines just smooth annual observations along 1950–2011. I also added GDP per worker under the markers.
Overall, if German firms cut hours by 40% since 1950, US firms cut only by 10%. Working hours stopped declining in the US around 1980 (perhaps to offset stagnating real incomes). Regardless of which counterfactual you like more (the US trend before 1980 or Germany’s), it implies a substantial difference in output — fueled by labor input, just as capital input helped East Asian economies decades ago.
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.
I’m going to do a couple of case studies in growth diagnostics. The first country is Russia for reasons I’ll explain in the next post. The second country is likely to be China, but you’re still free to send your suggestions.
I’m using a constraint analysis framework by Hausmann–Rodrik–Velasco (HRV). HRV developed a comprehensive, yet structured, framework with a 10-year record of practical applications. It includes a formal model and handy heuristics. It’s also compatible with the literature on growth factors, such as physical and human capital.
The Formal Model
The formal model comes from HRV (2004) — an early draft that still contains all the math of an augmented neoclassical model of economic growth. The equation of interest:
where is the return on capital defined as
The first equation describes accumulation of capital and consumption under distortions. The distortions are denoted with the Greeks and fall into five categories:
A very formal approach would require picking values for these parameters and simulating the model to compare it with actual values of consumption and capital. A well-calibrated model would predict responses to the changes in the parameters, which would immediately reveal the constraint. I won’t follow this approach because some parameters have no direct or estimable counterparts in the data.
Instead, I’m using this formal model for discipline and test candidate constraints with heuristics. The summary so far:
The shortcut to growth constraints is a useful table from HRV (2008):
Compared to the formal model, this table includes human capital and specific tests for each constraint mentioned in the header.
Estimating the responses to constraints may be challenging. For example, if you have an indicator for expropriation, you can’t readily say by how much an increase in “expropriation” would reduce economic growth. There’s no universal solution to this problem. For this, I’ll focus on constraints we can estimate with reasonable confidence.
A candidate for the binding variable is often a compromise among different priorities. The interest rate has to balance inflation and unemployment. Taxes raise some costs via taxation and reduce other costs via public goods. Macro stability after government spending cuts may be followed by political instability.
In this case, growth diagnostics would send contradictory signals. You must increase and decrease the same variable simultaneously! This seems possible in politics, but not in mathematics. To clarify such ambiguities, constraint testing requires a few more models.
Though the list of models is open, most of the job is done by a few conventional macro tools.
The Next Post
In the text post, I’ll briefly review the Russian economy and challenges it poses to growth diagnostics.
The entire case study will be accompanied with the replication files, which I try to make suitable for an immediate replication for any other major economy.
Over the last quarter century, less productive states in America had been catching up with the rich states. I’m talking about unconditional beta convergence:
GSP PC is Gross State Product per capita. The green line excludes territories colored with red (see “Technical details” for the reasons and OLS estimates). Otherwise, less developed states grew faster than the rest.
However, most of this convergence occurred before 2000:
Slopes after 1992 are not statistically significant. Including the post-2008 recovery:
And after the 1990s, the dispersion of GSP (another perspective on the catch-up process) no longer declines in the US:
Unconditional convergence is not an empirical fact, but something we expect in the workhorse models of economic growth. It exists in the data (especially for developed countries) and in some intra-country studies. Its disappearance from the American economy is not a good sign, however. Unconditional growth acceleration leaves a possibility that regions can catch up with the best neighbors simply by waiting long enough. Now, it’s not the case: states must do something.
A return to the pre-2000 conditions (whatever it means) would not necessarily help. One confirmed source of unconditional convergence is manufacturing (see Dani Rodrik’s 2013). But until the costs of getting manufacturing jobs back to the US remain unclear, that’s not a plan.
I’m going to write more on this problem later, but you can explore the GSP dataset yourself:
The GSP data is a straightforward extension of SIC-NAICS files from the BEA. See “usa_gdp_state_convere_data.do” for details.
Key charts exclude three US regions. District of Columbia is out because it’s small and not a state. North Dakota and Alaska have been heavily influenced by oil production and prices. Their inclusion would be distortive. I kept Texas because its oil sector is relatively small compared to the entire state’s economy.
Anyway, convergence is still disappearing in the 2000s, even if we keep all 50 states:
“Log of real GSP” refers to the level of GSP at the beginning of the period (e.g. for 1987, it’s 1987-1992). On the left-hand side of the regression is cumulative 5-year growth.
With 48 states:
So the overall convergence looks deceptive:
For completeness, the data on oil production by state from the EIA: chart.
In the mid-2000s, Ricardo Hausmann and Dani Rodrik developed a growth diagnostics framework for dealing with persistent economic growth failures:
With this decision tree:
The symptoms in the table indicate binding constraints. According to Hausmann and Rodrik, easing binding constraints would accelerate economic growth. Therefore, government should address its country’s constraints first. But before it must find these constraints.
Such evidence-based prioritizing could balance politics and fashion as the major determinants of public policies. It’s worth remembering that the major cost of government is not public spending, but the time wasted on implementing wrong reforms. This cost grows exponentially when measured against the scenario in which evidence-based policies indeed change things for better.
To be sure, governmental decisions are always accompanied by some sort of research. This research, however, often suffers from biases and politics. An economist needs a framework that keeps him disciplined. Hausmann-Rodrik growth diagnostics is such a framework.
A crash course in this framework would look like this:
First, a formal growth model. Doing diagnostics without modeling may seem easier, but after a while you’ll lose the big picture. As you lose the big picture, you can no longer rank priorities, even with microeconomic estimates of returns to policies. The Solow model and its modifications would suffice.
Also, unlike the authors, I’m more cautious about focusing on a single constraint. First, economic evidences are often inconclusive (but better than non-economic non-evidences). Second, governments fail to implement at least some of the policies that they’ve planned. In the end, you may advocate a wrong policy that isn’t going to be implemented anyway! As a remedy, I recommend stylized diversification akin to the Kelly criterion, when government allocates efforts proportionally to the expected payoffs from each constraint-policy pair.
In the next posts, I’ll review a couple of major economies in the spirit of Hausmann and Rodrik. Stay tuned!
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:
(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:
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.
Authors preaching creativity often use the nine-dots puzzle to encourage the reader to think, well, wider.
So, I did the experiment on the favorite topic. In economic growth, the box is a country. And researchers try to get most out of its economy, either by flattening the economic cycle or changing the long-term growth rates. While macroeconomists learned powerful tools for managing the cycles, the long-term rates remain untamed. Several competing frameworks describe the determinants of the rates, but not the determinants of the determinants. Which leaves you confused.
But you can think outside the box! Outside the box, you have other countries. A few of them have higher GDP per capita, so instead of thinking how to make people inside Country A richer, you can think how to relocate people from poor countries to the rich ones. The trick is, productivity grows when a person moves to a more industrious place, and so does output.
Urbanization is an old example of relocation at work, still relevant for many developing countries. But urbanization makes a small fraction of global income differences, which generally look like this:
Growth theory is figuring out how to change the shape and placements of these curves. This is difficult. But a single person can move along his country’s plot, or he can jump into another country’s plot. While jumping, the person boosts his productivity and the world GDP increases, despite both countries retain their GDP per capita levels.
As Branko Milanovic says in the paper where this chart comes from, migration is “probably the most powerful tool for reducing global poverty.” It’s not only powerful, it’s simple, compared to other solutions.
Now, what’s wrong with it. Like any solution, migration needs devoted advocates. It’s easy to find advocates for sound macro policies. Citizens don’t want to spend years in recession, so they wage research and lobbying. But advocating immigration reforms is like a part-time job, because citizens don’t care about the foreigner’s income. For example, some think tanks like the idea of letting foreign doctors and lawyers in the US, since that would reduce domestic inequality created by premium wages in these sectors. (No other country has 14 healthcare professionals in the top 20 of highest paying occupations.)
There’re, of course, bargains with undocumented immigrants in exchange for political support, like the great pardon proposed by Obama. This is a poor replacement for a legal-immigration reform, which would be more beneficial for the US at large.
What works? Developed countries invite immigrants to fill the gaps in the shrinking population. The current generation seek someone who will support them in the future. This looks like a perpetual immigration engine: when you have no children and retire, you just “adopt” an immigrant in his 20s who’ll pay the taxes that fund public spending. Then this immigrant gets older and lets a younger one to come in, and so on. Since the real birthrates are never zero, few workers change countries this way.
Business lobby promotes another channel, the expansionary one. When Bill Gates writes that the US needs immigrants to remain competitive, he means that Indian software firms are threatening Microsoft. Giving Indian software engineers US visas deprives Indian firms of skilled labor, so both India and Indian firms no longer compete with American software developers. That works well for both US business and citizens and, therefore, is a viable solution.
However, these channels create opportunities for a small fraction of internationally attractive professionals. The others remain dependent on domestic growth. The international response? Investments, not visas. That’s getting us back into the box, because investments depend on the country’s growth rates. The investor won’t come for the same reasons why the country doesn’t manage its currently available resources well. And despite the problem of growth has reasonable outside-the-box solutions, domestic politics accepts only inside-the-box options.
Maybe that’s why thinking in the box is still very useful in economics.
This is Lee Kuan Yew’s miracle everybody’s talking about today:
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:
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.
Policymakers pay a heck of a lot of attention to foreign direct investments when it comes to economic development. Almost no one mentions another driver of growth: domestic savings. That’s strange because even for major economies there’s no question what’s more important:
Both savings and direct investment enter capital that then gets mixed up with labor to produce stuff, but savings are 22 times larger than FDI (2005, 187 countries). And no research shows impact of FDI on productivity of the magnitude that would compensate this difference. This is how it looks with growth:
Most developing countries outside of this sample don’t have to choose between foreign capital and domestic savings because they have no foreign capital at all. Their savings rates also hit the bottom (see, for example, “Are We Consuming Too Much?” by Arrow and coauthors). Countries seem to need more knowledge about accumulating domestic capital than about attracting money from abroad.
What do development agencies and business media respond to this? The World Bank published 7 papers on savings and 58 papers on FDI. Google News finds 3,000 news on “domestic savings” and 58,000 results on “foreign direct investment.” Well, all attention to capital inflow.
But then where does this FDI fixation come from?
As for economics, savings have been considered an exogenous variable for a long time. Sort of, if a nation likes spending, then it saves. An exogenous saving rate is implausible. Faster economic growth implies higher return to capital and labor, so households save more knowing that their deposits and investments yield high returns. Insofar as technology backs this growth, decreasing marginal returns to capital are of less importance. Whatever discount rate households have, growth pays. In the sample above, China, India, and Korea reduced their consumption during the growth times:
But policymakers can’t control growth expectations much. It makes domestic savings less interesting to them. On the other hand, foreign direct investments are institutional and opportunistic. A national leader gives a talk, assures corporate executives that their investments are safe, shows opportunities to invest in—and FDI flow into the country. Well, actually, they don’t. But it still looks easier than convincing millions of people to bring their wages to banks.
The emphasis on foreign capital is hard to justify with numbers, anyway. People’s saving rates respond to their long-term confidence in the economy. If they don’t invest, FDI have little to add.
Ideas about “structural reforms” get copy-pasted from one development report to another, and for a good reason. These recommendations—basically about improving the economy’s fundamentals—indeed matters. But guess who’s supposed to implement them? Governments! And the quality of reforms depend on the quality of governments that implement them. What’s happening to government?
So, why is that?
The rule of law, which government is supposed to provide, is crucial for economic development:
But the rule of law implies incorruptible public officials:
Which is not the case when a country lacks specific institutions:
However, these institutions undermine narrow political power and, therefore, unlikely to emerge:
In brief, we ask corrupted officials to stop being corrupted and limit their power. Actually, it does make sense because development economists also address honest officials, who are more numerous and try to change things. It may work. Ruling parties in non-democracies attempt to improve governance without giving much power away to the press or opposition. They initiate genuine openness reforms, let citizens request information, complain, sue the government—unless it becomes political.
Still, the quality of government stagnates around the world. Partly, it happens because dark forces hiding in ruling parties defend their interests. Hey, that’s the problem we’ve started from! Not surprisingly. The literature says about the benefits of good governance, but its recommendations follow from the relationships found in developed countries, which already have uncorrupted governments to enforce the rule of law and the rest. Demanding Switzerland-style governance from corrupted governments looks like a hopeless idea. Not only the dark force resists, we also have few reliable solutions in mind—solutions that would be feasible given all peculiarities of political institutions in developing countries.
What sort of knowledge is to look for? Perhaps, of two types:
How to improve governance when the dark force resists? Honest judiciary, transparent elections, and able police create conditions for economic development. Well done. Now we want to know more about paths to these conditions. Much work has been done before in law and political studies. But as an ignorant economist, I see much space for improvements. Economists got their invisible hands on these subjects just recently and noticed the scarcity of (a) formal models, (b) suitable data. These are nice things to have. Theories escaping these two pieces leave us in the Middle Ages, which is not nice.
How to run an economy with dark forces? Given its history, economic theory paid more attention to well-governed nations, not to those with problems. For one example, corruption creates information asymmetries of the type that economists haven’t paid much attention to. Take a firm that has political connections and can generate profits above the market average. Can it gain access to capital? No. For this, it must credibly disclose its superiority to banks, which is impossible because the advantage comes from informal political connections. One way or another, capital finds these opportunities, but imperfections remain, so the equilibrium level of investments is lower than the economy and technology allow. So, the problem has implications that have not been studied as deeply as the economics of good governance.
These issues arise in development economics; it’s impossible to ignore them. But the field is small compared to the rest of econ-worlds:
Economics of poor governance awaits intellectual reinforcement from other fields. Wellbeing of 6 bn people is at stake.