Do You Have to Choose Growth or Development?

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A number of posts/comments have been floating around the last few days that deal with the goals or the World Bank. Lant Pritchett published a piece that asks whether rich countries are in fact good partners for poor countries looking to develop. Pritchett is worried that rich-country development agencies (including the World Bank) have altered their focus from promoting overall economic development, and “defined development down” to be only about alleviating the conditions for the extremely poor – those earning less than $1 per day.

Pritchett suggests that the reason for this is a “post-materialist” attitude within rich countries. More crudely, you could say that this is another example of rich countries attempting to impose their goals/values/hopes onto developing countries. We in rich countries in general – and most likely highly paid development agency workers specifically – have the luxury of saying that material economic growth is not that important. Pritchett argues that this is to ignore the goals/values/hopes of actual people in those developing countries, who very much would like some material economic growth, please.

I’m very much on Pritchett’s side on this, with a caveat I’ll get to later in the post. I wrote a post back when I started this blog on defining development economics. I contrasted “development economics” with the “economics of poverty”. Development economics, to me, is the study of what allows countries to shift from poor, agricultural, rural economies to rich, industrial, urban economies. It is “development economics” in a classic sense, but today you’d probably call it “growth economics” or “macroeconomic development”.

The economics of poverty is about the constraints facing poor people in un-developed economies, how they cope with those constraints organically, and what kind of interventions will alleviate these constraints. The problem is that what I call the economics of poverty is what everyone else calls “development economics” – field studies and surveys in poor countries, running randomized control trials of interventions, and the like.

Pritchett is arguing, in my mind, for the World Bank to return to thinking about growth economics, or about development in the classic sense. Looking for projects like ports, roads, energy generation, and the like. Scale-intensive activities that need someone to coordinate the investment, and investments that will not take place organically because they are essentially public goods. Things that might allow or push economies into sustained growth.

Pritchett’s article generated a response in defense of the World Bank’s focus on poverty alleviation. The main example I know of is here, by Emre Ozaltin. He argues that Pritchett has a “growth fetish”, and that we have evidence that this does not lead to development. That’s debatable, but Ozaltin is correct that this is not an either/or decision. One does not have forgo poverty alleviation to focus on growth, or vice versa.

But Ozaltin also overstates the case for focusing on poverty alleviation. He says, “The sum of the activities in which we are engaged are not incidental to the challenge of development. They are development. For example targeting, investing in health and education, and doing so in multisectoral and coordinated ways, are all critical to growth.”

No, they are not. We have no convincing evidence that improving on those dimensions leads to growth. Yes, we have hundreds of well-designed studies showing how specific interventions improve health or education outcomes, but that does not mean they lead to economic growth. Acting to alleviate poverty is a noble, useful, moral activity. But you do not get sustained growth as a freebie on top of it. What Pritchett is arguing (I think. I’m putting words in his mouth here.) is that the Bank has presumed that their poverty alleviation efforts will generate growth as a byproduct. They haven’t, and most likely won’t. Growth is a distinct dimension of development different from poverty alleviation.

Now, here is my caveat to supporting Pritchett’s position. Who cares if it is specifically the World Bank that provides that infrastructure investment supporting economic growth? If the aims and goals of the World Bank have changed to poverty alleviation, fine. Let that be their focus, and the business of promoting growth can be left in the hands of other entities.

This has essentially already happened, and it isn’t clear why one should try to stop it. Tim Taylor had a nice post on the World Bank. In it, he links to research showing that the World Bank is rapidly running out of countries that qualify for its help. Further, official development assistance (ODA) is being dwarfed by foreign direct investment, remittances, and sovereign bonds as a source of investment funds for developing countries. Development banks such as the Inter-American Development Bank, the African Development Bank, the Asian Development Bank, and the new bank proposed by China are all in the business of lending for large infrastructure projects. Let them.

I think Pritchett is wasting his time here, trying to turn the World Bank to a new (actually, old) heading. The Bank is a gargantuan organization, and has reached the point where self-perpetuation is as important as the actual mission. This isn’t to trash the World Bank, it’s no worse than any other large organization on this front. But if the nature of the interventions that the Bank wants to undertake has changed, so be it. Argue instead for increased funding to the existing development banks. Argue for the US to drop its opposition to the Chinese-led development bank. It may be useful or best to separate the poverty alleviation and growth-promotion, anyway. But you need both. Poverty alleviation alone is not a robust path to long-run sustained economic development.

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Measuring Real GDP

NOTE: The Growth Economics Blog has moved sites. Click here to find this post at the new site.

This morning Angus Deaton and Bettina Aten released an NBER working paper (gated, sorry) about understanding changes to international measures of real GDP and poverty that occurred following the release of a new round of price indices from the International Comparison Project (ICP).

Price indices? Methodological nuance? I know, ideal subject matter to drive my web traffic to zero.

For those of you still here (thanks mom!), the paper by Deaton and Aten is a great chance to understand where comparisons of real GDP across countries come from, and to highlight that these comparisons are inherently imprecise and should be used with that in mind.

The basic idea of the Penn World Tables, or any other attempt to measure real GDP across countries, is to compute the following

\displaystyle  RGDP_i = \frac{NGDP_i}{PPP_i} \ \ \ \ \ (1)

where {RGDP_i} is the real GDP number we want, {NGDP_i} is the nominal GDP reported by a country, and {PPP_i} is the “purchasing-power-parity” price index for that country. While there can be severe issues with the reporting of nominal GDP, particularly from poor countries with a bare-bones (or no) national statistics office, the primary concern in these calculations is with the {PPP_i}.

Think of {PPP_i} as the cost of one “bundle of goods” in country {i}. So dividing nominal GDP by {PPP_i} gives us the number of real bundles that a country produced. If we do that for every country, we can compare the number of real bundles produced across countries, and that crudely captures real GDP.

The ICP produces these measures of {PPP_i} for each country. I’m going to avoid the worst sausage-making aspect of this, because it involves lots of details about surveys to find prices for specific goods, how to get the right “average” price for each good, and then how to roll those back up to {PPP_i} for each country. The important thing about the methodology for computing {PPP_i} is that there is no right way to do it. There are methods that might be less sensible (i.e. let {PPP_i} be the price of a can of Diet Coke in a country) than what the ICP does, but that doesn’t imply that the ICP is correct in some absolute sense.

It also means that the ICP can, and does, change methodology over time. The paper by Deaton and Aten works through the changes in methodology from 1993/5 to 2005 to 2011 and how we measure real GDP. The tentative conclusion is that the 2005 iteration of the ICP probably was over-stating the {PPP_i} levels for many developing African and Asian countries. From the equation above, you can see that over-stating the {PPP_i} means under-stating real GDP. So in 2005, we were likely too pessimistic about the economic conditions in a lot of these developing countries. Chandy and Kharas found that using the 2005 values of {PPP_i} implied that 1.215 billion people in 2010 lived below the World Bank’s $1.25 per day poverty line. Using the 2011 values of {PPP_i} instead, there are only 571 million people living below $1.25 per day. That’s a reclassification of some 700 million people. Their domestic income stayed the same, but the 2011 ICP suggests that they were paying lower prices for their “bundle of goods” than we assumed in 2005, and hence their real income went above $1.25.

But as I said before, these are tentative conclusions because there is no way of knowing this for sure. Deaton and Aten’s conclusion is that the 1993/5 and 2011 rounds of the ICP seem more consistent with each other, and 2005 looks like an outlier. So just to keep things comparable over time, we should probably avoid the 2005 numbers. But again, who knows. It’s quite possible that mankind’s true welfare is measured in the number of cans of Diet Coke that we can produce.

Measuring real GDP or global poverty levels is – to put it kindly – a fuzzy process. There is not the right method for this. As you can see, the measurements can be pushed around a lot by differences in methodology that are inherently trying to make apples-to-oranges comparison (I mean that literally – how do you value apples compared to oranges in national output? What’s the right price? It’s different in Washington, Florida, and Wisconsin. So how do you compare the total “real” value of fruit consumption in different states or countries?).

The implication is that we shouldn’t be asking real GDP measures or poverty line measures to do too much. For really crude comparisons, real GDP from the Penn World Tables is fine. The U.S. has higher real GDP per capita than Kenya, and the Penn World Tables pick that up. Is it a 40/1 ratio? A 35/1 ratio? A 20/1 ratio? Not entirely clear. Different methodologies for computing {PPP_i} in the US and Kenya will yield different results. But is it really important if it is 40/1 versus 20/1? In either case, it is clear that Kenya is poorer. We can go forth and try to explain why, or make some policy advice to Kenya to help close the gap, or go to Kenya to work on interventions to alleviate poverty there.

Where these real GDP comparisons, or poverty line counts, should not be used is in finer-grain comparisons. Is Kenya’s real GDP per capita lower or higher than Lesotho’s? According to the Penn World Tables, in 2011 Kenya’s was lower. But should we do any kind of serious analysis based on this? No. The difference is as likely to be from discrepancies in how we measure {PPP_i} for those countries as from real economic differences in capital stocks, human capital, technology, or institutions.

Real GDP comparisons are best thought of as similar to baseball stats. The top career OPS (on-base plus slugging percent) players are Babe Ruth, Ted Williams, Lou Gehrig, Barry Bonds, and other names you might recognize. Players like Albert Pujols and Miguel Cabrera are in the top 20, giving you a good idea that these guys are playing at a level similar to the greats of all time. You can’t use this career OPS to tell me that Pujols is definitively better than Stan Musial or definitively worse than Rogers Hornsby. But career OPS does make it clear that Pujols and Cabrera are definitely better than guys like Davey Lopes, Edgar Renteria, and Devon White (and distinguishing between Lopes, Renteria, and White is hopeless using OPS).

The fact that ICP revises the {PPP_i} values over time doesn’t make them useless, just as OPS isn’t useless even though it ignores defense and steals. But you cannot ask too much of the real GDP measures that are derived using them. They are useful for big, crude comparisons, not fine-grained analysis.

Defining Development Economics

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Trying to precisely define an area of study is impossible, but thinking through the definition of “development economics” is an interesting diversion. As with most fields, the definition is tied closely to the people doing research in that area. So today, “development economics” is the kind of research done by people like Esther Duflo, Ted Miguel, Michael Kremer, and a group of other very smart people who I will offend by not mentioning here. This kind of development economics has several key features. (1) It very consciously takes place in developing countries. These researchers are out collecting surveys or doing studies “in the field”. Perhaps the best way to define a development economist today is as someone whose presentation includes a picture of the village they worked in to collect data. (2) It is intensely concerned with identification of causal effects. Thus this field aspires to do randomized control trials (RCTs) to identify the causal effect of some {X} (e.g. de-worming treatments) on some {Y} (e.g. school attendance), as in Kremer and Miguel (2004). Failing that, some kind of natural experiment that features quasi-random treatment effects is examined. (3) It tends to be a-theoretical. The RCTs are showing reduced-form empirical effects of some kind of treatment on some kind of outcome. The de-worming paper of Kremer and Miguel is purely empirical, for example. This isn’t generally true, as there are papers that explicitly are testing some theory, but the dominant portion of the literature is purely empirical.

Through some historical inertia in the profession, we call this research “development economics”. But I think that this type of research is more properly called “poverty economics”, the study of individuals living in particularly poor, under-developed countries. Duflo and Banerjee‘s 2011 book is actually called Poor Economics, and the tag-line is A Radical Rethinking of the Way to Fight Global Poverty. The focus is on alleviating the conditions of extreme poverty: poor health, poor nutrition, and low education. The RCTs are evaluations of interventions that aim to improve health, or nutrition, or educational attainment. By going out into these developing countries, these researchers are acutely aware of the constraints facing poor people, and are studying ways to alleviate those constraints.

This is all valuable research. It is perhaps more admirable in its motivations than other sub-fields of economics (*cough* finance *cough*). But it is not about “development”.

Economic development is about the transition of whole economies from low-productivity, poor places into high-productivity industrial economies. This transition encompasses several aspects: a move out of agriculture and into manufacturing or services, urbanization, declining fertility rates, integration with global markets. Current research in development economics – the RCTs and their like – does not study the transition. “What will make these people better off today?” is a different question than “What will make this economy develop?”.

If you go back far enough in the development literature, you’ll find that the second question is the dominant one. Lewis, Nurske, Rosenstein-Rodan, Boserup, Gerschenkron, Hirschman all were concerned with what drove the transition to high-productivity industrial economies. But while they focused on this broader question, their work also contained assumptions that steered the profession away towards “poverty economics”. An (often unspoken) assumption of much of this early development work was that rural peasants were irrational. That is, they did not respond to prices or incentives the way that people in modern economies did. They were tradition-bound, stuck in their ways. Development meant breaking this resistance to change and educating them to operate in a market-based economy.

The reaction to this, most notably associated with T. W. Schultz’s 1964 book on Transforming Traditional Agriculture, was that peasants were in fact rational, but faced a unique set of constraints. If they stuck to traditional means for organizing production, then that is because those traditions were solving some concrete problem. Perhaps the best example is share-cropping, which even Alfred Marshall critiqued for being inefficient. It seems that by share-cropping, the marginal return for the peasant of more labor or capital is lowered, and hence less effort or investment is put forth. To the early development economists, share-cropping was an example of a traditional institution that prevented higher output. Except that once you appreciate the uncertainty involved in family farming, it is possible that share-cropping is the optimal contract to pick because it shares risk between the land-owner and farmer.

This led development economists on a different heading. The hunt was on for reasonable explanations of the observed behavior in these underdeveloped villages. What were the constraints or conditions that prevented these peasants from making more investments, or adopting better technology? This led to all kinds of seminal insights. Joseph Stiglitz, as one example, cites his time in Kenya in the late 60’s as pivotal for developing his ideas on the economics of information.

However, in pursuing this line of thinking, development economics got so deep into the details of optimizing behavior in under-developed villages that it lost track of the larger question: “What will make this economy develop?”. The study of the nuances of under-developed markets became an end in itself. A concrete example is the survey by Otsuka, Chuma, and Hayami (1992, JEL, sorry no link) on “Land and Labor Contracts in Agrarian Economies”. They say, “Through a critical review of the existing studies of agrarian contracts, this essay points towards building a `general model’ in which land tenancy, labor employment, and owner cultivation are modeled together as substitutes along a continuous spectrum of contract choice.”. And it is a very nice synthesis of the literature in this area to that point. But what implications does it have for development? What does this general model tell us about how or why a country will make the transition into an industrial economy? Knowing that peasants are rational rather than irrational is great, but I still would like to know how those peasants’ kids or grandkids will (or will not) end up as machinists or office workers living in city one day.

This is where development economics started turning into poverty economics. The focus became purely on understanding the constraints facing poor people in under-developed countries. As these constraints were dire, and led to such bad outcomes (poor health, low education, etc..), alleviating those constraints became the first-order concern. And let’s be clear, it is very much a first-order concern. Millions of people dying from an easily preventable disease is a travesty. Running RCTs to establish the best way to distribute that treatment is incredibly valuable research.

Despite that, current development economics doesn’t address the broader questions, the older questions, of what drives development in the long-run. The field of growth economics has essentially adopted this set of questions as part of its own research agenda. One of the things that this “macro-development” research does is establish the aggregate impact of micro-level features of under-developed economies. Does a given micro-level distortion or constraint incur such costs that it is a material reason for why a country remains relatively poor? Two recent examples are Hsieh and Klenow‘s 2009 paper on the aggregate effects of misallocations across firms in China and India, or Lagakos and Waugh‘s 2013 model of selection and cross-country income differences.

This doesn’t make the growth/macro-development approach better or worse than poverty economics. The two fields are just looking at different questions, with different implications. It’s worth keeping that in mind when evaluating the research in the two fields. In particular, it is not helpful to criticize one literature with the tools of the other (e.g. “But how do you plan on getting identification of this effect?” or “But who cares about the reduced form effect? What’s the mechanism you think is at work here?”). Different questions, different approaches, different techniques.