To EAs, "development economics" evokes the image of RCTs on psychotherapy or deworming. That is, after all, the closest interaction between EA and development economists. However, this characterization has prompted some pushback, in the form of the argument that all global health interventions pale in comparison to the Holy Grail: increasing economic growth in poor countries. After all, growth increases basically every measure of wellbeing on a far larger scale than any charity intervention, so it's obviously more important than any micro-intervention. Even a tiny chance of boosting growth in a large developing country will have massive expected value, more than all the GiveWell charities you can fund.

The argument is compelling^[1] and well-received - so why haven't "growth interventions" gone anywhere? I think the EA understanding of growth is just too abstract to yield really useful interventions that EA organizations could lobby for or implement directly. We need specific interventions to evaluate, and "lobby for general economic liberalization" won't cut it.

The good news is that a large and active group of "macro-development" economists have been enhancing our understanding of growth in developing countries. They (mostly) don't run RCTs, but they still have credible research designs that can tell us important things about the causes and constraints of growth. In this series of posts, I want to lay out some stylized facts about growth in developing countries. These are claims which are backed up by the best research on this topic, and which tell us something useful about the causes and constraints of growth in developing countries.

My hope is not to pitch any specific interventions, but rather to give you the lay of the land, on which you can build the case for specific interventions. The way I hope for you to read this series is with an entrepreneurial eye. "This summary suggests that X is a key bottleneck to growth; I suspect Y could help solve X at scale. I should look more into Y as a potential intervention." or "This summary says that X process helps with growth; let me brainstorm ways we could accelerate X."

As part of that, an important caveat is that I will not cover topics where I believe there's no prospect for an effective intervention. For example, a large body of work emphasizes the importance of good institutions for development; I don't believe that topic will yield any promising interventions, so I won't cover it.

Sectoral Transformation

In this post, I will start with the fundamental path of growth: sectoral transformation. Every country that has ever gotten rich has had the following transformation: first, most of the population works in agriculture. Then, people start to move from agriculture to manufacturing, coinciding with a large increase in the country's growth rate. Finally, people move out of manufacturing and into services, coinciding with the country's growth slowing down as it matures into a rich economy. This is the process of sectoral transformation, and it is basically a universal truth of development. So it's no surprise that a big focus of macro-development is how to catalyze sectoral transformation in developing countries. That research has yielded four takeaways:

1. Agricultural productivity growth can drive sectoral transformation... or hurt it.

Every economy starts out as agrarian, because everyone needs food to survive. Agricultural productivity growth allows economies to produce enough food with fewer people, so that most people can move out of agriculture. This is why the US can produce more food per person than India, even though 2% of the US workforce in agriculture compared to 45% of India's workforce. So it seems natural that productivity growth in agriculture is the necessary push for sectoral transformation. However, agricultural productivity growth also increases the income people can earn in agriculture relative to in other sectors, so it could also incentivize people to stay in agriculture. That is the opposite of what we want! Which of these two stories is true?

The evidence on this question is very mixed, with studies finding support for opposite conclusions, sometimes even in the same setting. For example, Gollin, Hansen and Wingender (2021) find that the Green Revolution reduced land use for agriculture and dramatically increased incomes, while Moscona (2019) finds no income gains from the Green Revolution and in fact a decrease in urbanization.^[2] In general, however, agricultural productivity growth will probably promote sectoral transformation under two conditions:

1. Productivity growth reduces labor demand. When an agricultural technology reduces the labor required to plant an acre - because it replaces that labor with machines, or because new seeds require less maintenance, or because farms become larger and there are economies of scale - it will generally reduce the demand for labor. That in turn pushes people out of agriculture. (Bustos, Caprettini and Ponticelli 2016) Mechanized planting and harvesting technologies, weed-resistant plants that don't require a lot of labor to weed plants in the fields, irrigation systems that reduce the time farmers need to spend on water management - all of these will help release workers from agriculture and into the sectors that can make a country rich.
2. The country is relatively closed to trade. When farmers sell only within their country, there's only so much demand for food; agricultural productivity growth allows that demand to be satisfied with less labor, and thus promotes sectoral transformation. In contrast, when farmers can sell to the world, the demand for food is large enough that no country can fully satisfy it, so agricultural productivity growth makes the country specialize in agriculture. Indeed, the Green Revolution reduced sectoral transformation more in countries that were more open to trade. (Moscona 2019) This story can also explain why generations of development scholars who studied industrialization in the US and Europe were convinced of the need for agricultural productivity growth. Historically, the world was much less globalized, so agricultural exporting was less of a phenomenon and thus agricultural productivity growth did actually cause sectoral transformation. Unfortunately, that may not be true anymore.

These are both sufficient conditions; agricultural productivity growth will boost sectoral transformation if either of these conditions are met. In general, 1) is a more robust condition, but 2) could still hold especially in sub-Saharan African countries where trade is quite costly.

It's worth contrasting the agricultural productivity growth story with a mirror-image story; maybe instead of agricultural productivity growth pushing workers into the industrial sector, we could have industrial productivity growth pulling workers into that sector by increasing industrial wages. The research isn't very satisfactory on whether the "pull" story constitutes a viable path of development today.^[3] Industrial productivity growth is obviously worthwhile, and I'll cover it more in this series, but whether it specifically pulls workers out of agriculture in practice is a question without great answers.

But why is agricultural productivity in poor countries so low to begin with? What are the most promising sources of agricultural productivity growth? The main culprit is mechanization/input intensification. Rich country farms use 300-800x more intermediates and machines than poor country farms, and this gap accounts for 2/3 of the productivity gap between poor-country agriculture and rich-country agriculture. (Boppart et al, 2023) So why does this gap exist?

1. Agricultural machines and intermediate inputs have systematically higher prices in poor countries than in rich countries. (Boppart et al, 2023) This can be interpreted as a consequence of low manufacturing productivity, since that makes it expensive to produce agricultural inputs and thus discourages their usage. Reducing the prices of these productive inputs and machines would be the single biggest contributor to increasing mechanization/input intensification in poor country agriculture, and thus a critical part of sectoral transformation.
2. Farms in developing countries are extremely small, and some intermediates or machines could have scale economies that make them unprofitable at a small scale. There is also evidence that farm sizes in developing countries are systematically distorted by government policies (Adamopoulos and Restuccia 2014), but that ventures into politically-sensitive territory where I don't see prospects for effective interventions.

2. Education leads people to move out of agriculture (but with some negative spillovers).

A lot of "working in agriculture" starts in someone's first job; they start working in the fields and they just never leave. I have used the term "moving out of agriculture" loosely, as if the process is driven by individuals working in agriculture, one day deciding to switch to a job outside of agriculture, and then switching. But half of all sectoral transformation is driven by new cohorts entering the workforce. (Porzio et al, 2022) In other words, sectoral transformation happens when one year, 70% of school-leavers work in agriculture, but 10 years later, only 30% of school-leavers work in agriculture. The fact that half of this enormous trend is driven by new cohorts points to a critical role for education in driving sectoral transformation. Indeed, it's strongly established that education pushes people out of agriculture. In Indonesia, school construction reduced people's propensity to work in agriculture (Karachiwalla and Palloni 2019); in China, the expansion of higher education across regions did the same (Coelli 2023); globally, education expansions tend to reduce agricultural employment, to the extent that 20% of all sectoral transformation globally can be attributed to education. (Porzio et al, 2022)

One caveat that matters for these results is that these studies also find negative spillovers: when people get educated and leave agriculture, it makes the uneducated people in that area and neighboring areas even more likely to stay in agriculture, probably through reducing the supply of agricultural workers and thus raising their wages. This mutes the overall effect of education on sectoral transformation. Nonetheless, the 20% attribution is net of these spillovers, and so education is firmly established as a key driver of sectoral transformation.

3. Barriers to reallocation are surprisingly small; people select into sectors based on their skills.

A long-standing puzzle is why sectoral transformation doesn't happen faster. In developing countries, agricultural productivity (and thus wages) are significantly lower than non-agricultural productivity (and thus wages) (Gollin, Lagakos and Waugh 2014), so shouldn't people find it profitable to just switch sectors and increase their income? To rationalize why people don't move out of agriculture faster, researchers historically imagined large barriers to reallocation---e.g. migration costs, or difficulty of finding jobs in the non-agricultural sector, or family constraints. Many development interventions today are based on the idea of tearing down these barriers to people leaving agriculture.

These interventions have a shaky foundation, because it turns out that there is not much of a puzzle: the answer is probably due to selection. People who work in agriculture are significantly less skilled and educated than people who work outside agriculture, which explains why they earn less even with no barriers to reallocation. (Herrendorf and Schoellman 2018) When people actually leave agriculture, and we observe their wages before and after they switch sectors, their wage gains from switching are 8-40% of the average wage differences. (Hamory et al, 2020) There's still some doubt you can cast over this interpretation, but I consider it settled.^[4]

This is a negative result, in that it cuts against most interventions you could imagine that simply push people across sectors without any underlying changes to their skills. Such interventions are unlikely to benefit the movers, but they're also unlikely to promote growth if those movers are not very productive in the manufacturing sector (which is suggested by the fact that they don't see wage gains). Instead, this result points us towards interventions that actually improve the human capital of agricultural workers, like education or job training.

4. Most sectoral transformation today comes from people moving into services, not manufacturing.

The transition I described before - where people leave agriculture for the high-growth manufacturing sector, which helps countries grow really fast, until eventually they mature into rich countries and work in services instead - used to describe the path of development. For better or worse, that is not what happens today. Instead, a large number of movement out of agriculture is movement into services. Countries today are seeing a lower peak of manufacturing employment relative to the past, and a large movement of workers from the high-growth manufacturing sector to the low-growth services sector. (Rodrik 2016; McMillan and Rodrik 2014) This is the famous "premature deindustrialization" thesis, which warns us that developing countries today are not industrializing in the way that rich countries of today did in the past. There are many proposed explanations - competition from China, automation, reduced global demand for manufacturing goods, etc - but what matters are the consequences of this trend.

This distinction between manufacturing-led growth and service-led growth matters. Manufacturing has historically had a number of advantages over services as a path of development. First and most importantly, it's tradable, so a country can serve the whole global economy and make a lot more prosperity, relative to making services that can only be consumed domestically. Second, manufacturing is intensive in unskilled labor, so it can uplift a huge number of uneducated workers, relative to services which employs mainly educated workers. Third, manufacturing has high returns to scale, enabling large-scale production, whereas services generally are more limited in this dimension. Thus, services have historically not been a good path of development.^[5]

Nevertheless, global trends are hard to fight. They happen often for reasons outside any country's control. Any serious interventions that move people out of agriculture are likely to move them into services, whether we want that or not. So it's better to know that and design interventions with that in mind.

Can transformation directly into services be beneficial? In India, growth in services definitely did improve living standards, but the benefits accrued mainly to high-income urban residents. (Fan, Peters and Zilibotti 2021) In other countries, the evidence for service-led growth is grimmer; in China, when the expansion of universities spurred movement from agriculture to services, this reallocation actually slowed income growth relative to if there had been no reallocation. (Coelli 2023) These findings suggest that maybe developing countries should actively resist this trend and aim to grow world-class manufacturing sectors anyway. This is the shadow of industrial policy that looms over every discussion of growth, which I will cover in a following post.

The optimistic perspective is that the characteristics that made manufacturing special - tradability, scale, and employing unskilled workers - are not so special today as they used to be. Trade in services is growing, making it conceivable that countries could export services at scale (e.g. India's IT sector) and gain all the benefits of exporting; technology could make services easier to deliver with lower skill. So it would be exceptionally valuable to have a) technology/policy that increases trade in services, b) technology that increase the scale of production of services, and c) technology that reduces the skill barrier for services work. Whether these are feasible goals will be one of the defining questions of growth in the 21st century.