Product Space

Over the past two centuries, mankind has accomplished what used to be unthinkable. When we look back at our long list of achievements, it is easy to focus on the most audacious of them, such as our conquest of the skies and the moon. Our lives, however, have been made easier and more prosperous by a large number of more modest, yet crucially important feats. Think of electric bulbs, telephones, cars, personal computers, antibiotics, TVs, refrigerators, watches and water heaters. Think of the many innovations that benefit us despite our minimal awareness of them, such as advances in port management, electric power distribution, agrochemicals and water purification. This progress was possible because we got smarter. During the past two centuries, the amount of productive knowledge we hold expanded dramatically. This was not, however, an individual phenomenon. It was a collective phenomenon. As individuals we are not much more capable than our ancestors, but as societies we have developed the ability to make all that we have mentioned – and much, much more.

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Countries differ markedly in the diversification of their exports. Products differ in the number of countries that export them, which we define as their ubiquity. We document a new stylized fact in the global pattern of exports: there is a systematic relationship between the diversification of a country’s exports and the ubiquity of its products. We argue that this fact is not implied by current theories of international trade and show that it is not a trivial consequence of the heterogeneity in the level of diversification of countries or of the heterogeneity in the ubiquity of products. We account for this stylized fact by constructing a simple model that assumes that each product requires a potentially large number of non-tradable inputs, which we call capabilities, and that a country can only make the products for which it has all the requisite capabilities. Products differ in the number and specific nature of the capabilities they require, as countries differ in the number/nature of capabilities they have. Products that require more capabilities will be accessible to fewer countries (i.e., will be less ubiquitous), while countries that have more capabilities will have what is required to make more products (i.e., will be more diversified). Our model implies that the return to the accumulation of new capabilities increases exponentially with the number of capabilities already available in a country. Moreover, we find that the convexity of the increase in diversification associated with the accumulation of a new capability increases when either the total number of capabilities that exist in the world increases or the average complexity of products, defined as the number of capabilities products require, increases. This convexity defines what we term as aquiescence trap, or a trap of economic stasis: countries with few capabilities will have negligible or no return to the accumulation of more capabilities, while at the same time countries with many capabilities will experience large returns - in terms of increased diversification - to the accumulation of additional capabilities. We calibrate the model to three different sets of empirical data and show that the derived functional forms reproduce the empirically observed distributions of product ubiquity, the relationship between the diversification of countries and the average ubiquity of the products they export, and the distribution of the probability that two products are co-exported. This calibration suggests that the global economy is composed of a relatively large number of capabilities – between 23 and 80, depending on the level of disaggregation of the data – and that products require on average a relatively large fraction of these capabilities in order to be produced. The conclusion of this calibration is that the world exists in a regime where the quiescence trap is strong.

This paper establishes a robust stylized fact: changes in the revealed comparative advantage of nations are governed by the pattern of relatedness of products at the global level. As countries change their export mix, there is a strong tendency to move towards related goods rather than to goods that are farther away. The pattern of relatedness of products is only very partially explained by similarity in broad factor or technological intensities, suggesting that the relevant determinants are much more product-specific. Moreover, the pattern of relatedness of products exhibits very strong heterogeneity: there are parts of this ‘product space’ that are dense while others are sparse. This implies that countries that are specialized in a dense part of the product space have an easier time at changing their revealed comparative advantage than countries that are specialized in more disconnected products.

In this paper we examine the product space and its consequences for the process of structural transformation. We argue that the assets and capabilities needed to produce one good are imperfect substitutes for those needed to produce other goods, but the degree of asset specificity varies widely. Given this, the speed of structural transformation will depend on the density of the product space near the area where each country has developed its comparative advantage. While this space is traditionally assumed to be smooth and continuous, we find that in fact it is very heterogeneous, with some areas being very dense and others quite sparse. We develop a measure of revealed proximity between products using comparative advantage in order to map this space, and then show that its heterogeneity is not without consequence. The speed at which countries can transform their productive structure and upgrade their exports depends on having a path to nearby goods that are increasingly of higher value.

The comparative advantage of a location shapes its industrial structure. Current theoretical models based on this principle do not take a stance on how comparative advantages in different industries or locations are related with each other, or what such patterns of relatedness might imply about the underlying process that governs the evolution of comparative advantage. We build a simple Ricardian-inspired model and show this hidden information on inter-industry and inter-location relatedness can be captured by simple correlations between the observed patterns of industries across locations or locations across industries. Using the information from related industries or related locations, we calculate the implied comparative advantage and show that this measure explains much of the location’s current industrial structure. We give evidence that these patterns are present in a wide variety of contexts, namely the export of goods (internationally) and the employment, payroll and number of establishments across the industries of subnational regions (in the US, Chile and India). The deviations between the observed and implied comparative advantage measures tend to be highly predictive of future industry growth, especially at horizons of a decade or more; this explanatory power holds at both the intensive as well as the extensive margin. These results suggest that a component of the long-term evolution of comparative advantage is already implied in today’s patterns of production.

Income per capita in Uganda has doubled in the last 20 years. This remarkable performance has been buoyed by significant aid flows and large external imbalances. Economic growth has been concentrated in non-tradable activities leading to growing external imbalances and a growing gap between rural and urban incomes. Future growth will depend on achieving sufficient export dynamism. In addition, growth faces a number of other challenges: low urbanization rate, rapid rural population growth and high dependency ratios. However, both the dependency ratio and fertility rates have begun to decline recently. Rural areas are also severely overcrowded with low-productivity subsistence agriculture as a pervasive form of production. Commercial agriculture has great possibilities to increase output, but as the sector improves its access to capital, inputs and technology it will shed jobs rather than create them.

These challenges combined tell us that future growth in Uganda will require a rapid rate of export growth and economic diversification. The country faces the prospect of an oil boom of uncertain size and timing. It could represent an important stepping stone to achieve external sustainability, expanded income and infrastructure and a greater internal market. However, as with all oil booms, the challenges include avoiding the Dutch disease, managing the inevitable volatility in oil incomes and avoiding inefficient specialization in oil. Policies that set targets for the non-oil deficit could help manage some of these effects, but a conscious strategy to diversify would still be needed.

The best strategy is therefore to use the additional oil revenue and accompanying investments to promote a diversification strategy that is sustainable. To determine how to encourage such a transformation, we draw on a new line of research that demonstrates how development seldom implies producing more of the same. Instead, as countries grow, they tend to move into new industries, while they also increase productivity in existing sectors. In this report, we analyze what those new industries might be for Uganda.

To do so, we first look to those products which balance the desire to increase the diversification and complexity of production, while not over-stretching existing capabilities. These include mostly agricultural inputs, such as agrochemicals and food processing. In addition, Uganda should concurrently develop more complex industries, such as construction materials, that are reasonably within reach of current capabilities and will be in great demand in the context of an oil boom. Here, the fact that Uganda is landlocked and faces high import costs will provide natural protection to the expanding demand in Uganda and neighboring countries. We conclude with a discussion of the government policies that will support Uganda in developing new tradable industries.