Economic Complexity

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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Much of the analysis of economic growth has focused on the study of aggregate output. Here, we deviate from this tradition and look instead at the structure of output embodied in the network connecting countries to the products that they export. We characterize this network using four structural features: the negative relationship between the diversification of a country and the average ubiquity of its exports, and the non-normal distributions for product ubiquity, country diversification and product co-export. We model the structure of the network by assuming that products require a large number of non-tradable inputs, or capabilities, and that countries differ in the completeness of the set of capabilities they have. We solve the model assuming that the probability that a country has a capability and that a product requires a capability are constant and calibrate it to the data to find that it accounts well for all of the network features except for the heterogeneity in the distribution of country diversification. In the light of the model, this is evidence of a large heterogeneity in the distribution of capabilities across countries. Finally, we show that the model implies that the increase in diversification that is expected from the accumulation of a small number of capabilities is small for countries that have a few of them and large for those with many. This implies that the forces that help drive divergence in product diversity increase with the complexity of the global economy when capabilities travel poorly.

For Adam Smith, wealth was related to the division of labor. As people and firms specialize in different activities, economic effi- ciency increases, suggesting that development is associated with an increase in the number of individual activities and with the complexity that emerges from the interactions between them. Here we develop a view of economic growth and development that gives a central role to the complexity of a country’s economy by interpreting trade data as a bipartite network in which countries are connected to the products they export, and show that it is possible to quantify the complexity of a country’s economy by characterizing the structure of this network. Furthermore, we show that the measures of complexity we derive are correlated with a country’s level of income, and that deviations from this relationship are predictive of future growth. This suggests that countries tend to converge to the level of income dictated by the complexity of their productive structures, indicating that development efforts should focus on generating the conditions that would allow complexity to emerge to generate sustained growth and prosperity.

For Adam Smith, wealth was related to the division of labor. As people and firms specialize in different activities, economic efficiency increases, suggesting that development is associated with an increase in the number of individual activities and with the complexity that emerges from the interactions between them. Here we develop a view of economic growth and development that gives a central role to the complexity of a country's economy by interpreting trade data as a bipartite network in which countries are connected to the products they export, and show that it is possible to quantify the complexity of a country's economy by characterizing the structure of this network. Furthermore, we show that the measures of complexity we derive are correlated with a country's level of income, and that deviations from this relationship are predictive of future growth. This suggests that countries tend to converge to the level of income dictated by the complexity of their productive structures, indicating that development efforts should focus on generating the conditions that would allow complexity to emerge in order to generate sustained growth and prosperity.

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.