The network structure of economic output
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.
Diagnostics before Prescription
Development Policy and Development Economics: An Introduction
Anyone who undertakes to produce a volume of surveys in economic development must confront the question: Does the world really need another one? The field changes over time and, one hopes, knowledge accumulates. So, one motive is the desire to cover the more recent advances. And indeed, economic development has been one of the most dynamic and innovative fields within economics in recent years. While one primary goal is to inform policy makers, it also hoped that the volume will assist scholars in designing research agendas that are informed by policy questions, in particular, by the gaps in knowledge that would speak to major policy issues. The development field has always been one in which the worlds of research and practice are in close relationship with each other and move in tandem. The large number of PhD economists who work in international organizations such as the World Bank and the influence of academia among developing-country officialdom ensure that ideas emanating from the ivory tower often find quick application. But equally important, in principle, is the reverse feedback—the need to tilt researchers’ attention on the questions that are, or should be, on the policy agenda. The organization of the present volume around policy issues is designed to make a contribution toward both of these goals.
The Building Blocks of Economic Complexity
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.
Trillions Gained and Lost: Estimating the Magnitude of Growth Episodes
We propose and implement a new technique for measuring the total magnitude of a growth episode: the change in output per capita resulting from one structural break in the trend growth of output (acceleration or deceleration) to the next. The magnitude of the gain or loss from a growth episode combines (a) the difference between the post-break growth rate versus a counter-factual “no break” growth rate and (b) the duration of the episode to estimate the difference in output per capita at the end of an episode relative to what it would have been in the “no break” scenario. We use three “counter-factual” growth rates that allow for differing degrees of regression to global average growth: “no change” (zero regression to the mean), “world episode average” (full regression to the mean) and “unconditional predicted growth” (which uses a regression for each growth episode to predict future growth based only on past growth and episode initial level). We can also calculate the net present value at the start of an episode of the gain or loss in output comparing the actual evolution of output per capita versus a counter-factual. This method allows us to place dollar figures on growth episodes. The top 20 growth accelerations have Net Present Value (NPV) magnitude of 30 trillion dollars – twice US GDP. Conversely, the collapse in output in Iran between 1976 and 1988 produced an NPV loss of $143,000 per person. The top 20 growth decelerations account for 35 trillion less in NPV of output. Paraphrasing Lucas, once one begins to think about what determines growth events that cause the appearance or disappearance of output value equal to the total US economy, it is hard to think about anything else.