Estimating the capabilities, or inputs of production, that drive and constrain the economic development of urban areas has remained a challenging goal. We posit that capabilities are instantiated in the complexity and sophistication of urban activities, the know-how of individual workers, and the city-wide collective know-how. We derive a model that indicates how the value of these three quantities can be inferred from the probability that an individual in a city is employed in a given urban activity. We illustrate how to estimate empirically these variables using data on employment across industries and metropolitan statistical areas in the USA. We then show how the functional form of the probability function derived from our theory is statistically superior when compared with competing alternative models, and that it explains well-known results in the urban scaling and economic complexity literature. Finally, we show how the quantities are associated with metrics of economic performance, suggesting our theory can provide testable implications for why some cities are more prosperous than others.

A little over a year ago, the EU’s political leaders agreed on an unprecedented fiscal package – dubbed ‘Next Generation EU’ – to aid Europe’s recovery from the pandemic. Ricardo Hausmann, Miguel Angel Santos, Corrado Macchiarelli and Renato Giacon write that economic complexity theories can provide a useful tool for evaluating whether the recovery and resilience plans submitted by EU member states to receive this funding are well-designed. Assessing the case of Greece, they argue that investments should be tailored toward export-oriented sectors and aim to help close the country’s product complexity gap with other EU states. 

The Growth Lab at Harvard University, with funding provided by the Gordon and Betty Moore Foundation, has undertaken this investigation with the aim of identifying the existing productive capacities in Loreto, as well as the economic activities with potential to drive the structural transformation of its economy. This paper is part of a broader investigation – Promoting Sustainable Economic Growth and Structural Transformation in the Amazon Region of Loreto, Peru – which seeks to contribute with context-specific inputs for the development of national and sub-national public policies that promote productive development and prosperity in this Peruvian state.

The Government of Western Australia (WA), acting through its Department of Primary Industries and Regional Development (DPIRD), invited the Growth Lab of the Center for International Development (CID) at Harvard University to partner with the state to better understand and address constraints to economic diversification through a collaborative applied research project. The project seeks to apply growth diagnostic and economic complexity methodologies to inform policy design in order to accelerate productive transformation, economic diversification, and more inclusive and resilient job creation across Western Australia.

This Economic Complexity Report is organized in six sections, including this brief introduction. Section 2 explains the methodology of economic complexity, including its theoretical foundations and main concepts, as well as the adjustments that were required to obtain the required export data at a subnational level and incorporate the service sector to the analysis. Section 3 describes the structure of the WA economy, identifying its productive capacities and exploring its complexity profile. This is done at the state, regional, and city levels. Section 4 identifies industries with high potential and organizes them into groupings to capture important patterns among the opportunities. Section 5 contextualizes the opportunities further by identifying relevant viability and attractiveness factors that complement the complexity metrics and consider local conditions, as well as a criterion for regional participation in the state-wide diversification strategy. Finally, Section 6 summarizes the main findings of this report and discusses implications for Government of WA strategy and policy toward capitalizing on these revealed opportunities.

Assignment models in trade predict that countries with higher productivity levels are assortatively matched to industries that make better use of these higher levels. Here, we assume that the driver of productivity differences is the differential distribution of factors among countries. Utilizing such a structure, we define and estimate the average factor level (AFL) for countries and products using only the information about the production patterns. Interestingly, our estimates coincide with the complexity variables of (Hidalgo and Hausmann, 2009), providing an underlying economic rationale. We show that AFL is highly correlated with country-level characteristics and predictive of future economic growth.

The literature on wage gaps between Chiapas and the rest of Mexico revolves around individual factors, such as education and ethnicity. Yet, twenty years after the Zapatista rebellion, the schooling gap has shrunk while the wage gap has widened, and we find no evidence indicating that Chiapas indigenes are worse-off than their likes elsewhere in Mexico. We explore a different hypothesis and argue that place-specific characteristics condition the choices and behaviors of individuals living in Chiapas and explain persisting income gaps. Most importantly, they limit the necessary investments at the firm level in dynamic capabilities. Based on census data, we calculate the economic complexity index, a measure of the knowledge agglomeration embedded in the economic activities at the municipal level. Economic complexity explains a larger fraction of the wage gap than any individual factor. Our results suggest that the problem is Chiapas, and not Chiapanecos.

Economic development depends on the accumulation of know-how. The theory of economic growth has long emphasised the importance of something called technical progress, but what that is, and how it grows has not been well elucidated. Technical progress is really based on three separate aspects: tools, or embodied knowledge, recipes or blueprints or codified knowledge and know-how or tacit knowledge. While tools can be shipped and codes can be e-mailed, know-how exists only as a particular wiring of the brain and as such it is hard to move around. That is why the growth of know-how can easily become the binding constraint on the development process.

We analyze Ukraine's opportunities to participate in European value chains, using traditional gravity models, combined with tools from Economic Complexity Analysis to study international trade (exports) and Foreign Direct Investment (FDI). This toolbox is shown to be predictive of the growth and entry of new exports to the EU's Single Market, as well as foreign direct investments from the Single Market in Ukraine. We find that Ukraine has suffered from a decline of trade with Russia, which has led not only to a quantitative but also a qualitative deterioration in Ukrainian exports. Connecting to western European value chains is in principle possible, with several opportunities in the automotive, information technology and other sectors. However, such a shift may lead to a spatial restructuring of the Ukrainian economy and a mismatch between the geographical supply of and demand for labor.

El Laboratorio de Crecimiento de la Universidad de Harvard, bajo el auspicio de la Fundación Gordon and Betty Moore, ha desarrollado esta investigación para identificar las capacidades productivas existentes en Loreto y las actividades económicas con potencial para liderar la transformación estructural de su economía. Este reporte forma parte de una investigación más amplia – Transformación estructural y restricciones limitantes a la prosperidad en Loreto, Perú – que busca aportar insumos para el desarrollo de políticas públicas a escala nacional y regional que contribuyan a promover el desarrollo productivo y la prosperidad de la región, tomando en cuenta sus características particulares.