After a large growth acceleration within the context of the commodity super cycle (2000-2015), Namibia has been grappling with three interrelated challenges: economic growth, fiscal sustainability, and inclusion. Accelerating technological progress and enhancing Namibia’s knowhow agglomeration is crucial to the process of fostering new engines of growth that will deliver progress across the three targets. Using net exports data at the four-digit level, we estimate the economic complexity of Namibia – a measure of knowhow agglomeration – vis-à-vis its peers. Our results suggest that Namibia’s economy is relatively less complex and attractive opportunities to diversify tend to be more distant. Based on economic complexity metrics, we define a place-specific path for productive diversification, identifying industries with high potential and providing inputs – related to their feasibility and attractiveness in Namibia – for further prioritization. Namibia’s path to structural transformation will likely be steeper than for most peers, calling for a more active policy stance geared towards progressive accumulation of productive capacities, well-targeted “long jumps”, and strengthening state capacity to sort out market failures associated with the process of self-discovery.

Economic complexity offers a potentially powerful paradigm to understand key societal issues and challenges of our time. The underlying idea is that growth, development, technological change, income inequality, spatial disparities, and resilience are the visible outcomes of hidden systemic interactions. The study of economic complexity seeks to understand the structure of these interactions and how they shape various socioeconomic processes. This emerging field relies heavily on big data and machine learning techniques. This brief introduction to economic complexity has three aims. The first is to summarize key theoretical foundations and principles of economic complexity. The second is to briefly review the tools and metrics developed in the economic complexity literature that exploit information encoded in the structure of the economy to find new empirical patterns. The final aim is to highlight the insights from economic complexity to improve prediction and political decision-making. Institutions including the World Bank, the European Commission, the World Economic Forum, the OECD, and a range of national and regional organizations have begun to embrace the principles of economic complexity and its analytical framework. We discuss policy implications of this field, in particular the usefulness of building recommendation systems for major public investment decisions in a complex world.

The empirical literature on the contributions of human capital investments to economic growth shows mixed results. While evidence from OECD countries demonstrates that human capital accumulation is associated with growth accelerations, the substantial efforts of developing countries to improve access to and quality of education, as a means for skill accumulation, did not translate into higher income per capita. In this Element, we propose a framework, building on the principles of 'growth diagnostics', to enable practitioners to determine whether human capital investments are a priority for a country's growth strategy. We then discuss and exemplify different tests to diagnose human capital in a place, drawing on the Harvard Growth Lab's experience in different development context, and discuss various policy options to address skill shortages.

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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 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 report is organized in six sections, including this brief introduction. Section 2 is an Executive Summary. Section 3 explains the methodologies of Growth Diagnostics and Economic Complexity, including its theoretical foundations and main concepts. Section 4 describes the main findings of the Economic Complexity Report, including a characterization of Western Australia’s complexity profile. This is done at the state, regional, and city levels. Additionally, this section identifies diversification opportunities with high potential and organizes them into groupings to capture important patterns among the opportunities. This section also contextualizes the opportunities further by identifying relevant viability and attractiveness factors that complement the complexity metrics and consider local conditions. Section 5 highlights the main findings of the Growth Perspective Report. This section describes the economic growth process of Western Australia — with a focus on the past two decades — and identifies several issues with the way that growth has occurred. This section highlights three key channels through which negative externalities have manifested: labor market imbalances, pro-cyclicality of fiscal policy, and a misalignment of public goods. The section provides perspectives on the ways in which each of these channels have hampered the quality of growth and explores the deep-rooted factors that underpin these adverse dynamics. Section 6 introduces a policy framework that can be leveraged by WA to capitalize on revealed diversification opportunities and address the factors that impact the quality of the growth process of the 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.