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Working Papers
Complexity: Hausmann-Hidalgo Economic Complexity
Economic complexity is an active field with a growing number of methodologies and applications. Among the different paradigms, the Hausmann-Hidalgo economic complexity framework offers a way to quantify the sophistication […]
Economic complexity is an active field with a growing number of methodologies and applications. Among the different paradigms, the Hausmann-Hidalgo economic complexity framework offers a way to quantify the sophistication and productive knowledge embedded in an economy. In this work, we provide an overview of its foundational concepts, empirical applications, policy uses, and directions for future research. We aim to equip readers with a basic understanding of this framework in simple words and to help them navigate the vast literature. We argue that the Hausmann-Hidalgo economic complexity serves as a flexible framework for understanding the dynamics of knowledge diversification across multiple economic domains and provides a starting point for the design of place-based policies. -
Working Papers
Japan’s Innovation Challenge: Escaping the Middle-Technology Trap
Japan remains one of the world’s most technologically sophisticated economies, yet its labor productivity has been stagnant for more than two decades. This paper investigates the apparent contradiction between Japan’s high R&D intensity and its weak productivity performance by examining the allocation, composition, and effectiveness of innovation across industries.
Japan remains one of the world’s most technologically sophisticated economies, yet its labor productivity has been stagnant for more than two decades. This paper investigates the apparent contradiction between Japan’s high R&D intensity and its weak productivity performance by examining the allocation, composition, and effectiveness of innovation across industries. Using industry-level data from the OECD, patent-level data linked across technology and industry classifications, and a set of nine technological taxonomies, we document that Japan disproportionately concentrates R&D in mid-technology manufacturing sectors—such as motor vehicles, electrical equipment, and chemicals—that generate relatively low productivity spillovers. High-technology sectors, including ICT, pharmaceuticals, scientific R&D, and advanced digital services, receive a significantly smaller share of investment and exhibit much higher productivity contributions in other countries. We further show that Japan’s indirect, tax-based system of R&D support reinforces this equilibrium by favoring large incumbents and under-supporting SMEs. We conclude by assessing the potential of Japan’s new 17-sector strategy to reorient the innovation system toward frontier technologies. -
Working Papers
AI Meets Trade: Global Linkages and the Cross-country Distribution of the Gains from AI
This paper provides estimates of expected per capita real income gains from AI over the next decade in OECD and G20 economies. It relies on a multi-country, multi-sector general equilibrium […]This paper provides estimates of expected per capita real income gains from AI over the next decade in OECD and G20 economies. It relies on a multi-country, multi-sector general equilibrium model to incorporate the role of international trade and considers different scenarios regarding AI adoption paths and AI capabilities. In our central scenario, AI-driven productivity gains vary widely across countries and are expected to raise per capita real income growth by 0.1–0.95 percentage points annually. The model’s dynamics reveal a key insight: while countries lagging in AI adoption can gain from cheaper, AI-intensive imports generated by global diffusion, maintaining competitiveness – especially in highly AI-exposed sectors – ultimately requires strong domestic AI adoption. As a further channel, the paper quantifies the welfare effects generated by international knowledge spillovers boosting AI adoption of countries with relatively lower AI adoption.
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Working Papers
Mapping Economic Opportunities in Global Clean Energy Supply Chains
The energy transition offers countries that can manufacture clean energy technologies substantial opportunities for sustainable economic growth. This paper provides a framework for context-aware industrial policy by applying economic complexity […]
The energy transition offers countries that can manufacture clean energy technologies substantial opportunities for sustainable economic growth. This paper provides a framework for context-aware industrial policy by applying economic complexity theory to a newly constructed dataset of twelve key clean energy supply chains (CESCs). We find that CESCs are diverse but highly interdependent; they are also growing faster and are more concentrated than other industries. CESCs exhibit substantial entry, exit and competitive churn, and countries are more likely to enter CESC industries that are related to their existing productive capabilities. We also explore changing global competitiveness and country positioning in these industries, and draw out implications of these patterns for industrial policymakers. -
Reports
Innovation Capabilities Outlook 2026
Knowledge is expanding globally, yet most countries struggle to harness this growth effectively. Global innovation remains strikingly concentrated: a small number of leading economies account for the vast majority of […]Knowledge is expanding globally, yet most countries struggle to harness this growth effectively. Global innovation remains strikingly concentrated: a small number of leading economies account for the vast majority of scientific publications, patents, trademarks, and advanced exports, whereas most contribute less than 1 percent to any innovation dimension. Success does not require a big push in all fields, but instead lies in strategically diversifying into complex skills while at the same time maintaining intensity in high-value areas – a balancing act that only the most sophisticated innovation ecosystems have mastered.
Mapping the global innovation landscape
The Innovation Capabilities Outlook (ICO) 2026 analyzes 2,508 innovation capabilities across four dimensions – science, technology, entrepreneurship, and production – using comprehensive datasets spanning 2001–2023. The analysis reveals that innovation emergence depends critically on connections between these four dimensions, with the most sophisticated capabilities emerging only in highly diversified ecosystems able to support complex, interdependent knowledge networks.A tale of two innovation worlds
Global innovation output has expanded dramatically, yet this growth remains highly uneven and concentrated in no more than 30 percent of the world’s economies. Asian economies – led by China, India and Viet Nam – have mastered sophisticated capability development strategies, consistently achieving both smart diversification (gaining breadth and complexity simultaneously) and smart capability management (intensifying focus on high-value skills while protecting them with complementary knowledge). In contrast, many established and emerging economies struggle with this dual challenge: 46 percent of ecosystems have not meaningfully diversified, and complexity gains remain elusive for 70 percent of economies.Strategic opportunities
The ICO 2026 identifies substantial untapped potential – only 10 percent of economies fulfill their technological potential. Ecosystems collectively underperform by 339,000 technological innovations annually. Regional patterns reveal distinct strategic pathways: Europe possesses strong foundations, but struggles with technological translation; Asia shows balanced capabilities, but faces entrepreneurial commercialization challenges; and Africa should focus on foundational capability building while gradually targeting more complex activities.Policy implications
Innovation policy cannot rely on one-size-fits-all approaches. Success requires tailoring strategies to regional development levels, existing capability portfolios, and institutional contexts. Countries that align innovation investments with these evidence-based insights can break traditional development constraints and accelerate a transition toward knowledge-based competitiveness. The systematic nature both of diversification constraints and untapped potential suggests that targeted, level-appropriate interventions yield the highest probability of success.The Innovation Capabilities Outlook 2026 was developed through a partnership between WIPO and Harvard University’s Growth Lab (HGL), under the general direction of Daren Tang (Director General) and Marco Alemán (Assistant Director General). The report was supervised by Carsten Fink (Chief Economist) and Ricardo Hausmann (founder and Director of HGL), prepared by a team led by Julio Raffo (Head of Innovation Economy Section, WIPO) and Muhammed A. Yildirim (Director of Academic Research, HGL). The team included Christian Chacua, Matte Hartog, Shreyas Gadgin Matha, and Federico Moscatelli.
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Journal Articles
Bridging the short-term and long-term dynamics of economic structural change
Nature Communications, 16
Economic development hinges on structural change, that is, transformations in what an economy produces. The field of economic complexity has investigated this process through two related but distinct branches: one […]
Economic development hinges on structural change, that is, transformations in what an economy produces. The field of economic complexity has investigated this process through two related but distinct branches: one studying how economies diversify, the other how the complexity of an economy is reflected in its output. However, a formal connection between these approaches, and their relationship to classic accounts of structural transformation (for example, from agriculture to manufacturing), remains unclear. Here we introduce a simple dynamical model that links these perspectives through one core idea: economies diversify preferentially into activities related to those they already do. Studying this model yields three main results: It generates quantities resembling economic complexity metrics, suggests these metrics summarize long-term structural change rather than directly infer an economy’s complexity, and reproduces stylized facts of development. Our framework formally connects the field’s conceptual strands, bridges short and long timescales of change, and adds granularity to classic descriptions of development.
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Journal Articles
The Coherence of US Cities
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 122
Diversified economies are critical for cities to sustain their growth and development, but they are also costly because diversification often requires expanding a city’s capability base. We analyze how cities […]
Diversified economies are critical for cities to sustain their growth and development, but they are also costly because diversification often requires expanding a city’s capability base. We analyze how cities manage this trade-off by measuring the coherence of the economic activities they support, defined as the technological distance between randomly sampled productive units in a city. We use this framework to study how the US urban system developed over almost two centuries, from 1850 to today. To do so, we rely on historical census data, covering over 600M individual records to describe the economic activities of cities between 1850 and 1940, as well as 8 million patent records and detailed occupational and industrial profiles of cities for more recent decades. Despite massive shifts in the economic geography of the United States over this 170-year period, average coherence in its urban system remains unchanged. Moreover, across different time periods, datasets, and relatedness measures, coherence falls with city size at the exact same rate, pointing to constraints to diversification that are governed by a city’s size in universal ways.
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Working Papers
Global Networks, Monetary Policy and Trade
We develop a novel framework to study the interaction between monetary policy and trade. Our New Keynesian open economy model incorporates international production networks, sectoral heterogeneity in price rigidities, and […]We develop a novel framework to study the interaction between monetary policy and trade. Our New Keynesian open economy model incorporates international production networks, sectoral heterogeneity in price rigidities, and trade distortions. We decompose the general equilibrium response to trade shocks into distinct channels that account for demand shifts, policy effects, exchange rate adjustments, expectations, price stickiness, and input–output linkages. Tariffs act simultaneously as demand and supply shocks, leading to endogenous fragmentation through changes in trade and production network linkages. We show that the net impact of tariffs on domestic inflation, output, employment, and the dollar depends on the endogenous monetary policy response in both the tariff-imposing and tariff-exposed countries, within a global general equilibrium framework. Our quantitative exercise replicates the observed effects of the 2018 tariffs on the U.S. economy and predicts a 1.6 pp decline in U.S. output, a 0.8 pp rise in inflation, and a 4.8% appreciation of the dollar in response to a retaliatory trade war linked to tariffs announced on “Liberation Day.” Tariff threats, even in the absence of actual implementation, are self-defeating— leading to a 4.1% appreciation of the dollar, 0.6% deflation, and a 0.7 pp decline in output, as agents re-optimize in anticipation of future distortions. Dollar appreciates less or even can depreciate under retaliation, tariff threats, and increased global uncertainty.
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Working Papers
De Facto Openness to Immigration
Various factors influence why some countries are more open to immigration than others. Policy is only one of them. We design country-specifc measures of openness to immigration that aim to […]Various factors influence why some countries are more open to immigration than others. Policy is only one of them. We design country-specifc measures of openness to immigration that aim to capture de facto levels of openness to immigration, complementing existing de jure measures of immigration, based on enacted immigration laws and policy measures. We estimate these for 148 countries and three years (2000, 2010, and 2020). For a subset of countries, we also distinguish between openness towards tertiary-educated migrants and less than tertiary-educated migrants. Using the measures, we show that most places in the World today are closed to immigration, and a few regions are very open. The World became more open in the first decade of the millennium, an opening mainly driven by the Western World and the Gulf countries. Moreover, we show that other factors equal, countries that increased their openness to immigration, reduced their old-age dependency ratios, and experienced slower real wage growth, arguably a sign of relaxing labor and skill shortages.
Explore the country rankings in our interactive visualization website and learn more about the project, Leveraging the Global Talent Pool to Jumpstart Prosperity in Emerging Economies.
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Working Papers
A New Algorithm to Efficiently Match U.S. Census Records and Balance Representativity with Match Quality
We introduce a record linkage algorithm that allows one to (1) efficiently match hundreds of millions of records based not just on demographic characteristics but also name similarity, (2) make […]We introduce a record linkage algorithm that allows one to (1) efficiently match hundreds of millions of records based not just on demographic characteristics but also name similarity, (2) make statistical choices regarding the trade-off between match quality and representativity and (3) automatically generate a ground truth of true and false matches, suitable for training purposes, based on networked family relationships. Given the recent availability of hundreds of millions of digitized census records, this algorithm significantly reduces computational costs to researchers while allowing them to tailor their matching design towards their research question at hand (e.g. prioritizing external validity over match quality). Applied to U.S Census Records from 1850 to 1940, the algorithm produces two sets of matches, one designed for representativity and one designed to maximize the number of matched individuals. At the same level of accuracy as commonly used methods, the algorithm tends to have a higher level of representativity and a larger pool of matches. The algorithm also allows one to match harder-to-match groups with less bias (e.g. women whose names tend to change over time due to marriage).