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 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.
Escaping from Hardship, Searching for Comfort: Climate Matching in Refugees’ Destination Choices
Do refugees settle in destinations that are ecologically similar to their origins? We assess the relevance of “climate matching” theories of migration for Venezuelan refugees in South America. Leveraging social media data, we build and validate the first local bilateral matrix of Venezuelan flows across the region. We measure bilateral ecological similarities in terms of temperature, precipitation, elevation, and distance to the coastline. Performing Poisson Pseudo-Maximum Likelihood gravity models of migration, we show that Venezuelan flows are more likely between ecologically similar areas. Model predictions explain independent measurements of Venezuelans’ settlement choices at both bilateral and destination levels.
The Devil’s in the Dance: Elements of a Growth Diagnostic in Bolivia
Bolivia’s economy stands at a crossroads. Weakened by the fiscal and external imbalances triggered by the 2014 fall in gas prices and exacerbated by the COVID-19 pandemic, the country faces a complex challenge: how to reignite economic growth while restoring macroeconomic stability. This paper applies the Growth Diagnostic methodology to identify the most binding constraints to growth in Bolivia and proposes pathways forward for policy reform.
The paper presents Bolivia’s growth syndrome as “La Diablada” or the dance of the devil—a dance between opposing priorities. On one side lies the need for fiscal consolidation to address mounting imbalances; on the other, an urgent need to stimulate demand and support recovery after the COVID-19 shock. This collision of policy needs creates a situation where missteps in either direction could be highly disruptive, risking either prolonged stagnation or macroeconomic crisis.
The paper finds that Bolivia’s current growth model—heavily reliant on commodity-led rents and public sector-led investment—has reached its limits. The economic challenge is that the historical engine of growth in Bolivia—net government spending fueled by rising gas prices—cannot drive growth in the current period. Even a short-run recovery in gas prices belies the structural challenges in demand for gas exports in Argentina and Brazil, along with the supply of gas, in the lack of investments in new discovery. Structural weaknesses also include a rising wage bill dominated by public employment, the lack of foreign investment, and a lack of economic diversification into higher complexity sectors. Political uncertainty and institutional inefficiencies, especially among state-owned enterprises (SOEs), further erode the country’s fiscal space and growth potential.
To manage current macroeconomic imbalances and lay the groundwork for inclusive growth, the government must prioritize the sequencing of actions across four key policy fronts:
- Fiscal Response: Focus on increasing fiscal space to allow for stimulus to drive economic recovery, including smart fiscal consolidation, cutting unproductive spending—especially in loss-making SOEs and an inflated wage bill, while guarding against the recessionary pressures of fiscal consolidation.
- External Finance Response: Maximize access to external finance while balancing debt sustainability. Foreign reserves risk not being able to cover medium-term debt obligations, if no action is taken.
- Monetary Response: Restore confidence in monetary policy by preparing for a gradual move toward a more flexible exchange rate regime, supported by stronger institutions and clearer communication. Not addressing the overvalued boliviano risks a currency crisis, a balance of payments crisis, or both.
- Private Sector Response: Shift the growth model by enabling private sector-led diversification, removing investment bottlenecks, and targeting support to export-oriented, higher-complexity sectors.
At stake is whether Bolivia can shift from managing crises to enabling a more resilient, inclusive, and sustainable future.
Last updated on 05/20/2025
On Globalization and the Concentration of Talent: A General Result on Superstar Effects and Matching
We analyze how globalization affects the allocation of talent across competing teams in large matching markets. Focusing on amplified superstar effects, we show that a convex transformation of payoffs promotes positive assortative matching. This result holds under minimal assumptions on how skills translate into competition outcomes and how competition outcomes translate into payoffs. Our analysis covers many interesting special cases, including simple extensions of Rosen (1981) and Melitz (2003) with competing teams. It also provides new insights on the distributional consequences of globalization, and on the role of technological change, urban agglomeration, and taxation for the composition of teams.
Quality Differentiation, Comparative Advantage, and International Specialization Across Products
We introduce quality differentiation into a Ricardian model of international trade. We show that (1) quality differentiation allows industrialized countries to be active across the full board of products, complex and simple ones, while developing countries systematically specialize in simple products, in line with novel stylized facts. (2) Quality differentiation may thus help to explain why richer countries tend to be more diversified and why, increasingly over time, rich and poor countries tend to export the same products. (3) Quality differentiation implies that the gains from inter-product trade mostly accrue to developing countries. (4) Guided by our theory, we use a censored regression model to estimate the link between a country’s GDP per capita and its export quality. We find a much stronger relationship than when using OLS, in line with our theory.
Profit Sharing, Industrial Upgrading, and Global Supply Chains: Theory and Evidence
This paper constructed a simple model to illustrate the global supply chain profit sharing and industrial upgrading mechanism, from which it was found that the average profitability distribution in the different supply chain stages was determined by two main factors: (1) the average product of the labor in the firms at each production stage; and (2) the ratio of the output elasticity of capital to the output elasticity of labor in each stage. This paper also proposed a new industrial upgrading mechanism, the ‘inter-supply chain upgrading’, for supply chain firms. Rises in production complexity and increased factor intensity in each production stage were found to be the two essential conditions for the inter-supply chain upgrading. The empirical study results were found to be broadly consistent with the proposed theories.
Automation, Skills Use and Training
This study focuses on the risk of automation and its interaction with training and the use of skills at work. Building on the expert assessment carried out by Carl Frey and Michael Osborne in 2013, the paper estimates the risk of automation for individual jobs based on the Survey of Adult Skills (PIAAC). The analysis improves on other international estimates of the individual risk of automation by using a more disaggregated occupational classification and identifying the same automation bottlenecks emerging from the experts’ discussion. Hence, it more closely aligns to the initial assessment of the potential automation deriving from the development of Machine Learning. Furthermore, this study investigates the same methodology using national data from Germany and United Kingdom, providing insights into the robustness of the results.
The risk of automation is estimated for the 32 OECD countries that have participated in the Survey of Adult Skills (PIAAC) so far. Beyond the share of jobs likely to be significantly disrupted by automation of production and services, the accent is put on characteristics of these jobs and the characteristics of the workers who hold them. The risk is also assessed against the use of ICT at work and the role of training in helping workers transit to new career opportunities.
Social Networks and the Intention to Migrate
Using a large individual-level survey spanning several years and more than 150 countries, we examine the importance of social networks in influencing individuals’ intention to migrate internationally and locally. We distinguish close social networks (composed of friends and family) abroad and at the current location, and broad social networks (composed of same-country residents with intention to migrate, either internationally or locally). We find that social networks abroad are the most important driving forces of international migration intentions, with close and broad networks jointly explaining about 37% of variation in the probability intentions. Social networks are found to be more important factors driving migration intentions than work-related aspects or wealth (wealth accounts for less than 3% of the variation). In addition, we nd that having stronger close social networks at home has the opposite effect by reducing the likelihood of migration intentions, both internationally and locally.
Last updated on 12/10/2021
Is Our Human Capital General Enough to Withstand the Current Wave of Technological Change?
The degree to which modern technologies are able to substitute for groups of job tasks has renewed fears of near-future technological unemployment. We argue that our knowledge, skills and abilities (KSA) go beyond the specific tasks we do at the job, making us potentially more adaptable to technological change than feared. The disruptiveness of new technologies depends on the relationships between the job tasks susceptible to automation and our KSA. Here we first demonstrate that KSA are general human capital features while job tasks are not, suggesting that human capital is more transferrable across occupations than what job tasks would predict. In spite of this, we document a worrying pattern where automation is not randomly distributed across the KSA space – it is concentrated among occupations that share similar KSA. As a result, workers in these occupations are making longer skill transitions when changing occupations and have higher probability of unemployment.
Fool’s Gold: On the Impact of Venezuelan Devaluations in Multinational Stock Prices
This paper documents negative cumulative abnormal returns (CARs) to five exchange rate devaluations in Venezuela within the context of stiff exchange controls and large black-market premiums, using daily stock prices for 110 multinationals with Venezuelan subsidiaries. The results suggest evidence of statistically and economically significant negative CARs of up to 2.07% over the ten-day event window. We find consistent results using synthetic controls to causally infer the effect of each devaluation on the stock prices of global firms active in the country at the time of the event. Our results are at odds with the predicaments of the efficient market hypothesis stating that predictable devaluations should not impact stock prices of large multinational companies on the day of the event, and even less so when they happen in small countries. We interpret these results as suggestive indication of market inefficiencies in the process of asset pricing.