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Portugal
Portugal: Selected Issues
Exposure to Artificial Intelligence and Occupational Mobility: A Cross-Country Analysis
We document historical patterns of workers' transitions across occupations and over the life-cycle for different levels of exposure and complementarity to Artificial Intelligence (AI) in Brazil and the UK. In both countries, college-educated workers frequently move from high-exposure, low-complementarity occupations (those more likely to be negatively affected by AI) to high-exposure, high-complementarity ones (those more likely to be positively affected by AI). This transition is especially common for young college-educated workers and is associated with an increase in average salaries. Young highly educated workers thus represent the demographic group for which AI-driven structural change ...
The Distributional Impacts of Worker Reallocation: Evidence from Europe
Using individual-level data for 30 European countries between 1983 and 2019, we document the extent and earning consequences of workers’ reallocation across occupations and industries and how these outcomes vary with individual-level characteristics, namely (i) education, (ii) gender, and (iii) age. We find that while young workers are more likely to experience earnings gains with on-the-job sectoral and occupational switches, low-skilled workers’ employment transitions are associated with an earnings loss. These differences in earnings gains and losses also mask a high degree of heterogeneity related to trends in routinization. We find that workers, particularly low-skilled and older workers during recessions, experience a severe earning penalty when switching occupations from non-routine to routine occupations.
Gen-AI
Artificial Intelligence (AI) has the potential to reshape the global economy, especially in the realm of labor markets. Advanced economies will experience the benefits and pitfalls of AI sooner than emerging market and developing economies, largely due to their employment structure focused on cognitive-intensive roles. There are some consistent patterns concerning AI exposure, with women and college-educated individuals more exposed but also better poised to reap AI benefits, and older workers potentially less able to adapt to the new technology. Labor income inequality may increase if the complementarity between AI and high-income workers is strong, while capital returns will increase wealth inequality. However, if productivity gains are sufficiently large, income levels could surge for most workers. In this evolving landscape, advanced economies and more developed emerging markets need to focus on upgrading regulatory frameworks and supporting labor reallocation, while safeguarding those adversely affected. Emerging market and developing economies should prioritize developing digital infrastructure and digital skills
Labor Market Exposure to AI: Cross-country Differences and Distributional Implications
This paper examines the impact of Artificial Intelligence (AI) on labor markets in both Advanced Economies (AEs) and Emerging Markets (EMs). We propose an extension to a standard measure of AI exposure, accounting for AI's potential as either a complement or a substitute for labor, where complementarity reflects lower risks of job displacement. We analyze worker-level microdata from 2 AEs (US and UK) and 4 EMs (Brazil, Colombia, India, and South Africa), revealing substantial variations in unadjusted AI exposure across countries. AEs face higher exposure than EMs due to a higher employment share in professional and managerial occupations. However, when accounting for potential complementarity, differences in exposure across countries are more muted. Within countries, common patterns emerge in AEs and EMs. Women and highly educated workers face greater occupational exposure to AI, at both high and low complementarity. Workers in the upper tail of the earnings distribution are more likely to be in occupations with high exposure but also high potential complementarity.
The Macroeconomic and Distributional Implications of Fiscal Consolidations in Low-income Countries
We quantitatively investigate the macroeconomic and distributional impacts of fiscal consolidations in low-income countries (LICs) through value added tax (VAT), personal income tax (PIT), and corporate income tax (CIT). We extend the standard heterogeneous agents incomplete markets model by including multiple sectors and rural-urban distinction to capture salient features of LICs. We find that overall, VAT has the least efficiency costs but is highly regressive, while PIT impacts the economy in the opposite way with CIT staying in between. Cash transfers targeting rural households mitigate the negative distributional impacts of VAT most effectively, while public investment leads to little redistribution.
Promoting Gender Equality and Tackling Demographic Challenges
Two broad contrasting demographic trends present challenges for economies globally: countries with aging populations, often advanced economies and increasingly emerging markets, anticipate a significant shrinking of the labor force, with implications for growth, economic stability, and public finances. Economies with rapidly growing populations, as is the case in many low-income and developing countries, will face a burgeoning young population entering the labor market in the next decades—a large potential to reap the demographic dividend if the right skills and economic and social conditions are in place. This note highlights how gender equality, in both cases, can serve as a stabilizing ...
Recoveries After Pandemics: The Role of Policies and Structural Features
To shed light on the possible scarring effects from Covid-19, this paper studies the economic effects of five past pandemics using local projections on a sample of fifty-five countries over 1990-2019. The findings reveal that pandemics have detrimental medium-term effects on output, unemployment, poverty, and inequality. However, policies can go a long way toward alleviating suffering and fostering an inclusive recovery. The adverse output effects are limited for countries that provided relatively greater fiscal support. The increases in unemployment, poverty, and inequality are likewise lower for countries with relatively greater fiscal support and relatively stronger initial conditions (as defined by higher formality, family benefits, and health spending per capita).
Haiti
Haiti is facing exceptional challenges. While security has deteriorated steadily since the last 2019 Article IV Consultation, it reached crisis proportions in the first few months of 2024. Gangs controlled 80 percent of the capital during March-May 2024, paralyzing economic activity by disrupting supply chains, destroying much infrastructure, and rekindling inflation pressures. The escalation of violence has destroyed human and physical capital and led to a surge in the number of displaced people and greatly accelerated brain drain. The worsened security situation has amplified Haiti’s fragility, compounding its multiple shocks, including the pandemic, a devastating earthquake, political c...
Macroeconomic Research in Low-income Countries
Despite strong economic growth since 2000, many low-income countries (LICs) still face numerous macroeconomic challenges, even prior to the COVID-19 pandemic. Despite the deceleration in real GDP growth during the 2008 global financial crisis, LICs on average saw 4.5 percent of real GDP growth during 2000 to 2014, making progress in economic convergence toward higher-income countries. However, the commodity price collapse in 2014–15 hit many commodity-exporting LICs and highlighted their vulnerabilities due to the limited extent of economic diversification. Furthermore, LICs are currently facing a crisis like no other—COVID-19, which requires careful policymaking to save lives and livelihoods in LICs, informed by policy debate and thoughtful research tailored to the COVID-19 situation. There are also other challenges beyond COVID-19, such as climate change, high levels of public debt burdens, and persistent structural issues.
