Papers

Using nationally representative micro panel data on flu incidence from the Medical Expenditure Panel Survey in the United States, we show that employed individuals are on average 35.3% more likely to be infected with the flu virus. Our results are robust to individual characteristics including vaccinations, health insurance, and individual fixed effects. Within the employed, we find significant differences in flu incidence by occupation (e.g., sales occupations show 40.5% higher probability of infection than farmers) and by industry (e.g., education, health, and social services show 52.2% higher probability of infection than mining). Further, we show that the interaction between occupations and industries is important to understand contagion. Indeed, cross-industry differences in flu incidence cannot be fully explained by differences in the within-industry occupation structure. As a potential mechanism for contagion, we study how flu incidence varies with the extent of human contact interaction at work—with an occupation-industry-specific score that we construct based on O*NET occupational characteristics. We find that the higher the human contact at work, the greater are the odds of infection. Our results are larger in years of high aggregate flu incidence and robust to firm size, the number of jobs, and hours worked.

We study the behavior of the US labor share over the past 90 years. We find that the observed decline of the labor share is entirely explained by the capitalization of intellectual property products in the national income and product accounts.

We study the labor share in the OECD corporate sector for the (early) 21st century. Firstly, the cross-country average is trendless over this medium-run horizon after adjusting for intellectual property products (IPP) rents as in Koh et al. (2017). Secondly, the behavior of the labor share is heterogeneous: increasing for equally as many countries (e.g., France and the United Kingdom) as it decreases (e.g., Germany and the United States). Thirdly, the cross-country differences in labor share are driven by the differences in labor productivity growth and not wages.

Using novel microdata, we explore lifecycle consumption in Sub-Saharan Africa (SSA). We find that households' ability to smooth consumption over the lifecycle is large, particularly in rural areas. Interestingly, consumption in old age is sustained by shifting to self-farmed staple food, as opposed to traditional savings mechanisms or food gifts. This smoothing strategy entails two important costs. First, there is a loss of human capital as children are diverted away from school and into producing self-farmed food. Second, a diet largely concentrated in staple food (e.g., maize in Malawi) in old age results in a loss of nutritional quality for households headed by the elderly.

A large literature documents that modern technical change has been skill-biased and contributes to rising wage inequality between skilled and unskilled workers. The literature mainly proxies skill by education, tasks, or occupations, aggregating over heterogeneous underlying skills and potentially obscuring the precise margins along which technology operates. This paper constructs four skill components from O*NET—socio-cognitive, management, STEM, and dexterity—using hierarchical clustering, and develops a framework showing that conventional measures of skill-biased technical change are weighted averages of shifts at the primitive skill level. Applying the framework to two plausibly exogenous technological episodes via a difference-in-differences design, we find that remote work adoption following COVID-19 raises returns to management skills while reducing those for STEM skills, whereas generative AI diffusion following the release of ChatGPT raises returns to socio-cognitive skills. Our findings suggest that effective reskilling policy requires targeting specific primitive skill components rather than broad education or task categories, as different technologies augment and displace fundamentally different skills.

When a husband loses his job, households often count on his wife working more to replace lost earnings, yet the data show that this added-worker effect is limited. Using U.S. household panel data, we document that many households struggle to smooth consumption after male unemployment and that added-worker effects are modest, concentrated on employment participation rather than hours worked. Childcare obligations limit wives' participation responses, while employer-side adjustment frictions appear to bind on hours. We embed these constraints in a two-earner life-cycle model with unemployment risk, childcare time allocation, one-time entry costs, and hours-adjustment frictions, and quantify the welfare value of unemployment insurance (UI). When female labor adjustment is costly, UI improves welfare not only by supplementing lost income but also by reducing households' reliance on costly adjustments to spousal labor supply. Models that assume flexible female labor supply therefore underestimate the welfare gains from UI.

We empirically show that the short-run elasticity of substitution (EOS) between capital and labor is countercyclical. In recessions, capital and labor are more substitutable than in expansions. This countercyclicality of EOS introduces an asymmetry in an otherwise standard competitive-markets business cycle model that contributes to resolving several labor-market puzzles: the labor productivity puzzle, the Dunlop–Tarshis phenomenon, the hours–productivity puzzle, and the labor share puzzle. Interestingly, the cyclicality of EOS is per se not a source of aggregate fluctuations, but it propagates the effects of other shocks.

Following the shocks of the COVID-19 pandemic, the economy may be significantly changed relative to the pre-pandemic world. One critical shift induced by the COVID-19 pandemic is a need for physical distance (at least 6 feet apart) between workers and customers. In this study, we examine the impacts of social distancing in the workplace on employment and productivity across industries. Using our constructed measure of adaptability to social distancing, we empirically find that industries that are more adaptive to social distancing had less decline in employment and productivity during the pandemic. Using this empirical evidence, our model predicts that employment and productivity dispersion would induce labor reallocation across sectors, while imperfect labor mobility may result in a long road to economic recovery.

Easier access to high-performance computing (HPC) systems has enabled parallel computing to become more ubiquitous in numerically solving economic models. For the maximal use of the full capacity of computing power and resources in HPC, it is essential to eliminate parallelization overhead—the additional time required to parallelize a series of tasks to multiple processors. In this study, we demonstrate three parallel computing techniques that effectively reduce the main sources of parallelization overhead in HPC systems.

We document a rise of intellectual property products (IPP) captured by up-to-date national accounts in 31 OECD countries. These countries gradually adopt the new system of national accounts (SNA08) that capitalizes IPP—which was previously treated as an intermediate expense in the pre-SNA93 accounting framework. We examine how the capitalization of IPP affects stylized growth facts and the big ratios (Kaldor, 1957; Jones, 2016). We find that the capitalization of IPP generates (a) a decline of the accounting labor share, (b) an increase in the capital-to-output ratio across time, and (c) an increase in the rate of return to capital across time. The key accounting assumption behind the IPP capitalization implemented by national accounts is that the share of IPP rents that are attributed to capital, φ, is equal to one. That is, national accounts assume that IPP rents are entirely owed to capital. We question this accounting assumption and apply an alternative split of IPP rents between capital and labor based on the cost structure of R&D as in Koh et al. (2018). We find that this alternative split generates a secularly trendless labor share, a constant capital-to-output ratio, and a constant rate of return across time. We discuss the implications of these new measures of IPP capital conditional on φ for cross-country income per capita differences using standard development and growth accounting exercises.