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We construct a series of posttax income for France over the 1900–2018 period and compare them with US series. We quantify the extent of redistribution—the reduction from pretax to posttax inequality—and estimate the contribution of redistribution in explaining differences in posttax inequality. We find that differences in pretax inequality drive most of the differences in posttax inequality between France and the United States, and that changes over time in both countries are mostly due to changes in pretax inequality. We highlight that the concept of redistribution can be empirically misleading for judging how policies reduce inequalities.

This paper uses a rich quantitative model with endogenous skill acquisition to show that capital-skill complementarity provides a quantitatively significant rationale to tax capital for redistributive governments. The optimal capital income tax rate is 67 percent, while it is 61 percent in an identically calibrated model without capital-skill complementarity. The skill premium falls from 1.9 to 1.84 along the transition following the optimal reform in the capital-skill complementarity model, implying substantial indirect redistribution from skilled to unskilled workers. These results show that a redistributive government should take into account capital-skill complementarity when taxing capital.

I assess the efficiency of transport networks for every country in Africa. Using spatial data from various sources, I simulate trade flows over more than 70,000 links covering the entire continent. I maximise over the space of networks and find the optimal road system for every African state. My simulations predict that Africa would gain 1.3% of total welfare from reorganising its national road systems, and 0.8% from optimally expanding it by a tenth. I then construct a dataset of local network inefficiency and find that colonial infrastructure projects significantly skew trade networks towards a sub-optimal equilibrium today. I find suggestive evidence that regional favouritism played a role sustaining these imbalances.

We use linked parent-child administrative data for five countries in North America and Europe, as well as detailed survey data for two more, to investigate methodological challenges in the estimation of absolute income mobility. We show that the commonly used "copula and marginals" approximation methods perform well across countries in our sample, and the greatest challenges to their accuracy stem not from assumptions about relative mobility rates over time but from the use of nonrepresentative marginal income distributions. We also provide a multicountry analysis of sensitivity to specification decisions related to age of income measurement, income concept, family structure, and price index.

We estimate long-run trends in intergenerational relative mobility for representative samples of the U.S. - born population. Harmonizing all surveys that include father's occupation and own family income, we develop a mobility measure that allows for the inclusion of non-whites and women for the 1910s-1970s birth cohorts. We show that mobility increases between the 1910s and 1940s cohorts and that the decline of Black-white income gaps explains about half of this rise. We also find that excluding Black Americans, particularly women, considerable overstates the level of mobility for twentieth-century birth cohorts while simultaneously understating its increase between the 1910s and 1940s.

Income inequality and worker migration significantly affect sovereign default risk. Governments often impose progressive taxes to reduce inequality, which redistribute income but discourage labor supply and induce emigration. Reduced labor supply and a smaller high-income workforce erode the current and future tax base, reducing government's ability to repay debt. I develop a sovereign default model with endogenous nonlinear taxation and heterogeneous labor to quantify this effect. In the model, the government chooses the optimal combination of taxation and debt, considering its impact on workers' labor and migration decisions. Income inequality accounts for one-fifth of the average US state government spread.

This paper examines how objective and subjective heterogeneity in life expectancy affects savings behavior of healthy and unhealthy people. Using data from the Health and Retirement Study, we first document systematic biases in survival beliefs across self‐reported health: those in poor health not only have a shorter actual lifespan but also underestimate their remaining life time. To gauge the effect on savings behavior and wealth accumulation, we use an overlapping‐generations model where survival probabilities and beliefs evolve according to a health and survival process estimated from data. We conclude that differences in life expectancy are important to understand savings behavior, and that the belief biases, especially among the unhealthy, can explain up to a fifth of the observed health‐wealth gap.

There are two broad views as to why people stay poor. One emphasizes differences in fundamentals, such as ability, talent, or motivation. The poverty traps view emphasizes differences in opportunities that stem from access to wealth. To test these views, we exploit a large-scale, randomized asset transfer and an 11-year panel of 6,000 households who begin in extreme poverty. The setting is rural Bangladesh, and the assets are cows. The data support the poverty traps view—we identify a threshold level of initial assets above which households accumulate assets, take on better occupations (from casual labor in agriculture or domestic services to running small livestock businesses), and grow out of poverty. The reverse happens for those below the threshold. Structural estimation of an occupational choice model reveals that almost all beneficiaries are misallocated in the work they do at baseline and that the gains arising from eliminating misallocation would far exceed the program costs. Our findings imply that large transfers, which create better jobs for the poor, are an effective means of getting people out of poverty traps and reducing global poverty.

Are slums stepping-stones to better lives or poverty traps? To do so, we will leverage unique administrative data from Brazil alongside an intergenerational quantitative urban model which integrates human capital investment decisions and thus social mobility.

In this project we study ethnic discrimination by states as an organizational problem. To do so, we have collaborated with Peru's anti-corruption agency to accurately characterize differential treatment of public officials.