This paper provides an analytical characterization of Markov perfect equilibria in a model with repeated voting, where agents vote over distortionary income redistribution. A key result is that the future constituency for redistributive policies depends positively on current redistribution, since this affects both private investments and the future distribution of voters. The model features multiple equilibria. In some equilibria, positive redistribution persists forever. In other equilibria, even a majority of beneficiaries of redistribution vote strategically so as to induce the end of the welfare state next period. Skill-biased technical change makes the survival of the welfare state less likely.

We develop a model where the allocation of human resources, intergenerational social mobility, and technological growth are jointly determined. High growth endogenously increases the equilibrium return to innate cognitive ability and makes the allocation of individuals depend more on innate ability and less on social background. Individuals with a higher level of innate cognitive ability can deal better with less known, bur more productive, technologies and thus choose a higher rate of technological growth. A social allocation based on innate ability and high growth will thus reinforce each other, implying the possibility of multiple endogenous growth equilibrium.

Payments systems generate vast amounts of naturally occurring transaction data rarely used for constructing official statistics. We consider billions of transactions from card data from a large bank, Banco Bilbao Vizcaya Argentaria, as an alternative source of information for measuring consumption. We show, via validation against official consumption measures, that transaction data complements national accounts and consumption surveys. We then analyse the impact of COVID-19 in Spain, and document: (i) strong consumption responses to business closures, but smaller effects for capacity restrictions; (ii) a steeper decline in spending in rich neighbourhoods; (iii) higher mobility for residents of lower-income neighbourhoods, correlating with increased disease incidence.

We propose a new methodology for measuring intergenerational mobility in economic wellbeing. Our method is based on the joint distribution of surnames and economic outcomes. It circumvents the need for intergenerational panel data, a long-standing stumbling block for understanding mobility. It does so by using cross-sectional data alongside a calibrated structural model in order to recover the traditional intergenerational elasticity measures. Our main idea is simple. If 'inheritance' is important for economic outcomes, then rare surnames should predict economic outcomes in the cross-section. This is because rare surnames are indicative of familial linkages. If the number of rare surnames is small this approach will not work. However, rare surnames are abundant in the highly-skewed nature of surname distributions from most Western societies. We develop a model that articulates this idea and shows that the more important is inheritance, the more informative will be surnames. This result is robust to a variety of different assumptions about fertility and mating. We apply our method using the 2001 census from Catalonia, a large region of Spain. We use educational attainment as a proxy for overall economic well-being. A calibration exercise results in an estimate of the intergenerational correlation of educational attainment of 0.60. We also find evidence suggesting that mobility has decreased among the different generations of the 20th century. A complementary analysis based on sibling correlations confirms our results and provides a robustness check on our method. Our model and our data allow us to examine one possible explanation for the observed decrease in mobility. We find that the degree of assortative mating has increased over time. Overall, we argue that our method has promise because it can tap the vast mines of census data that are available in a heretofore unexploited manner.