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The mounting evidence on the demographics of COVID-19 fatalities points to an overrepresentation of minorities and an underrepresentation of women. Using individual-level, race-disaggregated, and georeferenced death data collected by the Cook County Medical Examiner, we jointly investigate the racial and gendered impact of COVID-19, its timing, and its determinants. Through an event study approach we establish that Blacks individuals are affected earlier and more harshly and that the effect is driven by Black women. Rather than comorbidity or aging, the Black female bias is associated with poverty and channeled by occupational segregation in the health care and transportation sectors and by commuting on public transport. Living arrangements and lack of health insurance are instead found uninfluential. The Black female bias is spatially concentrated in neighborhoods that were subject to historical redlining.

Discussion on the disproportionate impact of COVID-19 on African Americans has been at center stage since the outbreak of the epidemic in the United States. To present day, however, lack of race-disaggregated individual data has prevented a rigorous assessment of the extent of this phenomenon and the reasons why blacks may be particularly vulnerable to the disease. Using individual and georeferenced death data collected daily by the Cook County Medical Examiner, we provide first evidence that race does affect COVID-19 outcomes. The data confirm that in Cook County blacks are overrepresented in terms of COVID-19 related deaths since—as of June 16, 2020—they constitute 35 percent of the dead, so that they are dying at a rate 1.3 times higher than their population share. Furthermore, by combining the spatial distribution of mortality with the 1930s redlining maps for the Chicago area, we obtain a block group level panel dataset of weekly deaths over the period January 1, 2020-June 16, 2020, over which we establish that, after the outbreak of the epidemic, historically lower-graded neighborhoods display a sharper increase in mortality, driven by blacks, while no pretreatment differences are detected. Thus, we uncover a persistence influence of the racial segregation induced by the discriminatory lending practices of the 1930s, by way of a diminished resilience of the black population to the shock represented by the COVID-19 outbreak. A heterogeneity analysis reveals that the main channels of transmission are socioeconomic status and household composition, whose influence is magnified in combination with a higher black share.

In this article we compare two techniques that are widely used in the analysis of life course trajectories, latent class analysis (LCA) and sequence analysis (SA). In particular, we focus on the use of these techniques as devices to obtain classes of individual life course trajectories. We first compare the consistency of the classification obtained via the two techniques using an actual dataset on the life course trajectories of young adults. Then, we adopt a simulation approach to measure the ability of these two methods to correctly classify groups of life course trajectories when specific forms of "random" variability are introduced within pre-specified classes in an artificial dataset. In order to do so, we introduce simulation operators that have a life course and/or observational meaning. Our results contribute on the one hand to outline the usefulness and robustness of findings based on the classification of life course trajectories through LCA and SA, on the other hand to illuminate the potential pitfalls of actual applications of these techniques.

This article provides a picture of long-term developments in the relationship between population and resources in Northern Italy that takes fully into account climate. It analyzes both the slow underlying development of climatic conditions over the centuries  (in the theoretical framework of the Little Ice Age) and the consequences of short-term periods of heightened instability. The most severe famines are shown to be events triggered by climatic and environmental factors operating at a time when the maximum carrying capacity of the system had been reached or, at least, when the population was exerting considerable pressure on the potential for food production. This is the case of the famine of the 1590s, the greatest demographic catastrophe of a non-epidemic nature to strike Northern Italy since the Black Death and up to the end of the eighteenth century. The article also analyzes long-term paths of agrarian innovation, suggesting that most (but not all) of this was consistent with Boserup's idea of chain-reactions of innovations induced by demographic pressure. These processes, though, were too slow to compensate for a rapidly growing population. Finally, the article provides a periodization in which the period between the famine of the 1590s and the great plague pandemic of 1630 is shown to be the crucial turning point in how population dynamics, climate and agrarian innovation interacted.

We consider the case when it is of interest to study the different states experienced over time by a set of subjects, focusing on the resulting trajectories as a whole rather than on the occurrence ofspecific events. Such situation occurs commonly in a variety of settings, for example in social and biomedical studies. Model‐based approaches, such as multistate models or Hidden Markov models, are being used increasingly to analyze trajectories and to study their relationships with a set of explanatory variables. The different assumptions underlying different models typically make the comparison of their performances difficult. In this work we introduce a novel way to accomplish this task, based on microsimulation‐based predictions. We discuss some criteria to evaluate one model and/or to compare competing models with respect to their ability to generate trajectories similar to the observed ones.

In the last few years, the UK has adopted a fiercely competitive business tax policy by reducing the general tax burden on business and expanding individual regimes targeted to mobile factors: CFC rules, interest deductibility rules, and the Patent Box have made the UK very attractive for internationally mobile capital and profits. As the same time, the UK has strongly supported the OECD BEPS project aimed at reducing multinationals’ tax avoidance and, hence, we argue, at eliminating or constraining forms of tax competition among countries based on individual regimes targeted to mobile capital and profits. We claim that, especially in the implementation phase of the BEPS recommendations, there will be tensions between the UK competitiveness agenda and its support for the BEPS. Such tensions will be reconciled by shifting the UK tax competition policy from a mix of rate-based plus individual regimes policy to more of a rate-based approach. In this scenario, the government will have to tighten some specific measures aimed at attracting highly mobile capital and profits, such as the patent box regime and possibly interest deductions. At the same time, it will reduce the tax burden on both mobile and less mobile activities by implementing economy-wide cuts, allowed under BEPS. Most likely, such cuts would come from a further reduction in the headline corporate tax rate and the cuts announced in the July 2015 Budget should be interpreted in this light. Cuts in the headline rate essentially reduce the taxation on profits but they do not take account of the fact that for other decisions such as investment in tangible assets and information and communications technology, other elements of the tax code, such as capital allowances, are more important. To foster real investment, the government could consider an increase in capital allowances. Another option would be the introduction of an Allowance for Corporate Equity (ACE). The interesting feature of the ACE in the context of BEPS is that it reduces the incentive to classify financing instruments as tax-advantaged debt.

ABSTRACT Evidence suggests that the significantly higher life expectancy levels witnessed over the past centuries are associated with a lower concentration of survival times, both cross-country and over time. The purpose of this work is to study the relationships that exist among models for the evolution of survival distributions, longevity measures, and concentration. We first study relationships between concentration and cohort longevity through empirical comparisons. We then propose a family of survival models that can be used to capture such trends in longevity and concentration across survival distributions.

ABSTRACT During the demographic transition that in Europe tended to take place from the early 19th to the end of the 20th century, the population in European countries and its overseas offshoots increased by a factor of five or less, which is low compared to the increase now taking place in most other regions of the world. This study provides simulations showing what global and regional population sizes would be if the rest of the world experienced similar population growth patterns as were observed in Europe. European culture distinguished itself through choices that led to the European marriage pattern, characterized by late marriage, significant shares not marrying, low levels of extramarital childbearing, and comparatively low fertility. One important consequence was the relatively low population growth characterizing the cultures, religions, and ethno-linguistic groups where the European marriage pattern was dominant.

ABSTRACT The aim of this paper is to understand how traditional societies faced a period of general crises and more specifically, which behaviours were adopted to limit the increase of local socio-economic inequality. Thus, this paper focuses on a boundary area (the Geradadda) disputed by Milan and Venice that was constantly crossed and occupied by armies during the long period of the Italian Wars (1494-1559). Analysing the management of local finances, and specifically the local commons, it is possible to show the different ways in which these societies organized themselves and, generally, how economic growth occurred in the early modern period.

ABSTRACT This paper examines how companies’ capital structure is affected by the corporate income tax system. Our analysis employs confidential company-level corporation tax return data in the UK. Our main identification strategy is based on variation in companies␣ marginal tax rates due to the existence of kinks in the corporate tax rate schedule. Using a dynamic adjustment model of capital structure, we find a positive and substantial long-run tax effect on companies' financial leverage. We show that there are considerable discrepancies between estimates of taxable profits reported in tax return data and in financial statements and that the estimated tax effect on capital structure using financial statements is likely to be biased downward. We find that companies adjust their capital structures gradually in response to changes in the marginal tax rate. Moreover, we find that the external leverage of domestic stand-alone companies and of multinational companies responds strongly to corporate tax incentives