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• The Bolsonaro administration and its class allies used the pandemic as a political opportunity and the state as a tool to advance dispossessions. • Dispossessions such as debt interest payments or privatizations simply redistribute surpluses or means of production, with no impact on capital expansion. • Dispossessions of peasants or indigenous people from lands and forests expand capital by turning their means of subsistence into means of capitalist production. • The transfer to for-profit companies of public services, facilities, or spaces turns means of subsistence into commodities and thus expands capital. • Capitalization, commodification, or the termination of contemporary commons reduce means of subsistence and thus increase the availability of exploitable labor-power. In 2020–2021 Brazil simultaneously experienced the far-right presidency of Jair Bolsonaro and the world's largest health crisis in a century. The Covid-19 pandemic struck the country deeply, killing about 690 thousand people by late 2022. They were also years of increased pressure by capital on peasants and indigenous people, targets of the violence with which capital, ever since its dawn, has wielded to advance over spaces that serve the subsistence of immediate producers. In this period, the Brazilian state continued to comply with decades-old demands from neoliberal ideology for privatizations and the dismantling of protections for workers and the poor in general. These phenomena, when articulated by theory inspired by the Marxian concept of primitive accumulation, suggest that the Bolsonaro administration and its class allies used the pandemic as a political opportunity for dispossessing policies. The article discusses this based on concepts that distinguish dispossessions that serve capital expansion from those that do not. The first group includes processes that lead to proletarianization of immediate producers in addition to the capitalization or commodification of hitherto means of subsistence. Among dispossessions that do not expand capital are those that involve the simple redistribution of surpluses or means of production. The paper contributes to the literature on dispossession by analyzing concrete manifestations of it, drawing on a conceptual framework that distinguishes dispossession types that have been conflated in much current research. [ABSTRACT FROM AUTHOR]

• This paper estimates the effect of a limit on police use of force on violence – both police and civilian violence – in Rio de Janeiro, Brazil. • Police killings and shootings plummeted after the limit. I argue that the internal oversight effectively tied the police's hands in the short run. • Civilian homicides, usually associated with organized crime, also fell. I show two ways that less police violence can slow criminal conflict. • A key takeaway is that restraining the police in high-crime settings may lower violence, both that committed by police and by criminal groups. • These results cast doubt on the efficacy of hard-on-crime policies and suggest that more police restraint, at a minimum, does no harm. Governments in the Americas rely on aggressive policing tactics to fight crime, despite scant evidence of impact. While recent studies depict militarized policing as a driver of violence, few governments have reconsidered their use of it. What impact does a restriction on aggressive policing have on violence, and why? This paper examines limits on police use of force and how they can be implemented to reduce both police and civilian violence. I argue that reforms that require internal, non-police oversight can be effective institutional constraints, minimizing police violence. In settings where organized crime is widespread, these limits can have spillover effects and further decrease civilian violence by (1) slowing the territorial diffusion of criminal conflict and (2) making conflict more predictable. I test these claims by examining an abrupt limit on police raids in Rio de Janeiro, Brazil. I find that limiting raids – militarized police strikes targeting criminal gangs and communities under their control – led to a 66% decrease in police killings and a 58% decrease in homicides. The effects were concentrated in police precincts where rival criminal groups are in close proximity. Limiting raids did not lead police to be more violent during ordinary patrolling duties, and did not affect property crimes. The implication is that restraining police use of force in high-violence settings may save lives and be no worse than hard-on-crime strategies. [ABSTRACT FROM AUTHOR]

There are growing concerns that automation technology may have far-reaching implications for development, by restructuring global value chains and substituting workers. This paper investigates how domestic and foreign automation impact a resource-rich emerging economy. The empirical analysis builds on a Ricardian model of trade and a shift-share approach. Differences in regional industrial compositions are used to translate domestic industry-level robot adoption to local labor markets in Brazil. Differential trade and inter-sectoral input–output linkages between a foreign industry and regions in Brazil are leveraged to construct a measure of exposure to foreign automation. Instrumental variables account for endogeneity in robot adoption. Larger exposure to foreign automation is found to decrease the share of manufacturing employment and increase the share of employment in the mining sector. These shifts are driven by changes in the demand for export goods from local labor markets. Domestic automation benefits higher skilled and female workers. The findings suggest that foreign automation may contribute to "premature deindustrialization" in emerging economies. • This study examines the effects of automation technology adoption by domestic and trade-partner industries on employment in 557 regions of Brazil. • The empirical analysis is grounded on a Ricardian model of trade, and instrumental variables account for endogeneity in robot adoption. • Automation in trade-partner countries reduces the employment share in manufacturing, while increasing employment shares in the mining sector. • The same pattern is found for sectoral and regional exports, suggesting that shifts in the demand for export goods are causing employment changes. • Automation within Brazil increases the ratio of female and higher-skilled workers, indicating skill complementary with the robot technology. [ABSTRACT FROM AUTHOR]

• We study the associations between Short-Cycle Programs quality determinants and student academic and labor market outcomes. • We use multiple data sources from five Latin American countries on quality determinants and academic and labor market outcomes. • Quality determinants account for a substantial share of explained variation in student-level academic and labor market outcomes. • We identify quality determinants favoring academic and labor market outcomes and show how they might help reduce quality gaps. Short-cycle higher education programs (SCPs) can play a central role in skill development and higher education expansion, yet their quality varies greatly within and among countries. In this paper, we explore the relationship between programs' practices and inputs (quality determinants) and student academic and labor market outcomes. We design and conduct a novel survey to collect program-level information on quality determinants and average outcomes for Brazil, Colombia, Dominican Republic, Ecuador, and Peru. Categories of quality determinants include training and curriculum, infrastructure, faculty, link with productive sector, costs and funding, and practices on student admission and institutional governance. We also gather administrative student-level data on higher education and formal employment for SCP students in Brazil and Ecuador and match it to survey data. Using machine learning methods, we select the quality determinants that predict outcomes at the program and student levels. We show that specific quality determinants may favor academic and labor market outcomes. Two practices predict improvements in all labor market outcomes in Brazil and Ecuador—teaching numerical competencies and providing job market information—and one practice—teaching numerical competencies—additionally predicts improvements in labor market outcomes for all survey countries. Since quality determinants account for 20–40 percent of the explained variation in student-level outcomes, quality determinants might have a role shrinking program quality gaps. These findings have implications for the design and replication of high-quality SCPs, their regulation, and the development of information systems. [ABSTRACT FROM AUTHOR]

• Paper studies wages differentials across levels of governments in Brazil, Mexico, and Uruguay. • National government employees earn on average higher wages than observationally similar subnational employees, but difference disappears once individual heterogeneity is considered. • National and subnational public employees receive on average a wage premium with respect to private sector employment. • Results indicate public sector employees are positively selected in terms of their earnings potential in the private sector. Workers at subnational governments play a prominent role in the delivery of public services in most countries. Yet, information about their remuneration is scarce. Using data for Brazil, Mexico and Uruguay, we document that national government employees earn on average higher wages than observationally similar subnational employees; consequently, public–private sector wage gaps vary significantly by level of government. Then we use individual fixed-effects to estimate the wage premium to public sector employment (the wage gap net of selection effects) for Brazil and Mexico. We find that (i) both national and subnational public employees receive a significant wage premium with respect to private sector employment; and (ii) the difference between the national and subnational wage premiums is small in Brazil and null in Mexico. [ABSTRACT FROM AUTHOR]

• Adverse weather shocks in the form of droughts increases violent crime rate in rural Brazil. • This effect appears to persist beyond the growing season and over the medium run. • Weather fluctuations are positively associated with agriculture yields as well as the overall economic activity. • The dominance of opportunity cost mechanism reflected in the income fluctuations of the agriculture and unskilled workers. This paper examines the effect of weather shocks on violent crime using disaggregated data from Brazilian municipalities over the period 1991–2015. Employing a distributed lag model that takes into account temporal correlations of weather shocks and spatial correlation of crime rates, I document that adverse weather shocks in the form of droughts lead to a significant increase in violent crime in rural regions. This effect appears to persist beyond the growing season and over the medium run in contrast to the conventional view perceiving weather effects as transitory. To explain this persistence, I show that weather fluctuations are positively associated not only with agriculture yields, but also with the overall economic activity. Moreover, evidence shows the dominance of opportunity cost mechanism reflected in the fluctuations of the earnings especially for the agriculture and unskilled workers, giving credence that it is indeed the income that matters and not the general socio-economic conditions. Other factors such as local government budget capacity, (un)-employment, poverty, inequality, and psychological factors do not seem to explain violent crime rates. [ABSTRACT FROM AUTHOR]

• Air pollution in the Brazilian Amazon leads to increases in hospitalization rates. • Adverse effects are concentrated in respiratory conditions. • Effects are higher among children and the elderly. • Effects increase non-linearly with air pollution levels. • There are negative externalities related to deforestation in the Brazilian Amazon. In this paper we assess the effects of fire-related air pollution on population health in the Brazilian Amazon. Our empirical strategy is based on a municipality-by-month fixed effects model, coupled with an instrumental variables approach that explores wind direction and air pollution in surrounding areas in order to exogenously shift exposure to air pollution at the locality. We find that exposure to air pollution, measured by PM2.5 concentration levels, is robustly associated with an increase in hospital admissions for respiratory conditions. The effects are higher among children and the elderly, and increase non-linearly with pollution levels. Our benchmark estimates indicate that an increase of one standard deviation in PM2.5 is related to an increase of 1.5% of the monthly hospitalization rate for respiratory conditions. The latter estimate reaches 14% if monthly average PM2.5 crosses thresholds as high as 75 μ g/m3. We do not observe significant effects on hospitalization rates related to other health conditions nor on mortality rates. [ABSTRACT FROM AUTHOR]