In most legal systems, detaining individuals pretrial is a common practice. Pretrial detention prevents that defendants commit crimes while they wait for their trials, but prison experiences can also encourage future criminal activity. In this paper, we use novel data on detention hearings and in flagrante delicto arrests in the state of Rio de Janeiro to assess the effect of pretrial detention on future crime. Since detention assignment is endogenous to defendants’ characteristics, we adopt an instrumental variable approach that exploits randomly assigned judges who differ in terms of their idiosyncratic tendencies of ordering pretrial detention. Our findings suggest that pretrial incarceration reduces rearrest in the medium term, and that this effect is entirely driven by incapacitation effects. We also provide evidence that pretrial detention increases the probability and the severity of post-release crime.

In this paper, I study the relationship between allocation of credit and political campaign contribution. In order to achieve this goal, I use loan data on indirect operations from Brazilian development bank (BNDES) at the firm level between 2003 and 2014. Exploring variation for the same firm contributing and not contributing to political campaign and for type of bank, I test if firms that contribute to political campaign at the federal level have preferential access to credit through firm-bank, firm-time and bank-time fixed effect. I find that politically connected firms increase their likelihood of receiving a loan from state-owned banks. On the other hand, they have a lower probability of receiving a loan from private banks. Results for intensive margin show that companies connected with politicians at the federal level receive, on average, greater credit from federal banks. In addition, these companies borrow lower amounts from private banks. This effect is concentrated on the credit line used to fund machine and equipment. Heterogeneous effects of connections with winning and losing candidates vary according to the econometric model I use.

O presente trabalho traz 6 diferentes técnicas de previsão para a variação mensal do Índice da Produção Industrial americana em 3 ambientes diferentes totalizando 18 modelos.  No primeiro ambiente foram usados como variáveis explicativas a própria defasagem da variação mensal do Índice da produção industrial e outras 55 variáveis de mercado e de expectativa tais quais retornos setoriais, prêmio de risco de mercado, volatilidade implícita, prêmio de taxa de juros (corporate e longo prazo), sentimento do consumidor e índice de incerteza. No segundo ambiente foi usado a database do FRED com 130 variáveis econômicas como variáveis explicativas. No terceiro ambiente foram usadas as variáveis mais relevantes do ambiente 1 e do ambiente 2. Observa-se no trabalho uma melhora em prever o IP contra um modelo AR e algumas interpretações a respeito do comportamento da economia americana nos últimos 45 anos (importância de setores econômicos, períodos de incerteza, mudanças na resposta a prêmio de risco, volatilidade e taxa de juros).

As (1) points out, monetary policy predictability can enhance a Central Bank stabilization policy efficacy. In this paper we aim to reduce uncertainty about one Federal Reserve forward guidance instrument by estimating full association probabilities distributions between members and the interest rate dot plot for each FOMC meeting. Our contribution to the literature is twofold: first, we propose a general Bayesian algorithm which estimates these association hypotheses between agents and actions whenever they are not observed. Second, we elaborate a novel and less subjective technique for quantifying text into data, using Latent Dirichlet Allocation (LDA) and shrinkage econometric tools. This method shows some desirable features such as positive correlation between the FOMC chair and the rest of the committee, and a policy stance ordering which partially reflects analysts and market participants views on this hawk-dove spectrum. Our tracking algorithm performs successfully in a simulated environment, in a sense that it on average considers the correct member-to-dot association as the most likely one. Using real data on speeches and Fed dots, it is also able to attribute the highest probability to the correct assignment hypothesis in the only meeting it is known for sure

This thesis consists of three chapters. In the first one we investigate whether the provision of information about research findings regarding effectiveness of policies cause political leaders to enact policy change. To do so, we use two types of experiments to measure elected heads of government: (1) demand for research and (2) policy responses to supply of research. We find that policymakers are willing to pay relatively high amounts to learn the results of impact evaluations, update their posterior over the expected impact of a policy in the “correct” direction if informed of research findings, and pay more for types of studies that subsequently affect their beliefs more. Correspondingly, providing information about research findings indicating positive, cost-effective impact of a policy increases the probability that mayors implement the policy in their own municipality by 10 percentage points. In the second chapter, we study the role that revenue shocks play on government investment in fiscal capacity. Using a differencein-difference event-study design, we analyze local budget adjustments to an exogenous revenue shock in formula transfers to Brazilian municipalities. We find that positive revenue shocks translate into additional spending, while the adjustment after a negative shock depends on local characteristics. On average, municipalities increase tax collection, but this effect disappears in jurisdictions with low-educated mayors, which rather tend to cut expenditures. We show that hiring tax related workers is the main mechanism behind the increase in tax revenues. In the third chapter, we follow the theory of knowledge-based hierarchies to study the internal organization of municipal governments in Brazil. Using detailed matched employer-employee data, we construct bureaucrats’ hierarchies within municipalities and show that the empirical patterns match the theoretical predictions. We then present suggestive evidence linking the organization structure in which bureaucrats operate and public sector productivity

This dissertation is comprised of two chapters. In the first chapter, we assess how a large public housing program in Brazil affected short and medium-run employment probability and other labor market outcomes. We use data from lotteries in Rio de Janeiro to identify these impacts. We concluded that the program increased formal employment by about two percentage points and had no effect on informal employment. Moreover, we also find evidence that receiving a house increased wages and the quality of jobs held for the treated individuals and reduced participation in other social programs. Additionally, we used reduced-form models to test the mechanisms that might explain the observed increase in employment probability. We found evidence that the mobility costs from the individual job to the provided houses is an important determinant of the impacts of the program. On the other hand, neighborhood effects, relocation from the individuals’ house, migration and the distance from individuals’ previous homes do not seem to be important mechanisms in explaining the effect of the program on employment. In the second chapter, we complement the previous analysis by building and estimating a static labor supply structural model. We incorporate in the model the simultaneous decision to participate in the labor market and a housing program. We use data for lotteries to help identify the parameters of the model. The lotteries data is also used to out-of-sample validation. Our estimated model is able to reproduce well both the behavior of individuals in the data used for estimation and in the experimental hold-up sample. Then, we use this model to perform policy experiments and evaluate counterfactuals.

Gender wage inequality has been widely studied and many explanations have been advanced in the literature. There is growing evidence that firms play an important role in explaining this inequality. In this paper, I make use of a unique setting with exogenous demand shocks to firms to identify if there is evidence of rent-sharing by firms and whether it differs between male and female workers. Controlling for worker quality, I find that increases in the value of the demand shock per worker do not lead to increases in wages. Demand shocks do not have effects on neither male nor female wages. Furthermore, I use a new dataset containing information on gender of firm’s owner and I examine if female and male-led firms behave differently towards their employees. I find no evidence of differential rent-sharing through the structure of the firms’ ownership.

Suspeitas de compra de votos e barganha de favores políticos marcaram os processos de impedimentos presidenciais no Brasil. É o toma-lá-dácá no Congresso. Essas atividades são menos relevantes nos processos de impedimento norte americanos e nos votos de desconfiança em regimes parlamentaristas. Nesta dissertação, desenvolvo um modelo no qual o tomalá-dá-cá no Congresso implementa o mecanismo ótimo de incentivos a chefes de governo sujeitos a risco moral na execução de suas plataformas políticas. Há um tradeoff entre a execução da plataforma vitoriosa nas eleições e tomalá-dá-cá no Congresso. Se a base aliada é capaz de induzir o presidente a governar conforme suas promessas de campanha, o desenho ótimo inclui a possibilidade de impedimento, mas votos no Congresso sobre o impedimento refletem o desempenho de governo.

This paper studies the relationship between geographic heterogeneity and technology adoption in the context of the direct planting system (DPS) in Brazil. The DPS is a no-till farming technique that increases productivity and decreases soil degradation. However, it requires adaptation to local conditions to be profitably used. Combining detailed geographic and agricultural data, we show that geographic heterogeneity reduces DPS adoption. This effect is robust to the inclusion of controls and not observed for technologies that do not require local adaptation. These findings are consistent with models in which geographic heterogeneity increases the cost of adapting technologies to local conditions

Esta dissertação documenta e analisa os empréstimos concedidos pela Finep entre 2004 e 2017. São respondidas as seguintes questões: Qual a magnitude dos subsídios? Como têm evoluído? Como variam entre indústrias e regiões? Na amostra analisada, o valor médio dos subsídios implícitos nos empréstimos é de 8,6 milhões, sendo maior para contratos com taxas de juros pré-fixadas: R$10,9 milhões, ou 21,5% do valor presente dos empréstimos. Para os empréstimos pós-fixados, indexados pela TJLP, o subsídio médio é menor, mas ainda assim relevante: R$2,6 milhões ou 11,7% do valor presente dos empréstimos. Tanto os valores dos empréstimos quanto os subsídios concedidos foram substancialmente elevados a partir de 2008, atingindo seus picos entre 2013 e 2014. As indústrias de transformação e as regiões Sudeste e Sul tem sido as maiores beneficiárias.

Using a rich Brazilian panel dataset and an occupation-task mapping, we investigate whether returns to experience depend on the types of jobs performed by workers. We find that returns to experience in non-routine tasks, especially returns to analytical tasks, are much larger than returns to routine tasks. This gap increases with schooling, suggesting that schooling and nonroutine tasks are complementary in the human capital production function. These are important findings for developing countries similar to Brazil, where approximately 70% of workers’ tasks are routine

This paper considers an optimal renegotiation-proof dynamic Bayesian mechanism in which two privately informed players repeatedly have to take a joint action without resorting to side-payments. We provide a general framework which accommodates as special cases committee decision and collective insurance problems. Thus, we formally connect these separate strands of literature. We show: (i) first-best values can be arbitrarily approximated (but not achieved) when the players are sufficiently patient; (ii) our main result, the provision of intertemporal incentives necessarily leads to a dictatorial mechanism: in the long run the optimal scheme converges to the adoption of one player's favorite action. This can entail one agent becoming a permanent dictator or a possibility of having sporadic “regime shifts.”

O objetivo do presente trabalho é examinar a situação fundiária no Brasil Imperial nos seus aspectos econômicos, mas também sociais e legais, a partir de seus antecedentes coloniais, e examinar criticamente a questão tradicionalmente enfatizada na historiografia da onipresença e predominância de latifúndios no período imperial. 

This dissertation assesses the aggregate and distributional effects of the recent transport infrastructure expansion in Rio de Janeiro (Brazil) triggered by 2014 Football World Cup and 2016 Olympic Games. In preparation for the sports events, the city invested more than 4.5 billion dollars in its public transport system, which included the extension of a subway line, the construction of a light-rail system and two BRT corridors that stretch  approximately 108 kilometers. Chapter 1 provides a  escription of new transport infrastructure and estimates its potential effects on commuting times. I compute travel times in the absence of the investments using random forest regression methodology and data from 2011 and 2018 travel times. Estimates suggest that the new infrastructure significantly reduced travel times. The remaining chapters explore two different methodologies to account for the impacts of the transport investments. Chapter 2 explores the timing of announcement and inauguration of new BRT and subway stations in Rio  de Janeiro City to investigate the effects of the expansion of transport  infrastructure on growth and reorganization of economic activity. Firm’s addresses were geocoded to construct a panel data set  hat contains information on number of firms and jobs per 100 meter’s grid cell from 2006 to 2016. Applying a difference-in-differences methodology on this novel data set, I estimate the heterogeneous effects of the transport expansion according to workers’ characteristics and industry. All effects are obtained for eight different distance rings ranging from 250m to 2km. Chapter 3 aims to measure the effects of transportation infrastructure on the city’s wages, productivity and welfare, investigating heterogeneous impacts for high and low skilled workers. To answer these questions, I construct an extensive database for the Rio de Janeiro Metropolitan Area that combines information on residence and employment for each skill group inside each city block. In order to measure general equilibrium effects, I develop a model ofinternal city structure that features heterogeneous workers and production externalities across worker’s skill levels. I estimate structural parameters using generalized method of moments. Finally, I perform contrafactual exercises to assess the impacts of the recent transport infrastructure expansion in Rio de Janeiro using 2018 travel times collected from Google Maps API and travel times computed in the first chapter. Results show that  connecting new areas to the central business district results in lower residential concentration and higher employment  concentration. The improvement of transportation services allows citizens to work in high productivity locations and live in high amenity locations, which leads to higher overall welfare. Nevertheless, benefits are not evenly split. High-skilled workers benefit twice since they have higher benefits from agglomeration and, consequently, they are able to pay for higher residential prices from lower commuting costs. Moreover, areas in the vicinity of the new transport stations saw an increase in economic activity. The bulk of the impact is characterized by small firms, from the commerce and service sectors. Additionally, most of the workforce employed by these firms are low-skilled.