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 description 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 that 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 of internal 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.