Evaluating the Impact of Urban Transit Infrastructure: Evidence from Bogotá’s TransMilenio
This paper estimates the effects of improving transit infrastructure on city structure and welfare. It derives a new reduced form framework from a class of general equilibrium urban models to examine how they capture Bogotá's response to the construction of the world's largest Bus Rapid Transit system. To quantify the system's distributional impacts, it extends these models to incorporate low- and high-skilled workers with non-homothetic preferences over neighborhoods and transit modes. Relative to valuing benefits based on time savings alone, welfare gains are 20-40% larger and there is little impact on inequality after accounting for reallocation and general equilibrium effects.
The Welfare Consequences of Formalizing Developing Country Cities: Evidence from the Mumbai Mills Redevelopment
Developing country cities are characterized by informal housing–slums–but growing urban populations and incomes will lead governments to pursue a host of policies that promote the construction of modern, formal sector housing. This has the potential to affect entire neighborhoods since the effects are likely to spillover beyond directly targeted locations. In this paper, we ask how large are the spillovers from formal development, and what do these imply for the welfare consequences of pro-formalization policies in developing country cities? We address this question in three steps. First, we exploit a unique natural experiment in Mumbai that led 15% of central city land occupied by the city’s defunct textile mills to come onto the market for redevelopment in the 2000s. Second, we use a “deep learning” approach to measure slums from satellite images, and combine this with administrative sources to construct a uniquely spatially disaggregated dataset spanning the period. Third, we develop a quantitative general equilibrium model of a city featuring formal and informal housing supply to guide our empirical analysis. We find evidence of substantial housing and agglomeration externalities, and provide reduced-form evidence suggestive of both efficiency gains (through increased employment density in central areas) and potential equity losses (through the conversion of slums and gentrification near redeveloped mill sites).
Contract Labor and Firm Growth in India
Many observers have pointed to the bargaining power of organized labor, as initially implemented by the Industrial Disputes Act (IDA) of 1947, as an important constraint on growth in India. This act raises the cost of labor and of laying off workers, particularly for large firms with more than 100 workers. Since the late 1990s, large Indian manufacturing firms have increasingly relied on contract workers supplied by staffing companies who are not subject to the IDA. By 2011, contract workers accounted for 36% of total employment of firms with more than 100 workers. At the same time, the thickness of the right tail of the firm size distribution in formal Indian manufacturing plants has increased, the average product of labor for large firms has declined, the volatility of growth rates among large firms has increased, and the probability that large firms introduce new products has risen. We provide evidence in support of the causal effect of the increased supply of contract labor on the relaxation of employment constraints among large establishments following an Indian Supreme Court decision in 2001. We develop a model of firm growth subject to firing costs to quantify the effect of contract labor on TFP growth in Indian manufacturing.
Work in Progress
Refugee Influx and City Structure: Evidence from CDR Data in Amman
Where do migrants choose to live and work in cities, how do they adjust and integrate into new communities, and what does an influx imply for city structure and the welfare of inhabitants? We answer these questions in Amman, Jordan, a city where 16% of current inhabitants are refugees from the Syrian crisis. We combine administrative data available before and after the height of the crisis with call data records (CDR) and proceed in three stages. First, we merge the CDR with an external survey and use machine learning to classify migrants and non-migrants in the data. We establish new stylized facts over the dynamics of migrants’ locations of residence and employment, and how their networks integrate into neighborhoods. Second, we use the administrative data to empirically assess the characteristics of neighborhoods migrants were drawn to, and the effect of migrant influxes on neighborhoods themselves, using a neighborhood’s initial composition by nationality and the city’s geography to instrument for the migrant influx in a particular location. Finally, we develop a dynamic model of a city featuring two types of workers (migrants and non-migrants), and estimate its parameters using the variation provided by the Syrian crisis. The model allows us to evaluate the impact of various counterfactual policies, such as temporary housing, on the evolution of city structure and welfare.