Research and Work in Progress
Did the Rise of the South Deindustrialize the North?
with Gordon Hanson
(slides)
During the middle of the 20th century, U.S. manufacturing reorganized itself. A substantial share of industrial jobs were reallocated from the U.S. North to the U.S. South, presaging the exodus of manufacturing from the global North to the global South that would occur several decades hence. We study how the rise of the South affected labor market outcomes in the North. First, we account for the factors behind the timing of the South's industrialization, including the region's delayed transition out of agriculture, the Great Migration, the construction of interstate highways, the rise of unionism, and shifting patterns of industry innovation. Second, we estimate the causal impact of Southern manufacturing job growth on Northern local labor markets. Northern regions more exposed to the rise of the South saw larger declines in manufacturing employment, no offsetting gains in service employment, no differential change in population headcounts, and lower earnings among low-wage workers. These impacts were substantial larger for Black workers than for white workers. Third, we examine the social consequences of the Northern shift out of manufacturing. Regions exposed to the rise of the South saw larger decreases in marriage rates, and larger increases in the fraction of children living with single mothers, where these impacts were most pronounced among Black households. In ongoing work, we are studying impacts on Northern housing markets, educational attainment, takeup of public income assistance, and social mobility.
The wage tax and suburbanization
with Matt Jacob
More than 9 million jobs in the United States are subject to a local wage tax, a kind of local income tax that applies to residents and non-resident workers. The wage tax has long been argued to have caused firms and workers to jointly abandon large cities in favor of suburbs. Guided by a quantitative spatial model, we test this hypothesis with historical commuting in Philadelphia and a spatial regression discontinuity design around its borders. Our key insight is that the elasticity of commuting with respect to the net-of-tax rate can be estimated with a panel of commuting shares at the city limits. We find that the elasticity is of about 7, and perform some tax policy counterfactuals.
How Does Place-Based Policy Work?
with Gordon Hanson, Dani Rodrik, and Rohan Sandhu
Place-base based policies are in vogue. Over the last two decades, U.S. state and local governments have expanded their efforts to recruit large companies, invest in low-income communities, promote small business, and retrain dislocated workers, often supported by federal funds. Recent literature clarifies theoretical rationales for place-based policy and estimates the causal impacts of specific interventions. Yet, we still know little about how policies are designed and implemented, the magnitude and targeting of resource flows, and the coordination of policies across various levels of government. We examine how place-based policy works in the United States by (1) tracking resource flows by policy domain across regions and time, (2) identifying the actors involved in allocating and managing these flows, and (3) evaluating how well flows target regional levels of and changes in economic distress. The fragmentation of policy across government entities (due to earlier efforts to decentralize decision-making) devolves authority to local actors, who are a mix of public, public-private, and nonprofit entities. The result is wide regional variation in policy-making capacity and choices. For many policies, constraints on local capacity combine with federal spending rules to channel resources not to distressed places but to ones with high employment rates.
Automation Technologies and Employment at Risk
with Alfonso Cebreros, Aldo Heffner-Rodríguez, and Daniela Puggioni
Bank of Mexico Working Paper 2020-04
We use estimates for the probability of automation of occupations in Frey and Osborne (2017) together with household survey data on the occupational distribution of employment to provide a risk assessment for the threat that automation may pose to the Mexican labor market. We find that almost two thirds of total employment is at high risk of automation; slightly more than half if we only consider employment in the formal sector. We argue that, while these estimates provide a useful benchmark to start thinking about the impact that automation may have on the labor market, they should be interpreted with care as they are solely based on the technical feasibility to automate and do not reflect the economic incentives, or other factors such as the accumulation of human capital through education, to adopt automation technologies.