Post-Doctoral Fellow
Department of Economics
Stanford University
Assistant Professor (in July 2025)
Haas School of Business
UC Berkeley
[[lauraweiwu@stanford.edu||mailto:lauraweiwu@stanford.edu]]
[[lauraww@berkeley.edu||mailto:lauraww@berkeley.edu]]
[[ [Curriculum Vitae]||/assets/files/Laura_Weiwu_CV.pdf]]
I study questions in labor and urban economics by applying methods from spatial economics and insights from economic history. My research focuses on the causes and consequences of inequality in cities and often employs large-scale administrative datasets for the United States.
I received my Ph.D. in Economics from MIT in 2024 and my B.A. in Economics and B.S. in Applied Mathematics from Stanford in 2018.
From 2020 to 2024 during my Ph.D., I was also employed at the Census Bureau’s Center for Economic Studies to build new measures of intergenerational mobility for the post-Civil Rights era.
This paper investigates the impact of the largest infrastructure project in American history—the Interstate highway system—on inequality and the role of institutional segregation in its disparate incidence. To evaluate the distributional impacts, I develop a general equilibrium spatial framework that incorporates empirical estimates from disaggregated Census microdata in 1960 and 1970 for 25 cities. Highways generated substantial costs from local harms on adjacent areas as well as benefits from reductions in commute times. In the urban core, costs outweigh benefits as proximity to highways is greater and commute connectivity improves predominantly in remote suburbs. I find residential constraints account for much of the initial concentration of the Black population in central areas and their low mobility away, which contribute to racial rather than class gaps in impacts from the Interstate highway system. When barriers are eliminated and Black households are granted access beyond central neighborhoods, the gap in highway impacts is reduced while all groups experience large gains from interstate development. These results highlight how institutions shape inequality in the incidence of place-based shocks.
Best Student Paper, Urban Economics Association. Allan Nevins Prize, Economic History Association
Place-based policies often aim to improve local economic opportunity and at large scale, trigger household migration that alters the peer composition of neighborhoods (1) directly targeted and (2) indirectly affected through migration. Aside from the immediate impact of the policy, general equilibrium (GE) changes in peer composition are also important determinants of economic mobility—and create winners and losers. I study these equilibrium effects in the context of the interstate highway system, a transformative place-based policy for U.S. cities. I employ novel measures of intergenerational mobility for the near universe of 57 million children born between 1964 to 1979. I find areas with commuting access improvements from highway construction experienced increases in average income and inflows of higher-educated, higher-occupational status, and White households. With detailed income and location for 1974 to 2018, I extend the movers design to find that both Black and White children benefit from growing up in neighborhoods (tracts) with greater average income and higher status peers. In areas with lower access improvements, which experience outflows of high-status peers, children subsequently face declines in economic opportunity. I incorporate these GE forces into a spatial equilibrium framework to quantify the aggregate consequences of the interstate system on intergenerational mobility by race.
with Martha Stinson and Sean Wang
We study the channels through which changes in local economic conditions during early childhood affect long-run outcomes for children from differing economic backgrounds. We exploit geographic variation across counties in the decline of manufacturing employment during the 1979 to 1984 period with microdata from the Longitudinal Business Database. To assess the exogeneity of local labor market shocks, we construct additional shocks by combining industry-level energy intensity with spikes in oil prices as a result of the 1979 energy crisis. With administrative and survey data that trace the full trajectory of the children’s lives, we measure how these local changes impact educational attainment, income, and the quality of the firm of employment in the modern day. We explore how migration of parents away from counties experiencing declines and changes in parental income during childhood are central mediators for our findings.
with Vincent Rollet
We study the political economy of local zoning decisions and its impact on public goods provision. In the United States, public goods are provided locally and financed through property taxation. This arrangement incentivizes municipalities to attract more affluent residents (or rather to exclude poorer ones) which they often achieve through stringent zoning regulations. As restrictive land-use exerts a negative externality on other municipalities in the same metropolitan area, zoning decisions at the municipality level can generate inefficiency more broadly. To study the impacts of local decisionmaking, we develop a dynamic framework of residential choice that integrates voting models from political economy. Our framework is estimated using historical series of Censuses of Governments on municipal revenue and expenditures, individual-level migration history, and a novel panel dataset on land-use regulations. We examine if a counterfactual with inter-municipal coordination, rather than local authority in zoning, is a politically feasible path to reducing inefficiency in housing and inequality in public goods.
with Martha Stinson. Census Bureau Center for Economic Studies (CES) Technical Note
We construct novel parent-child linkages between the universe of parent tax filers in IRS 1040 forms in 1974 and 1979 and the universe of children from the Census Numident in the cohorts of 1964 to 1979. Variables used for matching are parent names of children and names of parent tax filers, which are obtained from a restricted name file provided by the Social Security Administration. Applying name-matching techniques that incorporate supervised learning methods, we flexibly compare parent names and disambiguate parent-to-parent matches. This report documents the iterative process for identifying matches and the algorithm that is used for assessing the likelihood of a match. We provide match rates for different demographic groups and validate the accuracy of the linkages.
Name pronunciation tip: my last name is two Chinese characters (危吴) and spoken as way-woo