“The Efficiency of Local Government: The Role of Privatization and Public Sector Unions” with Matthew E. Kahn & Shanjun Li (Journal of Public Economics (2017), 154: 95-121)
Selected media coverage: Forbes
Local governments spend roughly $1.6 trillion per year to provide a variety of public goods ranging from police and fire protection to public schools and public transit. Despite the fact that a sizable amount of economic activity is supplied by local governments, we know little about this sector’s productivity in delivering key services. We argue that the operating cost of providing public transit bus miles offers a standardized output for benchmarking the cost of local government service provision both over time and across space. We measure the cost savings from privatization and study the cost premium associated with unionization. We explore the political economy of why privatization rates are lower in high cost unionized areas.
I use the 1972 Clean Water Act to estimate how local governments finance federal mandates and their impacts on house price and population growth. My empirical strategy takes advantage of the spatial nature of river networks and pre-1972 pollution regulation to instrument for mandate compliance. Local governments financed the non-subsidized costs of mandate compliance through a two-fold increase in resident user fees. Despite these higher fees, house prices and populations grew faster in the twenty years following mandate compliance, particularly among smaller communities. These findings suggest that mandates can alleviate under-provision of local public goods, particularly for smaller municipalities.
“Road Rationing Policies & Housing Markets” with Panle Barwick, Shanjun Li, & Jing Wu (revisions requested at The Journal of Urban Economics)
Canonical urban models postulate transportation cost as a key element in determining urban spatial structure. This paper examines how road rationing policies impact the spatial distribution of households using rich micro data on housing transactions and resident demographics in Beijing. We find that Beijing’s road rationing policy significantly increased the demand for housing near subway stations as well as CBD. The premium for proximity is stable in the periods prior to the driving restriction, but shifts significantly in the aftermath of the policy. The composition of households living close to subway stations and Beijing’s CBD shifts toward wealthier households, consistent with theoretical predictions of the monocentric city model with income-stratified transit modes. Our findings suggest that city-wide road rationing policies can have the unintended consequence of limiting access to public transit for lower income individuals.
Since 1980, over 2,000 local governments in US Atlantic and Gulf states have been hit by a hurricane. Such natural disasters can exert severe budgetary pressure on local governments’ ability to provide critical infrastructure, goods, and services. We study local government revenue, expenditure, and borrowing dynamics in the aftermath of hurricanes. These shocks reduce tax revenues and expenditures, and increase the cost of debt in the decade following exposure. Major hurricanes have much larger effects than minor hurricanes. Our results reveal how hurricanes create collateral fiscal damage for local governments by increasing the cost of debt at critical moments after a hurricane strike. Municipalities with a racial minority composition 1 standard deviation above the sample mean suffer expenditure losses more than 2 times larger and debt default risk 8 times larger than municipalities with average racial composition in the decade following a hurricane strike. These results suggest that climate change can exacerbate environmental justice challenges.
Selected Works in Progress
“Urban Surface Water Pollution & Health” with Carlos Hurtado
“Information, Technology, & Public Transit Use” with Andrea LaNauze
“Do Protected Immigrants Make Better Neighbors?” with Jorgen Harris
“Understanding Heterogeneity in the Value of Time” with Avralt-Od Purevjav, Ziye Zhang, and Shanjun Li