{"title":"Does political partisanship affect housing supply? Evidence from US cities","authors":"Fernando Ferreira , Joseph Gyourko","doi":"10.1016/j.jue.2026.103842","DOIUrl":"10.1016/j.jue.2026.103842","url":null,"abstract":"<div><div>We study the relationship between housing supply and political partisanship in US cities using an expanded database of mayoral elections combined with local housing permits since 1980. The endogeneity of which party holds the mayoral office is addressed via a regression discontinuity design that relies on closely contested races between Republicans and Democrats. Across a variety of election samples and econometric specifications, we find that partisanship does not have a statistically or economically significant effect on the supply of total, single- or multifamily housing unit permits despite recent increases in measured partisanship. This suggests that solutions to limitations on housing supply will not be dependent upon the political party in power at the local level.</div></div>","PeriodicalId":48340,"journal":{"name":"Journal of Urban Economics","volume":"152 ","pages":"Article 103842"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"JUE insight: Floods & urban density","authors":"Pierre Magontier , Rodrigo Martinez-Mazza","doi":"10.1016/j.jue.2026.103831","DOIUrl":"10.1016/j.jue.2026.103831","url":null,"abstract":"<div><div>This paper examines the effects of floods on urban development dynamics using geolocalized data on the universe of buildings in Spain from 1996 to 2021. We provide empirical evidence that floods promote local urban development, resulting in taller, more compact urban layouts that attract populations, increase property values, and shift land use away from the agricultural and industrial sectors. We argue that adaptive responses to natural disasters may trigger positive local spillovers strong enough to overcompensate for the flood’s destructive nature.</div></div>","PeriodicalId":48340,"journal":{"name":"Journal of Urban Economics","volume":"152 ","pages":"Article 103831"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145996553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andreas Fidjeland , Tora Knutsen , Magnus Stubhaug
{"title":"Sticky places: The effect of college on where you live","authors":"Andreas Fidjeland , Tora Knutsen , Magnus Stubhaug","doi":"10.1016/j.jue.2026.103843","DOIUrl":"10.1016/j.jue.2026.103843","url":null,"abstract":"<div><div>Does the location of higher education institutions affect where graduates live? We use Norway’s centralized admissions system as a natural experiment to quantify the causal effect of study location on residence later in life. Leveraging students’ rankings of study programs and locations alongside GPA-based admission scores, we identify unpredictable cutoffs that create discontinuities in admission for near-identical applicants. Our analysis shows that being admitted to the preferred study location increases the likelihood of residing in the same region after graduation by 15–20 percentage points. This effect is consistent across both larger and smaller cities, highlighting the “stickiness” of educational locations.</div></div>","PeriodicalId":48340,"journal":{"name":"Journal of Urban Economics","volume":"152 ","pages":"Article 103843"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"JUE insight: Moving cost magnitudes in moving cost models","authors":"Greg Howard","doi":"10.1016/j.jue.2025.103827","DOIUrl":"10.1016/j.jue.2025.103827","url":null,"abstract":"<div><div>The internal migration literature has estimated a wide range of moving costs, including some that are several times larger than annual income. How should economists interpret this estimate? I show that in standard models, average moving costs can be decomposed into an “information” term and a “returns to migration” term. The information term is proportional to the Shannon entropy of next period’s location minus the Shannon information of staying in the same location. In simple models, the information term is much larger than the returns to migration term; in some cases, the returns to migration term is zero. Therefore, average moving costs are a helpful statistic about the model’s predictive power regarding future moves but are not invariant to seemingly innocuous choices of the modeler.</div></div>","PeriodicalId":48340,"journal":{"name":"Journal of Urban Economics","volume":"151 ","pages":"Article 103827"},"PeriodicalIF":4.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"JUE Insight: Shovel ready projects and commercial construction activity’s long and variable lags","authors":"David Glancy , Robert Kurtzman , Lara Loewenstein","doi":"10.1016/j.jue.2025.103816","DOIUrl":"10.1016/j.jue.2025.103816","url":null,"abstract":"<div><div>We use microdata on the phases of commercial construction projects to document three facts regarding the sector’s time-to-plan lags: (1) plan times are long and highly variable, (2) nearly half of projects in planning are abandoned, and (3) property-price appreciation reduces the likelihood of abandonment. We present a tractable model of endogenous planning starts and abandonment that can match these facts. The model has the testable implication that supply is more elastic when there are more “shovel ready” projects ready for construction. We use local projections to validate this prediction in a panel dataset for US cities.</div></div>","PeriodicalId":48340,"journal":{"name":"Journal of Urban Economics","volume":"151 ","pages":"Article 103816"},"PeriodicalIF":4.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145532709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Corrigendum to “Impact of fertility relaxation on the housing market outcomes” [Journal of Urban Economics Volume 150, November 2025, 103812]","authors":"Keyang Li , Yixun Tang , Qiuyi Wang","doi":"10.1016/j.jue.2025.103828","DOIUrl":"10.1016/j.jue.2025.103828","url":null,"abstract":"","PeriodicalId":48340,"journal":{"name":"Journal of Urban Economics","volume":"151 ","pages":"Article 103828"},"PeriodicalIF":4.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Industrial Transfer Policy in China: Migration and development","authors":"Michiel Gerritse, Zhiling Wang, Frank van Oort","doi":"10.1016/j.jue.2025.103815","DOIUrl":"10.1016/j.jue.2025.103815","url":null,"abstract":"<div><div>China’s Industrial Transfer Policy (ITP) is a novel place-based development policy of unprecedented scale. The policy targets a set of inland cities aiming (i) to grow them in size and (ii) to restructure them into manufacturing hubs. These cities would eventually relieve pressure in China’s coastal manufacturing hubs. We use a detailed migrant survey to estimate the impact of ITP on targeted cities by matching cities on policy assignment propensities. The ITP status led to a rapid but short-lived growth of migrant inflows up to 60%, representing millions of internal migrations. Migrants in manufacturing and from coastal origins show stronger migration and wage responses. However, skilled migrants respond less elastically, and migrant employment in manufacturing is offset by the exit of native workers. Additionally, manufacturing industries in targeted cities show no development in terms of output, pollution or production strategies. The ITP expands the population of targeted cities, but the evidence for a restructuring of the cities is weak.</div></div>","PeriodicalId":48340,"journal":{"name":"Journal of Urban Economics","volume":"151 ","pages":"Article 103815"},"PeriodicalIF":4.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Migration crisis in the local news: Evidence from the French–Italian border","authors":"Silvia Peracchi","doi":"10.1016/j.jue.2025.103808","DOIUrl":"10.1016/j.jue.2025.103808","url":null,"abstract":"<div><div>This paper examines how undocumented migrant displacements affect local news markets and the political economy of EU internal borders. I focus on a policy that took place in June 2015, in which French authorities introduced militarized controls at their borders with Italy, to return waves of irregular border-crossing migrants transiting from Italy to Italian lands. Natives’ exposure to resettled migrants varied across Italian municipalities, depending on their proximity to push-back areas. I exploit this quasi-experimental setting in a diff-in-diff framework and compile novel text and count data from local news in Liguria, Italy. Results show that migration coverage declined with distance from the border after the push-backs. In contrast, anti-immigrant discourse intensified away from the events and weakened at the border. Exploring further this framing dimension, I observe readers’ demand to be closely associated with local news discourse and voting preferences to broadly follow anti-immigrant slant in the news.</div></div>","PeriodicalId":48340,"journal":{"name":"Journal of Urban Economics","volume":"150 ","pages":"Article 103808"},"PeriodicalIF":4.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145134828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Will you follow your job to the suburbs?","authors":"Gregory Verdugo , Malak Kandoussi","doi":"10.1016/j.jue.2025.103814","DOIUrl":"10.1016/j.jue.2025.103814","url":null,"abstract":"<div><div>We examine how relocations from the center to the suburbs of establishments employing mainly skilled workers affect the composition and wages of their employees. Using data from the Paris metro area, we find that these relocations increase average commuting time by 19%. In response, firms compensate highly paid workers with 10 to 20% of their hourly wage per additional hour of commuting. Lower-paid workers receive no compensation and are more likely to leave. Consistent with workers valuing locational amenities, we find little increase in separation and no wage adjustment for increased commuting time when establishments relocate to more attractive neighborhoods.</div></div>","PeriodicalId":48340,"journal":{"name":"Journal of Urban Economics","volume":"150 ","pages":"Article 103814"},"PeriodicalIF":4.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145474421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Elasticities and tax incidence in urban ridesharing markets: Evidence from Chicago","authors":"Matthew Tarduno","doi":"10.1016/j.jue.2025.103809","DOIUrl":"10.1016/j.jue.2025.103809","url":null,"abstract":"<div><div>Over the past decade, many U.S. cities have imposed taxes on Uber and Lyft, leading to debate over the impacts and incidence of these policies. This paper answers three questions about these taxes: (i) How do ridesharing taxes impact trip prices and quantities? (ii) What are the implied market supply and demand elasticities, and (iii) Who bears the burden of ridesharing taxes? Using data from Chicago, I show that ridesharing demand is inelastic in both gross terms, and relative to supply. Accordingly, 89% of the city’s ridesharing tax is passed through to passengers. From a distributional standpoint, travel survey data suggest that ridesharing taxes are roughly as progressive as the federal income tax schedule. Finally, back-of-the-envelope calculations informed by these results suggest that ridesharing taxes of the size typically seen in the U.S. are unlikely to generate meaningful improvements in congestion or air pollution.</div></div>","PeriodicalId":48340,"journal":{"name":"Journal of Urban Economics","volume":"150 ","pages":"Article 103809"},"PeriodicalIF":4.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}