Ms Inessa Tregubova (p)

The COVID-19 pandemic has reshaped urban dynamics by disrupting the traditional "home-work-third place" triad, giving rise to a new "home-third place-home" spatial pattern. In this structure, 'third places' (i.e. non-traditional work places such as coffee shops and public libraries) increasingly function as workplace (office) substitutes, decentralizing professional activity and potentially driving local housing demand. While classic urban economics links local amenities to increased house prices, the specific impact of remote-work-compatible amenities remains under-researched due to identification complexities. This study develops a novel methodology to identify these emerging third places in the Tel Aviv Metropolitan Area (TAM) and measures their heterogeneous impact on residential housing demand. Utilizing an extensive GPS-signal dataset (2019–2023) mapped to Points of Interest, we adapt the Natural Language Processing Word2Vec model to analyze residents' daily trajectories. This approach successfully identifies new behavioral trends, such as work from home, as well as physical locations that have semantically shifted toward a 'work' concept in the post-pandemic era. We validate the list of detected third places against a ground-truth sample augmented with Google Places reviews. Next, we link this final list of venues with visitor behavioral profiles and local spatial externalities to construct a comprehensive cross-sectional dataset. To understand the spatial distribution of these third places and the drivers behind remote workers' location choices, we estimate two models: an Ordinary Least Squares (OLS) regression for the former, and a Multinomial Logit (MNL) discrete choice model for the latter. The results are communicated to policymakers via an interactive dashboard and mapping tool, allowing users to observe the impact of different location characteristics on the emergence of third places. By providing empirical evidence on changing urban mobility patterns, this research offers policymakers novel, data-driven tools for identifying and quantifying real-time shifts in the increasingly complex relationship between the place of work and residence.

Mr Ricardo Martinez De Vega Perancho (p), Mr Wladimir Cerda Cerda

Spain faces an unprecedented demographic challenge. Declining birth rates and rapid population aging threaten the sustainability of public finances, economic growth, and the efficient allocation of resources. In this context, immigration has emerged as a key driver of population dynamics, with the foreign-born population growing by nearly \textbf{48\%} between 2014 and 2025. This resurgence in immigration flows has sparked an intense public and political debate about the consequences of immigration, not only for the labour market but also for the housing market. This concern is particularly pressing given that, over the same period, housing supply has remained highly inelastic relative to the construction boom of the early 2000s, leaving local housing markets with limited capacity to absorb demand shocks. In this context, and at a time when the government has announced new regularisation measures for 2026, housing has become a focal point of the social and political agenda.

We study how local housing markets adjust to immigration using a novel municipal-level panel that offers substantially greater spatial detail and measurement accuracy than existing evidence for Spain, which largely operates at the provincial (NUTS 3) level and often relies on listing or appraisal values. Our analysis draws on a balanced panel of 699 municipalities (LAU 2 level), those municipalities with more than 10,000 inhabitants, excluding Vasque Country, Navarra, Ceuta and Melilla due to data limitations.), combining administrative population registers (Padrón Continuo) with transaction-level housing data from the Portal Estadístico del Notariado for the period 2014--2025. Housing variables include the average transaction price per square metre and the average transaction price per dwelling.

Our IV estimates show that a one percentage point increase in the local immigration rate raises housing prices by 0.7\% in the short run, with the effect growing to 2.36\% in the long run. These estimates are robust to the use of alternative price measures, including appraisal values and rental prices, although the effects are smaller in those cases.