When natural disasters strike, the impact on housing markets can be far-reaching. This paper explores the unique dynamics of natural disaster-induced migration on the housing market, focusing on the 1930s Dust Bowl migration to Los Angeles—the top migrant destination. We use U.S. Census-linked and geocoded address data to show that the arrival of "Dust Bowlers" significantly impacted the city's housing market. We show that houses inhabited by Dust Bowl migrants had lower price growth over the decade. Critically, we uncover valuation spillovers within highly granular neighborhoods, where houses inhabited by non-migrants experienced lower price growth modulated by how close they were to Dust Bowl migrants. Our analysis of potential mechanisms suggests that these effects were primarily driven by a disinvestment channel and the economic vulnerability of migrants rather than generalized discrimination. Our research contributes to a better understanding of how natural disaster-induced migration shapes housing markets and underscores the dimensions in which climate refugees differ from other migrants.

Is ethnic segregation in Europe driven by native flight or immigrant self-isolation? If the former, which natives avoid immigrants? Which immigrants? What is the geographic scope of homophilic residential preferences? We answer these questions using a matched panel containing the universe of individuals and properties in Denmark from 1987 through 2017. We take advantage of the quasi-random nature of refugee placements and simulated exogenous Markov-chain predictions to generate experimental variation regarding local immigrant arrivals. We find strong evidence of native flight, even at the building level. Flight is stronger among the old and a reaction to the arrival of low-income immigrants. As neighborhoods become more immigrant-dense, housing prices decline, and subsequent move-ins are more likely to be other immigrants or young, low-income native citizens without children.

Leveraging administrative firm-level data on the universe of South African exporters between 2010–2019, we document that cross-border payment integration catalyzes international trade by as much as standard tariff reductions. Using the staggered implementation of a Real-Time Gross Settlement (RTGS) system across 14 Southern African Development Community countries that facilitated cross-border payments among participating countries, we document that payment integration increases bilateral trade by about 34% within member countries. This economically significant effect is comparable to a reduction of 8.3 to 12.1 percentage points in tariffs. Crucially, we find no negative spillovers to non-participant trade partners after the system’s implementation. Effects on bilateral trade are only present for partners with low financial connections to South Africa through their bank branch network, destinations with domestic RTGS systems, and firms with high levels of financial dependence. Aggregate country-partner data further suggests the system leads to higher bilateral country trade volumes.

While developed nations increasingly debate the adoption of large-scale immigrant deportation, their consequences to cities and housing markets are vastly unknown. We study the 1930s mass repatriation of Mexicans and its effects on U.S. housing markets. Developing a novel Census house-linking algorithm, we document that the repatriation negatively impacted U.S. cities. Mexican-occupied properties saw decreased values and rents but were not subsequently occupied by U.S.-born families. Instead, the repatriation lowered neighboring U.S.-born house values and depressed cities' real estate growth. Our findings reveal significant adverse effects on individual and aggregate housing wealth, challenging the notion that deportations benefit U.S.-born households.

We study the effect of the bilateral trade integration with China on wage inequality in Brazil. Previous studies have documented the contribution of trade opening to the decline in inequality since the 1990s, driven primarily by cross-firm pay differences. We find a sharper reduction in wage inequality over the 2000s, parallel to China’s accession to the WTO. Our analysis of the China shock suggests that some firms are harmed by import competition, especially the ones in the High-Tech Manufacturing sector, while others profit from increased exports and cheaper inputs. We rationalize these patterns by extending the theoretical framework of Helpman et al. (2017) to include sector heterogeneity in trade exposure and firm-level selection into imports. Our model indicates that the rise of China led to a reduction in cross-firm wage inequality in Brazil by about 5%.

This paper studies how and why the bilateral trades in manufacturing and services differ in their response to changes in the determinants, both theoretically and empirically. We build a unified theoretical framework that incorporates a demand bias towards services and a difference in the degree of national product differentiation between the two product groups. Estimation results support the theoretical predictions. The empirical model includes, among others, two non-standard trade-cost variables: a measure of internet penetration and virtual proximity (the number of bilateral hyperlinks). An important finding is that virtual proximity—thus far ignored in most gravity models—is a strong predictor of aggregate trade in both services and manufacturing. Also, physical distance is an important determinant of bilateral trade in manufacturing and services, even while controlling for virtual proximity.

We study the role of port efficiency on international trade, estimating the impact of vessel turnaround time on Brazilian exports. The main empirical challenge is to control for non-observed local factors that determine trade flows. This paper addresses this challenge by combining detailed data of Brazilian exports with an empirical strategy that allows us to control for various unobserved local determinants of exports. We use a unique database with vessel turnaround time at each port and city-level exports, including information on the Brazilian port used, the destination country, and products. The empirical strategy relies on a difference-gravity equation to explore the variation in port procedures turnaround. This approach controls for unobserved characteristics and determinants common to geographically close cities, exporting the same product to the same destination country. The results suggest that port delays are associated with decreased volumes of exports and decreased product variety. We find that each additional hour of port procedure delay is equivalent to a reduction in relative local exports of 2%. On average, a 10% relative reduction in vessel turnaround time increases the number of exported product categories by 1%. Our findings suggest that delays in port procedures represent costs to Brazilian exporters, affecting both the intensive and extensive margins of trade.