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This paper analyzes how a specific differentiation by governments throughout the world - whether a sector was deemed "essential" or "key" - affected firm performance. During the COVID-19 pandemic, governments designated specific services as "essential," which allowed firms operating in those sectors to remain (partially) open as well as being granted other preferential treatment. This paper analyses the effects of the key-status, by mapping the countries' lists to the sectoral level, and matching these sectors with firm-level Covid-19 survey data from 27 countries. The findings reveal that, controlling for a rich set of firm-level and sectoral characteristics, firms deemed key less often reported declining sales and demand for their goods or services, and had a smaller number of furloughed workers. Nonetheless, non-key firms were more likely to employ online business activities and to change the main product or service they offered, reflecting the necessity to otherwise adjust to the economic downturn and changes in demand.

We derive a novel estimation approach to quantify three-party relocation effects in a dyadic framework. Applied to the effects of civil conflicts on trade, we find robust evidence that importers substitute away from exporters that are engaged in conflict. This trade relocation persists after the resolution of a conflict. As a potential explanation for the longevity of this effect, we provide evidence that trade relocation increases the likelihood of the two countries signing a Preferential Trade Agreement, which persistently decreases their bilateral trade costs. A heterogeneity analysis suggests that trade relocation does not occur in the fuels sector, and that highly integrated supply chains are less likely to relocate. We derive our estimation approach from the structural gravity model of international trade, translating the triadic relationship between a conflict country and an exporter-importer pair into an estimable dyadic relationship. Our estimation approach can be adapted to either cover alternative unilateral shocks, e.g. natural disasters, or to analyze other bilateral dependent variables, e.g. migration or FDI flows.

This paper looks at individual risk behavior and disability in Vietnam, where many households live with a disabled family member. Due to the Vietnam war, disability is a common phenomenon and shapes individuals' daily life and decision making. Using longitudinal data of 2200 households in Vietnam and an instrumental variable strategy, we show that individuals who live with a disabled family member are more risk averse than others. In addition we employ field experiments and psychological primes to elicit risk and loss behavior of individuals living in the Vietnam province Ha-Thinh. The experimental results, underpin our panel results. We show in addition that a negative recollection of health issues, leads to a lower risk attitude of individuals who do not live with a disabled family member and that individuals who live with a disabled family member are less loss averse. Our findings are causal and contribute to existing studies showing that households who are characterized by higher backward risks are more risk averse than others.

This paper investigates several channels through which automation affects an emerging economy. Building on a Ricardian model of trade with sectoral linkages and a two-stage production technology, in which robots replace labor in certain tasks, it is shown that domestic and foreign automation have differential effects on labor markets. Based on this model, the impact of automation on local labor markets in Brazil are estimated using a shift-share approach. Local labor market exposures to industry-level stocks of robots are derived from their initial industry-employment composition. Foreign automation is found to decrease manufacturing employment through the channel of final goods exports, while it increases employment in the mining sector through the channel of input exports. This may stimulate what has been called "premature deindustrialization" in emerging economies. To account for possible endogeneity in adopting robots domestically, robot uptake in other emerging economies is used as an instrumental variable. Domestic automation is found to directly decrease the ratio of unskilled industry workers and increase the ratio of skilled workers. Also, the wage gap between the two groups widens as a consequence of domestic automation, reinforcing income inequality.

[Zur Orientierung] Wie der Projekttitel „Analyse der Verteilung von Einkommen und Vermögen in Deutschland“ bereits deutlich macht, gliedert sich der Forschungsauftrag in zwei Themenbereiche: das Einkommen und das Vermögen. Im Rahmen des Projekts wurden zunächst eine Aktualisierung und behutsame Weiterentwicklung früherer Analysen - hier ist vor allem die entsprechende Vorstudie zum Vierten Armuts- und Reichtumsbericht zu nennen - vorgenommen. Dabei galt es, die Kontinuität und Anschlussfähigkeit zu den bereits vorliegenden Auswertungen zu wahren. Im Weiteren wurden im Vergleich zur Vorstudie neue Aspekte aufgegriffen, beispielsweise die Erweiterung des Vermögensbegriffs oder die Einbeziehung des Konsums beim Thema Reichtum. Die durchgeführten Analysen basieren fast ausschließlich auf Mikrodaten, d.h. auf durch Befragungen gewonnene Daten zu einzelnen Personen oder Haushalten. Lediglich bei Thema Vermögen wurde an einzelnen Stellen auf Makrodaten in Form fertiger Indexgrößen oder Angaben zu den Vermögensbeständen in der Volkswirtschaftlichen Gesamtrechnung zurückgegriffen. Als Datenquellen fanden im Wesentlichen das Sozio-oekonomische Panel (SOEP), die Einkommens- und Verbrauchsstichprobe (EVS) und die European Union Statistics on Income and Living Conditions (EU-SILC) Verwendung, wobei wir die Ergebnisse der EU-SILC nur aus Gründen der Vollständigkeit in Tabellenform mitliefern. Alle genannten Datengrundlagen wurden bereits im Vorläuferbericht verwendet. Neu hinzugekommen ist der „Household Finance and Consumption Survey” (HFCS), ein umfragebasierter Datensatz, der Finanz- und Konsumdaten auf Haushaltsebene für die Länder der Eurozone beinhaltet. Im Kapitel 2 werden die Datenquellen mit Blick auf die für die Aufgabenstellung relevanten Merkmale vorgestellt. Das Datenkapitel endet mit Ausführungen zur statistischen Signifikanz der dargestellten Ergebnisse. Dieser Abschnitt weist auf eine der wesentlichen Weiterentwicklungen der vorliegenden Arbeit hin: In allen Darstellungen werden Konfidenzbereiche für die jeweiligen Indikatoren mit ausgewiesen, um den Leserinnen und Lesern eine Einschätzung der statistischen Zuverlässigkeit der Schätzergebnisse zu erlauben. [...] Lebenslagen in Deutschland - Armuts- und Reichtumsberichterstattung der Bundesregierung.