What is the best way to reform Social Security? Academic literature offers diverging advice. There is a well-known result that the optimal size of Social Security is zero, implying it is best to phase the program out. Other studies argue that much can be gained by redesigning the program, given its current size. We provide a unified analysis that examines how the optimal size of Social Security depends on the key features of its design. We first develop a theoretical decomposition tracing the program's welfare effects to (i) income redistribution, (ii) distortions on the annuitization level, and (iii) intertemporal distortions. We then quantitatively assess the role of these channels. We show that the zero-optimal-size result arises because Social Security is too distortive and not redistributive enough. Once these design flaws are corrected, it is even optimal to increase the size of the program.
We develop a model of international trade and geopolitical disputes [...]. Bilateral disputes arise exogenously, and rival countries engage in negotiations to avoid war. All welfare-relevant geoeconomic factors [...] depend on the opportunity cost of war, itself shaped by observed trade flows. We provide a simple procedure to estimate these factors in a model of trade calibrated to current data. This approach is then used to quantify the geoeconomic factors characterizing the US-China relationship. We find that the growing US dependence to Chinese products and markets over the past thirty years has increased the cost of geopolitical disputes with China for the US. In this context, decoupling [...] may offer geopolitical benefits. Yet, the analysis highlights a fundamental security dilemma: because export and import dependencies influence bargaining power [...], decoupling may reduce the diplomatic concessions needed to maintain peace but can paradoxically raise the risk of escalation.
Als Volkswirtin forschen und Ideen für die Zukunft entwickeln: Du interessierst dich für Wirtschaft und Forschung? Du möchtest später in deinem Beruf zur Lösung von Problemen in Wirtschaft und Gesellschaft beitragen? Du möchtest Ideen entwickeln, wie man die knappen Ressourcen von heute mit Rücksicht auf die Natur für den Wohlstand von Vielen effizient einsetzen kann? Dann lerne eine Ökonomin kennen, die mit ihrer Forschung zu Lösungen aktueller Probleme beiträgt, und erfahre, wie du selbst Ökonomin werden kannst. Außerdem nimmst du an einem spannenden wirtschaftswissenschaftlichen Experiment teil. Lerne dabei, wie unser Verhalten die Gesellschaft und Umwelt beeinflusst und wie wir gemeinsam Lösungen für gesellschaftliche Herausforderungen entwickeln können. Beim gemeinsamen Lunch Snack bleibt noch Zeit für Eure Fragen. Unser Angebot richtet sich an Schülerinnen ab der 8. Klasse.
Conduct research as an economist and develop ideas for the future: Are you interested in economics and research? Would you like to contribute to solving economic and social problems in your future career? Would you like to develop ideas on how to use today's scarce resources efficiently for the prosperity of many, while respecting nature? Then meet an economist who contributes to solving current problems with her research and find out how you can become an economist yourself. You will also take part in an exciting economic experiment. Learn how our behavior influences society and the environment and how we can work together to develop solutions to social challenges. There will be time for your questions during a joint lunch snack. Our offer is aimed at female students from the 8th grade onwards. The event will be held in German.
Fragen stellen, zuhören, zählen: So erforschen wir das Leben im Ahrtal nach der Flut Wie kann man herausfinden, wie es Menschen nach einer großen Flut geht? Und wie kann die Forschung beim Wiederaufbau helfen? Das alles erfahren Kinder bei einem Kinderuni-Vortrag von Svenja Hippel und Julia Mink im Rahmen der Bonner Kinderuni. Jedes Semester lädt die Universität Bonn Kinder zwischen 8 und 13 Jahren ein, Uni-Luft zu schnuppen, Wissenschaft und Forschung kennen zu lernen und Fragen zu stellen. In ihrem Projekt untersuchen Julia Mink und Svenja Hippel das Leben im Ahrtal nach der Flut im Jahr 2021. Bei ihrem Vortrag werden sie erklären, wie aus Ideen Forschungsfragen werden, wie ein Fragebogen entsteht und wie aus vielen Antworten Zahlen werden, die Politik und Gesellschaft dazu benutzen können, um Menschen besser zu unterstützen.
Asking questions, listening, counting: How we’re studying life in the Ahr Valley after the flood How can we find out how people are doing after a major flood? And how can research help with the recovery effort? Children will learn all this at a Children’s University lecture by Svenja Hippel and Julia Mink as part of the Bonn Children’s University. Every semester, the University of Bonn invites children between the ages of 8 and 13 to get a taste of university life, learn about science and research, and ask questions. In their project, Julia Mink and Svenja Hippel are studying life in the Ahr Valley following the 2021 flood. In their presentation, they will explain how ideas become research questions, how a questionnaire is developed, and how numerous responses are transformed into data that policymakers and society can use to better support people. The event will be in German.
This paper quantifies why households save and work using a life-cycle model that incorporates wage risk, endogenous labor supply of both spouses, marital transitions, health, medical expenses, mortality, and bequest motives at the death of the first and last household member. We estimate it using PSID and HRS data and conduct counterfactuals to assess the quantitative role of individual mechanisms. Precautionary saving against wage risk is smaller than in models that abstract from labor supply and within-household insurance. Bequest motives and medical expenses remain important drivers of wealth, while marriage and divorce generate large but offsetting effects across household types.
Research data management (RDM) is an integral part of good scientific practice. At the same time, very practical questions arise in everyday research: How can I ensure that my data is securely stored and properly backed up? What services, IT tools, and advisory support are available at the University of Bonn to assist me and make my RDM workflow more efficient? To address these key questions, we invite you to the Research Data Service Center Roadshow 2026, an information session on research data management and the services and support available at the University of Bonn. As part of its roadshow, the Research Data Service Center will provide a concise and hands-on overview of support services and IT tools designed to help you manage your research data effectively — from DMP checks and individual consultations to suitable storage solutions, IT tools, and data publication options.
Research data management (RDM) is an integral part of good scientific practice. At the same time, very practical questions arise in everyday research: How can I ensure that my data is securely stored and properly backed up? What services, IT tools, and advisory support are available at the University of Bonn to assist me and make my RDM workflow more efficient? To address these key questions, we invite you to the Research Data Service Center Roadshow 2026, an information session on research data management and the services and support available at the University of Bonn. As part of its roadshow, the Research Data Service Center will provide a concise and hands-on overview of support services and IT tools designed to help you manage your research data effectively — from DMP checks and individual consultations to suitable storage solutions, IT tools, and data publication options.
We present a new approach to formulating and solving heterogeneous agent mod- els with aggregate risk. We replace the cross-sectional distribution with low-dimensional prices as state variables and let agents learn equilibrium price dynamics directly from sim- ulated paths. To do so, we introduce a structural reinforcement learning (SRL) method which treats prices via simulation while exploiting agents’ structural knowledge of their own in- dividual dynamics. Our SRL method yields a general and highly efficient global solution method for heterogeneous agent models that sidesteps the Master equation and handles models traditional methods struggle with, like those with nontrivial market-clearing con- ditions. We illustrate the approach in the Krusell-Smith model, the Huggett model with aggregate shocks, and a HANK model with a forward-looking Phillips curve, all of which we solve globally within minutes.