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In an extensive research project, we have assessed the application of different service models by export credit agencies (ECAs) and export-import banks (EXIMs). We conducted interviews with 35 representatives of ECAs and EXIMs from 27 countries. The question guiding this study is: How do ECAs and EXIMs adopt public service models for supporting exporters? We conducted a holistic multiple case study, investigating if and how these organisations apply public service models developed by Schedler and Guenduez, and which roles of the state are relevant. We find that there is a variety of different service models used by ECAs and EXIMs, and that the service model approaches have great potential to learn from each other and innovate existing services.
Staatliche Exportkreditagenturen und Export-Import-Banken finanzieren, versichern und garantieren jährlich fast 1 Bio. US-Dollar – mehr als 3 % der globalen Güterexporte. Ihre Interventionen sind an internationale Rahmenbedingungen gebunden, insbesondere an das WTO-Subventionsübereinkommen (ASCM) und den OECD-Konsensus. Das komplexe Zusammenspiel beider Rechtsrahmen sorgt seit langem für Herausforderungen, vor allem hinsichtlich des Anwendungsbereichs des “safe haven” des ASCM und des “Matching”-Mechanismus der OECD. In den vergangenen Jahren hinzugekommen ist die Problematik neuer Instrumente der Exportvor- sowie der Klimafinanzierung. Der folgende Beitrag erörtert Herausforderungen und Lösungsansätze. Er zeigt auf, dass der neue OECD-Konsensus trotz zahlreicher Verbesserungen zentrale rechtliche Probleme nicht behebt.
Prediction of Claims in Export Credit Finance: A Comparison of Four Machine Learning Techniques
(2020)
This study evaluates four machine learning (ML) techniques (Decision Trees (DT), Random Forests (RF), Neural Networks (NN) and Probabilistic Neural Networks (PNN)) on their ability to accurately predict export credit insurance claims. Additionally, we compare the performance of the ML techniques against a simple benchmark (BM) heuristic. The analysis is based on the utilisation of a dataset provided by the Berne Union, which is the most comprehensive collection of export credit insurance data and has been used in only two scientific studies so far. All ML techniques performed relatively well in predicting whether or not claims would be incurred, and, with limitations, in predicting the order of magnitude of the claims. No satisfactory results were achieved predicting actual claim ratios. RF performed significantly better than DT, NN and PNN against all prediction tasks, and most reliably carried their validation performance forward to test performance.
Provides a state-of-the-art overview of international trade policy research
The Handbook of Global Trade Policy offers readers a comprehensive resource for the study of international trade policy, governance, and financing. This timely and authoritative work presents contributions from a team of prominent experts that assess the policy implications of recent academic research on the subject. Discussions of contemporary research in fields such as economics, international business, international relations, law, and global politics help readers develop an expansive, interdisciplinary knowledge of 21st century foreign trade.
Accessible for students, yet relevant for practitioners and researchers, this book expertly guides readers through essential literature in the field while highlighting new connections between social science research and global policy-making. Authoritative chapters address new realities of the global trade environment, global governance and international institutions, multilateral trade agreements, regional trade in developing countries, value chains in the Pacific Rim, and more. Designed to provide a well-rounded survey of the subject, this book covers financing trade such as export credit arrangements in developing economies, export insurance markets, climate finance, and recent initiatives of the World Trade Organization (WTO). This state-of-the-art overview:
• Integrates new data and up-to-date research in the field
• Offers an interdisciplinary approach to examining global trade policy
• Introduces fundamental concepts of global trade in an understandable style
• Combines contemporary economic, legal, financial, and policy topics
• Presents a wide range of perspectives on current issues surrounding trade practices and policies
The Handbook of Global Trade Policy is a valuable resource for students, professionals, academics, researchers, and policy-makers in all areas of international trade, economics, business, and finance.
Comparing anomalies and exceptions to multilateral dysfunction across a number of spheres of world politics, the book chapter explores pathways through and beyond gridlock in trade. It provides a vital new perspective on world politics as well as a practical guide for positive change in global policy.
Risk aversion, financing and real servicThe Global CEO Survey was launched in 2015 by researchers from Offenburg University, the University of Westminster and the London School of Economics and Political Science (LSE) to better understand and discover what factors influence exporters’ demand for credit insurance. Although some scholars discussed aspects of corporate insurance demand with regard to exporters, there is limited research concerning the demand for export credit insurance associated with firm-specific factors. Only few empirical studies support existing theories on corporate insurance demand and export credits. This project investigates and fills the relevant gap of official export credit insurance demand.es
Economic growth is usually driven by improvements in productivity, economic efficiency, trade and innovation. Increasing efficiency means to produce larger output using the same amount of factors for production such as raw materials, labour, and capital. However, regardless of the driver, growth is often investment-hungry and it is not rare to find an economy with potential for growth but lacking locally available investment. In this scenario, Foreign Direct Investment (FDI) can fill the gap between investment needed to promote economic growth and locally available investments.