Folgen des Klimawandels: Versicherungspflicht wird unausweichlich!

Zusammenfassung   Der Wirbelsturm Ike, der Mitte September die texanische Stadt Galveston traf, machte einmal wieder deutlich, wie verletzlich die Zivilisation gegenüber dem Klimawandel ist. Auch in Deutschland werden die Folgen des Klimawandels zunehmend spürbar. Wie werden Betroffene von Naturkatastrophen in Deutschland entsch?digt? Was w?re das ?konomisch und ?kologisch effiziente Instrument beim Umgang mit den Klimafolgen? Prof. Dr. Gert G. Wagner, 55, lehrt zur Zeit als Fellow am Max Weber Kolleg in Erfurt. Am Deutschen Institut für Wirtschaftsforschung (DIW Berlin) leitet er die L?ngsschnittstudie SOEP.     

Marginal Employment: No Jobs Miracle

Original Papers

Marginal Employment: No Jobs MiracleTowards a permanent decline of secondary employment?     

Benchmarking regression algorithms for loss given default modeling

The introduction of the Basel II Accord has had a huge impact on financial institutions, allowing them to build credit risk models for three key risk parameters: PD (probability of default), LGD (loss given default) and EAD (exposure at default). Until recently, credit risk research has focused largely on the estimation and validation of the PD parameter, and much less on LGD modeling. In this first large-scale LGD benchmarking study, various regression techniques for modeling and predicting LGD are investigated. These include one-stage models, such as those built by ordinary least squares regression, beta regression, robust regression, ridge regression, regression splines, neural networks, support vector machines and regression trees, as well as two-stage models which combine multiple techniques. A total of 24 techniques are compared using six real-life loss datasets from major international banks. It is found that much of the variance in LGD remains unexplained, as the average prediction performance of the models in terms of R² ranges from 4% to 43%. Nonetheless, there is a clear trend that non-linear techniques, and in particular support vector machines and neural networks, perform significantly better than more traditional linear techniques. Also, two-stage models built by a combination of linear and non-linear techniques are shown to have a similarly good predictive power, with the added advantage of having a comprehensible linear model component.     

Formal and informal contract farming in Mozambique: Socially embedded relations of agricultural intensification

This paper explores the role of contract farming arrangements in agricultural intensification in sub-Saharan Africa, combining secondary literature and original case material from Mozambique. The paper extends the scope of “contract farming” beyond the formal contracts between large companies and small-scale producers to include less formal credit agreements between farmers and traders. It argues that such informal contract arrangements are evidence of farmers' agency in “real markets.” In the studied cases, farmers use contract farming opportunities to intensify agricultural production by investing in irrigation and inputs. While informal contracts typically concern locally consumed crops, thus with more possibilities for side selling than formal contracts for export crops with company-controlled markets, informal contract compliance reflects closely knit social ties between the contracting parties. In both formal and informal contracts, purchasers tend to seek out producers who are already irrigating, thus obtaining gains from farmers' earlier investments. This also implies contract farming as a mechanism for accelerating social differentiation arising from unequal access to irrigation. The paper argues that the significance of informal contracts in the studied cases raises the possibility that informal contract farming by local traders plays a more important role in agrarian transformation in Africa than formal contract farming by large companies.