In the “faster, better, and cheaper” information age, rapid technological breakthroughs create significant risks of obsolescence at the product level or the component level. Consequently, enormous challenges in jointly coordinating inventory replenishment and technology selection arise. The purpose of this dissertation is to develop analytical models to study technology selection and inventory replenishment joint optimization in inventory systems that face frequent technology innovations.
The structure of wages is crucial for economic performance and the evolution of employment in particular; see the handbook article of Katz and Autor (1999) and the more recent survey of Autor, Katz, and Kearney (2005b). With the growing availability of large micro data sets not only the wage level, but also the degree of wage dispersion or compression has received increasing attention.
The evolution of the West German wage structure between the mid-1970s and the mid-1990s has been extensively studied. By and large, the wage structure has been found to be relatively compressed in international comparison and rather stable over time; see Fitzenberger (1999) and Prasad (2000) and the literature cited therein. Returns to human capital components as well as residual wage inequality showed fairly little variation. In face of an ongoing skill-biased technical change (Acemoglu, 2002), this “unbearable stability” (Prasad, 2000) is considered a key aspect for the growing unemployment among low-skilled workers and it is frequently attributed to institutional rigidities.
The implementation of credit risk models has largely relied either on the use of historical default dependence, as proxied by the correlation of equity returns, or on equicorrelation, as extracted from CDOs. The drawbacks of equicorrelation are well known from the correlation smile: credit derivative pricing would therefore profit from risk&neutral depen& dence measures without the equicorrelation assumption. Using the copula methodology, we show how to infer them from CDS data, taking counter& party risk into consideration. We also provide a market application and explore its impact on the fees of some higher dimensional credit deriva& tives. Both in the FtD and CDO case, the adoption of a copula with tail dependency instead of the Gaussian one, which has no tail dependency, has the same qualitative effect than the use of (the correct) risk neutral measure instead of equity dependency: therefore, tail dependency com& pensates for the lack of risk neutral correlation, whenever historical equity correlation is adopted.
