Tayloring Brazil: a system dynamics model for monetary policy feedback

The thesis introduces a system dynamics Taylor rule model of new Keynesian nature for monetary policy feedback in Brazil. The nonlinear Taylor rule for interest rate changes con-siders gaps and dynamics of GDP growth and inflation. The model closely tracks the 2004 to 2011 business cycle and outlines the endogenous feedback between the real interest rate, GDP growth and inflation. The model identifies a high degree of endogenous feedback for monetary policy and inflation, while GDP growth remains highly exposed to exogenous eco-nomic conditions. The results also show that the majority of the monetary policy moves during the sample period was related to GDP growth, despite higher coefficients of inflation parameters in the Taylor rule. This observation challenges the intuition that inflation target-ing leads to a dominance of monetary policy moves with respect to inflation. Furthermore, the results suggest that backward looking price-setting with respect to GDP growth has been the dominant driver of inflation. Moreover, simulation exercises highlight the effects of the new BCB strategy initiated in August 2011 and also consider recession and inflation avoid-ance versions of the Taylor rule. In methodological terms, the Taylor rule model highlights the advantages of system dynamics with respect to nonlinear policies and to the stock-and-flow approach. In total, the strong historical fit and some counterintuitive observations of the Taylor rule model call for an application of the model to other economies.

Green logistics: key elements for a well-functioning sustainable logistics system

A growing awareness of the modern society about the direct relationship between a growing global community with increasing total industrial activities on one hand and various environmental problems and a natural limitation of natural resources on the other hand set the base for sustainable or “green” approaches within the supply chain. This paper therefore will look at the issue of “Green Logistics” which seeks to reduce the environmental impact of logistics activities by taking into account functions such as recycling, waste and carbon emission reduction and the use of alternative sources of energy. In order to analyze how these approaches and ideas are being perceived by the system as a whole two models from the area of prospective and scenario planning are being used and described to identify the main drivers and tendencies within the system in order to create feasible hypothesis. Using the URCA/CHIVAS model allows us to identify the driver variables out of a high number of variables that best describe the system “Green Logistics”. Followed by the analysis of the actor’s strategies in the system with the Mactor model it is possible to reduce the complexity of a completely holistic system to a few key drivers that can be analyzed further on. Here the implications of URCA/CHIVAS and Mactor are being used to formulate hypotheses about the perception of Green Logistics and its successful implementation among logistics decision makers by an online survey. This research seeks to demonstrate the usefulness of scenario planning to a highly complex system observing it from all angles and extracting information about the relevant factors of it. The results of this demonstration indicate that there are drivers much beyond the factory walls that need to be considered when implementing successfully a system such as Green Logistics.