Macroeconomic Scenarios and Reality : A Frequency Domain Approach for Analyzing Historical Time Series and Generating Scenarios for the Future
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Macroeconomic scenarios are an important component of Asset and Liability Management (ALM) models as used by financial institutions around the world such as pension funds and insurance companies to support important strategic policy decisions, for example on the optimal strategic asset allocation. The scenarios are used to model the fundamental uncertainty about the future state of the economy that will effect the outcomes of the policy decisions in terms of the objectives and constraints of the various stakeholders. The exact statistical dynamic properties of the scenarios can have an enormous impact on the outcomes of ALM models and thereby also on the strategic policy decisions that are based on these outcomes. The objective of this book is therefore to contribute to a higher quality of economic scenarios and thereby to a higher quality of the strategic decision making that is based on these scenarios. The book is divided into four parts. Part I serves as an introduction. Part II provides the necessary technical background. Part III presents almost ninety stylized facts about the empirical behavior of important macroeconomic variables in the Netherlands, the United States and the United Kingdom which are consistently obtained by means of a specific, clear and extensively tested frequency domain methodology. The results of Part III can serve as a complete and consistent reference for all those interested in the empirical behavior of macroeconomic variables. Finally, Part IV tests existing Vector AutoRegressive (VAR) scenario models against the benchmark empirical knowledge from Part III and presents a flexible and transparent frequency domain VAR scenario framework that resolves many of the shortcomings of the existing models. The book is complete and consistent in terms of data, techniques and notation used. It is completely self contained and can be studied without having to resort to much additional literature and can even be used as a (partial) textbook in the fields of autoregressive models, spectral analysis and filtering techniques. Hens Steehouwer (1972) studied econometrics at the Erasmus University of Rotterdam from which he graduated in 1996. Since that time he has been working as a consultant in the field of ALM and scenario analysis at ORTEC. For the last three years he has been heading a separate unit that focuses on ALM for insurance companies. Parallel to his work at ORTEC, he worked on the research described in this book for which he received a Ph.D. in economics at the Free University of Amsterdam in 2005. The author gratefully acknowledges the support he received for these purposes from the Bank Nederlandse Gemeenten (BNG) and ORTEC.