Suchergebnisse

Die 'klassischen' Methoden der spektralen Einschätzung von Zeitreihen weisen ernsthafte Mängel bei der Anwendung auf ökonomische Daten auf. Der vorliegende Beitrag demonstriert, daß die Maximum-Entropie Spektral-Analyse für solche Daten mehr Erfolg verspricht. Analysiert werden mit dieser Methode die Schwankungen in den Abgaben zum Zehnten als ein wichtiger Indikator für die Getreideernteerträge in Deutschland (Mittelfranken) und der Schweiz. Getreide war das wichtigste Agrarprodukt in der vorindustriellen Wirtschaft, das nicht weniger als 70 Prozent des menschlichen Kalorienbedarfs deckte. Die Schwankungen der Ernteerträge hatten daher entscheidende Implikation für Leben und Tod der Bevölkerung. Anhand der Methode finden die Autoren einen Vierjahreszyklus bei den Abgaben und den Marktpreisen für Getreide sowohl in Deutschland als auch in der Schweiz. Inwieweit klimatischen Schwankungen bei diesen Zyklen eine Rolle spielen, soll in weiteren Studien untersucht werden. (ICE)

Die Magisterarbeit enstand parallel zur Mitarbeit an einem Projekt, einer feasability study mit dem Titel "A Methodological Study for Measuring the Diversity of Science". Diese Studie hatte das Ziel, die Diversität einer Forschungslandschaft mit bibliometrischen Mitteln zu messen. Neuere Entwicklungen in der Wissenschaftspolitik – die Organisation der Mittelvergabe unter der Prämisse der Exzellenzförderung – bewirken, so die Ausgangsthese, eine Abnahme an Vielfalt in der Forschung, da einerseits die Anzahl geförderter Projekte abnimmt und andererseits WissenschaftlerInnen sich zunehmend dazu gezwungen sehen können, sich auf besonders Erfolg versprechende oder sogar wissenschaftliche Modethemen zu konzentrieren und randständigere Themen zu vernachlässigen. Durch bibliometrische Methoden sollen Kriterien entwickelt werden, die unabhängig von der naturgemäß subjektiven Wahrnehmung der WissenschaftlerInnen sind. Mit Hilfe einer Clusteranalyse werden die Zitationsdaten eines Fachgebietes – der Elektrochemie – in inhaltlich kohärenten Strukturen abgebildet und diese Partitionierung anschließend mit der Shannon-Wiener-Entropie gemessen. Inhalt der Magisterarbeit ist neben der Darstellung der feasability study eine vertiefte Erarbeitung und Analyse der methodischen Grundlagen der Studie sowie alternativer Methoden von Zitationsstudien in Bezug auf Clustermethoden und Ähnlichkeitsmaße. ; This Magister Artium thesis resulted from a project collaboration, a feasability study called "A Methodological Study for Measuring the Diversity of Science". This study was aimed at measuring the diversity of science with bibliometric measures. The study`s assumption is, that recent developments in science politics - oganization of funding with focus on excellence - result in a decrease of diversity of research. Diversity might be reduced due to a lesser amount of funded projects as well as due to the fact that scientists might feel compelled to concentrate on most promising or even trendy issues and therefore disregard more marginal themes. By way of bibiometric methods criteria shall be developed which are independend of scientists` subjective perception. A cluster analysis is performed in order to map citation data of the research field of electrochemistry to coherent structures. Afterwards the entropy of this partitioning is assessed with the Shannon-Weaver entropy measure. The thesis describes the feasability study and offers a thorough analysis of methodic fundamentals of the applied procedures as well as of alternative methods in the field of citation analysis with regard to cluster methods and similarity measures.

The advent of electronic computing permits the empirical analysis of economic models of far greater subtlety and rigour than before, when many interesting ideas were not followed up because the calculations involved made this impracticable. The estimation and testing of these more intricate models is usually based on the method of Maximum Likelihood, which is a well-established branch of mathematical statistics. Its use in econometrics has led to the development of a number of special techniques; the specific conditions of econometric research moreover demand certain changes in the interpretation of the basic argument. This book is a self-contained introduction to this field. It consists of three parts. The first deals with general features of Maximum Likelihood methods; the second with linear and nonlinear regression; and the third with discrete choice and related micro-economic models. Readers should already be familiar with elementary statistical theory, with applied econometric research papers, or with the literature on the mathematical basis of Maximum Likelihood theory. They can also try their hand at some advanced econometric research of their own

The economics and statistics literature using computer simulation based methods has grown enormously over the past decades. Maximum Simulated Likelihood is a statistical tool useful for incorporating individual differences (called heterogeneity in the econometrics literature) and variations into a statistical analysis. Problems that can be intractable with traditional methods are solved using computer simulation integrated with classical methods. Instead of assuming that everyone responds to stimuli in the same way, allowances are made for the possibility that different decision makers will respond in different ways. The techniques can be applied to problems of individual choice, such as the choice of a transportation model, or choice among health care options, as well as to the problem of making financial and macroeconomic predictions. Contributors to the volume discuss alternative simulation methods that permit faster and more accurate inference, as well as applications of established methods.

The economics and statistics literature using computer simulation based methods has grown enormously over the past decades. Maximum Simulated Likelihood is a statistical tool useful for incorporating individual differences (called heterogeneity in the econometrics literature) and variations into a statistical analysis. Problems that can be intractable with traditional methods are solved using computer simulation integrated with classical methods. Instead of assuming that everyone responds to stimuli in the same way, allowances are made for the possibility that different decision makers will respond in different ways. The techniques can be applied to problems of individual choice, such as the choice of a transportation model, or choice among health care options, as well as to the problem of making financial and macroeconomic predictions. Contributors to the volume discuss alternative simulation methods that permit faster and more accurate inference, as well as applications of established methods.

This collection of methodological developments and applications of simulation-based methods were presented at a workshop at Louisiana State University in November, 2009. Topics include: extensions of the GHK simulator; maximum-simulated likelihood; composite marginal likelihood; and modelling and forecasting volatility in a bayesian approach.