Autoregressive Neural Network Processes - Univariate, Multivariate and Cointegrated Models with Application to the German Automobile Industry

Autoregressive Neuronale Netze - Univariate, Multivariate und Kointegrierte Modelle mit einer Anwendung aus dem Bereich der deutschen Automobilindustrie

  • Prediction of economic variables is a basic component not only for economic models, but also for many business decisions. Nevertheless it is difficult to produce accurate predictions in times of economic crises, which cause nonlinear effects in the data. In this dissertation a nonlinear model for analysis of time series with nonlinear effects is introduced. Linear autoregressive processes are extended by neural networks to overcome the problem of nonlinearity. This idea is based on the universal approximation property of single hidden layer feedforward neural networks of Hornik (1993). Univariate Autoregressive Neural Network Processes (AR-NN) as well as Vector Autoregressive Neural Network Processes (VAR-NN) and Neural Network Vector Error Correction Models (NN-VEC) are introduced. Various methods for variable selection, parameter estimation and inference are discussed. AR-NN's as well as a NN-VEC are used for prediction and analysis of the relationships between 4 variables related to the German automobile industry: The US Dollar to Euro exchange rate, the industrial output of the German automobile industry, the sales of imported cars in the USA and an index of shares of German automobile manufacturing companies. Prediction results are compared to various linear and nonlinear univariate and multivariate models.

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Metadaten
Author:Sebastian Dietz
URN:urn:nbn:de:bvb:739-opus-22524
Advisor:Gertrud Moosmüller
Document Type:Doctoral Thesis
Language:English
Year of Completion:2011
Date of Publication (online):2011/06/08
Publishing Institution:Universität Passau
Granting Institution:Universität Passau, Wirtschaftswissenschaftliche Fakultät
Date of final exam:2011/05/18
Release Date:2011/06/08
Tag:Econometrics; Neural Networks; Nonlinear Optimization; Nonlinear Time Series Analysis
GND Keyword:Nichtlineare Optimierung; Nichtlineare Zeitreihenanalyse; Zeitreihenanalyse; Ökonometrie
Institutes:Wirtschaftswissenschaftliche Fakultät / Sonstiger Autor der Wirtschaftswissenschaftlichen Fakultät
Dewey Decimal Classification:3 Sozialwissenschaften / 31 Statistiken / 310 Sammlungen allgemeiner Statistiken
Licence (German):License LogoStandardbedingung laut Einverständniserklärung

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