Nonlinear dynamics in economics. A theoretical and statistical approach to agriculture markets
type: Item
instance of: scholarly article
title: Nonlinear dynamics in economics. A theoretical and statistical approach to agriculture markets
zbMATH Open document ID: 0844.90019
author: B. F. Finkenstädt
published in: Lecture Notes in Economics and Mathematical Systems
publication date: 1995-08-10T00:00:00Z
review text: This study is motivated by the ``nonlinear'' perspective. It consists of five chapters that can be read almost independently of each other. The first chapter gives an introduction to nonlinear dynamics to a reader who is not familiar with the topic. There are a lot of interesting features about chaos that attract both specialists and nonspecialists. The introductory chapter is restricted to a selection of properties, which are important to understand the remaining chapters. The fundamental ideas are stated in a somewhat informal style using simple, worked-out cases from the natural sciences. Attention is given to the one-dimensional quadratic map as it exhibits almost all interesting properties. Aside from its theoretical properties, the nonlinear approach sheds a different light upon the traditional linear statistical methodology, which is outlined in view of the statistical part of the thesis. The second chapter deals with one of the simplest dynamic models in economics, namely the cobweb model, which is often used to describe a highly stylized version of an agricultural market. It is shown that the introduction of a nonlinear demand function to the cobwed model under adaptive expectations broades the possible range of dynamic outcomes significantly. Although it can hardly be assumed that such a simplified model -- be it linear or nonlinear -- is able to perfectly explain the real world data, it is necessary to examine some observed time series from agricultural markets for typical nonlinear behavior such as the occurence of asymmetric cycles, low-dimensional clustering in phase space, and possible short-time predictability. The third and the fourth chapters are concerned with detecting such special nonlinear patterns in the agricultural price series. The third chapter draws upon selection of relatively new tests for (non)linearity, as suggested in the nonlinear time series literature. The fourth chapter deals with a new neighbor forecasting algorithm to distingui…
reviewed by: Krzysztof Piasecki
Mathematics Subject Classification ID: 91B62
zbMATH DE Number: 783770
zbMATH Keywords: nonlinear dynamics
zbMATH Keywords: chaos
zbMATH Keywords: cobweb model
zbMATH Keywords: agricultural market
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 783770