A service provided by the WU Library and the WU IT-Services

Random walks and non-linear paths in macroeconomic time series. Some evidence and implications.

Bevilacqua, Franco and vanZon, Adriaan (2002) Random walks and non-linear paths in macroeconomic time series. Some evidence and implications. Working Papers Series "Growth and Employment in Europe: Sustainability and Competitiveness", 22. Inst. für Volkswirtschaftstheorie und -politik, WU Vienna University of Economics and Business, Vienna.

[img]
Preview
PDF
Download (1998Kb) | Preview

Abstract

This paper investigates whether the inherent non-stationarity of macroeconomic time series is entirely due to a random walk or also to non-linear components. Applying the numerical tools of the analysis of dynamical systems to long time series for the US, we reject the hypothesis that these series are generated solely by a linear stochastic process. Contrary to the Real Business Cycle theory that attributes the irregular behavior of the system to exogenous random factors, we maintain that the fluctuations in the time series we examined cannot be explained only by means of external shocks plugged into linear autoregressive models. A dynamical and non-linear explanation may be useful for the double aim of describing and forecasting more accurately the evolution of the system. Linear growth models that find empirical verification on linear econometric analysis, are therefore seriously called in question. Conversely non-linear dynamical models may enable us to achieve a more complete information about economic phenomena from the same data sets used in the empirical analysis which are in support of Real Business Cycle Theory. We conclude that Real Business Cycle theory and more in general the unit root autoregressive models are an inadequate device for a satisfactory understanding of economic time series. A theoretical approach grounded on non-linear metric methods, may however allow to identify non-linear structures that endogenously generate fluctuations in macroeconomic time series. (authors' abstract)

Item Type: Paper
Keywords: random walks / real business cycle theory / chaos
Classification Codes: JEL C22, E32
Divisions: Departments > Volkswirtschaft
Depositing User: Repository Administrator
Date Deposited: 28 May 2002 14:13
Last Modified: 16 Jun 2011 12:05
URI: http://epub.wu.ac.at/id/eprint/1098

Actions

View Item