The evolution of nonlinear dynamics in political science and public administration: Methods, modeling and momentum

L Douglas Kiel

doi:10.1155/s1026022600000571

Abstract

This paper examines the evolution of the application of nonlinear dynamics and related methods to the study of political science and public administration throughout the 20th century. Some analysts understood the importance of nonlinearity to political and administrative studies in the early part of the century. More recently, a growing number of scholars understand that the political and administrative worlds are ripe with nonlinearity and thus amenable to nonlinear dynamical techniques and models. The current state of the application of both discrete and continuous time models in political science and public administration are presented. There is growing momentum in political and public administration studies that may serve to enhance the realism and applicability of these sciences to a nonlinear world.

Highlights

Professor of Public Administration and Political Economy, School of Social Sciences, University of Texas at Dallas, P.O
The reaching out, the self-presentation which offers new symbiotic relations, the risk accompanying innovation, This paper examines the evolution of the application of nonlinear dynamics and related methods to the study of political science and public administration throughout the 20th century
A growing number of scholars understand that the political and administrative worlds are ripe with nonlinearity and amenable to nonlinear dynamical techniques and models

Summary

Early Recognition of Nonlinearity

Some early 20th century social scientists were cognizant of the possibility of nonlinearity in political and public administrative phenomena. Relative to political science the literature of public administration reveals far fewer efforts to use nonlinear methods of analysis and model building. Ongoing efforts to expand the array of spatial nonlinear methods to political and administrative studies are likely to be enhanced by the introduction of journal outlets such as the Journal of Artificial Societies and Social Simulation, recently established at the University of Surrey The fact that this journal is electronic and computer-based raises interesting possibilities for social science spatial modeling. Studies of Functional nonlinearity in political science and public administration generally include attempts to either discern nonlinearities in existing data or to identify instances where nonlinear and chaotic behavior has the potential to occur. Continuous time models continue to serve as the dominant modality due to the strength of Brown’s (1995a) argument and because these methods are more widely recognized and known among political scientists

Dynamical Models in Discrete Time

Dynamical Models in Continuous Time

Findings

VENTURING A PREDICTION IN AN UNPREDICTABLE WORLD