Michael J. Radzicki

Institutional Dynamics: An Extension of the Institutionalist Approach to Socioeconomic Analysis

In a 1978 article in this journal, Charles K. Wilber and Robert S. Harrison made a significant contribution to the economic literature by outlining the methodology that had been implicitly used by institutional economists since the time of Thorstein Veblen and John R. Commons [Wilber and Harrison 1978]. This holistic pattern modeling approach is quite different from the traditional logical empiricist approach used by neoclassical economists and is responsible for the rich social science flavor that is the strength of institutional analysis.2 One of the biggest criticisms that has been leveled against pattern modeling however, even if its inductive underpinnings are accepted, is

Mr. Hamilton, Mr. Forrester, and a Foundation for Evolutionary Economics

Conceptualization Watching Observations & Reflections ences must then be tested through doing (an active physical activity) or experimentation, which can be conducted mentally or with physical and/or mathematical tools. Finally, the results of experimentation must be translated into abstract concepts and generalizations through a cognitive process driven at the outset by feeling (an abstract cognitive activity). Of course, new abstract concepts and generalizations create a framework for watching, and a new cycle of learning can be initiated. Kotbs Model and the System Dynamics Modeling Process. When an experienced system dynamicist creates a model, he or she utilizes a set of skills, and undertakes an evolutionary process, that is strikingly similar to Kolbs model of learning. As shown in figure 6 (reproduced from Saeed 1998, 405), each of Kolbs four primary learning activities corresponds to a skill that a system dynamicist needs in order to build insightful models. Fee~ ing corresponds to the model conceptualization skill, watching corresponds to the pattern recognition skill, thinking corresponds to the system identification skill, and doing corresponds to the experimentation skill. Mr. Hamilton, Mr. Forrester, and Evolutionary Economics 159 Figure 6. System Dynamics Interpretation of Kolbs Model of Experiential Learning System Identification a) System Boundary b) Feedback Structure c) Information Structure d) Experimental Design for Model Validity e) Experimental Design for Policy Exploration

Stability in a Superpower-Dominated Global Economic System

This paper provides an example of a system dynamics model that incorporates soft variables. The model examines the challenges that a superpower faces while maintaining its position in the global economic system. The effects on aggregate welfare of the population at home and abroad, as well as, issues of sustaining authority in the long run are explored through experimentation with a computer model. This theory is an extension of the framework developed by Saeed (1990), which was used to understand political instability and the failure of the government to stay committed to welfare agendas in the developing countries. The present model captures the interaction between several institutional actors involved with the economic and the governance systems. They include the public, the authoritarian regime, the reformist movements that seek change within the existing framework, and the dissident movements that turn to violent methods.

Use of System Dynamics to Understand Long-Term Impact of Climate Change on Pavement Performance and Maintenance Cost

An increase in the vulnerability of the nations roadway network to changes in climatic conditions has become an issue of significant concern. Heavy rainfall and high temperatures are examples of climatic factors that can affect pavement performance and conditions in a detrimental way. Some of these effects, specifically on costs associated with constructing and maintaining roads, may not be significant in the short term but may become significant in the long term. The objective of this study was to present a framework to use system dynamics to understand the long-term impact of climate change on pavement performance and maintenance activity. A system dynamics model was created with available pavement performance and climate change data, and the effects on various key factors, such as pavement life and maintenance cost, were evaluated through simulation. Preliminary results show that the long-term effects of changes in air temperature, rainfall, seawater–level rise, and number of hurricanes on pavement performance are significant and that costs are expected to increase significantly (>160% in 100 years) and nonlinearly. From these findings, recommendations are made for obtaining more accurate and reliable data on relevant climate change factors and for using a system dynamics approach to integrate the multi-disciplinary topics of climate change, pavement design and performance, and economics into comprehensive studies.

An Institutional Dynamics Model of Sterling, Massachusetts: Indicative Planning at the Local Level

In a series of papers, Radzicki [1988, 1990a, 1990bl and Radzicki and Sterman [19931 have argued that system dynamics computer simulation modeling and institutionalist pattern modeling are strikingly similar and hence should be combined to form a more powerful institutional dynamics approach to socioeconomic analysis. Although these papers put forth the theoretical case for a marriage between the two perspectives, they did not present an actual institutional dynamics pattern model. The purpose of this paper is to fill that void. In addition, this paper will discuss how the institutional dynamics modeling process can add value to indicative planning at the local level.

In Defense of System Dynamics: A Response to Professor Hayden

In a 2006 paper, Professor Gregory Hayden argued that system dynamics is an inadequate tool for explaining the institutional systems principles of hierarchy, feedback and openness. The purpose of this paper is to show that many of Professor Haydens claims are either misguided or incorrect. The paper also reinforces the argument that system dynamics modeling can add significant value to traditional institutional economic analysis.

Convergence of the Social Fabric Matrix and Complex Modeling

System dynamics is a computer modeling technique that is used to solve problems in complex socioeconomic systems through the design or redesign of system structure. Its application often involves the elicitation and mapping of knowledge from experts and stakeholders who possess detailed information about the relevant structure and behavior of the system under study. A digital computer is then used to accurately trace through the dynamics inherent in the mapping – a task that humans cannot do reliably via thought and debate due to their inherent cognitive limitations.

The Design of Educational Programs in System Dynamics at Worcester Polytechnic Institute (WPI)

Educational programs leading to degrees in system dynamics are rare and thus of critical importance to the future of the field of system dynamics. However, to a large extent such programs have not yet been made transparent to the system dynamics community as a whole. The present article describes the design and rationale for undergraduate and graduate programs at Worcester Polytechnic Institute (WPI). The goal of the article is to invite feedback from the system dynamics community about our specific programs as well as to facilitate wider discussion about the appropriate content, design, and pedagogy of degree programs and courses in system dynamics.

A Simulation Model of Katouzian's Theory of Arbitrary State and Society

This paper represents an initial effort to model the volatile behavior of Irans socio-political-economic system. More specifically, Homa Katouzians theory of Iranian political economy—a well-established descriptive theory of Irans unstable economic development—is translated into a system dynamics model, tested for internal consistency, and used for policy analysis. Simulation results confirm Katouzians claim that periodic episodes of significant arbitrary power are key to understanding the historically less-than-optimal behavior of the Iranian socioeconomic system. They also confirm the significance of oil revenue, economic sanctions, and civil resistance on Iranian economic development. Of note is that experimentation with the model reveals that educational policies that generate increased respect for the law by Iranian citizens can significantly improve the behavior of the Iranian socioeconomic system. The paper concludes with suggestions for future research.

Resurrecting a Forgotten Model: Updating Mashayekhi’s Model of Iranian Economic Development

In this chapter, Mashayekhi’s system dynamics model, which was built in 1978 to analyze Iranian economic development, is resurrected through a comprehensive restructuring and revalidation process. The focus of the original model was on the dependency of Iran’s economy on oil and its vulnerability to “petro dollars.” Since oil dependency is still a major issue in contemporary Iranian economic policy debates, reexamining Mashayekhi’s model is beneficial. It is shown that the original model is unable to reproduce the historical behavior of the Iranian economy from the mid-1980s onward. However, updating its exogenous variables, modifying some of its assumptions, and recalibrating some of its parameters significantly improve its ability to reproduce Iranian economic history. Revalidation of the modified model shows that it is fairly robust and generally reliable. Since the boundary of the original model was drawn somewhat narrowly, even the updated version presented in this chapter is an inadequate platform for analyzing many contemporary Iranian macroeconomic policies. However, the updated model is an excellent tool for analyzing questions directly related to the issue of Iranian oil dependency. Finally, it is argued that this chapter can serve as a starting point for those who wish to develop a system dynamics macroeconomic model of any resource-dependent developing nation.