1. Complexity, Emergence, and Chaos: Geog 220: Geosimulation Lisa Murawski 1/31/05 Application to Regional Industrial Systems

2. Complexity Has many guises –Information processing, physical systems, computer science/computation, psychology Our concern: the study of the emergence of macro-properties from the micro-properties Complex systems have field-specificity (economics, biology, physical science) –Consist of agents –Agents interact in non-linear ways –Exhibit properties of emergence

3. Emergence Slippery fish – But not quite “eye-of-the-beholder”! Properties: –Repeating patterns in a system that exhibits perpetual novelty (regularities) –Building block-type organization –Interactions are bottom-up and top-down –Whole is more than the sum of its parts

4. Regional Economies as Complex Systems Regional economies exhibit regularities Definite building-block structure Feedback-type interaction at many levels Regional economy has properties that individual parts of the system don’t have Bottom line: regional economies can be viewed as self- organizing, complex adaptive systems composed of agents that exhibit emergence and chaotic behavior Individual decisions Business decisions Government decisions

5. So What? R. W. White. Transitions to chaos with increasing system complexity: the case of regional industrial systems Environment and Planning A, 1985, v.17, p. 387- 396

6. Economic Model Objective: –Represent onset of chaotic behavior in a spatially distributed economic system Method: –Simulation models economies and diseconomies of scale and aggregation Profit = Revenue – Cost Cost = f (economies and diseconomies of scale and urbanization) Revenue = f (output, price (in all centers))

7. Methodology Simulate happenings for t=1-1000, for one- and two-sector cases, for one or more centers Find the intrinsic growth rate r where chaotic behavior begins Chaos –Formal mathematical definition (unlike emergence?) –Chaotic behavior is: Aperiodic Extremely sensitive to initial conditions

8. Results Greater complexity  systems exhibit chaotic behavior for a lower intrinsic growth rate r Greater complexity  harder to tell exactly where chaotic behavior begins Chaotic systems do exhibit some periodicity, predictable to some degree

9. Discussion Relevance to real economic behavior Realistic interpretation of growth rate Chaotic behavior in one industry may induce same in others Evolution of economic system may be chaotic, not stochastic Business cycle itself may be one chaotic oscillation!

10. Doggie Bag of Ideas Emergence, complexity and chaos are not just abstract ideas Chaotic behavior of self-organizing systems can be a useful explanatory (and exploratory) tool Complex systems thinking is a framework, a different approach

11. Journal of Complexity