This is an abstract of a presentation I gave at AEA 2014. Click here for the slide deck.

How can “complexity” be used to identify program theory, specify data collection, interpret findings, and make recommendations? Substitute “multiple regression” for “complexity”, and we know the answer because our familiarity with regression is practical and instrumental. This presentation will nudge our understanding of “complexity” closer to our comfort level with the tools we already know and love so well. It will then present a brief overview of key concepts in complexity, starting with agents and iteration, and identify some of the many concepts that derive from probing those two ideas (e.g. attractors, state changes, fractals, evolution, network behavior and power laws.) Finally, a few elements of complexity will be chosen, and examples given of how they can be applied in evaluation.

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