The literature on the role of institutions in economic growth and development is well-established. In contrast, the relationship between institutional quality and competitiveness, while important, received much less attention until recently, when there has been a growing interest in incorporating variables representing institutional quality into country competitiveness indices. Such attempts take cognizance of the results from cross-country empirical findings. However, any attempt to construct a satisfactory mapping of institutions to competitiveness is fraught with difficulties, including data consistencies, omission of causal factors and the lack of theoretical foundations. Some of these difficulties stem from differences in the overall objectives of the research literature and the development of competitiveness indices. The research literature can explain why, whether and what type of institutions are important, but such findings do not lend themselves to the construction of appropriate policy variables.
Emergence refers to the spontaneous formation of higher level (macro) structures or patterns in complex systems. Attempts to formalize the notion of emergence via algorithmic complexity theory runs into the problem that the Kolmogorov complexity function is not computable. The reason for this motivates a closer examination of the link between emergence and universal computation. Following Wolfram's pioneering work in the classification of cellular automata behavior, the research programs of Langton and Crutchfield, while incomplete, provide important insights to economists seeking to understand the relevance of emergence and universal computation to their discipline. They lead to questions on the emergence of institutions and the concomitant changes in rule-based behavior on the part of economic agents.
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