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In economic applications, model averaging has found principal use examiningthe validity of various theories related to observed heterogeneity in outcomessuch as growth, development, and trade.Though often easy to articulate, thesetheories are imperfectly captured quantitatively. A number of different proxiesare often collected for a given theory and the uneven nature of this collectionrequires care when employing model averaging. Furthermore, if valid, thesetheories ought to be relevant outside of any single narrowly focused outcomeequation. We propose a methodology which treats theories as represented bylatent indices, these latent processes controlled by model averaging on theproxy level. To achieve generalizability of the theory index our frameworkassumes a collection of outcome equations. We accommodate a flexible set ofgeneralized additive models, enabling non-Gaussian outcomes to be included.Furthermore, selection of relevant theories also occurs on the outcome level,allowing for theories to be differentially valid. Our focus is on creating aset of theory-based indices directed at understanding a country's potentialrisk of macroeconomic collapse. These Sovereign Risk Indices are calibratedacross a set of different "collapse" criteria, including default on sovereigndebt, heightened potential for high unemployment or inflation and dramaticswings in foreign exchange values. The goal of this exercise is to render aportable set of country/year theory indices which can find more general use inthe research community.

Sovereign Risk Indices and Bayesian Theory Averaging