Sovereign Risk Indices and Bayesian Theory Averaging
Alex Lenkoski, Fredrik Lohne Aanes

TL;DR
This paper introduces a Bayesian model averaging approach to create latent theory indices for sovereign risk, accommodating multiple proxies and outcome types to improve macroeconomic risk assessment.
Contribution
It develops a novel methodology for constructing generalizable, theory-based risk indices using Bayesian model averaging and flexible models across multiple outcome equations.
Findings
Successful calibration of sovereign risk indices across various collapse criteria
Indices effectively differentiate countries based on macroeconomic risk
Framework accommodates non-Gaussian outcomes and differential theory relevance
Abstract
In economic applications, model averaging has found principal use examining the validity of various theories related to observed heterogeneity in outcomes such as growth, development, and trade.Though often easy to articulate, these theories are imperfectly captured quantitatively. A number of different proxies are often collected for a given theory and the uneven nature of this collection requires care when employing model averaging. Furthermore, if valid, these theories ought to be relevant outside of any single narrowly focused outcome equation. We propose a methodology which treats theories as represented by latent indices, these latent processes controlled by model averaging on the proxy level. To achieve generalizability of the theory index our framework assumes a collection of outcome equations. We accommodate a flexible set of generalized additive models, enabling non-Gaussian…
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