Summary
Focus
We examine how tail risk in a country’s production affects the benefits of international consumption risk-sharing. Our analysis unfolds in three steps. First, we develop (approximate) analytical results linking welfare gains from risk-sharing to key economic factors like country size, trade elasticity and trade openness. We also take into account more detailed statistical aspects – like variability, imbalance and the shape – of production patterns that do not follow a normal distribution. This extends beyond the traditional mean-variance framework to study how these factors influence welfare distribution across countries. Second, we validate these findings using precise calculations based on broader assumptions. Finally, we apply the framework to 55 groups of three countries, using real-world data to estimate how welfare gains are distributed. To make sense of the results, we group countries with similar traits using statistical techniques, helping us to better understand the patterns.
Contribution
Our study makes several contributions to the literature. It provides the first analytical decomposition of international risk-sharing gains in a real business cycle model, linking higher-order cumulants (advanced statistical measures) to economic indicators like trade openness, trade elasticity and country size. By bridging asset pricing literature and international macroeconomics, our paper offers an analytical solution to better understand welfare gains. Furthermore, it distinguishes between the “level effect”, which reflects the implicit insurance premium paid by riskier countries, and the “smoothing effect”, which improves the statistical distribution of consumption and leisure. Departing from the traditional assumption of Gaussian shocks (ie those fully described by mean and variance), the model incorporates non-Gaussian distributions using precise numerical techniques. Calibration to real data from 55 economies and the application of statistical clustering provide insights into how economic features shape welfare outcomes.
Findings
Our analysis underscores the importance of accounting for “fat tails” (rare but extreme outcomes) in production distributions, which significantly improve the accuracy of welfare gain estimates. Without real-world differences in size and trade openness, gains from risk-sharing would be negligible – less than 1% of annual consumption. However, calibrating the model to observed data increases the median gain to 6%. Fat tails alone account for at least one third of these gains, emphasising their critical role. Safer countries benefit from asset appreciation (level effect), while riskier ones pay an implicit premium to reduce consumption risk (smoothing effect). Finally, the statistical clustering of countries aligns closely with model-derived welfare gains, validating the robustness of the approach.
Abstract
We study international risk sharing across countries differing in size, openness, and productivity distributions, emphasizing fat tails. In a canonical IRBC model, safer economies benefit through asset and terms-of-trade revaluations, while riskier ones smooth consumption at the cost of lower wealth. Calibrated to non-Gaussian shocks, country size and openness, the model predicts welfare gains between 0.03% and 6.9% of permanent consumption (median 6%). Assuming Gaussian shocks reduces gains by about 2 percentage points, while assuming equal country size and no home bias renders them negligible. Clustering economies by openness, size, and higher moments accounts for the cross-country distribution of gains.
JEL classification: F15, F41, G15
Keywords: asymmetries in risk, openness, country size, tail risk, gains from risk sharing, consumption smoothing, terms of trade, wealth transfers
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