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Soft Landing or Stagnation? A Framework for Estimating the Probabilities of Macro Scenarios
Amid ongoing trade policy shifts and geopolitical uncertainty, concerns about stagflation have reemerged as a key macroeconomic risk. This paper develops a probabilistic framework to estimate the likelihood of stagflation versus soft landing scenarios over a four-quarter horizon. Building on Bekaert, Engstrom, and Ermolov (2025), the model integrates survey forecasts, structural shock decomposition, and a non-Gaussian BEGE-GARCH approach to capture time-varying volatility and skewness. Results suggest that the probability of stagflation was elevated at around 30 percent in late 2022, while the chance of a soft landing was below 5 percent. As inflation moderated and growth remained strong through 2024, these probabilities reversed. However, by mid-2025, renewed tariff concerns drove stagflation risk back up and the probability of a soft landing lower. These shifts highlight the potential value of distributional forecasting for policymakers and market participants navigating uncertain macroeconomic conditions.
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