The Rise of Zero-Shot Modeling Artificial intelligence is reshaping economics. A key innovation is the zero-shot model, AI, thatcan solve tasks it was never trained on. For economists, this means faster forecasts, new waysto use data, and insights without custom-built models Why Zero-Shot Matters Speed and Scale: Economists usually build new models for each case. Zero-shot systemsadapt instantly, saving time and effort.Bridging Data Gaps: In regions with scarce data, zero-shot approaches provide useful insights.Merging Text

The Shift from Globalisation to Fragmentation Globalisation once promised seamless integration of markets. However, in 2025, businessesface a different reality: trade fragmentation. Rising tariffs, geopolitical rivalries, and shiftingregulations are reshaping the global economy. The European Commission (2023) warns that growing trade fragmentation and higher policyuncertainty could result in long-term output losses. Global Trade at a Turning Point For decades, globalisation has fueled unprecedented growth. Trade as a share of global GDPexpanded rapidly between 1990 and

Introduction: Analysing the Current Situation In recent years, trade wars have re-emerged as a defining factor in global economic developments. The term describes situations in which countries impose tariffs, quotas, or other restrictions. Often, these actions come as retaliation for similar measures by other states. Such conflicts are most visible between the United States and China. They also appear in tensions between the United States and the European Union. Additionally, protectionist policies are gaining traction

Introduction When Your Map Becomes Outdated Faster Than You Use It In today’s volatile world, a rolling forecast is becoming an essential business tool. Traditional annual forecasts, once seen as reliable compasses, now resemble outdated maps. They look neat, but they can lead companies in the wrong direction. Unexpected events, such as pandemics, energy crises, inflation spikes, and rapid technological changes, have made fixed forecasts increasingly risky. As a result, organisations are searching for new

Introduction In today’s business world, forecasting models play a central role in decision-making. Companies use them to predict demand, optimise supply chains, and manage finances. However, despite their importance, even advanced algorithms often fail. This article explains why. We explore four common issues that undermine forecast accuracy: poor data quality, unpredictable “black swan” events, overfitting, and the human factor. Each section highlights examples and offers advice for businesses. By the end, it becomes clear that

Introduction: Why Crisis Economic Forecasts Are Both Valuable and Risky During an economic downturn, uncertainty rises sharply. This may happen in a recession, during geopolitical turbulence, or in an industry-specific slowdown. People, companies, and governments often look for clear guidance. In such times, crisis economic forecasts can seem like a roadmap for strategy and resource allocation. However, not all forecasts are equally reliable. Some rely on outdated data or flawed assumptions. Emotional reactions rather than