On November 20, 2025, the Department of Economics at John Cabot University hosted a seminar with Dr. Fabio Scacciavillani, offering students a rare insider’s perspective on how economic forecasts are built, interpreted, and often misunderstood. The seminar, attended by students from courses taught by Prof. Sergio Scicchitano and Prof. Nicola Favia, explored the delicate boundary between economic science, judgment, and uncertainty.
Scacciavillani is an economist with a Ph.D. from the University of Chicago. From 2011 to 2019, he was Chief Strategist of the Oman Investment Fund, the Sultanate’s sovereign wealth fund, and previously held positions at the Dubai International Financial Centre, Goldman Sachs, the European Central Bank, the International Monetary Fund, and Confindustria.
Drawing on both theory and professional experience, Scacciavillani opened with a striking literary parallel. Much like the lawyer in Kafka’s The Trial, the economic forecaster operates in an environment filled with ambiguity, expectations, and partial truths. Forecasts, he argued, are often perceived as authoritative verdicts on the future, when in reality, they are closer to interpretative tools, necessary, but far from infallible.
Forecasts as scenarios, not prophecies
The central theme of the lecture was semantic confusion. The term “forecast,” Scacciavillani suggested, is misleading: “scenario” would be more accurate. Rather than predicting a single outcome, a forecast represents a distribution of probabilities generated by a model under a specific set of assumptions. These assumptions, about exchange rates, fiscal policy, wages, or energy prices, are the true starting point of any macroeconomic projection.
Using practical examples, Scacciavillani showed how treating certain variables as exogenous can profoundly shape results. An assumed appreciation of the euro, for instance, feeds through export and import equations, affecting the current account and ultimately GDP. Yet such assumptions are often subjective, reflecting the forecaster’s judgment rather than any immutable economic law.
Rational assumptions and rational expectations
Not all assumptions are arbitrary. Some are grounded in institutional reality: public deficits are set in budget laws well in advance, and wages in countries like Italy or Germany are determined by multi-year collective agreements. However, even well-founded assumptions must contend with the behavior of economic agents.
Here, Scacciavillani recalled the concept of rational expectations. When policies change, people adapt: they cannot be systematically “misled” by policy decisions based on models that reflect past behavior. The post-COVID surge in inflation and wages, he noted, is a clear reminder that estimated parameters may break down when the economic environment shifts.
Forecasts in policy and markets
The seminar also addressed how forecasts are actually used by institutions and investors. At central banks such as the European Central Bank, forecasts are deliberately constructed under restrictive assumptions, unchanged interest rates, stable exchange rates, constant oil prices, not because these outcomes are realistic, but because they provide a neutral benchmark. Policymakers then ask a crucial question: if we leave interest rates unchanged, where would the economy be heading?
If inflation appears persistently above target in this scenario, policy intervention becomes likely. In this sense, forecasts function less as predictions and more as maps: reference paths against which reality can be compared.
The same logic applies to financial markets. Traders and asset managers may react to discrepancies between actual data and forecasted values, or to unusually large deviations from confidence intervals. In fiscal policy, overly optimistic revenue assumptions can act as early warning signals, prompting corrective action.
A disciplined way to face uncertainty
Scacciavillani concluded with a cautionary, but humorous, anecdote about a team of economists whose model predicted interest rate decisions with uncanny accuracy, only to render its creators redundant. The lesson was clear: the value of forecasts lies not in being “right,” but in structuring disciplined thinking under uncertainty.
For students, the seminar offered a powerful takeaway. Economic forecasting is neither magic nor pure science. It is a pragmatic tool, imperfect, assumption-driven, and open to interpretation, that, when used critically, can support sound decision-making in policy and markets alike. Understanding its limits, Scacciavillani suggested, is the first step toward using it wisely.
