Maurizio Bovi summarizes a new published paper he wrote with Roy Cerqueti. The paper examines lay agents' forecasts amid great recessions (with a special focus on Greece). The paper is Bovi, M. and R. Cerqueti (2015) "Forecasting macroeconomic fundamentals in economic crises" Annals of Operations Research DOI 10.1007/s10479-015-1879-4:
Forecasting in Economic Crises: Expectations are a key factor in economics and heterogeneous forecasts are a fact of life. Just to mention, there are quite significant and well-known incentives to become a sport champion or to win a Nobel Prize, yet very few persons succeed in the endeavor. The brutal truth is that the majority lags behind or gives up - heterogeneity is the rule, not the exception. By the same token lay forecasters may learn, but it is unrealistic to think that all of them—even in the long run—will achieve Muth-optimal and, hence, homogeneous forecasts. The situation is made even more complex, and more interesting to study, when the fundamental to predict, the real GDP growth rate, is well below zero and highly volatile.
In recent work (Bovi and Cerqueti, 2015) we address the topic of heterogeneous forecasting performances amid deep recessions. Lay agents are assumed to have different predictive ability in that they have equal loss functions, but different asymmetry parameters that are used as control to minimize their forecasting errors. Simulating poor performing economies populated by three groups of forecasters, we have obtained the following results.
The less sophisticated forecasters in our setting – the “medians” (using passive rule-of-thumb) - never perform as the best predictors – the “muthians” – whereas “second best” (SB) agents (acting as attentive econometricians) do that only occasionally. This regardless the size of the crisis. Thus, as in the real world, in our artificial economy heterogeneity is a structural trait. More intriguingly, simulations also show that the medians’ behavior tend to be relatively smoother than that of SB agents, and that the difference between them widens in the case very serious crises. In particular, great recessions make SB agents’ predictions relatively more biased. An explanation is that dramatic crises extend the available information set (e.g., due to greater mass media coverage), and this leads SB agents, who are more prompt to revise their forecasts than medians.
Our results are somewhat in line with Simon’s famous statement about the fact that more information does not necessarily mean better forecasting performances. Furthermore, our outcomes shed some light on what has been happening in the freak macroeconomic expectations in Greece these years. The current crisis, in fact, may be thought of as a sort of natural experiment to understand how lay decision makers react to very dramatic years. In particular, due to its terrible recent downturn, Greece is one of the most suitable cases, raising the following question: How do Greeks perceive their own personal financial situation with respect to that of their country? Clearly, the representative citizen cannot by definition systematically drift apart from that of the country where she lives, given that the nation-wide economic situation is the (weighted) sum of the individual ones in the country. Yet, it may be hard to remain objective in the course of very deep and prolonged economic crises. The evidence depicted in the following graph looks rather suggestive of the effects of deep recessions on the rationality of people’s expectations, something that conform with our findings.