What “being wrong” means in the world of macroeconomic forecasting

Economic forecasting aims at outlining possible futures and thus forming actors’ expectations. It describes an institutional environment actors conform to. Expectations look similar to what Keynes (1936) named “convention” and may give rise to speculative bubbles and self-fulfilling prophecies (Orléan, 2011). The latter provides paradoxical evidence of the institutional nature of foreseen environment: the common belief that behaviors shall take future states of the economy into consideration contributes to the actual coming of these states. To put it in the classical economic terms of F. H. Knight, (1921), economic forecasting is a way to shift from uncertain to risky futures by translating scenarios about the future into numbers, e.g. GDP growth forecasts. Forecasts may be regarded as “beliefs” which guide economic actions. They emerge and endure because the reasons for which they are endorsed make sense to actors located in a peculiar historic environment (Weber, 1905). A key issue is thus that of beliefs-standing in adverse situations and of the conditions under which rational actors interpret a sign as a “confirmation” or an “invalidation” of their beliefs. One of the key issues of the presentation is to understand how beliefs and expectations maintain when challenged, or proven “wrong” – and therefore to deal with the issue of “error” in the field of economic forecasting. The word “error” (as well as adjectives like “right” or “wrong”) is kept between quotes to underline it is not here considered from a positivist point of view which attempts to assess forecasts accuracies to a so-called “reality”, but regarded with respect to how actors react to what they regard as “erroneous” statements. In other words, the presentation studies the conditions under which beliefs are “suspended” in situations of fictional expectations (Beckert, 2013). It argues “error” can be defined in various ways, depending on the way forecasting is regarded: the technical limit of a practical activity, a drawback with the founding beliefs of a field, or a threat to forecasters’ trustworthiness and market positions. Firstly, “error” is to be understood with reference to the practical activity of macroeconomic forecasting. Economic future is not known and the coming economic situation is too singular and complex to be exhaustively described, hence forecasting involves conjectures and deliberation: it implies “prudential practices” (Champy, 2011). This process decisively relies on the gathering of information through different channels, including both fellow forecasters and economic actors (Evans, 1997; Reichman, 2013). The forecasting “work in progress” leads to continuous revision in order to reduce “residual errors”. In such perspective, “error” marks the ever-postponed limit to knowledge and highlights the discrepancies between what is known (of the relationship between variables in an econometric model and the values they are expected to take) and the actual economic situations. Secondly, ex post-assessed “errors” are not usually considered as “mistakes” (from a forecaster) but as results of events that could not have been anticipated: the more forecasters missed them, the more unexpectable they were. Drawing from the example of the Survey of Professional Forecasters conducted by the ECB, the presentation shed light on the ways “errors” are explained by forecasters, who emphasize unforeseen inflationist shocks or the similarities of information used by forecasters (Garcia, 2003; Bowles et al., 2007). This incapacitation of “errors” may be linked to the forecasting field, in the Bourdieusian sense (Bourdieu, 1992): in this perspective, reminding the difficulties and limits of forecasting is a way to preserve “illusio”, the necessary collective agreement between all field participants (despite their oppositions), which, in the case of forecasting, is an agreement upon the possibility and importance of the activity which founds the field. Thirdly, “errors” refer to forecasting as a market in which forecasters are not only in relation with each other in a structural perspective, but are also in relation with consumers or clients. They compete to address foresight users. Believing in the possibility of forecasting does not mean believing in all forecasters and all forecasts. When the foreseen environment does not match the fulfilled one, forecasters’ reputation are in jeopardy, for they might not be considered reliable and trustworthy anymore, and their former clients might turn to rival forecasters. That is the principle of a well-known saying, “an economist is an expert who knows tomorrow why the things he predicted yesterday didn’t happen today”, which regularly rejuvenates. Economic crises are moments which have to be paid special attention to, even though not the only ones. Notably, Friedman (2014) has shown that one of the aftermaths of the 1929 crisis has been to shift positions in the forecasting field