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Un futur antérieur. Le rapport aux données dans le travail de prévision macroéconomique

Author

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  • Olivier Pilmis

Abstract

Macroeconomic forecasting decisively relies on the assessment of economies? current situations. Forecasters? work therefore shares common features with statistical work. This paper draws upon A. Desrosières?s typology to emphasize how forecasting combines various ways of tackling ?data? and assessing their ?realism.? It also sheds light on some principles according to which such combinations may be understood, such as the division of labor in the world of forecasting, forecasters? categories of classification, instruments that are used for the purpose of forecasting, and the temporalities of forecasting exercises.

Suggested Citation

  • Olivier Pilmis, 2018. "Un futur antérieur. Le rapport aux données dans le travail de prévision macroéconomique," Revue française de socio-Economie, La découverte, vol. 0(2), pages 59-76.
    • Handle: RePEc:cai:rfsdec:rfse_021_0059
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    Cited by:

    1. Olivier Pilmis, 2022. "Is economic forecasting a science? [Une science de la prévision économique ?]," Post-Print hal-03894747, HAL.
    2. Olivier Pilmis, 2022. "Is economic forecasting a science? [Une science de la prévision économique ?]," SciencePo Working papers Main hal-03894747, HAL.

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