Bijak Jakub, Alberts Isabel, Alho Juha, Bryant John, Buettner Thomas, Falkingham Jane, Forster Jonathan J, Gerland Patrick, King Thomas, Onorante Luca, Keilman Nico, O'Hagan Anthony, Owens Darragh, Raftery Adrian, Ševčíková Hana, Smith Peter W F
University of Southampton.
German Weather Service.
J Off Stat. 2015 Dec;31(4):537-544. doi: 10.1515/jos-2015-0033.
Demographic forecasts are inherently uncertain. Nevertheless, an appropriate description of this uncertainty is a key underpinning of informed decision making. In recent decades various methods have been developed to describe the uncertainty of future populations and their structures, but the uptake of such tools amongst the practitioners of official population statistics has been lagging behind. In this letter we revisit the arguments for the practical uses of uncertainty assessments in official population forecasts, and address their implications for decision making. We discuss essential challenges, both for the forecasters and forecast users, and make recommendations for the official statistics community.
人口预测本质上具有不确定性。然而，对这种不确定性进行恰当描述是明智决策的关键支撑。近几十年来，已经开发出各种方法来描述未来人口及其结构的不确定性，但官方人口统计从业者对这些工具的采用一直滞后。在这封信中，我们重新审视在官方人口预测中进行不确定性评估的实际用途的相关论据，并探讨其对决策的影响。我们讨论了预测者和预测使用者面临的基本挑战，并为官方统计界提出建议。
