600全讯白菜网系列讲座
2019年第20讲 总第583讲
题目：Probabilistic household and living arrangement forecasts
主讲人：Nico Keilman，挪威奥斯陆大学教授
主持人：Samir KC，全讯600cc大白菜官网亚洲人口研究中心人力资本方向负责人、教授
讲座时间：2019年5月20日，星期一，10:00-11:30am
讲座地点：东区2号楼600全讯白菜网516
主办单位：全讯600cc大白菜官网亚洲人口研究中心暨人口研究所
讲座简介：First, we discuss the shortcomings of deterministic forecasting models, and argue why probabilistic household and living arrangement forecasts are necessary for informed decision-making. Information from probabilistic forecasts allows policy makers, planners, and other forecast users in the fields of housing, energy, social security etc. to take appropriate decisions, because some household variables are more difficult to predict, and hence more uncertain, than others. It also guides them once actual developments start to deviate from the most likely path. New actions or updated plans are unnecessary as long as developments are likely to remain close to the expected future. Next, we review probabilistic household forecasts published since the turn of the century. An important issue is how to evaluate, ex-post facto, the accuracy of these probabilistic forecasts. We introduce the notion of a scoring function, the general idea of which is that a forecast that predicts the actual outcome with high probability should receive a better score than one that predicts the same outcome with lower probability. Scoring functions are useful for evaluating both interval forecasts (given in the form of prediction intervals with pre-specified coverage probability), and forecasts available in the form of a full probability distribution, either analytically or as a sample. Finally, we give empirical results for scoring functions applied to the first known probabilistic household forecasts.
（由于确定性预测模型有无法避免的缺点，概率性的家庭户和居住安排预测以及建构相应评估函数对于更好地决策有不可替代的作用。本此讲座首先讨论确定性预测模型的缺点以及概率性的家庭户和居住安排预测的必要性；然后回顾21世纪以来学者们提出的基于概率方法的家庭户模型，并引入评估函数；最后给出一个将评分函数应用于家庭户预测的经验结果。）
主讲人简介：
Nico Keilman, Department of Economics, University of Oslo.
MSc in applied Mathematics at Delft University of Technology, PhD in Demography at the University of Utrecht. Has worked for more than thirty years in the fields of mathematical demography, modelling of household dynamics, and forecasting methodology. His current interest is in the link between period and cohort mortality.
