Methods for forecasting in the Danish National Transport model

The present paper is concerned with the forecasting methodology applied in the new Danish national model. The new national model will apply two forecast methods depending on the type of demand model considered. For models which can be estimated on the basis of TU data and is further covered by register data from Statistic Denmark, a prototypical sample enumeration approach will be used. For models, where this is not the case, a matrix model approach will be used. Typically, this will be the case for models where respondents include foreigners. In this case we do not have register data for the respondents and the TU data will only cover the Danish segment. The key to do forecasting based on a prototypical sample enumeration methodology is to apply a population synthesiser, which can forecast the population profile. By combining the population forecast with the micro- survey, it is possible to derive expansion factors which can be used to up-scale the demand model. The “expansion” is used to lifts the TU data base to a representative population level. The paper will first in brief terms discuss the choice of forecast methodology. Hereafter, we will consider the design of the population synthesiser in some details. Finally, we will test the proposed population synthesiser by back-casting.

本研究聚焦丹麦全新国家级模型所采用的预测方法论。该模型将依据所适配的需求模型类型，选用两种预测方案：针对可基于时间使用数据（TU data）开展估算，且可进一步获得丹麦统计局（Statistic Denmark）登记数据支撑的模型，将采用典型样本枚举法；对于不满足上述条件的模型，则采用矩阵模型法。当模型的调研对象包含外籍人士时，通常即属于后一类情形：此时我们无法获取对应调研对象的登记数据，且时间使用数据（TU data）仅能覆盖丹麦本土群体。基于典型样本枚举法开展预测的核心，在于引入可刻画人口结构特征的人口合成器（population synthesiser）。通过将人口预测结果与微观调研数据相结合，可推导得到用于扩增需求模型规模的扩展因子。该“扩展”环节用于将时间使用数据库提升至具有代表性的总体人口层级。本文将首先简要探讨预测方法论的选型逻辑，随后详细剖析人口合成器的设计细节，最后将通过回溯预测（back-casting）对所提出的人口合成器进行有效性检验。