This study provides an application of dynamic time warping algorithm with a new window constraint to assess consumer expectations’ information content regarding current and future inflation. Our study’s contribution is the novel application of DTW for testing expectations’ forward-lookingness. Additionally, we modify the algorithm to adjust it for a specific question on the information content of our data. The DTW overcomes constraints of the standard tool that examines forward-lookingness: DTW does not impose assumptions on time series properties. In empirical study we cover seven European counties and compare the DTW outcomes with the results of previous studies in these economies using a standard methodology. The research period covers 2001 to mid-2018. Application of DTW provides information on the degree of expectations’ forward-lookingness. The result, after standardization, are similar to the standard parameters of hybrid specification of expectations. Moreover, the rankings of most forward-looking consumers are replicated. Our results confirm the economic intuition, and they do not contradict previous studies.

这项研究提供了一种具有新窗口约束的动态时间规整算法的应用程序，用于评估有关当前和未来通货膨胀的消费者期望的信息内容。我们研究的贡献是DTW在测试期望的前瞻性方面的新颖应用。此外，我们修改了算法，以针对数据信息内容中的特定问题对算法进行调整。DTW克服了检查前瞻性的标准工具的限制：DTW不对时间序列属性进行假设。在实证研究中，我们涵盖了七个欧洲县，并使用标准方法将DTW结果与这些经济体中先前研究的结果进行了比较。研究期为2001年至2018年中。DTW的应用程序提供了有关期望的前瞻性程度的信息。标准化后的结果类似于期望的混合规范的标准参数。此外，大多数具有前瞻性的消费者的排名也被复制。我们的结果证实了经济直觉，并且与先前的研究没有矛盾。