Description:
The literature shows that the nowcasting models generally use structured data such as real, financial and survey indicators. Recent research has focused on finding the way how to use the unstructured data in the nowcasting models. The search items such as sentiments or emotions were gathered from internet platforms and used as unstructured data. In this study, it is analysed how the ECB presidents' speeches are included in the nowcasting model and to what degree they affect the quarterly gross domestic product (GDP) of Germany. First, ECB presidents' speeches are analysed to obtain the emotion indicators with assistance of the newly harmonised complex dictionary. These emotion indicators are next added to the unbalanced and mixed frequency data and the nowcasting model estimation for GDP is performed with these data using the expectation-maximisation algorithm in the dynamic factor model representation. Moreover, the news analysis is performed to show how the revisions in the real-time data, including emotion indicators, affect the nowcasts for the current and next quarter GDPs. Finally, a forecast scenario is performed to demonstrate the effects of emotion indicators in the nowcasting model of GDP which shows a slowdown for the last two years. In conclusion, it is suggested that ECB presidents' speeches may increase the performance of nowcasting models for the German GDP.