Business Cycle Measurement With Semantic Filtering: A Micro Data Approach

In this paper the authors develop a business cycle measure that can be shown to have excellent ex-ante forecasting properties for GDP growth. For identifying business cycle movements, they use a semantic approach. They infer nine different states of the economy directly from firms' responses in business tendency surveys. Hence, they can identify the current state of the economy. They there with measure business cycle fluctuations. One of the main advantages of the methodology is that it is a structural concept based on shock identification and therefore does not need any - often rather arbitrary - statistical filtering.