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Claudio Lissona

5 August 2026
WORKING PAPER SERIES - No. 3269
Details
Abstract
We analyse whether textual information extracted from firms’ earnings calls can improve forecasts of the euro area job vacancy rate. Using transcripts from euro area headquartered firms, we construct a monthly indicator of labour demand based on keywords related to labour market pressures and include it into a mixed frequency Bayesian VAR alongside standard hard and soft indicators. A pseudo–real-time evaluation shows that earnings calls provide timely and valuable signals for tracking vacancy dynamics. Among soft indicators, factors limiting production deliver the largest forecasting gains, while real labour-market indicators such as unemployment add little once qualitative signals are included. Forecast improvements are largely driven by information from the manufacturing sector, whose signals prove substantially more informative than those from services, especially when paired with earnings calls. Taken together, our results highlight the usefulness of high-frequency text-based information for improving short-term labour-demand forecasts in the euro area.
JEL Code
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E24 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Employment, Unemployment, Wages, Intergenerational Income Distribution, Aggregate Human Capital
E27 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Forecasting and Simulation: Models and Applications