Constructing a new leading indicator for unemployment from a survey among German employment agencies

Artikel

The paper investigates the predictive power of a new survey implemented by the Federal Employment Agency (FEA) for forecasting German unemployment in the short run. Every month, the CEOs of the FEA's regional agencies are asked about their expectations of future labor market developments. We generate an aggregate unemployment leading indicator that exploits serial correlation in response behavior through identifying and adjusting temporarily unreliable predictions. We use out-of-sample tests suitable in nested model environments to compare forecasting performance of models including the new indicator to that of purely autoregressive benchmarks. For all investigated forecast horizons (1, 2, 3 and 6 months), test results show that models enhanced by the new leading indicator significantly outperform their benchmark counterparts. To compare our indicator to potential competitors we employ the model confidence set. Results reveal that models including the new indicator perform very well at the 10 percent level.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Applied Economics ; ISSN: 1466-4283 ; Volume: 47 ; Year: 2015 ; Issue: 33 ; Pages: 3540-3558 ; London: Taylor & Francis

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Model Evaluation, Validation, and Selection ; Forecasting Models; Simulation Methods ; Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
• Subject: Survey Data ; Forecast Evaluation ; Nested Models ; Model Confidence Set ; Unemployment

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Hutter, Christian ; Weber, Enzo
• Event: Veröffentlichung
• (who): Taylor & Francis ; ZBW - Leibniz Information Centre for Economics
• (where): London
• (when): 2015

Further information

• DOI: https://www.tandfonline.com/doi/full/10.1080/00036846.2015.1018672
• Handle: http://hdl.handle.net/10419/263252
• Last update: 10.03.2025, 11:43 AM CET