Estimating Dynamic Equilibrium Models Using Mixed Frequency Macro and Financial Data

Arbeitspapier

We provide a framework for inference in dynamic equilibrium models including financial market data at daily frequency, along with macro series at standard lower frequency. Our formulation of the macro-finance model in continuous-time conveniently accounts for the difference in observation frequency. We suggest the use of martingale estimating functions (MEF) to infer the structural parameters of the model directly through a nonlinear optimization scheme. This method is compared to regression-based methods and the general method of moments (GMM). We illustrate our approaches by estimating the AK-Vasicek model with mean-reverting interest rates. We provide Monte Carlo evidence on the small sample behavior of the estimators and report empirical estimates using 30 years of U.S. macro and financial data.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CESifo Working Paper ; No. 5030

Classification and Topics

• Classification: Wirtschaft ; Estimation: General ; Business Fluctuations; Cycles ; Economic Growth and Aggregate Productivity: General
• Subject: structural estimation ; AK-Vasicek model ; Martingale estimating function

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Christensen, Bent Jesper ; Posch, Olaf ; van der Wel, Michel
• Event: Veröffentlichung
• (who): Center for Economic Studies and ifo Institute (CESifo)
• (where): Munich
• (when): 2014

Further information

• Handle: http://hdl.handle.net/10419/103139
• Last update: 10.03.2025, 11:42 AM CET