Estimating Dynamic Equilibrium Models Using Mixed Frequency Macro and Financial Data
Bent Jesper Christensen (),
Olaf Posch () and
Michel van der Wel ()
No 5030, CESifo Working Paper Series from CESifo
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.
Keywords: structural estimation; AK-Vasicek model; Martingale estimating function (search for similar items in EconPapers)
JEL-codes: C13 E32 O40 (search for similar items in EconPapers)
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Journal Article: Estimating dynamic equilibrium models using mixed frequency macro and financial data (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_5030
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