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Estimating Dynamic Equilibrium Models Using Mixed Frequency Macro and Financial Data

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  • Bent Jesper Christensen
  • Olaf Posch
  • Michel van der Wel
Abstract
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.

Suggested Citation

  • Bent Jesper Christensen & Olaf Posch & Michel van der Wel, 2014. "Estimating Dynamic Equilibrium Models Using Mixed Frequency Macro and Financial Data," CESifo Working Paper Series 5030, CESifo.
    • Handle: RePEc:ces:ceswps:_5030
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    Cited by:

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    2. Parra-Alvarez, Juan Carlos & Polattimur, Hamza & Posch, Olaf, 2021. "Risk matters: Breaking certainty equivalence in linear approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    3. Foroni, Claudia & Gelain, Paolo & Marcellino, Massimiliano, 2022. "The financial accelerator mechanism: does frequency matter?," Working Paper Series 2637, European Central Bank.
    4. Posch, Olaf, 2018. "Resurrecting the New-Keynesian Model: (Un)conventional Policy and the Taylor rule," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181616, Verein für Socialpolitik / German Economic Association.
    5. van der Wel, M., 2020. "Connecting Silos : On linking macroeconomics and finance, and the role of econometrics therein," ERIM Inaugural Address Series Research in Management 124748, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam..
    6. Emanuele BACCHIOCCHI & Andrea BASTIANIN & Alessandro MISSALE & Eduardo ROSSI, 2016. "Structural Analysis With Mixed Frequency: Monetary Policy, Uncertainty And Gross Capital Flows," Departmental Working Papers 2016-11, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    7. Meyer-Gohde, Alexander & Shabalina, Ekaterina, 2022. "Estimation and forecasting using mixed-frequency DSGE models," IMFS Working Paper Series 175, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    8. Max Ole Liemen & Michel van der Wel & Olaf Posch, 2018. "Structural Estimation of Dynamic Macroeconomic Models using Higher-Frequency Financial Data," 2018 Meeting Papers 1049, Society for Economic Dynamics.
    9. Bacchiocchi, Emanuele & Bastianin, Andrea & Missale, Alessandro & Rossi, Eduardo, 2020. "Structural analysis with mixed-frequency data: A model of US capital flows," Economic Modelling, Elsevier, vol. 89(C), pages 427-443.

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    More about this item

    Keywords

    structural estimation; AK-Vasicek model; Martingale estimating function;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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