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Structural Estimation of Dynamic Macroeconomic Models using Higher-Frequency Financial Data

Author

Listed:
  • Max Ole Liemen

    (Universität Hamburg)

  • Michel van der Wel

    (Erasmus University Rotterdam)

  • Olaf Posch

    (Universität Hamburg)

Abstract

In this paper we show how high-frequency financial data can be used in a combined macro-finance framework to estimate the underlying structural parameters. Our formulation of the model allows for substituting macro variables by asset prices in a way that enables casting the relevant estimation equations partly (or completely) in terms of financial data. We show that using only financial data allows for identification of the majority of the relevant parameters. Adding macro data allows for identification of all parameters. In our simulation study, we find that it also improves the accuracy of the parameter estimates. In the empirical application we use interest rate, macro, and S&P500 stock index data, and compare the results using different combinations of macro and financial variables.

Suggested Citation

  • 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.
  • Handle: RePEc:red:sed018:1049
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    File URL: https://economicdynamics.org/meetpapers/2018/paper_1049.pdf
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    References listed on IDEAS

    as
    1. Christensen, Bent Jesper & Posch, Olaf & van der Wel, Michel, 2016. "Estimating dynamic equilibrium models using mixed frequency macro and financial data," Journal of Econometrics, Elsevier, vol. 194(1), pages 116-137.
    2. Bent Jesper Christensen & Olaf Posch & Michel van der Wel, 2011. "Estimating Dynamic Equilibrium Models using Macro and Financial Data," CREATES Research Papers 2011-21, Department of Economics and Business Economics, Aarhus University.
    Full references (including those not matched with items on IDEAS)

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