Remarks

I try to make my work publicly available and reproducible. As publishing an open-access paper in a journal can be prohibitively expensive, please feel free to contact me for a personal copy of my papers. Please avoid paying any unfair fees to scientific publishers, see e.g. Projekt DEAL for more details.

You can find replication and work-in-progress codes on my GitHub Page: https://github.com/wmutschl

Books

  1. Local identification of nonlinear and non-Gaussian DSGE models

    Wissenschaftliche Schriften der WWU Münster, Reihe IV, Band 10, 2016, Paperback, ISBN: 978-3-8405-0135.
    This thesis adds to the literature on the local identification of nonlinear and non-Gaussian DSGE models. It gives applied researchers a strategy to detect identification problems and means to avoid them in practice. A comprehensive review of existing methods for linearized DSGE models is provided and extended to include restrictions from higher-order moments, cumulants and polyspectra. Another approach, established in this thesis, is to consider higher-order approximations. Formal rank criteria for a local identification of the deep parameters of nonlinear or non-Gaussian DSGE models, using the pruned state-space system are derived. The procedures can be implemented prior to estimating the nonlinear model. In this way, the identifiability of the Kim (2003) and the An and Schorfheide (2007) model are demonstrated, when solved by a second-order approximation.
    Online Access, Buy From Publisher

Refereed Publications

  1. Higher-order statistics for DSGE models

    Econometrics and Statistics, Volume 6, April 2018, Pages 44-56.
    Closed-form expressions for unconditional moments, cumulants and polyspectra of order higher than two are derived for non-Gaussian or nonlinear (pruned) solutions to DSGE models. Apart from the existence of moments and white noise property no distributional assumptions are needed. The accuracy and utility of the formulas for computing skewness and kurtosis are demonstrated by three prominent models: the baseline medium-sized New Keynesian model used for empirical analysis (first-order approximation), a small-scale monetary business cycle model (second-order approximation) and the neoclassical growth model (third-order approximation). Both the Gaussian as well as Student's t-distribution are considered as the underlying stochastic processes. Lastly, the efficiency gain of including higher-order statistics is demonstrated by the estimation of a RBC model within a Generalized Method of Moments framework.
    Online Access (DOI)Online AppendixReplication Code on Github, SFB823 DP4816, CQE WP43
  2. Identification of DSGE models - The effect of higher-order approximation and pruning

    Journal of Economic Dynamics and Control, Volume 56, July 2015, Pages 34-54.
    This paper shows how to check rank criteria for a local identification of nonlinear DSGE models, given higher-order approximations and pruning. This approach imposes additional restrictions on (higher-order) moments and polyspectra, which can be used to identify parameters that are unidentified in a first-order approximation. The identification procedures are demonstrated by means of the Kim (2003) and the An and Schorfheide (2007) models. Both models are identifiable with a second-order approximation. Furthermore, analytical derivatives of unconditional moments, cumulants and corresponding polyspectra up to fourth order are derived for the pruned state-space.
    Online Access (DOI)Replication Code and Additional Material on Github, CQE WP33

Working Papers

  1. A note on solving the functional equivalence between intertemporal and multisectoral investment adjustment costs (with Sergey Ivashchenko)

    Kim (2003, JEDC 27, pp. 533-549) shows functional equivalence between intertemporal and multisectoral investment adjustments costs in a log-linearized RBC model. We provide two strategies to solve this equivalence. First, the equivalence does not hold when intertemporal adjustment costs are specified in growth rates rather than in levels. Second, the level specification can be identified with a second-order approximation of the model solution. We estimate the quadratic approximation using two extended Kalman filters within a Bayesian framework. Our estimation results confirm that both parameters are estimable in finite samples. Moreover, we provide further evidence on the stabilizing effect of pruning on the estimation algorithm.
    Paper, Estimation Results, SFB823 DP7216
  2. Identification of DSGE models: a review

    Abstract coming soon
    Paper (coming soon), Code (coming soon)
  3. Fiscal and monetary policy in an estimated DSGE model with rare disaster (with Ludger Linnemann)

    Abstract coming soon
    Paper (coming soon), Code (coming soon)
  4. The effect of nonnormality on fiscal foresight (with Ludger Linnemann and Martin Wagner)

    Abstract coming soon
    Paper (coming soon), Code (coming soon)
  5. Fiscal shocks in an identified SVAR using cointegration and sign restrictions (with Ludger Linnemann and Martin Wagner)

    Abstract coming soon
    Paper (coming soon), Code (coming soon)

Other Publications

  1. Analyse und Lösung von DSGE Modellen - Ein Vergleich der Methoden

    Master thesis (in German), University of Münster.
    DSGE models offer a rigorous microeconomic foundation of the economy. Many different methods for the solution and the estimation of DSGE models have been developed and used in order to get a detailed description and thorough estimation of dynamic macroeconomic relationships. The goal of this thesis, therefore, aims at comparing both different solution techniques (first and second order) and a variety of estimation approaches (calibration, General-Method-of-Moments, Impulse-Response-Matching, Maximum-Likelihood and Bayesian estimation). All methods are derived theoretically and applied to a stylized model in the fashion of An and Schorfheide (2007).
    Master-Thesis
  2. Finanzökonomische Aspekte des Wirtschaftswachstums

    Bachelor thesis (in German), University of Bonn.
    Diese Arbeit verfolgt das Ziel, den Zusammenhang zwischen der Entwicklung des Finanzwesens und dem realen Wirtschaftswachstum theoretisch aufzuzeigen und empirisch zu überprüfen. Die Zielsetzung der Arbeit kann anhand folgender Erkenntis leitender Fragen konkretisiert werden: Durch welche Mechanismen kann das Finanzwesen Einfluss auf das langfristige Wachstum ausüben? Welchen Einfluss besitzt die Struktur des Finanzwesens auf das langfristige Wachstum? Kann mithilfe der Entwicklung des Finanzwesens das langfristige Wachstum vorhergesagt, also eine Granger-Kausalität unterstellt werden? Was sind mögliche Modellannahmen, die einen Einfluss der Geld- und Kreditschöpfung auf das Wirtschaftswachstum implizieren? Es wird theoretisch gezeigt, dass durch einen quantitativen Kapitalakkumulationskanal und einen qualitativen TFP-Kanal das Finanzsystem das langfristige Wirtschaftswachstum beeinflusst. Der Wachstumsprozess wird durch die Geld- und Kreditschöpfung mitfinanziert. In der empirische Analyse wird für Deutschland bestätigt, dass eine Granger-kausale Beziehung zwischen der Kreditvergabe der Banken und dem BIP vorherrscht. Darüber hinaus gibt auch die Entwicklung der Geldmenge Hinweise auf die Interdependenz zwischen der monetären und realen Volkswirtschaft.
    Bachelor-Thesis