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Hodges–Lehmann Detection of Structural Shocks – An Analysis of Macroeconomic Dynamics in the Euro Area

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  • Helmut Herwartz

Abstract

Structural shocks in multivariate dynamic systems are hidden and often identified with reference to a priori economic reasoning. Based on a non‐Gaussian framework of independent shocks, this work provides an approach to discriminate between alternative identifying assumptions on the basis of dependence diagnostics. Relying on principles of Hodges–Lehmann estimation, we suggest a decomposition of reduced form covariance matrices that yields implied least dependent (structural) shocks. A Monte Carlo study underlines the discriminatory strength of the proposed identification strategy. Applying the approach to a stylized model of the Euro Area economy, independent shocks conform with features of demand, supply and monetary policy shocks.

Suggested Citation

  • Helmut Herwartz, 2018. "Hodges–Lehmann Detection of Structural Shocks – An Analysis of Macroeconomic Dynamics in the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(4), pages 736-754, August.
    • Handle: RePEc:bla:obuest:v:80:y:2018:i:4:p:736-754
    DOI: 10.1111/obes.12234
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    Cited by:

    1. Berner, Anne & Bruns, Stephan & Moneta, Alessio & Stern, David I., 2022. "Do energy efficiency improvements reduce energy use? Empirical evidence on the economy-wide rebound effect in Europe and the United States," Energy Economics, Elsevier, vol. 110(C).
    2. Bruns, Stephan B. & Moneta, Alessio & Stern, David I., 2021. "Estimating the economy-wide rebound effect using empirically identified structural vector autoregressions," Energy Economics, Elsevier, vol. 97(C).
    3. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "Moment tests of independent components," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 429-474, May.
    4. Reinhold Heinlein & Scott M. R. Mahadeo, 2023. "Oil and US stock market shocks: Implications for Canadian equities," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(1), pages 247-287, February.
    5. Marques, André M. & Lima, Gilberto Tadeu, 2022. "Testing for Granger causality in quantiles between the wage share in income and productive capacity utilization," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 290-312.
    6. Fiorentini, Gabriele & Sentana, Enrique, 2023. "Discrete mixtures of normals pseudo maximum likelihood estimators of structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 235(2), pages 643-665.
    7. Mario Martinoli & Alessio Moneta & Gianluca Pallante, 2022. "Calibration and Validation of Macroeconomic Simulation Models by Statistical Causal Search," LEM Papers Series 2022/33, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    8. Giacomo Bormetti & Fulvio Corsi, 2021. "A Lucas Critique Compliant SVAR model with Observation-driven Time-varying Parameters," Papers 2107.05263, arXiv.org, revised Feb 2022.
    9. Moneta, Alessio & Pallante, Gianluca, 2022. "Identification of Structural VAR Models via Independent Component Analysis: A Performance Evaluation Study," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    10. Bernoth, Kerstin & Herwartz, Helmut, 2021. "Exchange rates, foreign currency exposure and sovereign risk," Journal of International Money and Finance, Elsevier, vol. 117(C).
    11. Herwartz, Helmut & Lange, Alexander & Maxand, Simone, 2019. "Statistical identification in SVARs - Monte Carlo experiments and a comparative assessment of the role of economic uncertainties for the US business cycle," University of Göttingen Working Papers in Economics 375, University of Goettingen, Department of Economics.
    12. Herwartz, Helmut & Rohloff, Hannes & Wang, Shu, 2022. "Proxy SVAR identification of monetary policy shocks - Monte Carlo evidence and insights for the US," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    13. Maxand, Simone, 2020. "Identification of independent structural shocks in the presence of multiple Gaussian components," Econometrics and Statistics, Elsevier, vol. 16(C), pages 55-68.
    14. Braun, Robin, 2021. "The importance of supply and demand for oil prices: evidence from non-Gaussianity," Bank of England working papers 957, Bank of England.
    15. Helmut Herwartz & Alexander Lange & Simone Maxand, 2022. "Data‐driven identification in SVARs—When and how can statistical characteristics be used to unravel causal relationships?," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 668-693, April.
    16. Francesco Cordoni & Nicolas Doremus & Alessio Moneta, 2023. "Identification of Vector Autoregressive Models with Nonlinear Contemporaneous Structure," LEM Papers Series 2023/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

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