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GMM Estimation of Non-Gaussian Structural Vector Autoregression

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  • Markku Lanne
  • Jani Luoto

Abstract

We consider estimation of the structural vector autoregression (SVAR) by the generalized method of moments (GMM). Given non-Gaussian errors and a suitable set of moment conditions, the GMM estimator is shown to achieve local identification of the structural shocks. The optimal set of moment conditions can be found by well-known moment selection criteria. Compared to recent alternatives, our approach has the advantage that the structural shocks need not be mutually independent, but only orthogonal, provided they satisfy a number of co-kurtosis conditions that prevail under independence. According to simulation results, the finite-sample performance of our estimation method is comparable, or even superior to that of the recently proposed pseudo maximum likelihood estimators. The two-step estimator is found to outperform the alternative GMM estimators. An empirical application to a small macroeconomic model estimated on postwar United States data illustrates the use of the methods.

Suggested Citation

  • Markku Lanne & Jani Luoto, 2021. "GMM Estimation of Non-Gaussian Structural Vector Autoregression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 69-81, January.
    • Handle: RePEc:taf:jnlbes:v:39:y:2021:i:1:p:69-81
    DOI: 10.1080/07350015.2019.1629940
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    Citations

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    Cited by:

    1. Sascha A. Keweloh, 2023. "Uncertain Short-Run Restrictions and Statistically Identified Structural Vector Autoregressions," Papers 2303.13281, arXiv.org, revised Apr 2024.
    2. Keweloh, Sascha A. & Hetzenecker, Stephan & Seepe, Andre, 2023. "Monetary policy and information shocks in a block-recursive SVAR," Journal of International Money and Finance, Elsevier, vol. 137(C).
    3. 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.
    4. 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).
    5. Brandts, Jordi & El Baroudi, Sabrine & Huber, Stefanie J. & Rott, Christina, 2021. "Gender differences in private and public goal setting," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 222-247.
    6. Zhang, Shuzhi & Xie, Guangxiong, 2023. "Promoting green investment for renewable energy sources in China: Case study from autoregressive distributed Lagged in error correction approach," Renewable Energy, Elsevier, vol. 214(C), pages 359-368.
    7. Ma, Cong & Cheok, Mui Yee & Chok, Nyen Vui, 2023. "Economic recovery through multisector management resources in small and medium businesses in China," Resources Policy, Elsevier, vol. 80(C).
    8. Allan W. Gregory & James McNeil & Gregor W. Smith, 2022. "US Fiscal Policy Shocks: Proxy-SVAR Overidentification via GMM," Working Paper 1461, Economics Department, Queen's University.
    9. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    10. Geert Mesters & Piotr Zwiernik, 2022. "Non-independent components analysis," Economics Working Papers 1845, Department of Economics and Business, Universitat Pompeu Fabra.
    11. Alfan Mansur, 2023. "Simultaneous identification of fiscal and monetary policy shocks," Empirical Economics, Springer, vol. 65(2), pages 697-728, August.
    12. Sascha A. Keweloh, 2023. "Structural Vector Autoregressions and Higher Moments: Challenges and Solutions in Small Samples," Papers 2310.08173, arXiv.org.
    13. Karamysheva, Madina & Skrobotov, Anton, 2022. "Do we reject restrictions identifying fiscal shocks? identification based on non-Gaussian innovations," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
    14. Dong, Chunlong & Wu, Hao & Zhou, Jianwen & Lin, Huifang & Chang, Lei, 2023. "Role of renewable energy investment and geopolitical risk in green finance development: Empirical evidence from BRICS countries," Renewable Energy, Elsevier, vol. 207(C), pages 234-241.
    15. Lukas Hoesch & Adam Lee & Geert Mesters, 2022. "Robust inference for non-Gaussian SVAR models," Economics Working Papers 1847, Department of Economics and Business, Universitat Pompeu Fabra.
    16. Lukas Hoesch & Adam Lee & Geert Mesters, 2022. "Locally Robust Inference for Non-Gaussian SVAR Models," Working Papers 1367, Barcelona School of Economics.
    17. Li Zhe & Serhat Yüksel & Hasan Dinçer & Shahriyar Mukhtarov & Mayis Azizov, 2021. "The Positive Influences of Renewable Energy Consumption on Financial Development and Economic Growth," SAGE Open, , vol. 11(3), pages 21582440211, August.
    18. Zhang, Yonggang & Hyder, Mansoor & Baloch, Zulfiqar Ali & Qian, Chong & Berk Saydaliev, Hayot, 2022. "Nexus between oil price volatility and inflation: Mediating nexus from exchange rate," Resources Policy, Elsevier, vol. 79(C).
    19. Herwartz, Helmut & Wang, Shu, 2023. "Point estimation in sign-restricted SVARs based on independence criteria with an application to rational bubbles," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    20. 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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