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Aleksei Netšunajev
(Aleksei Netsunajev)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Helmut Lütkepohl & Aleksei Netsunajev, 2018. "The Relation between Monetary Policy and the Stock Market in Europe," Discussion Papers of DIW Berlin 1729, DIW Berlin, German Institute for Economic Research.

    Cited by:

    1. Ivan Hajdukovic, 2022. "Transmission mechanisms of conventional and unconventional monetary policies in open economies," Post-Print hal-03912666, HAL.
    2. Fausto Pacicco & Luigi Vena & Andrea Venegoni, 2017. "Market Reactions to ECB Policy Innovations: A Cross-Country Analysis," LIUC Papers in Economics 2017-4, Cattaneo University (LIUC).
    3. Yao Séraphin PRAO & Kouassi Cyrille KONGOZA, 2025. "Asymmetric effect of monetary policy on stock market performance in the ECOWAS zone: empirical evidence from the NARDL approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(1(642), S), pages 149-166, Spring.
    4. Mihovil Anðelinoviæ & Filip Škunca, 2023. "Optimizing insurers investment portfolios: incorporating alternative investments," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 41(2), pages 361-389.
    5. Busu, Cristian & Busu, Mihail, 2019. "Modeling the predictive power of the singular value decomposition-based entropy. Empirical evidence from the Dow Jones Global Titans 50 Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).

  2. Helmut Lütkepohl & Mika Meitz & Aleksei NetŠunajev & Pentti Saikkonen, 2018. "Testing Identification via Heteroskedasticity in Structural Vector Autoregressive Models," Discussion Papers of DIW Berlin 1764, DIW Berlin, German Institute for Economic Research.

    Cited by:

    1. Jan Philipp Fritsche & Mathias Klein & Malte Rieth, 2020. "Government Spending Multipliers in (Un)certain Times," Discussion Papers of DIW Berlin 1901, DIW Berlin, German Institute for Economic Research.
    2. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    3. Justyna Wr'oblewska & {L}ukasz Kwiatkowski, 2024. "Identification of structural shocks in Bayesian VEC models with two-state Markov-switching heteroskedasticity," Papers 2406.03053, arXiv.org, revised Jun 2024.
    4. Ahmed, Rashad & Rebucci, Alessandro, 2024. "Dollar reserves and U.S. yields: Identifying the price impact of official flows," Journal of International Economics, Elsevier, vol. 152(C).
    5. Demetrescu, Matei & Kruse-Becher, Robinson, 2025. "Is U.S. real output growth non-normal? A tale of time-varying location and scale," Journal of Economic Dynamics and Control, Elsevier, vol. 171(C).
    6. Lukas Boer & Lukas Menkhoff & Malte Rieth, 2023. "The multifaceted impact of US trade policy on financial markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 388-406, April.
    7. Bacchiocchi, Emanuele & Bastianin, Andrea & Kitagawa, Toru & Mirto, Elisabetta, 2024. "Partially identified heteroskedastic SVARs," FEEM Working Papers 343513, Fondazione Eni Enrico Mattei (FEEM).
    8. Lütkepohl, Helmut & Woźniak, Tomasz, 2020. "Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    9. Gabriel Rodriguez-Rondon & Jean-Marie Dufour, 2024. "MSTest: An R-Package for Testing Markov Switching Models," Papers 2411.08188, arXiv.org.
    10. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
    11. Helmut Lutkepohl & Fei Shang & Luis Uzeda & Tomasz Wo'zniak, 2024. "Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference," Papers 2404.11057, arXiv.org.
    12. 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.

  3. Wenjuan Chen & Aleksei Netsunajev, 2018. "Structural vector autoregression with time varying transition probabilities: identifying uncertainty shocks via changes in volatility," Bank of Estonia Working Papers wp2018-02, Bank of Estonia, revised 13 Feb 2018.

    Cited by:

    1. Kamel Helali, 2022. "Markov Switching-Vector AutoRegression Model Analysis of the Economic and Growth Cycles in Tunisia and Its Main European Partners," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 656-686, March.
    2. Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.

  4. Konstantin A. Kholodilin & Aleksei Netsunajev, 2016. "Crimea and Punishment: The Impact of Sanctions on Russian and European Economies," Discussion Papers of DIW Berlin 1569, DIW Berlin, German Institute for Economic Research.

    Cited by:

    1. Nady Rapelanoro & Bali Morad, 2020. "International Economic Sanctions: Multipurpose Index Modelling in the Ukrainian Crisis Case," Working Papers hal-04159719, HAL.
    2. Pestova, Anna & Mamonov, Mikhail, 2019. "Should we care? The economic effects of financial sanctions on the Russian economy," BOFIT Discussion Papers 13/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
    3. Bayramov, Vugar & Rustamli, Nabi & Abbas, Gulnara, 2020. "Collateral damage: The Western sanctions on Russia and the evaluation of implications for Russia’s post-communist neighbourhood," International Economics, Elsevier, vol. 162(C), pages 92-109.
    4. Morad Bali, 2020. "Methodological Limitations of the Literature in the Study of Economic Sanctions, the Ukrainian Crisis Case," Post-Print hal-02472943, HAL.
    5. Morad Bali, 2018. "The Impact of Economic Sanctions on Russia and its Six Greatest European Trade Partners," Post-Print halshs-01918521, HAL.
    6. Yoshisada Shida, 2019. "Russian Business under Economic Sanctions: Is There Regional Heterogeneity?," Discussion papers 1903e, ERINA - Economic Research Institute for Northeast Asia.
    7. Jan Wedemeier & Lukas Wolf, 2022. "Navigating Rough Waters: Global Shipping and Challenges for the North Range Ports," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 57(3), pages 192-198, May.
    8. Ankudinov, Andrei & Ibragimov, Rustam & Lebedev, Oleg, 2017. "Sanctions and the Russian stock market," Research in International Business and Finance, Elsevier, vol. 40(C), pages 150-162.
    9. Prilepskiy, I., 2019. "Financial Sanctions: Impact on Capital flows and GDP Growth in Russia," Journal of the New Economic Association, New Economic Association, vol. 43(3), pages 163-172.
    10. Massimiliano Di Pace, 2017. "Eu and Usa sanctions and their impact on Russia: a logical-qualitative assessment," Argomenti, University of Urbino Carlo Bo, Department of Economics, Society & Politics, vol. 7(7), pages 1-16, May-Augus.
    11. Mirzosaid Sultonov, 2022. "Regional Economic and Financial Interconnectedness and the Impact of Sanctions: The Case of the Commonwealth of Independent States," JRFM, MDPI, vol. 15(12), pages 1-18, November.

  5. Nautz, Dieter & Netšunajev, Aleksei & Strohsal, Till, 2016. "The anchoring of inflation expectations in the short and in the long run," SFB 649 Discussion Papers 2016-015, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hachula, Michael & Nautz, Dieter, 2017. "The dynamic impact of macroeconomic news on long-term inflation expectations," Discussion Papers 2017/12, Free University Berlin, School of Business & Economics.
    2. Diegel, Max & Nautz, Dieter, 2021. "Long-term inflation expectations and the transmission of monetary policy shocks: Evidence from a SVAR analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 130(C).
    3. Kerstin Bernoth & Helmut Herwartz & Lasse Trienens, 2024. "Interest Rates, Convenience Yields, and Inflation Expectations: Drivers of US Dollar Exchange Rates," Discussion Papers of DIW Berlin 2100, DIW Berlin, German Institute for Economic Research.
    4. Diegel, Max & Nautz, Dieter, 2020. "The role of long-term inflation expectations for the transmission of monetary policy shocks," Discussion Papers 2020/19, Free University Berlin, School of Business & Economics.
    5. Demgensky, Lisa & Fritsche, Ulrich, 2023. "Narratives on the causes of inflation in Germany: First results of a pilot study," WiSo-HH Working Paper Series 77, University of Hamburg, Faculty of Business, Economics and Social Sciences, WISO Research Laboratory.
    6. Buono, Ines & Formai, Sara, 2018. "New evidence on the evolution of the anchoring of inflation expectations," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 39-54.
    7. Christina Anderl & Guglielmo Maria Caporale, 2023. "Functional Shocks to Inflation Expectations and Real Interest Rates and Their Macroeconomic Effects," CESifo Working Paper Series 10656, CESifo.
    8. Coleman, Winnie & Nautz, Dieter, 2020. "The credibility of the ECB's inflation target in times of Corona: New evidence from an online survey," Discussion Papers 2020/11, Free University Berlin, School of Business & Economics.
    9. Chen, Shi & Härdle, Wolfgang Karl & Wang, Weining, 2020. "The common and speci fic components of inflation expectation across European countries," IRTG 1792 Discussion Papers 2020-023, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Czudaj, Robert L., 2023. "Anchoring of Inflation Expectations and the Role of Monetary Policy and Cost-Push Factors," MPRA Paper 119029, University Library of Munich, Germany.
    11. Kenny, Geoff & Dovern, Jonas, 2017. "The long-term distribution of expected inflation in the euro area: what has changed since the great recession?," Working Paper Series 1999, European Central Bank.
    12. Dash, Pradyumna & Rohit, Abhishek Kumar & Devaguptapu, Adviti, 2020. "Assessing the (de-)anchoring of households’ long-term inflation expectations in the US," Journal of Macroeconomics, Elsevier, vol. 63(C).

  6. Nautz, Dieter & Netšunajev, Aleksei & Strohsal, Till, 2016. "The anchoring of inflation expectations in the short and in the long run," SFB 649 Discussion Papers 2016-015, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Hachula, Michael & Nautz, Dieter, 2017. "The dynamic impact of macroeconomic news on long-term inflation expectations," Discussion Papers 2017/12, Free University Berlin, School of Business & Economics.
    2. Diegel, Max & Nautz, Dieter, 2021. "Long-term inflation expectations and the transmission of monetary policy shocks: Evidence from a SVAR analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 130(C).
    3. Kerstin Bernoth & Helmut Herwartz & Lasse Trienens, 2024. "Interest Rates, Convenience Yields, and Inflation Expectations: Drivers of US Dollar Exchange Rates," Discussion Papers of DIW Berlin 2100, DIW Berlin, German Institute for Economic Research.
    4. Diegel, Max & Nautz, Dieter, 2020. "The role of long-term inflation expectations for the transmission of monetary policy shocks," Discussion Papers 2020/19, Free University Berlin, School of Business & Economics.
    5. Demgensky, Lisa & Fritsche, Ulrich, 2023. "Narratives on the causes of inflation in Germany: First results of a pilot study," WiSo-HH Working Paper Series 77, University of Hamburg, Faculty of Business, Economics and Social Sciences, WISO Research Laboratory.
    6. Buono, Ines & Formai, Sara, 2018. "New evidence on the evolution of the anchoring of inflation expectations," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 39-54.
    7. Christina Anderl & Guglielmo Maria Caporale, 2023. "Functional Shocks to Inflation Expectations and Real Interest Rates and Their Macroeconomic Effects," CESifo Working Paper Series 10656, CESifo.
    8. Coleman, Winnie & Nautz, Dieter, 2020. "The credibility of the ECB's inflation target in times of Corona: New evidence from an online survey," Discussion Papers 2020/11, Free University Berlin, School of Business & Economics.
    9. Chen, Shi & Härdle, Wolfgang Karl & Wang, Weining, 2020. "The common and speci fic components of inflation expectation across European countries," IRTG 1792 Discussion Papers 2020-023, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Czudaj, Robert L., 2023. "Anchoring of Inflation Expectations and the Role of Monetary Policy and Cost-Push Factors," MPRA Paper 119029, University Library of Munich, Germany.
    11. Kenny, Geoff & Dovern, Jonas, 2017. "The long-term distribution of expected inflation in the euro area: what has changed since the great recession?," Working Paper Series 1999, European Central Bank.
    12. Dash, Pradyumna & Rohit, Abhishek Kumar & Devaguptapu, Adviti, 2020. "Assessing the (de-)anchoring of households’ long-term inflation expectations in the US," Journal of Macroeconomics, Elsevier, vol. 63(C).

  7. Netésunajev, Aleksei & Winkelmann, Lars, 2016. "International dynamics of inflation expectations," SFB 649 Discussion Papers 2016-019, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Nautz, Dieter & Netšunajev, Aleksei & Strohsal, Till, 2016. "The anchoring of inflation expectations in the short and in the long run," SFB 649 Discussion Papers 2016-015, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Hachula, Michael & Nautz, Dieter, 2017. "The dynamic impact of macroeconomic news on long-term inflation expectations," Discussion Papers 2017/12, Free University Berlin, School of Business & Economics.

  8. Lütkepohl, Helmut & Netšunajev, Aleksei, 2015. "Structural vector autoregressions with heteroskedasticity: A comparison of different volatility models," SFB 649 Discussion Papers 2015-015, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Braun, Robin & Brüggemann, Ralf, 2022. "Identification of SVAR models by combining sign restrictions with external instruments," Bank of England working papers 961, Bank of England.
    2. YAMAMOTO, Yohei & 山本, 庸平, 2018. "Identifying Factor-Augmented Vector Autoregression Models via Changes in Shock Variances," Discussion paper series HIAS-E-72, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    3. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    4. Dobromił Serwa & Piotr Wdowiński, 2017. "Modeling Macro-Financial Linkages: Combined Impulse Response Functions in SVAR Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(4), pages 323-357, December.

  9. Helmut Lütkepohl & Aleksei Netšunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticity - A Comparison of Different Volatility Models," CESifo Working Paper Series 5308, CESifo.

    Cited by:

    1. Braun, Robin & Brüggemann, Ralf, 2022. "Identification of SVAR models by combining sign restrictions with external instruments," Bank of England working papers 961, Bank of England.
    2. YAMAMOTO, Yohei & 山本, 庸平, 2018. "Identifying Factor-Augmented Vector Autoregression Models via Changes in Shock Variances," Discussion paper series HIAS-E-72, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    3. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    4. Dobromił Serwa & Piotr Wdowiński, 2017. "Modeling Macro-Financial Linkages: Combined Impulse Response Functions in SVAR Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(4), pages 323-357, December.

  10. Winkelmann, Lars & Netsunajev, Aleksei, 2015. "International Transmissions of Inflation Expectations in a Markov Switching Structural VAR Model," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112900, Verein für Socialpolitik / German Economic Association.

    Cited by:

    1. Strohsal, Till & Melnick, Rafi & Nautz, Dieter, 2015. "The time-varying degree of inflation expectations anchoring," SFB 649 Discussion Papers 2015-028, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  11. Chen, Wenjuan & Netsunajev, Aleksei, 2015. "On the long-run neutrality of demand shocks," SFB 649 Discussion Papers 2015-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Nautz, Dieter & Netšunajev, Aleksei & Strohsal, Till, 2016. "The anchoring of inflation expectations in the short and in the long run," SFB 649 Discussion Papers 2016-015, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    3. Martin Bruns & Helmut Lutkepohl, 2024. "Heteroskedastic Structural Vector Autoregressions Identified via Long-run Restrictions," University of East Anglia School of Economics Working Paper Series 2024-06, School of Economics, University of East Anglia, Norwich, UK..
    4. Lütkepohl, Helmut & Meitz, Mika & Netšunajev, Aleksei & Saikkonen, Pentti, 2021. "Testing identification via heteroskedasticity in structural vector autoregressive models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 24(1), pages 1-22.
    5. Ngomba Bodi, Francis Ghislain, 2018. "Contributions relatives des chocs de demande agrégée et d’offre agrégée aux fluctuations de la croissance réelle en zone CEMAC [Relative contributions of aggregate demand and supply shocks to busin," MPRA Paper 116376, University Library of Munich, Germany.

  12. Chen, Wenjuan & Netsunajev, Aleksei, 2015. "On the long-run neutrality of demand shocks," SFB 649 Discussion Papers 2015-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Nautz, Dieter & Netšunajev, Aleksei & Strohsal, Till, 2016. "The anchoring of inflation expectations in the short and in the long run," SFB 649 Discussion Papers 2016-015, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    3. Martin Bruns & Helmut Lutkepohl, 2024. "Heteroskedastic Structural Vector Autoregressions Identified via Long-run Restrictions," University of East Anglia School of Economics Working Paper Series 2024-06, School of Economics, University of East Anglia, Norwich, UK..
    4. Lütkepohl, Helmut & Meitz, Mika & Netšunajev, Aleksei & Saikkonen, Pentti, 2021. "Testing identification via heteroskedasticity in structural vector autoregressive models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 24(1), pages 1-22.
    5. Ngomba Bodi, Francis Ghislain, 2018. "Contributions relatives des chocs de demande agrégée et d’offre agrégée aux fluctuations de la croissance réelle en zone CEMAC [Relative contributions of aggregate demand and supply shocks to busin," MPRA Paper 116376, University Library of Munich, Germany.

  13. Helmut Lütkepohl & Aleksei Netsunajev, 2014. "Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction between U.S. Monetary Policy and the Stock Market," Discussion Papers of DIW Berlin 1388, DIW Berlin, German Institute for Economic Research.

    Cited by:

    1. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    2. Guay, Alain, 2021. "Identification of structural vector autoregressions through higher unconditional moments," Journal of Econometrics, Elsevier, vol. 225(1), pages 27-46.
    3. Dominik Bertsche & Robin Braun, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2018-03, Department of Economics, University of Konstanz.
    4. Bernoth, Kerstin & Herwartz, Helmut, 2021. "Exchange rates, foreign currency exposure and sovereign risk," Journal of International Money and Finance, Elsevier, vol. 117(C).
    5. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
    6. Benjamin Beckers & Kerstin Bernoth, 2016. "Monetary Policy and Mispricing in Stock Markets," Discussion Papers of DIW Berlin 1605, DIW Berlin, German Institute for Economic Research.
    7. Pierre Guérin & Danilo Leiva-Leon, 2017. "Monetary policy, stock market and sectoral comovement," Working Papers 1731, Banco de España.
    8. Chen, Wenjuan & Netšunajev, Aleksei, 2016. "On the long-run neutrality of demand shocks," Economics Letters, Elsevier, vol. 139(C), pages 57-60.

  14. Lütkepohl, Helmut & Netésunajev, Aleksei, 2014. "Structural vector autoregressions with smooth transition in variances: The interaction between US monetary policy and the stock market," SFB 649 Discussion Papers 2014-031, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    2. Guay, Alain, 2021. "Identification of structural vector autoregressions through higher unconditional moments," Journal of Econometrics, Elsevier, vol. 225(1), pages 27-46.
    3. Dominik Bertsche & Robin Braun, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2018-03, Department of Economics, University of Konstanz.
    4. Bernoth, Kerstin & Herwartz, Helmut, 2021. "Exchange rates, foreign currency exposure and sovereign risk," Journal of International Money and Finance, Elsevier, vol. 117(C).
    5. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
    6. Benjamin Beckers & Kerstin Bernoth, 2016. "Monetary Policy and Mispricing in Stock Markets," Discussion Papers of DIW Berlin 1605, DIW Berlin, German Institute for Economic Research.
    7. Pierre Guérin & Danilo Leiva-Leon, 2017. "Monetary policy, stock market and sectoral comovement," Working Papers 1731, Banco de España.
    8. Chen, Wenjuan & Netšunajev, Aleksei, 2016. "On the long-run neutrality of demand shocks," Economics Letters, Elsevier, vol. 139(C), pages 57-60.

  15. Aleksei Netsunajev, 2013. "Reaction to technology shocks in Markov-switching structural VARs: identification via heteroskedasticity," Bank of Estonia Working Papers wp2012-6, Bank of Estonia, revised 03 Jan 2013.

    Cited by:

    1. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    2. Lütkepohl, Helmut & Schlaak, Thore, 2019. "Bootstrapping impulse responses of structural vector autoregressive models identified through GARCH," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 41-61.
    3. Lütkepohl, Helmut & Velinov, Anton, 2014. "Structural vector autoregressions: Checking identifying long-run restrictions via heteroskedasticity," SFB 649 Discussion Papers 2014-009, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Noel Gaston & Gulasekaran Rajaguru, 2015. "A Markov-switching structural vector autoregressive model of boom and bust in the Australian labour market," Empirical Economics, Springer, vol. 49(4), pages 1271-1299, December.
    5. Lütkepohl, Helmut & Woźniak, Tomasz, 2020. "Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    6. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with smooth transition in variances," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 43-57.
    7. Juan Carlos Cuestas & Bo Tang, 2015. "Exchange Rate Changes and Stock Returns in China: A Markov Switching SVAR Approach," Working Papers 2015024, The University of Sheffield, Department of Economics.
    8. Dmitry Kulikov & Aleksei Netsunajev, 2016. "Identifying Shocks in Structural VAR models via heteroskedasticity: a Bayesian approach," Bank of Estonia Working Papers wp2015-8, Bank of Estonia, revised 19 Feb 2016.
    9. Mengheng Li & Ivan Mendieta-Munoz, 2019. "The multivariate simultaneous unobserved components model and identification via heteroskedasticity," Working Paper Series 2019/08, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    10. Marianna Oliskevych & Iryna Lukianenko, 2020. "European unemployment nonlinear dynamics over the business cycles: Markov switching approach," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 22(4), pages 375-401.

  16. Dmitry Kulikov & Aleksei Netsunajev, 2013. "Identifying monetary policy shocks via heteroskedasticity: a Bayesian approach," Bank of Estonia Working Papers wp2013-9, Bank of Estonia, revised 09 Dec 2013.

    Cited by:

    1. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    2. Canova, Fabio & Bluwstein, Kristina, 2015. "Beggar-thy-neighbor? The international effects of ECB unconventional monetary policy measures," CEPR Discussion Papers 10856, C.E.P.R. Discussion Papers.
    3. Marek A. Dąbrowski & Łukasz Kwiatkowski & Justyna Wróblewska, 2020. "Sources of Real Exchange Rate Variability in Central and Eastern European Countries: Evidence from Structural Bayesian MSH-VAR Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(4), pages 369-412, December.
    4. Helmut Lütkepohl & Aleksei Netsunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticity: A Comparison of Different Volatility Models," Discussion Papers of DIW Berlin 1464, DIW Berlin, German Institute for Economic Research.
    5. Lütkepohl, Helmut & Woźniak, Tomasz, 2020. "Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    6. Netésunajev, Aleksei & Glass, Katharina, 2016. "Uncertainty and employment dynamics in the euro area and the US," SFB 649 Discussion Papers 2016-002, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Helmut Lütkepohl & Aleksei Netsunajev, 2014. "Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction between U.S. Monetary Policy and the Stock Market," Discussion Papers of DIW Berlin 1388, DIW Berlin, German Institute for Economic Research.
    8. Mengheng Li & Ivan Mendieta-Munoz, 2019. "The multivariate simultaneous unobserved components model and identification via heteroskedasticity," Working Paper Series 2019/08, Economics Discipline Group, UTS Business School, University of Technology, Sydney.

  17. Helmut Lütkepohl & Aleksei Netsunajev, 2012. "Disentangling Demand and Supply Shocks in the Crude Oil Market: How to Check Sign Restrictions in Structural VARs," Discussion Papers of DIW Berlin 1195, DIW Berlin, German Institute for Economic Research.

    Cited by:

    1. Nautz, Dieter & Netšunajev, Aleksei & Strohsal, Till, 2016. "The anchoring of inflation expectations in the short and in the long run," SFB 649 Discussion Papers 2016-015, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    3. Li, Zheng & Zeng, Jingjing & Hensher, David A., 2023. "An efficient approach to structural breaks and the case of automobile gasoline consumption in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    4. Dirk-Jan van de Ven & Roger Fouquet, 2014. "Historical energy price shocks and their changing effects on the economy," GRI Working Papers 153, Grantham Research Institute on Climate Change and the Environment.
    5. Fratzscher, Marcel & Rieth, Malte, 2015. "Monetary policy, bank bailouts and the sovereign-bank risk nexus in the euro area," CEPR Discussion Papers 10370, C.E.P.R. Discussion Papers.
    6. Xian, Hui & Gregory, Colson & Michael, Wetzstein, 2015. "Impact of nonrenewable on renewable energy: The case of wood pellets," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196833, Southern Agricultural Economics Association.
    7. Lodge, David & Manu, Ana-Simona, 2022. "EME financial conditions: Which global shocks matter?," Journal of International Money and Finance, Elsevier, vol. 120(C).
    8. Carriero, Andrea & Marcellino, Massimiliano & Tornese, Tommaso, 2022. "Blended Identification in Structural VARs," CEPR Discussion Papers 17640, C.E.P.R. Discussion Papers.
    9. Jadidzadeh, Ali & Serletis, Apostolos, 2017. "How does the U.S. natural gas market react to demand and supply shocks in the crude oil market?," Energy Economics, Elsevier, vol. 63(C), pages 66-74.
    10. Holtemöller, Oliver & Kriwoluzky, Alexander & Kwak, Boreum, 2024. "Is there an information channel of monetary policy?," IWH Discussion Papers 17/2020, Halle Institute for Economic Research (IWH), revised 2024.
    11. Kilian, Lutz, 2022. "Facts and fiction in oil market modeling," Energy Economics, Elsevier, vol. 110(C).
    12. Lütkepohl, Helmut & Velinov, Anton, 2014. "Structural vector autoregressions: Checking identifying long-run restrictions via heteroskedasticity," SFB 649 Discussion Papers 2014-009, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. Arampatzidis, Ioannis & Dergiades, Theologos & Kaufmann, Robert K. & Panagiotidis, Theodore, 2021. "Oil and the U.S. stock market: Implications for low carbon policies," Energy Economics, Elsevier, vol. 103(C).
    14. Yin, Libo & Zhou, Yimin, 2016. "What drives long-term oil market volatility? Fundamentals versus Speculation," Economics Discussion Papers 2016-2, Kiel Institute for the World Economy (IfW Kiel).
    15. James D. Hamilton, 2019. "Measuring Global Economic Activity," NBER Working Papers 25778, National Bureau of Economic Research, Inc.
    16. Gong, Xu & Lin, Boqiang, 2018. "Time-varying effects of oil supply and demand shocks on China's macro-economy," Energy, Elsevier, vol. 149(C), pages 424-437.
    17. ElFayoumi, Khalid, 2018. "The balance sheet effects of oil market shocks: An industry level analysis," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 112-127.
    18. Nguyen, Bao H. & Okimoto, Tatsuyoshi, 2019. "Asymmetric reactions of the US natural gas market and economic activity," Energy Economics, Elsevier, vol. 80(C), pages 86-99.
    19. Gong, Xu & Chen, Liqiang & Lin, Boqiang, 2020. "Analyzing dynamic impacts of different oil shocks on oil price," Energy, Elsevier, vol. 198(C).
    20. Hou, Chenghan & Nguyen, Bao H., 2018. "Understanding the US natural gas market: A Markov switching VAR approach," Energy Economics, Elsevier, vol. 75(C), pages 42-53.
    21. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    22. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
    23. Herwartz, Helmut & Plödt, Martin, 2016. "The macroeconomic effects of oil price shocks: Evidence from a statistical identification approach," Journal of International Money and Finance, Elsevier, vol. 61(C), pages 30-44.
    24. Jamie L. Cross & Chenghan Hou & Bao H. Nguyen, 2018. "On the China factor in international oil markets: A regime switching approach," Working Papers No 11/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    25. Lütkepohl, Helmut & Woźniak, Tomasz, 2020. "Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    26. Raghavan, Mala, 2019. "An analysis of the global oil market using SVARMA models," Working Papers 2019-01, University of Tasmania, Tasmanian School of Business and Economics.
    27. Herwartz, Helmut & Plödt, Martin, 2014. "Sign restrictions and statistical identification under volatility breaks -- Simulation based evidence and an empirical application to monetary policy analysis," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100326, Verein für Socialpolitik / German Economic Association.
    28. Canepa, Alessandra & Zanetti Chini, Emilio & Alqaralleh, Huthaifa, 2023. "Modelling and Forecasting Energy Market Cycles: A Generalized Smooth Transition Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202318, University of Turin.
    29. Erdenebat Bataa & Marwan Izzeldin & Denise Osborn, 2015. "Changes in the global oil market," Working Papers 75761696, Lancaster University Management School, Economics Department.
    30. Fabio Santeramo, 2015. "A cursory review of the identification strategies," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 3(1), pages 1-8, December.
    31. James D. Hamilton, 2021. "Measuring global economic activity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 293-303, April.
    32. Han, Xu, 2015. "Tests for overidentifying restrictions in Factor-Augmented VAR models," Journal of Econometrics, Elsevier, vol. 184(2), pages 394-419.
    33. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with smooth transition in variances," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 43-57.
    34. Helmut Lütkepohl & Aleksei Netsunajev, 2014. "Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction between U.S. Monetary Policy and the Stock Market," Discussion Papers of DIW Berlin 1388, DIW Berlin, German Institute for Economic Research.
    35. Herwartz, Helmut & Theilen, Bernd & Wang, Shu, 2024. "Unraveling the structural sources of oil production and their impact on CO2 emissions," Energy Economics, Elsevier, vol. 132(C).
    36. Dmitry Kulikov & Aleksei Netsunajev, 2016. "Identifying Shocks in Structural VAR models via heteroskedasticity: a Bayesian approach," Bank of Estonia Working Papers wp2015-8, Bank of Estonia, revised 19 Feb 2016.
    37. Lodge, David & Manu, Ana-Simona & Van Robays, Ine, 2024. "China's footprint in global financial markets," BOFIT Discussion Papers 1/2024, Bank of Finland Institute for Emerging Economies (BOFIT).
    38. Daniele Valenti, 2018. "Modelling the Global Price of Oil: Is there any Role for the Oil Futures-spot Spread?," Working Papers 2018.06, Fondazione Eni Enrico Mattei.
    39. Abiad, Abdul & Qureshi, Irfan A., 2023. "The macroeconomic effects of oil price uncertainty," Energy Economics, Elsevier, vol. 125(C).
    40. Bruns, Martin & Lütkepohl, Helmut, 2023. "Have the effects of shocks to oil price expectations changed?," Economics Letters, Elsevier, vol. 233(C).
    41. Stella Chinye Chiemeke & Omokhagbo Mike Imafidor, 2020. "An assessment of the impact of digital technology adoption on economic growth and labour productivity in Nigeria," Netnomics, Springer, vol. 21(1), pages 103-128, December.
    42. Nguyen, Bao H. & Okimoto, Tatsuyoshi & Tran, Trung Duc, 2022. "Uncertainty-dependent and sign-dependent effects of oil market shocks," Journal of Commodity Markets, Elsevier, vol. 26(C).
    43. Michael Hachula & Malte Rieth, 2020. "Estimating the Impact of Financial Investments on Agricultural Futures Prices using Changes in Volatility," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(3), pages 759-785, May.
    44. Puonti, Päivi, 2016. "Fiscal multipliers in a structural VEC model with mixed normal errors," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 144-154.

Articles

  1. Helmut Lütkepohl & Mika Meitz & Aleksei Netšunajev & Pentti Saikkonen, 2021. "Testing identification via heteroskedasticity in structural vector autoregressive models," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 1-22.
    See citations under working paper version above.
  2. Konstantin A. Kholodilin & Aleksei Netsunajev, 2019. "Crimea and punishment: the impact of sanctions on Russian economy and economies of the euro area," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 19(1), pages 39-51.

    Cited by:

    1. Morad Bali & Nady Rapelanoro, 2021. "How to simulate international economic sanctions: A multipurpose index modelling illustrated with EU sanctions against Russia," International Economics, CEPII research center, issue 168, pages 25-39.
    2. Jerg Gutmann & Matthias Neuenkirch & Florian Neumeier, 2024. "Do China and Russia undermine Western sanctions? Evidence from DiD and event study estimation," Review of International Economics, Wiley Blackwell, vol. 32(1), pages 132-160, February.
    3. Jakub Horak, 2021. "Sanctions as a Catalyst for Russia’s and China’s Balance of Trade: Business Opportunity," JRFM, MDPI, vol. 14(1), pages 1-26, January.
    4. Morad Bali, 2020. "Methodological Limitations of the Literature in the Study of Economic Sanctions, the Ukrainian Crisis Case," Post-Print hal-02472943, HAL.
    5. Jerg Gutmann & Matthias Neuenkirch & Florian Neumeier, 2021. "The Economic Effects of International Sanctions: An Event Study," Research Papers in Economics 2021-03, University of Trier, Department of Economics.
    6. Nguyen, Trung Thanh & Do, Manh Hung, 2021. "Impact of economic sanctions and counter-sanctions on the Russian Federation’s trade," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 267-278.
    7. Mirzosaid Sultonov, 2020. "The Impact of International Sanctions on Russian Financial Markets," Economies, MDPI, vol. 8(4), pages 1-14, December.
    8. Charemza, Wojciech & Makarova, Svetlana & Rybiński, Krzysztof, 2022. "Economic uncertainty and natural language processing; The case of Russia," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 546-562.
    9. Korhonen, Iikka, 2019. "Sanctions and counter-sanctions: What are their economic effects in Russia and elsewhere?," BOFIT Policy Briefs 2/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
    10. Francisco Rodr'iguez, 2022. "Sanctions and Imports of Essential Goods: A Closer Look at the Equipo Anova (2021) Results," Papers 2212.09904, arXiv.org.
    11. Mikhail Mamonov & Anna Pestova, 2021. ""Sorry, You're Blocked." Economic Effects of Financial Sanctions on the Russian Economy," CERGE-EI Working Papers wp704, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    12. Bijoy Chandra Das & Fakhrul Hasan & Soma Rani Sutradhar & Sujana Shafique, 2023. "Ukraine–Russia Conflict and Stock Markets Reactions in Europe," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(3), pages 395-407, September.
    13. Mikhail Mamonov & Anna Pestova, 2023. "The Price of War: Macroeconomic and Cross-Sectional Effects of Sanctions on Russia," CERGE-EI Working Papers wp756, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    14. Özge Korkmaz & Semih Karacan, 2024. "The Impact of the Russo-Ukrainian War on the Bilateral Trade in the Region: Evidence from a Panel Gravity Model," Foreign Trade Review, , vol. 59(3), pages 412-428, August.
    15. Pavel Dovbnya, 2020. "Announcements of Sanctions and the Russian Equity Market: An Event Study Approach," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 74-92, March.
    16. Shakib, Mohammed & Sohag, Kazi & Hassan, M. Kabir & Vasilyeva, Rogneda, 2023. "Finance and export diversifications Nexus in Russian regions: Role of trade globalization and regional potential," Emerging Markets Review, Elsevier, vol. 57(C).
    17. Zareei, Afsaneh & Wadensjö, Eskil, 2024. "Sanctions and Their Effects on the Labor Market and the Economy," IZA Discussion Papers 17467, Institute of Labor Economics (IZA).
    18. Anna Miromanova, 2023. "Quantifying the trade‐reducing effect of embargoes: Firm‐level evidence from Russia," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(3), pages 1121-1160, August.
    19. Prilepskiy, I., 2019. "Financial Sanctions: Impact on Capital flows and GDP Growth in Russia," Journal of the New Economic Association, New Economic Association, vol. 43(3), pages 163-172.
    20. Morad Bali & Thanh T. Nguyen & Lincoln F. Pratson, 2024. "Impacts of EU Sanctions Levied in 2014 on Individual European Countries' Exports to Russia: Winners and Losers," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 50(2), pages 154-194, April.
    21. Iikka Korhonen, 2020. "Economic Sanctions on Russia and Their Effects," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 20(04), pages 19-22, January.
    22. Simola, Heli, 2023. "What the literature says about the effects of sanctions on Russia," BOFIT Policy Briefs 8/2023, Bank of Finland Institute for Emerging Economies (BOFIT).
    23. Sziklai, Balázs R. & Kóczy, László Á. & Csercsik, Dávid, 2020. "The impact of Nord Stream 2 on the European gas market bargaining positions," Energy Policy, Elsevier, vol. 144(C).
    24. Anna Miromanova, 2023. "The effectiveness of embargoes: Evidence from Russia," The World Economy, Wiley Blackwell, vol. 46(4), pages 906-940, April.
    25. Mohammed Shakib, 2023. "Innovation-Export Diversification Nexus in Russian Regions: Does Trade Globalization, Business Potential and Geopolitics Matter?," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 22(4), pages 932-974.
    26. Rodriguez, Francisco, 2022. "Sanctions and Imports of Essential Goods; A Closer Look at the Equipo Anova (2021) Results," MPRA Paper 115714, University Library of Munich, Germany.
    27. Mirzosaid Sultonov, 2022. "Regional Economic and Financial Interconnectedness and the Impact of Sanctions: The Case of the Commonwealth of Independent States," JRFM, MDPI, vol. 15(12), pages 1-18, November.

  3. Nautz, Dieter & Strohsal, Till & Netšunajev, Aleksei, 2019. "The Anchoring Of Inflation Expectations In The Short And In The Long Run," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1959-1977, July.
    See citations under working paper version above.
  4. Helmut Lütkepohl & Aleksei Netšunajev, 2018. "The Relation between Monetary Policy and the Stock Market in Europe," Econometrics, MDPI, vol. 6(3), pages 1-14, August.
    See citations under working paper version above.
  5. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.

    Cited by:

    1. Ahmadi, Maryam & Manera, Matteo & Sadeghzadeh, Mehdi, 2018. "Investment-Uncertainty Relationship in the Oil and Gas Industry," ETA: Economic Theory and Applications 273141, Fondazione Eni Enrico Mattei (FEEM).
    2. Braun, Robin & Brüggemann, Ralf, 2022. "Identification of SVAR models by combining sign restrictions with external instruments," Bank of England working papers 961, Bank of England.
    3. 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).
    4. Lütkepohl, Helmut & Woźniak, Tomasz, 2020. "Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    5. Helmut Lütkepohl & Aleksei Netšunajev, 2018. "The Relation between Monetary Policy and the Stock Market in Europe," Econometrics, MDPI, vol. 6(3), pages 1-14, August.
    6. Herwartz, Helmut & Theilen, Bernd & Wang, Shu, 2024. "Unraveling the structural sources of oil production and their impact on CO2 emissions," Energy Economics, Elsevier, vol. 132(C).
    7. 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.

  6. Netšunajev, Aleksei & Glass, Katharina, 2017. "Uncertainty and employment dynamics in the euro area and the US," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 48-62.

    Cited by:

    1. Idriss Fontaine & Laurent Didier & Justinien Razafindravaosolonirina, 2017. "Foreign policy uncertainty shocks and US macroeconomic activity: Evidence from China," Post-Print hal-03571723, HAL.
    2. Michel C. de Souza, 2023. "On the transmission of us uncertainty shocks to the European labor market," Economics Bulletin, AccessEcon, vol. 43(4), pages 1666-1679.
    3. Sangyup Choi & Davide Furceri & Seung Yong Yoo, 2023. "Heterogeneity in the Effects of Uncertainty Shocks on Labor Market Dynamics and Extensive vs. Intensive Margins of Adjustment," Working papers 2023rwp-222, Yonsei University, Yonsei Economics Research Institute.
    4. Christou, Christina & Gupta, Rangan, 2020. "Forecasting equity premium in a panel of OECD countries: The role of economic policy uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 243-248.
    5. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.
    6. Herwartz, Helmut & Maxand, Simone & Rohloff, Hannes, 2018. "Lean against the wind or float with the storm? Revisiting the monetary policy asset price nexus by means of a novel statistical identification approach," University of Göttingen Working Papers in Economics 354, University of Goettingen, Department of Economics.
    7. Petar Soric & Oscar Claveria, 2021. ""Employment uncertainty a year after the irruption of the covid-19 pandemic"," IREA Working Papers 202112, University of Barcelona, Research Institute of Applied Economics, revised May 2021.
    8. Oscar Claveria, 2020. "“Measuring and assessing economic uncertainty”," AQR Working Papers 2012003, University of Barcelona, Regional Quantitative Analysis Group, revised Jul 2020.
    9. Arigoni, Filippo & Lenarčič, Črt, 2023. "Foreign economic policy uncertainty shocks and real activity in the Euro area," MPRA Paper 120022, University Library of Munich, Germany.
    10. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.
    11. Andreas Dibiasi & Samad Sarferaz, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," Post-Print hal-04167343, HAL.
    12. Prüser, Jan & Schlösser, Alexander, 2017. "The effects of economic policy uncertainty on European economies: Evidence from a TVP-FAVAR," Ruhr Economic Papers 708, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    13. Fontaine, Idriss & Razafindravaosolonirina, Justinien & Didier, Laurent, 2018. "Chinese policy uncertainty shocks and the world macroeconomy: Evidence from STVAR," China Economic Review, Elsevier, vol. 51(C), pages 1-19.
    14. Ueda, Renan Mitsuo & Souza, Adriano Mendonça & Menezes, Rui Manuel Campilho Pereira, 2020. "How macroeconomic variables affect admission and dismissal in the Brazilian electro-electronic sector: A VAR-based model and cluster analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    15. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Aygun, Gurcan & Wohar, Mark E., 2022. "The macroeconomic impact of economic uncertainty and financial shocks under low and high financial stress," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    16. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    17. Dibiasi, Andreas & Abberger, Klaus & Siegenthaler, Michael & Sturm, Jan-Egbert, 2018. "The effects of policy uncertainty on investment: Evidence from the unexpected acceptance of a far-reaching referendum in Switzerland," European Economic Review, Elsevier, vol. 104(C), pages 38-67.
    18. Jan Prüser & Alexander Schlösser, 2020. "The effects of economic policy uncertainty on European economies: evidence from a TVP-FAVAR," Empirical Economics, Springer, vol. 58(6), pages 2889-2910, June.
    19. Horvath, Jaroslav & Zhong, Jiansheng, 2019. "Unemployment dynamics in emerging countries: Monetary policy and external shocks," Economic Modelling, Elsevier, vol. 76(C), pages 31-49.
    20. Chan, Kam Fong & Smales, Lee A., 2025. "U.S. Presidential news coverage: Risk, uncertainty and stocks," International Review of Economics & Finance, Elsevier, vol. 98(C).
    21. Marianna Oliskevych & Iryna Lukianenko, 2020. "European unemployment nonlinear dynamics over the business cycles: Markov switching approach," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 22(4), pages 375-401.
    22. Manocha, Parul & Hunt, Richard A. & Stallkamp, Maximilian & Townsend, David M., 2024. "A tale of two impacts: Entrepreneurial action and the gender-related effects of economic policy uncertainty," Journal of Business Venturing Insights, Elsevier, vol. 21(C).

  7. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with smooth transition in variances," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 43-57.

    Cited by:

    1. Lütkepohl, Helmut & Schlaak, Thore, 2019. "Bootstrapping impulse responses of structural vector autoregressive models identified through GARCH," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 41-61.
    2. BenSaïda, Ahmed & Litimi, Houda & Abdallah, Oussama, 2018. "Volatility spillover shifts in global financial markets," Economic Modelling, Elsevier, vol. 73(C), pages 343-353.
    3. Demetrescu, Matei & Salish, Nazarii, 2024. "(Structural) VAR models with ignored changes in mean and volatility," International Journal of Forecasting, Elsevier, vol. 40(2), pages 840-854.
    4. Helmut Herwartz & Alexander Lange, 2024. "How certain are we about the role of uncertainty in the economy?," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 126-149, January.
    5. 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).
    6. 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.
    7. Baldi, Guido & Lange, Alexander, 2019. "The Interest Rate Sensitivity of Investment," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 52(2), pages 173-190.
    8. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.
    9. Daniel Parra-Amado & Camilo Granados, 2025. "Output Gap Measurement after COVID for Colombia: Lessons from a Permanent-Transitory Approach," Borradores de Economia 1295, Banco de la Republica de Colombia.
    10. 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).
    11. Helmut Lütkepohl & Aleksei Netšunajev, 2018. "The Relation between Monetary Policy and the Stock Market in Europe," Econometrics, MDPI, vol. 6(3), pages 1-14, August.
    12. 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.
    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. Ngomba Bodi, Francis Ghislain, 2018. "Contributions relatives des chocs de demande agrégée et d’offre agrégée aux fluctuations de la croissance réelle en zone CEMAC [Relative contributions of aggregate demand and supply shocks to busin," MPRA Paper 116376, University Library of Munich, Germany.

  8. Chen, Wenjuan & Netšunajev, Aleksei, 2016. "On the long-run neutrality of demand shocks," Economics Letters, Elsevier, vol. 139(C), pages 57-60.
    See citations under working paper version above.
  9. Helmut Lütkepohl & Aleksei NetŠunajev, 2014. "Disentangling Demand And Supply Shocks In The Crude Oil Market: How To Check Sign Restrictions In Structural Vars," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 479-496, April.
    See citations under working paper version above.
  10. Netsunajev, Aleksei, 2013. "Reaction to technology shocks in Markov-switching structural VARs: Identification via heteroskedasticity," Journal of Macroeconomics, Elsevier, vol. 36(C), pages 51-62.
    See citations under working paper version above.
  11. Grigori Fainštein & Aleksei Netšunajev, 2010. "Foreign Trade Patterns Between Estonia and the EU," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 16(3), pages 311-324, August.

    Cited by:

    1. Mitchell Kellman & Mitchell Yochanan Shachmurove, 2012. "Trade Sophistication in a Transition Economy: Poland 1980–2009," Working Papers 64, Department of Applied Econometrics, Warsaw School of Economics.

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