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Vasja Sivec

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First Name:Vasja
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Last Name:Sivec
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RePEc Short-ID:psi806

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Working papers

  1. Sivec, Vasja & Volk, Matjaz & Chen, Yi-An, 2018. "Empirical Evidence on the Effectiveness of Capital Buffer Release," MPRA Paper 84323, University Library of Munich, Germany, revised 02 Jan 2018.
  2. Sivec, Vasja & Volk, Matjaz, 2017. "Bank Response to Policy Related Changes in Capital Requirements," MPRA Paper 83058, University Library of Munich, Germany.
  3. Marcellino, Massimiliano & Sivec, Vasja, 2015. "Monetary, Fiscal and Oil Shocks: Evidence based on Mixed Frequency Structural FAVARs," CEPR Discussion Papers 10610, C.E.P.R. Discussion Papers.

Articles

  1. Marcellino, Massimiliano & Sivec, Vasja, 2021. "Nowcasting Gdp Growth In A Small Open Economy," National Institute Economic Review, National Institute of Economic and Social Research, vol. 256, pages 127-161, May.
  2. Sivec, Vasja & Volk, Matjaž, 2021. "Bank response to policy-related changes in capital requirements," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 868-877.
  3. Marcellino, Massimiliano & Sivec, Vasja, 2016. "Monetary, fiscal and oil shocks: Evidence based on mixed frequency structural FAVARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 335-348.

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.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Marcellino, Massimiliano & Sivec, Vasja, 2016. "Monetary, fiscal and oil shocks: Evidence based on mixed frequency structural FAVARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 335-348.

    Mentioned in:

    1. > Econometrics > Time Series Models > Dynamic Factor Models > Structural Factor Models

Working papers

  1. Sivec, Vasja & Volk, Matjaz & Chen, Yi-An, 2018. "Empirical Evidence on the Effectiveness of Capital Buffer Release," MPRA Paper 84323, University Library of Munich, Germany, revised 02 Jan 2018.

    Cited by:

    1. Chen, David Xiao & Friedrich, Christian, 2023. "The countercyclical capital buffer and international bank lending: Evidence from Canada," Journal of International Money and Finance, Elsevier, vol. 139(C).
    2. Borsuk, Marcin & Budnik, Katarzyna & Volk, Matjaz, 2020. "Buffer use and lending impact," Macroprudential Bulletin, European Central Bank, vol. 11.
    3. Carla Marques, 2020. "Non-performing loans and bank lending: Evidence for Portugal," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.

  2. Sivec, Vasja & Volk, Matjaz, 2017. "Bank Response to Policy Related Changes in Capital Requirements," MPRA Paper 83058, University Library of Munich, Germany.

    Cited by:

    1. Lang, Jan Hannes & Menno, Dominik, 2023. "The state-dependent impact of changes in bank capital requirements," Working Paper Series 2828, European Central Bank.
    2. Matthieu Darracq Paries & Peter Karadi & Christoffer Kok & Kalin Nikolov, 2022. "The Impact of Capital Requirements on the Macroeconomy: Lessons from Four Macroeconomic Models of the Euro Area," International Journal of Central Banking, International Journal of Central Banking, vol. 18(5), pages 1-50, December.

  3. Marcellino, Massimiliano & Sivec, Vasja, 2015. "Monetary, Fiscal and Oil Shocks: Evidence based on Mixed Frequency Structural FAVARs," CEPR Discussion Papers 10610, C.E.P.R. Discussion Papers.

    Cited by:

    1. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
    2. Simon Beyeler & Sylvia Kaufmann, 2016. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08, Swiss National Bank, Study Center Gerzensee.
    3. Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
    4. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    5. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2020. "Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession," Papers 2007.15419, arXiv.org.
    6. Simon Beyeler & Sylvia Kaufmann, 2021. "Reduced‐form factor augmented VAR—Exploiting sparsity to include meaningful factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 989-1012, November.
    7. Chen, Chuanglian & Zhou, Lichao & Sun, Chuanwang & Lin, Yuting, 2024. "Does oil future increase the network systemic risk of financial institutions in China?," Applied Energy, Elsevier, vol. 364(C).
    8. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    9. Quan Yonghui & Miao Wenlong, 2025. "Asymmetric risk contagion effect of the interaction between the real economy and the financial sector—an analysis based on the domestic commodity price index," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-26, December.
    10. Fu Qiao & Yan Yan, 2020. "How does stock market reflect the change in economic demand? A study on the industry-specific volatility spillover networks of China's stock market during the outbreak of COVID-19," Papers 2007.07487, arXiv.org.
    11. Franz Ramsauer & Aleksey Min & Michael Lingauer, 2019. "Estimation of FAVAR Models for Incomplete Data with a Kalman Filter for Factors with Observable Components," Econometrics, MDPI, vol. 7(3), pages 1-43, July.
    12. Si, Deng-Kui & Li, Xiao-Lin & Xu, XuChuan & Fang, Yi, 2021. "The risk spillover effect of the COVID-19 pandemic on energy sector: Evidence from China," Energy Economics, Elsevier, vol. 102(C).
    13. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    14. 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.

Articles

  1. Marcellino, Massimiliano & Sivec, Vasja, 2021. "Nowcasting Gdp Growth In A Small Open Economy," National Institute Economic Review, National Institute of Economic and Social Research, vol. 256, pages 127-161, May.

    Cited by:

    1. Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
    2. Bae, Juhee, 2024. "Factor-augmented forecasting in big data," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1660-1688.
    3. Rudrani Bhattacharya & Bornali Bhandari & Sudipto Mundle, 2023. "Nowcasting India’s Quarterly GDP Growth: A Factor-Augmented Time-Varying Coefficient Regression Model (FA-TVCRM)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 213-234, March.
    4. Hwee Kwan Chow & Yijie Fei & Daniel Han, 2023. "Forecasting GDP with many predictors in a small open economy: forecast or information pooling?," Empirical Economics, Springer, vol. 65(2), pages 805-829, August.
    5. Bolivar, Osmar, 2024. "GDP nowcasting: A machine learning and remote sensing data-based approach for Bolivia," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(3).
    6. Alina Stundziene & Vaida Pilinkiene & Jurgita Bruneckiene & Andrius Grybauskas & Mantas Lukauskas & Irena Pekarskiene, 2024. "Future directions in nowcasting economic activity: A systematic literature review," Journal of Economic Surveys, Wiley Blackwell, vol. 38(4), pages 1199-1233, September.

  2. Sivec, Vasja & Volk, Matjaž, 2021. "Bank response to policy-related changes in capital requirements," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 868-877.
    See citations under working paper version above.
  3. Marcellino, Massimiliano & Sivec, Vasja, 2016. "Monetary, fiscal and oil shocks: Evidence based on mixed frequency structural FAVARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 335-348.
    See citations under working paper version above.

More information

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-CBA: Central Banking (2) 2017-12-18 2018-03-05
  2. NEP-RMG: Risk Management (2) 2017-12-18 2018-03-05
  3. NEP-BAN: Banking (1) 2018-03-05
  4. NEP-ECM: Econometrics (1) 2015-06-05
  5. NEP-ENE: Energy Economics (1) 2015-06-05
  6. NEP-MAC: Macroeconomics (1) 2015-06-05
  7. NEP-TRA: Transition Economics (1) 2018-03-05

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