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Thomas O. Zoerner

Personal Details

First Name:Thomas
Middle Name:O.
Last Name:Zoerner
Suffix:
RePEc Short-ID:pzo79
[This author has chosen not to make the email address public]

Affiliation

(90%) Oesterreichische Nationalbank

Wien, Austria
https://www.oenb.at/
RePEc:edi:oenbbat (more details at EDIRC)

(10%) Department Volkswirtschaft
WU Wirtschaftsuniversität Wien

Wien, Austria
http://www.wu.ac.at/economics
RePEc:edi:dvwuwat (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Ringwald, Leopold & Zörner, Thomas O., 2021. "The money-inflation nexus revisited," Department of Economics Working Paper Series 310, WU Vienna University of Economics and Business.
  2. Böck, Maximilian & Zörner, Thomas O., 2019. "The Impact of Credit Market Sentiment Shocks - A TVAR Approach," Department of Economics Working Paper Series 288, WU Vienna University of Economics and Business.
  3. Zens, Gregor & Böck, Maximilian & Zörner, Thomas O., 2019. "Of clerks & cleaners: the heterogeneous impact of monetary policy on the US labor market," Department of Economics Working Paper Series 297, WU Vienna University of Economics and Business.
  4. Christian Hotz-Behofsits & Florian Huber & Thomas O. Zorner, 2018. "Predicting crypto-currencies using sparse non-Gaussian state space models," Papers 1801.06373, arXiv.org, revised Feb 2018.
  5. Niko Hauzenberger & Florian Huber & Michael Pfarrhofer & Thomas O. Zorner, 2018. "Stochastic model specification in Markov switching vector error correction models," Papers 1807.00529, arXiv.org, revised Sep 2019.
  6. Huber, Florian & Zörner, Thomas, 2017. "Threshold cointegration and adaptive shrinkage," Department of Economics Working Paper Series 250, WU Vienna University of Economics and Business.
  7. Ingrid Kubin & Thomas O. Zörner, 2017. "Human Capital in a Credit Cycle Model," Department of Economics Working Papers wuwp251, Vienna University of Economics and Business, Department of Economics.

Articles

  1. Kubin, Ingrid & Zörner, Thomas O., 2021. "Credit cycles, human capital and the distribution of income," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 954-975.
  2. Hauzenberger Niko & Huber Florian & Pfarrhofer Michael & Zörner Thomas O., 2021. "Stochastic model specification in Markov switching vector error correction models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-17, April.
  3. Zens, Gregor & Böck, Maximilian & Zörner, Thomas O., 2020. "The heterogeneous impact of monetary policy on the US labor market," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
  4. Kubin, Ingrid & Zörner, Thomas O. & Gardini, Laura & Commendatore, Pasquale, 2019. "A credit cycle model with market sentiments," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 159-174.
  5. Huber, Florian & Zörner, Thomas O., 2019. "Threshold cointegration in international exchange rates:A Bayesian approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 458-473.
  6. Christian Hotz‐Behofsits & Florian Huber & Thomas Otto Zörner, 2018. "Predicting crypto‐currencies using sparse non‐Gaussian state space models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 627-640, September.

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. Böck, Maximilian & Zörner, Thomas O., 2019. "The Impact of Credit Market Sentiment Shocks - A TVAR Approach," Department of Economics Working Paper Series 288, WU Vienna University of Economics and Business.

    Cited by:

    1. Alessia Cafferata & Marwil J. Dávila-Fernández & Serena Sordi, 2020. "(Ir)rational explorers in the financial jungle: modelling Minsky with heterogeneous agents," Department of Economics University of Siena 819, Department of Economics, University of Siena.

  2. Christian Hotz-Behofsits & Florian Huber & Thomas O. Zorner, 2018. "Predicting crypto-currencies using sparse non-Gaussian state space models," Papers 1801.06373, arXiv.org, revised Feb 2018.

    Cited by:

    1. Kubin, Ingrid & Zörner, Thomas O. & Gardini, Laura & Commendatore, Pasquale, 2019. "A credit cycle model with market sentiments," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 159-174.
    2. Thanasis Stengos & Theodore Panagiotidis & Orestis Vravosinos, 2020. "A principal component-guided sparse regression approach for the determination of bitcoin returns," Working Papers 2001, University of Guelph, Department of Economics and Finance.
    3. Rick Bohte & Luca Rossini, 2019. "Comparing the Forecasting of Cryptocurrencies by Bayesian Time-Varying Volatility Models," JRFM, MDPI, vol. 12(3), pages 1-18, September.
    4. Catania, Leopoldo & Grassi, Stefano & Ravazzolo, Francesco, 2019. "Forecasting cryptocurrencies under model and parameter instability," International Journal of Forecasting, Elsevier, vol. 35(2), pages 485-501.
    5. Pratha Khandelwal & Philip Nadler & Rossella Arcucci & William Knottenbelt & Yi-Ke Guo, 2021. "A Scalable Inference Method For Large Dynamic Economic Systems," Papers 2110.14346, arXiv.org.
    6. Jin-Bom Han & Sun-Hak Kim & Myong-Hun Jang & Kum-Sun Ri, 2020. "Using Genetic Algorithm and NARX Neural Network to Forecast Daily Bitcoin Price," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 337-353, August.
    7. Camilla Muglia & Luca Santabarbara & Stefano Grassi, 2019. "Is Bitcoin a Relevant Predictor of Standard & Poor’s 500?," JRFM, MDPI, vol. 12(2), pages 1-10, May.
    8. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
    9. Gupta, Rangan & Huber, Florian & Piribauer, Philipp, 2020. "Predicting international equity returns: Evidence from time-varying parameter vector autoregressive models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    10. Phillip, Andrew & Chan, Jennifer & Peiris, Shelton, 2020. "On generalized bivariate student-t Gegenbauer long memory stochastic volatility models with leverage: Bayesian forecasting of cryptocurrencies with a focus on Bitcoin," Econometrics and Statistics, Elsevier, vol. 16(C), pages 69-90.
    11. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2020. "Exploring the Predictability of Cryptocurrencies via Bayesian Hidden Markov Models," Papers 2011.03741, arXiv.org, revised Dec 2020.
    12. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2020. "Do Cryptocurrency Prices Camouflage Latent Economic Effects? A Bayesian Hidden Markov Approach," Future Internet, MDPI, vol. 12(3), pages 1-19, March.
    13. Koki, Constandina & Leonardos, Stefanos & Piliouras, Georgios, 2022. "Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models," Research in International Business and Finance, Elsevier, vol. 59(C).
    14. Leopoldo Catania & Stefano Grassi & Francesco Ravazzolo, 2018. "Forecasting Cryptocurrencies Financial Time Series," Working Papers No 5/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    15. Anoop S Kumar & Taufeeq Ajaz, 2019. "Co-movement in crypto-currency markets: evidences from wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-17, December.
    16. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2019. "A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series," Papers 1909.10957, arXiv.org, revised Jul 2021.

  3. Niko Hauzenberger & Florian Huber & Michael Pfarrhofer & Thomas O. Zorner, 2018. "Stochastic model specification in Markov switching vector error correction models," Papers 1807.00529, arXiv.org, revised Sep 2019.

    Cited by:

    1. Hauzenberger, Niko & Pfarrhofer, Michael & Stelzer, Anna, 2021. "On the effectiveness of the European Central Bank’s conventional and unconventional policies under uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 822-845.

  4. Huber, Florian & Zörner, Thomas, 2017. "Threshold cointegration and adaptive shrinkage," Department of Economics Working Paper Series 250, WU Vienna University of Economics and Business.

    Cited by:

    1. Hauzenberger Niko & Huber Florian & Pfarrhofer Michael & Zörner Thomas O., 2021. "Stochastic model specification in Markov switching vector error correction models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-17, April.

Articles

  1. Hauzenberger Niko & Huber Florian & Pfarrhofer Michael & Zörner Thomas O., 2021. "Stochastic model specification in Markov switching vector error correction models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-17, April.
    See citations under working paper version above.
  2. Zens, Gregor & Böck, Maximilian & Zörner, Thomas O., 2020. "The heterogeneous impact of monetary policy on the US labor market," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).

    Cited by:

    1. Brand, Claus & Obstbaum, Meri & Coenen, Günter & Sondermann, David & Lydon, Reamonn & Ajevskis, Viktors & Hammermann, Felix & Angino, Siria & Hernborg, Nils & Basso, Henrique & Hertweck, Matthias & Bi, 2021. "Employment and the conduct of monetary policy in the euro area," Occasional Paper Series 275, European Central Bank.
    2. Fumitaka Nakamura & Nao Sudo & Yu Sugisaki, 2021. "Monetary Policy Shocks and the Employment of Young, Middle-Aged, and Old Workers," IMES Discussion Paper Series 21-E-06, Institute for Monetary and Economic Studies, Bank of Japan.

  3. Kubin, Ingrid & Zörner, Thomas O. & Gardini, Laura & Commendatore, Pasquale, 2019. "A credit cycle model with market sentiments," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 159-174.

    Cited by:

    1. Bischi, Gian Italo & Matsumoto, Akio & Carrera, Edgar J. Sanchez, 2020. "Foreword to the SCED special issue on “Nonlinear Social Dynamics”," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 236-237.

  4. Huber, Florian & Zörner, Thomas O., 2019. "Threshold cointegration in international exchange rates:A Bayesian approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 458-473.

    Cited by:

    1. Hauzenberger, Niko & Huber, Florian, 2018. "Model instability in predictive exchange rate regressions," Department of Economics Working Paper Series 276, WU Vienna University of Economics and Business.
    2. Kubin, Ingrid & Zörner, Thomas O. & Gardini, Laura & Commendatore, Pasquale, 2019. "A credit cycle model with market sentiments," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 159-174.
    3. Anna Pajor & Justyna Wróblewska, 2022. "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 427-448, September.
    4. Hauzenberger, Niko & Pfarrhofer, Michael & Stelzer, Anna, 2021. "On the effectiveness of the European Central Bank’s conventional and unconventional policies under uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 822-845.
    5. Hauzenberger Niko & Huber Florian & Pfarrhofer Michael & Zörner Thomas O., 2021. "Stochastic model specification in Markov switching vector error correction models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-17, April.
    6. Niko Hauzenberger & Michael Pfarrhofer & Luca Rossini, 2020. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," Papers 2011.04577, arXiv.org.

  5. Christian Hotz‐Behofsits & Florian Huber & Thomas Otto Zörner, 2018. "Predicting crypto‐currencies using sparse non‐Gaussian state space models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 627-640, September.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 10 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-ECM: Econometrics (4) 2017-06-18 2018-02-05 2018-07-09 2021-03-15. Author is listed
  2. NEP-ETS: Econometric Time Series (3) 2017-06-18 2018-02-05 2018-07-09. Author is listed
  3. NEP-MON: Monetary Economics (3) 2019-12-02 2021-03-15 2021-03-15. Author is listed
  4. NEP-ORE: Operations Research (3) 2017-06-18 2018-07-09 2018-11-19. Author is listed
  5. NEP-FDG: Financial Development & Growth (2) 2017-08-20 2019-08-19
  6. NEP-CBA: Central Banking (1) 2021-03-15
  7. NEP-CMP: Computational Economics (1) 2017-08-20
  8. NEP-CWA: Central & Western Asia (1) 2021-03-15
  9. NEP-FOR: Forecasting (1) 2018-02-05
  10. NEP-KNM: Knowledge Management & Knowledge Economy (1) 2018-07-09
  11. NEP-LMA: Labor Markets - Supply, Demand, & Wages (1) 2017-08-20

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