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Michael Pfarrhofer

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. Michael Pfarrhofer & Anna Stelzer, 2025. "Scenario Analysis with Multivariate Bayesian Machine Learning Models," Papers 2502.08440, arXiv.org, revised Nov 2025.

    Cited by:

    1. Marcellino, Massimiliano & Pfarrhofer, Michael, 2025. "Nonparametric mixed frequency monitoring macro-at-risk," Economics Letters, Elsevier, vol. 255(C).
    2. Niko Hauzenberger Massimiliano Marcellino Michael Pfarrhofer Anna Stelzer, 2026. "Direct Gaussian Process Predictive Regressions with Mixed Frequency Data," BAFFI CAREFIN Working Papers 26265, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    3. Joshua C. C. Chan & Michael Pfarrhofer, 2025. "Large Bayesian VARs for Binary and Censored Variables," Papers 2506.01422, arXiv.org.
    4. Tony Chernis & Niko Hauzenberger & Haroon Mumtaz & Michael Pfarrhofer, 2025. "A Bayesian Gaussian Process Dynamic Factor Model," Papers 2509.04928, arXiv.org.

  2. Tony Chernis & Niko Hauzenberger & Haroon Mumtaz & Michael Pfarrhofer, 2025. "A Bayesian Gaussian Process Dynamic Factor Model," Papers 2509.04928, arXiv.org.

    Cited by:

    1. Oliver Snellman, 2026. "Nonlinear Dynamic Factor Analysis With a Transformer Network," Papers 2601.12039, arXiv.org.
    2. Niko Hauzenberger Massimiliano Marcellino Michael Pfarrhofer Anna Stelzer, 2026. "Direct Gaussian Process Predictive Regressions with Mixed Frequency Data," BAFFI CAREFIN Working Papers 26265, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

  3. Massimiliano MARCELLINO & Michael PFARRHOFER, 2024. "Bayesian nonparametric methods for macroeconomic forecasting," BAFFI CAREFIN Working Papers 24224, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

    Cited by:

    1. Marcellino, Massimiliano & Pfarrhofer, Michael, 2025. "Nonparametric mixed frequency monitoring macro-at-risk," Economics Letters, Elsevier, vol. 255(C).
    2. Niko Hauzenberger Massimiliano Marcellino Michael Pfarrhofer Anna Stelzer, 2026. "Direct Gaussian Process Predictive Regressions with Mixed Frequency Data," BAFFI CAREFIN Working Papers 26265, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

  4. Niko Hauzenberger & Massimiliano Marcellino & Michael Pfarrhofer & Anna Stelzer, 2024. "Nowcasting with Mixed Frequency Data Using Gaussian Processes," Papers 2402.10574, arXiv.org, revised Sep 2024.

    Cited by:

    1. Philippe Goulet Coulombe & Maximilian Goebel & Karin Klieber, 2024. "Dual Interpretation of Machine Learning Forecasts," Papers 2412.13076, arXiv.org.
    2. Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2025. "Panel Machine Learning with Mixed-Frequency Data: Monitoring State-Level Fiscal Variables," CIRANO Working Papers 2025s-15, CIRANO.
    3. Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024. "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 339-366, November.
    4. Marcellino, Massimiliano & Pfarrhofer, Michael, 2025. "Nonparametric mixed frequency monitoring macro-at-risk," Economics Letters, Elsevier, vol. 255(C).

  5. Florian Huber & Christian Matthes & Michael Pfarrhofer, 2024. "General Seemingly Unrelated Local Projections," Papers 2410.17105, arXiv.org, revised Aug 2025.

    Cited by:

    1. Masahiro Tanaka, 2025. "Quasi-Bayesian Local Projections: Simultaneous Inference and Extension to the Instrumental Variable Method," Papers 2503.20249, arXiv.org, revised Dec 2025.
    2. Philippe Goulet Coulombe & Karin Klieber, 2025. "Opening the Black Box of Local Projections," Papers 2505.12422, arXiv.org, revised Jul 2025.

  6. Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.

    Cited by:

    1. Hauzenberger, Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2025. "Bayesian neural networks for macroeconomic analysis," Journal of Econometrics, Elsevier, vol. 249(PC).
    2. Florian Huber & Josef Schreiner, 2023. "Are Phillips curves in CESEE still alive and well behaved?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/23, pages 7-27.
    3. Maximilian Boeck & Michael Pfarrhofer, 2025. "Belief Shocks and Implications of Expectations About Growth‐at‐Risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(3), pages 341-348, April.
    4. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    5. Ta-Chung Chi & Ting-Han Fan & Raffaele M. Ghigliazza & Domenico Giannone & Zixuan & Wang, 2025. "Macroeconomic Forecasting and Machine Learning," Papers 2510.11008, arXiv.org.
    6. Oyebayo Ridwan Olaniran & Ali Rashash R. Alzahrani, 2023. "On the Oracle Properties of Bayesian Random Forest for Sparse High-Dimensional Gaussian Regression," Mathematics, MDPI, vol. 11(24), pages 1-29, December.
    7. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    8. Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024. "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 339-366, November.
    9. Onder Ozgur & Murat Aslan, 2025. "Monetary policy stance and foreign currency lending: evidence from a persistently dollarized emerging market," Economic Change and Restructuring, Springer, vol. 58(4), pages 1-34, August.
    10. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    11. Pedro A. Lima & Carlos M. Carvalho & Hedibert F. Lopes & Andrew Herren, 2025. "Minnesota BART," Papers 2503.13759, arXiv.org.
    12. Adämmer, Philipp & Prüser, Jan & Schüssler, Rainer A., 2025. "Forecasting macroeconomic tail risk in real time: Do textual data add value?," International Journal of Forecasting, Elsevier, vol. 41(1), pages 307-320.
    13. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Forecasting euro area inflation with machine-learning models," Research Bulletin, European Central Bank, vol. 112.
    14. Joseph, Andreas & Potjagailo, Galina & Chakraborty, Chiranjit & Kapetanios, George, 2024. "Forecasting UK inflation bottom up," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1521-1538.
    15. Marcellino, Massimiliano & Pfarrhofer, Michael, 2025. "Nonparametric mixed frequency monitoring macro-at-risk," Economics Letters, Elsevier, vol. 255(C).
    16. Tobias Adrian & Hongqi Chen & Max-Sebastian Dov`i & Ji Hyung Lee, 2025. "Machine-learning Growth at Risk," Papers 2506.00572, arXiv.org.
    17. Bobeica, Elena & Holton, Sarah & Huber, Florian & Martínez Hernández, Catalina, 2025. "Beware of large shocks! A non-parametric structural inflation model," Working Paper Series 3052, European Central Bank.
    18. Niko Hauzenberger Massimiliano Marcellino Michael Pfarrhofer Anna Stelzer, 2026. "Direct Gaussian Process Predictive Regressions with Mixed Frequency Data," BAFFI CAREFIN Working Papers 26265, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    19. Martin Ertl & Ines Fortin & Jaroslava Hlouskova & Sebastian P. Koch & Robert M. Kunst & Leopold Sögner, 2025. "Inflation forecasting in turbulent times," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 52(1), pages 5-37, February.
    20. Jan Prüser & Florian Huber, 2024. "Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 269-291, March.
    21. Tibor Szendrei & Arnab Bhattacharjee, 2024. "Momentum Informed Inflation-at-Risk," Papers 2408.12286, arXiv.org.
    22. Florian Huber & Karin Klieber & Massimiliano Marcellino & Luca Onorante & Michael Pfarrhofer, 2024. "Asymmetries in Financial Spillovers," Papers 2410.16214, arXiv.org.
    23. Sui, Jianli & Lv, Wenqiang & Gao, Xiang & Koedijk, Kees G., 2024. "China’s GDP-at-Risk: Real-Time Monitoring, Risk Tracing, and Macroeconomic Policy Effects," Journal of International Money and Finance, Elsevier, vol. 147(C).
    24. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
    25. Chen, Sihan & Ming, Lei & Yang, Haoxi & Yang, Shenggang, 2025. "Iterated Dynamic Model Averaging and application to inflation forecasting," International Review of Financial Analysis, Elsevier, vol. 102(C).
    26. Massimiliano MARCELLINO & Michael PFARRHOFER, 2024. "Bayesian nonparametric methods for macroeconomic forecasting," BAFFI CAREFIN Working Papers 24224, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    27. Tony Chernis & Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Predictive Density Combination Using a Tree-Based Synthesis Function," Staff Working Papers 23-61, Bank of Canada.
    28. Huang, Yu-Fan & Liao, Wenting & Wang, Taining, 2024. "Does US financial uncertainty spill over through the (asymmetric) international credit channel? The role of market expectations," Journal of International Money and Finance, Elsevier, vol. 148(C).
    29. Paponpat Taveeapiradeecharoen & Nattapol Aunsri, 2025. "Forecasting in small open emerging economies Evidence from Thailand," Papers 2509.14805, arXiv.org.
    30. Ramsey, A. Ford & Ghosh, Sujit K., 2025. "Bayesian Additive Regression Tree (BART) Models of Market Integration in the 19th-Century Trans-Atlantic Wheat Trade," 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO 361103, Agricultural and Applied Economics Association.
    31. Carboni, Giacomo & Fonseca, Luís & Fornari, Fabio & Urrutia, Leonardo, 2026. "Structural drivers of growth at risk: insights from a VAR-quantile regression approach," Working Paper Series 3171, European Central Bank.
    32. Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2024. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2126-2145, September.
    33. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.

  7. Fischer, Manfred M. & Hauzenberger, Niko & Huber, Florian & Pfarrhofer, Michael, 2022. "General Bayesian time-varying parameter VARs for modeling government bond yields," Working Papers in Regional Science 2021/01, WU Vienna University of Economics and Business.

    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.
    2. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2022. "Bayesian Modeling of TVP-VARs Using Regression Trees," Papers 2209.11970, arXiv.org, revised May 2023.

  8. Florian Huber & Luca Onorante & Michael Pfarrhofer, 2022. "Forecasting euro area inflation using a huge panel of survey expectations," Papers 2207.12225, arXiv.org.

    Cited by:

    1. Philippe Goulet Coulombe & Maximilian Goebel & Karin Klieber, 2024. "Dual Interpretation of Machine Learning Forecasts," Papers 2412.13076, arXiv.org.
    2. Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024. "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 339-366, November.
    3. Niko Hauzenberger Massimiliano Marcellino Michael Pfarrhofer Anna Stelzer, 2026. "Direct Gaussian Process Predictive Regressions with Mixed Frequency Data," BAFFI CAREFIN Working Papers 26265, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    4. Jirong Zhuang & Xuan Wu, 2025. "SABR-Informed Multitask Gaussian Process: A Synthetic-to-Real Framework for Implied Volatility Surface Construction," Papers 2506.22888, arXiv.org, revised Feb 2026.
    5. Jacques Sapir, 2025. "The French and European Multi-faceted Crisis (Part 1)," Studies on Russian Economic Development, Springer, vol. 36(5), pages 723-732, October.

  9. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2021. "General Bayesian time-varying parameter VARs for predicting government bond yields," Papers 2102.13393, arXiv.org.

    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.

  10. Martin Feldkircher & Florian Huber & Gary Koop & Michael Pfarrhofer, 2021. "Approximate Bayesian inference and forecasting in huge-dimensional multi-country VARs," Papers 2103.04944, arXiv.org, revised Feb 2022.

    Cited by:

    1. Hauzenberger, Niko & Pfarrhofer, Michael & Rossini, Luca, 2025. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," International Journal of Forecasting, Elsevier, vol. 41(1), pages 361-376.
    2. Shovon Sengupta & Sunny Kumar Singh & Tanujit Chakraborty, 2025. "Macroeconomic Forecasting for the G7 countries under Uncertainty Shocks," Papers 2510.23347, arXiv.org.
    3. Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
    4. Prüser, Jan & Blagov, Boris, 2022. "Improving inference and forecasting in VAR models using cross-sectional information," Ruhr Economic Papers 960, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. Dimitris Korobilis & Maximilian Schröder, 2023. "Monitoring multicountry macroeconomic risk," Working Paper 2023/9, Norges Bank.
    6. Korobilis, Dimitris & Schröder, Maximilian, 2025. "Monitoring multi-country macroeconomic risk: A quantile factor-augmented vector autoregressive (QFAVAR) approach," Journal of Econometrics, Elsevier, vol. 249(PC).
    7. Monica Billio & Roberto Casarin & Fausto Corradin & Antonio Peruzzi, 2025. "Bayesian Outlier Detection for Matrix-variate Models," Papers 2503.19515, arXiv.org, revised Aug 2025.

  11. Michael Pfarrhofer, 2021. "Modeling tail risks of inflation using unobserved component quantile regressions," Papers 2103.03632, arXiv.org, revised Oct 2021.

    Cited by:

    1. Maximilian Boeck & Michael Pfarrhofer, 2025. "Belief Shocks and Implications of Expectations About Growth‐at‐Risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(3), pages 341-348, April.
    2. Polat, Onur & Somani, Dhanashree & Gupta, Rangan & Karmakar, Sayar, 2025. "Shortages and machine-learning forecasting of oil returns volatility: 1900–2024," Finance Research Letters, Elsevier, vol. 79(C).
    3. Zheng, Tingguo & Gong, Lu & Ye, Shiqi, 2023. "Global energy market connectedness and inflation at risk," Energy Economics, Elsevier, vol. 126(C).
    4. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    5. Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024. "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 339-366, November.
    6. Ignacio Garr'on & C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "International vulnerability of inflation," Papers 2410.20628, arXiv.org, revised Oct 2024.
    7. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org, revised Aug 2024.
    8. Degiannakis, Stavros & Delis, Panagiotis & Filis, George, 2025. "Forecasting household-level inflation in Greece," MPRA Paper 127228, University Library of Munich, Germany.
    9. Thanoj K. Muddana & Komal S.R. Bhimireddy & Anandamayee Majumdar & Rangan Gupta, 2024. "Forecasting Gold Returns Volatility Over 1258-2023: The Role of Moments," Working Papers 202421, University of Pretoria, Department of Economics.
    10. Phella, Anthoulla & Gabriel, Vasco J. & Martins, Luis F., 2024. "Predicting tail risks and the evolution of temperatures," Energy Economics, Elsevier, vol. 131(C).
    11. Jan Prüser & Florian Huber, 2024. "Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 269-291, March.
    12. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2024. "Inflation Target at Risk: A Time-varying Parameter Distributional Regression," Papers 2403.12456, arXiv.org, revised Jan 2026.
    13. Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
    14. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2024. "Climate Risks and Forecastability of US Inflation: Evidence from Dynamic Quantile Model Averaging," Working Papers 202420, University of Pretoria, Department of Economics.
    15. Garrón Vedia, Ignacio & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2024. "International vulnerability of inflation," DES - Working Papers. Statistics and Econometrics. WS 44814, Universidad Carlos III de Madrid. Departamento de Estadística.

  12. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model," Papers 2110.03411, arXiv.org.

    Cited by:

    1. Hauzenberger, Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2025. "Bayesian neural networks for macroeconomic analysis," Journal of Econometrics, Elsevier, vol. 249(PC).
    2. Simon Lloyd & Ed Manuel & Konstantin Panchev, 2024. "Foreign Vulnerabilities, Domestic Risks: The Global Drivers of GDP-at-Risk," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(1), pages 335-392, March.
    3. Maximilian Boeck & Michael Pfarrhofer, 2025. "Belief Shocks and Implications of Expectations About Growth‐at‐Risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(3), pages 341-348, April.
    4. Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024. "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 339-366, November.
    5. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    6. Ignace De Vos & Gerdie Everaert, 2025. "GLS Estimation of Local Projections: Trading Robustness for Efficiency," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 24/1095, Ghent University, Faculty of Economics and Business Administration.
    7. Marcellino, Massimiliano & Pfarrhofer, Michael, 2025. "Nonparametric mixed frequency monitoring macro-at-risk," Economics Letters, Elsevier, vol. 255(C).
    8. Tobias Adrian & Hongqi Chen & Max-Sebastian Dov`i & Ji Hyung Lee, 2025. "Machine-learning Growth at Risk," Papers 2506.00572, arXiv.org.
    9. Andrey Polbin & Andrei Shumilov, 2025. "Nowcasting and forecasting Russian GDP and its components using quantile models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 79, pages 5-26.
    10. Hauzenberger, Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2025. "Machine learning the macroeconomic effects of financial shocks," Economics Letters, Elsevier, vol. 250(C).
    11. Lv, Mengdi & Jiao, Shoukun & Ye, Shiqi & Song, Hongmei & Xu, Jiexin & Ye, Wuyi, 2024. "Assessing time-varying risk in China’s GDP growth," Economics Letters, Elsevier, vol. 242(C).
    12. Dimitris Korobilis & Maximilian Schröder, 2023. "Monitoring multicountry macroeconomic risk," Working Paper 2023/9, Norges Bank.
    13. Korobilis, Dimitris & Schröder, Maximilian, 2025. "Monitoring multi-country macroeconomic risk: A quantile factor-augmented vector autoregressive (QFAVAR) approach," Journal of Econometrics, Elsevier, vol. 249(PC).
    14. Ramsey, A. Ford & Ghosh, Sujit K., 2025. "Bayesian Additive Regression Tree (BART) Models of Market Integration in the 19th-Century Trans-Atlantic Wheat Trade," 2025 AAEA & WAEA Joint Annual Meeting, July 27-29, 2025, Denver, CO 361103, Agricultural and Applied Economics Association.
    15. Polbin, Andrey & Shumilov, Andrei, 2025. "Наукастинг И Прогнозирование Ввп России И Его Компонентов С Помощью Квантильных Моделей [Nowcasting and forecasting Russian GDP and its components using quantile models]," MPRA Paper 125440, University Library of Munich, Germany.
    16. Mai Dao & Lam Nguyen, 2025. "Variable selection in macroeconomic stress test: a Bayesian quantile regression approach," Empirical Economics, Springer, vol. 68(3), pages 1113-1169, March.

  13. Florian Huber & Michael Pfarrhofer, 2020. "Dynamic shrinkage in time-varying parameter stochastic volatility in mean models," Papers 2005.06851, arXiv.org.

    Cited by:

    1. Peter Knaus & Sylvia Fruhwirth-Schnatter, 2023. "The Dynamic Triple Gamma Prior as a Shrinkage Process Prior for Time-Varying Parameter Models," Papers 2312.10487, arXiv.org, revised Jan 2025.
    2. Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2025. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Empirical Economics, Springer, vol. 68(2), pages 535-553, February.
    3. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    4. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    5. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    6. Dima, Bogdan & Dima, Ştefana Maria & Ioan, Roxana, 2025. "The short-run impact of investor expectations’ past volatility on current predictions: The case of VIX," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 98(C).
    7. Niko Hauzenberger & Florian Huber & Karin Klieber, 2020. "Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques," Papers 2012.08155, arXiv.org, revised Dec 2021.
    8. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.
    9. Zhongfang He, 2024. "Locally time-varying parameter regression," Econometric Reviews, Taylor & Francis Journals, vol. 43(5), pages 269-300, May.
    10. Gabriel Rodriguez & Mauricio Alvarado, 2025. "The Inflation Uncertainty-Inflation Relationship: Time Variation Across Latin America and the G7," Documentos de Trabajo / Working Papers 2025-544, Departamento de Economía - Pontificia Universidad Católica del Perú.

  14. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2020. "Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession," Papers 2007.15419, arXiv.org.

    Cited by:

    1. Mariana Hatmanu & Cristina Cautisanu, 2021. "The Impact of COVID-19 Pandemic on Stock Market: Evidence from Romania," IJERPH, MDPI, vol. 18(17), pages 1-22, September.
    2. Hakan Yilmazkuday, 2021. "COVID-19 and Monetary Policy with Zero Bounds: A Cross-Country Investigation," Working Papers 2112, Florida International University, Department of Economics.
    3. Ayhan Kuloğlu, 2021. "Covıd-19 Krizinin Petrol Fiyatları Üzerine Etkisi," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 6(3), pages 710-727.
    4. Bo Xu & Jingjing Li & Yujun Wu, 2024. "External shock, stimulus policy and economic resilience of small and micro businesses: evidence from COVID-19 pandemic in China," Asia-Pacific Journal of Regional Science, Springer, vol. 8(2), pages 585-613, June.
    5. Lendy Banegas & Fredy Vides, 2025. "Stochastically Structured Reservoir Computers for Financial and Economic System Identification," Papers 2507.17115, arXiv.org, revised Nov 2025.
    6. Müller, Fernanda Maria & Santos, Samuel Solgon & Righi, Marcelo Brutti, 2023. "A description of the COVID-19 outbreak role in financial risk forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    7. Andre Amaral & Taysir E. Dyhoum & Hussein A. Abdou & Hassan M. Aljohani, 2022. "Modeling for the Relationship between Monetary Policy and GDP in the USA Using Statistical Methods," Mathematics, MDPI, vol. 10(21), pages 1-20, November.
    8. Wang, Hao & Xu, Ning & Yin, Haiyan & Ji, Hao, 2022. "The dynamic impact of monetary policy on financial stability in China after crises," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    9. Vítor Castro & Rodrigo Martins, 2024. "Lockdowns, vaccines, and the economy: How economic perceptions were shaped during the COVID‐19 pandemic†," Scottish Journal of Political Economy, Scottish Economic Society, vol. 71(3), pages 439-456, July.
    10. Mahdi Goldani, 2025. "Daily Forecasting for Annual Time Series Datasets Using Similarity-Based Machine Learning Methods: A Case Study in the Energy Market," Papers 2511.05556, arXiv.org.
    11. Jacek Pietrucha, 2021. "Drivers of the Cash Paradox," Risks, MDPI, vol. 9(12), pages 1-17, December.
    12. Víctor Manuel Cuevas Ahumada & Cuauhtémoc Calderón Villarreal, 2023. "Government policies and manufacturing production during the COVID-19 pandemic," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 18(4), pages 1-19, Octubre -.

  15. Florian Huber & Gary Koop & Luca Onorante & Michael Pfarrhofer & Josef Schreiner, 2020. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Papers 2008.12706, arXiv.org, revised Dec 2020.

    Cited by:

    1. Hauzenberger, Niko & Huber, Florian & Klieber, Karin & Marcellino, Massimiliano, 2025. "Bayesian neural networks for macroeconomic analysis," Journal of Econometrics, Elsevier, vol. 249(PC).
    2. Florian Huber & Josef Schreiner, 2023. "Are Phillips curves in CESEE still alive and well behaved?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/23, pages 7-27.
    3. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
    4. Kaustubh & Soumya Bhadury & Saurabh Ghosh, 2024. "Reinvigorating Gva Nowcasting In The Postpandemic Period: A Case Study For India," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 27(Spesial I), pages 95-130, February.
    5. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    6. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2021. "Measuring the effectiveness of US monetary policy during the COVID‐19 recession," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 287-297, July.
    7. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    8. Serena Ng, 2021. "Modeling Macroeconomic Variations After COVID-19," Papers 2103.02732, arXiv.org, revised Jul 2021.
    9. Eller, Markus & Hauzenberger, Niko & Huber, Florian & Schuberth, Helene & Vashold, Lukas, 2021. "The impact of macroprudential policies on capital flows in CESEE," Journal of International Money and Finance, Elsevier, vol. 119(C).
    10. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    11. Maximilian Boeck & Massimiliano Marcellino & Michael Pfarrhofer & Tommaso Tornese, 2024. "Predicting Tail-Risks for the Italian Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 339-366, November.
    12. Matteo Iacopini & Aubrey Poon & Luca Rossini & Dan Zhu, 2022. "Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting tail risks of Monthly US GDP," Papers 2209.01910, arXiv.org.
    13. Varga, Katalin & Szendrei, Tibor, 2025. "Non-stationary financial risk factors and macroeconomic vulnerability for the UK," International Review of Financial Analysis, Elsevier, vol. 97(C).
    14. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    15. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    16. Woloszko, Nicolas, 2024. "Nowcasting with panels and alternative data: The OECD weekly tracker," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1302-1335.
    17. Pedro A. Lima & Carlos M. Carvalho & Hedibert F. Lopes & Andrew Herren, 2025. "Minnesota BART," Papers 2503.13759, arXiv.org.
    18. Hwee Kwan Chow & Keen Meng Choy, 2023. "Economic forecasting in a pandemic: some evidence from Singapore," Empirical Economics, Springer, vol. 64(5), pages 2105-2124, May.
    19. Shovon Sengupta & Sunny Kumar Singh & Tanujit Chakraborty, 2025. "Macroeconomic Forecasting for the G7 countries under Uncertainty Shocks," Papers 2510.23347, arXiv.org.
    20. Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
    21. Sofia Velasco, 2025. "Let the Tree Decide: FABART A Non-Parametric Factor Model," Papers 2506.11551, arXiv.org.
    22. Marcellino, Massimiliano & Pfarrhofer, Michael, 2025. "Nonparametric mixed frequency monitoring macro-at-risk," Economics Letters, Elsevier, vol. 255(C).
    23. Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers 2305.16827, arXiv.org.
    24. Florian Huber & Massimiliano Marcellino & Tobias Scheckel, 2023. "Coarsened Bayesian VARs -- Correcting BVARs for Incorrect Specification," Papers 2304.07856, arXiv.org, revised Sep 2025.
    25. Liu, Ying & Wen, Long & Liu, Han & Song, Haiyan, 2024. "Predicting tourism recovery from COVID-19: A time-varying perspective," Economic Modelling, Elsevier, vol. 135(C).
    26. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    27. Niko Hauzenberger Massimiliano Marcellino Michael Pfarrhofer Anna Stelzer, 2026. "Direct Gaussian Process Predictive Regressions with Mixed Frequency Data," BAFFI CAREFIN Working Papers 26265, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    28. Jan Prüser & Florian Huber, 2024. "Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 269-291, March.
    29. Kohns, David & Bhattacharjee, Arnab, 2023. "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1384-1412.
    30. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model," Papers 2110.03411, arXiv.org.
    31. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2022. "Addressing COVID-19 outliers in BVARs with stochastic volatility," Discussion Papers 13/2022, Deutsche Bundesbank.
    32. Paul Ho, 2021. "Forecasting in the Absence of Precedent," Working Paper 21-10, Federal Reserve Bank of Richmond.
    33. Ivan Stankevich, 2025. "Nowcasting and short-term forecasting of G-20 countries GDP with endogenous regime-switching MIDAS models," Empirical Economics, Springer, vol. 69(3), pages 1383-1410, September.
    34. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
    35. Lin, Jiahe & Michailidis, George, 2024. "A multi-task encoder-dual-decoder framework for mixed frequency data prediction," International Journal of Forecasting, Elsevier, vol. 40(3), pages 942-957.
    36. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2022. "Bayesian Modeling of TVP-VARs Using Regression Trees," Papers 2209.11970, arXiv.org, revised May 2023.
    37. Karin Klieber, 2023. "Non-linear dimension reduction in factor-augmented vector autoregressions," Papers 2309.04821, arXiv.org.
    38. Júlio, Paulo & Maria, José R., 2024. "Trends and cycles during the COVID-19 pandemic period," Economic Modelling, Elsevier, vol. 139(C).
    39. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    40. Durand, Luigi & Fornero, Jorge Alberto, 2024. "Estimating the output gap in times of COVID-19," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(4).
    41. Martin Guth, 2022. "Predicting Default Probabilities for Stress Tests: A Comparison of Models," Papers 2202.03110, arXiv.org.
    42. Paponpat Taveeapiradeecharoen & Nattapol Aunsri, 2025. "Forecasting in small open emerging economies Evidence from Thailand," Papers 2509.14805, arXiv.org.
    43. Andrew J. Patton & Yasin Simsek, 2023. "Generalized Autoregressive Score Trees and Forests," Papers 2305.18991, arXiv.org.
    44. Daniel Hopp, 2022. "Performance of long short-term memory artificial neural networks in nowcasting during the COVID-19 crisis," Papers 2203.11872, arXiv.org.
    45. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," Working Papers 21-08R, Federal Reserve Bank of Cleveland, revised 12 Jul 2022.
    46. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    47. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
    48. David Kohns & Galina Potjagailo, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    49. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    50. Kumar, Utkarsh & Ahmad, Wasim, 2024. "Navigating the “twin titans” of global manufacturing: The impact of US and China on industrial production forecasting in G20 nations," Pacific-Basin Finance Journal, Elsevier, vol. 87(C).
    51. Fabrizio Iacone & Luca Rossini & Andrea Viselli, 2024. "Comparing predictive ability in presence of instability over a very short time," Papers 2405.11954, arXiv.org.
    52. Tamás Kiss & Stepan Mazur & Hoang Nguyen & Pär Österholm, 2023. "Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 347-368, March.
    53. Hartwig, Benny, 2022. "Bayesian VARs and prior calibration in times of COVID-19," Discussion Papers 52/2022, Deutsche Bundesbank.
    54. Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2023. "Testing big data in a big crisis: Nowcasting under Covid-19," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1548-1563.
    55. Emilio Blanco & Fiorella Dogliolo & Lorena Garegnani, 2022. "Nowcasting during the Pandemic: Lessons from Argentina," BCRA Working Paper Series 202299, Central Bank of Argentina, Economic Research Department.

  16. Michael Pfarrhofer, 2020. "Forecasts with Bayesian vector autoregressions under real time conditions," Papers 2004.04984, arXiv.org.

    Cited by:

    1. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    2. Chenghan Hou & Bao Nguyen & Bo Zhang, 2023. "Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 418-451, March.
    3. Niko Hauzenberger & Florian Huber & Karin Klieber, 2020. "Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques," Papers 2012.08155, arXiv.org, revised Dec 2021.

  17. Niko Hauzenberger & Michael Pfarrhofer & Anna Stelzer, 2020. "On the effectiveness of the European Central Bank's conventional and unconventional policies under uncertainty," Papers 2011.14424, arXiv.org.

    Cited by:

    1. Laine, Olli-Matti, 2022. "Evidence about the transmission of monetary policy," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number e53, December.
    2. Roben Kloosterman & Dennis Bonam & Koen van der Veer, 2022. "The effects of monetary policy across fiscal regimes," Working Papers 755, DNB.
    3. Andrejs Zlobins, 2022. "Into the Universe of Unconventional Monetary Policy: State-dependence, Interaction and Complementarities," Working Papers 2022/05, Latvijas Banka.
    4. Gabriel Caldas Montes & Igor Mendes Marcelino, 2023. "Uncertainties and disagreements in expectations of professional forecasters: Evidence from an inflation targeting developing country," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 937-956, July.
    5. Andrejs Zlobins, 2021. "On the Time-varying Effects of the ECB's Asset Purchases," Working Papers 2021/02, Latvijas Banka.
    6. Morita, Hiroshi & Yuasa, Shiro, 2022. "Nonlinear Effects of Uncertainty Shocks : State-dependency and Asymmetry," RCESR Discussion Paper Series DP22-6, Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University.
    7. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2023. "Time-varying impacts of monetary policy uncertainty on China's housing market," Economic Modelling, Elsevier, vol. 118(C).

  18. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.

    Cited by:

    1. Hauzenberger, Niko & Pfarrhofer, Michael & Rossini, Luca, 2025. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," International Journal of Forecasting, Elsevier, vol. 41(1), pages 361-376.
    2. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    3. Goulet Coulombe, Philippe, 2025. "Time-varying parameters as ridge regressions," International Journal of Forecasting, Elsevier, vol. 41(3), pages 982-1002.
    4. 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.
    5. Niko Hauzenberger & Florian Huber & Gary Koop, 2020. "Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods," Papers 2005.03906, arXiv.org, revised May 2023.
    6. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    7. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    8. Michael Pfarrhofer, 2020. "Forecasts with Bayesian vector autoregressions under real time conditions," Papers 2004.04984, arXiv.org.

  19. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis," Papers 2001.03935, arXiv.org.

    Cited by:

    1. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    2. Kai Carstensen & Felix Kießner & Thies Rossian, 2024. "Estimation of the TFP Gap for the Largest Five EMU Countries," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(2), pages 243-296, July.
    3. Kai Carstensen & Felix Kießner & Thies Rossian, 2023. "Estimation of the TFP Gap for the Largest Five EMU Countries," CESifo Working Paper Series 10245, CESifo.
    4. Oguzhan Cepni & Hardik A. Marfatia & Rangan Gupta, 2025. "The time-varying impact of uncertainty shocks on the co-movement of regional housing prices of the United Kingdom," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-22, December.
    5. Nataliia Ostapenko, 2022. "Do output gap estimates improve inflation forecasts in Slovakia?," Working and Discussion Papers WP 4/2022, Research Department, National Bank of Slovakia.
    6. Florian Eckert & Nina Mühlebach, 2023. "Global and local components of output gaps," Empirical Economics, Springer, vol. 65(5), pages 2301-2331, November.
    7. Wu, Ping, 2024. "Should I open to forecast? Implications from a multi-country unobserved components model with sparse factor stochastic volatility," International Journal of Forecasting, Elsevier, vol. 40(3), pages 903-917.

  20. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.

    Cited by:

    1. Michael Pfarrhofer & Anna Stelzer, 2019. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Papers 1912.03158, arXiv.org, revised Dec 2024.
    2. Razieh Zahedi & Asghar Shahmoradi & Ali Taiebnia, 2022. "The ever-evolving trade pattern: a global VAR approach," Empirical Economics, Springer, vol. 63(3), pages 1193-1218, September.
    3. Baxa, Jaromír & Šestořád, Tomáš, 2025. "Common and country-specific uncertainty shocks in europe: Why their nature matters for policy," Economic Modelling, Elsevier, vol. 150(C).
    4. Wu, Ping, 2024. "Should I open to forecast? Implications from a multi-country unobserved components model with sparse factor stochastic volatility," International Journal of Forecasting, Elsevier, vol. 40(3), pages 903-917.
    5. Niko Hauzenberger & Michael Pfarrhofer & Anna Stelzer, 2020. "On the effectiveness of the European Central Bank's conventional and unconventional policies under uncertainty," Papers 2011.14424, arXiv.org.

  21. Michael Pfarrhofer & Anna Stelzer, 2019. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Papers 1912.03158, arXiv.org, revised Dec 2024.

    Cited by:

    1. Lukas Berend & Jan Pruser, 2025. "Large structural VARs with multiple linear shock and impact inequality restrictions," Papers 2505.19244, arXiv.org, revised Jul 2025.

  22. Niko Hauzenberger & Michael Pfarrhofer, 2019. "Bayesian state-space modeling for analyzing heterogeneous network effects of US monetary policy," Papers 1911.06206, arXiv.org, revised Sep 2020.

    Cited by:

    1. Yukang Jiang & Xueqin Wang & Zhixi Xiong & Haisheng Yang & Ting Tian, 2022. "Interpreting and predicting the economy flows: A time-varying parameter global vector autoregressive integrated the machine learning model," Papers 2209.05998, arXiv.org.
    2. Piribauer, Philipp & Glocker, Christian & Krisztin, Tamás, 2023. "Beyond distance: The spatial relationships of European regional economic growth," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    3. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2023. "Time-varying impacts of monetary policy uncertainty on China's housing market," Economic Modelling, Elsevier, vol. 118(C).
    4. Niko Hauzenberger & Michael Pfarrhofer & Anna Stelzer, 2020. "On the effectiveness of the European Central Bank's conventional and unconventional policies under uncertainty," Papers 2011.14424, arXiv.org.

  23. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2019. "The regional transmission of uncertainty shocks on income inequality in the United States," Working Papers in Regional Science 2019/01, WU Vienna University of Economics and Business.

    Cited by:

    1. Carl-Christian Groh, 2024. "Big Data and Inequality," CRC TR 224 Discussion Paper Series crctr224_2024_555, University of Bonn and University of Mannheim, Germany.
    2. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    3. Lucia Errico & Andrea Mosca & Sandro Rondinella & Carmela Ciccarelli, 2024. "The Role Of Natural Hazard On Income Inequality," Working Papers 202402, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    4. Xu, Zhiwei & Xue, Jianpo & Zhang, Zhewei, 2025. "Understanding the distributional effects of income uncertainty shocks," China Economic Review, Elsevier, vol. 91(C).
    5. Edmond Berisha & Ram Sewak Dubey & Orkideh Gharehgozli, 2022. "Inflation and income inequality: Does the level of income inequality matter?," Papers 2202.05743, arXiv.org.
    6. Popp, Aaron & Zhang, Fang, 2025. "Divergent effects of aggregate and local uncertainty shocks: Evidence from US metropolitan areas," Economic Modelling, Elsevier, vol. 152(C).
    7. Obiakor, Rowland & Akpa, Emeka & Okwu, Andy, 2022. "Economic Size, Uncertainty, and Income Inequality in Nigeria," MPRA Paper 113637, University Library of Munich, Germany.
    8. Edmond Berisha & John Meszaros & Rangan Gupta, 2021. "Income Inequality and House Prices across US States," Working Papers 202134, University of Pretoria, Department of Economics.
    9. Michael Pfarrhofer & Anna Stelzer, 2019. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Papers 1912.03158, arXiv.org, revised Dec 2024.
    10. Angeliki Theophilopoulou, 2022. "The impact of macroeconomic uncertainty on inequality: An empirical study for the United Kingdom," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(4), pages 859-884, June.
    11. Sangyup Choi & Jeeyeon Phi, 2022. "Impact of Uncertainty Shocks on Income and Wealth Inequality," Working papers 2022rwp-196, Yonsei University, Yonsei Economics Research Institute.
    12. Edmond Berisha & Orkideh Gharehgozli & Rangan Gupta, 2022. "Inflation-Inequality Puzzle: Is it Still Apparent?," Working Papers 202206, University of Pretoria, Department of Economics.

  24. Manfred M. Fischer & Florian Huber & Michael Pfarrhofer, 2018. "The transmission of uncertainty shocks on income inequality: State-level evidence from the United States," Papers 1806.08278, arXiv.org.

    Cited by:

    1. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    2. Michael Pfarrhofer & Anna Stelzer, 2019. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Papers 1912.03158, arXiv.org, revised Dec 2024.
    3. Theophilopoulou, Angeliki, 2018. "The impact of macroeconomic uncertainty on inequality: An empirical study for the UK," MPRA Paper 90448, University Library of Munich, Germany.

  25. Michael Pfarrhofer & Philipp Piribauer, 2018. "Flexible shrinkage in high-dimensional Bayesian spatial autoregressive models," Papers 1805.10822, arXiv.org.

    Cited by:

    1. Tamás Krisztin & Philipp Piribauer, 2021. "A Bayesian spatial autoregressive logit model with an empirical application to European regional FDI flows," Empirical Economics, Springer, vol. 61(1), pages 231-257, July.
    2. Liu, Hongbin & Sun, Zhanli & Luo, Xiaojuan & Dong, Xiuru & Wu, Mengyao, 2020. "A spatial-temporal analysis of the effects of households’ land-use behaviors on soil available potassium in cropland: A case study from urban peripheral region in Northeast China," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 9(5).

  26. Manfred M. Fischer & Florian Huber & Michael Pfarrhofer & Petra Staufer-Steinnocher, 2018. "The dynamic impact of monetary policy on regional housing prices in the US: Evidence based on factor-augmented vector autoregressions," Papers 1802.05870, arXiv.org.

    Cited by:

    1. Gianni La Cava & Calvin He, 2021. "The Distributional Effects of Monetary Policy: Evidence from Local Housing Markets in Australia," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 54(3), pages 387-397, September.
    2. Calvin He & Gianni La Cava, 2020. "The Distributional Effects of Monetary Policy: Evidence from Local Housing Markets," RBA Research Discussion Papers rdp2020-02, Reserve Bank of Australia.

  27. Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2018. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Papers 1805.12217, arXiv.org, revised Jul 2019.

    Cited by:

    1. Luis Gruber & Gregor Kastner & Anirban Bhattacharya & Debdeep Pati & Natesh Pillai & David Dunson, 2025. "A note on simulation methods for the Dirichlet-Laplace prior," Papers 2508.11982, arXiv.org.

  28. Manfred M. Fischer & Florian Huber & Michael Pfarrhofer & Petra Staufer-Steinnocher, 2018. "The dynamic impact of monetary policy on regional housing prices in the United States," Working Papers in Economics 2018-7, University of Salzburg.

    Cited by:

    1. Gianni La Cava & Calvin He, 2021. "The Distributional Effects of Monetary Policy: Evidence from Local Housing Markets in Australia," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 54(3), pages 387-397, September.
    2. Calvin He & Gianni La Cava, 2020. "The Distributional Effects of Monetary Policy: Evidence from Local Housing Markets," RBA Research Discussion Papers rdp2020-02, Reserve Bank of Australia.
    3. Margaris, Aristotelis, 2024. "Monetary policy and house price heterogeneity: Evidence from the U.K," Economics Letters, Elsevier, vol. 244(C).
    4. Egan, Paul & McQuinn, Kieran, 2023. "Monetary tightening in the Euro Area: Implications for residential investment," Papers WP767, Economic and Social Research Institute (ESRI).
    5. Petre Caraiani & Rangan Gupta & Chi Keung Marco Lau & Hardik A. Marfatia, 2019. "Effects of Conventional and Unconventional Monetary Policy Shocks on Housing Prices in the United States: The Role of Sentiment," Working Papers 201953, University of Pretoria, Department of Economics.
    6. Boge, Kevin Patrick & Rieth, Malte & Kholodilin, Konstantin, 2024. "The unequal impacts of monetary policies on regional housing markets," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302370, Verein für Socialpolitik / German Economic Association.
    7. Rangan Gupta & Jun Ma & Konstantinos Theodoridis & Mark E. Wohar, 2020. "Is there a National Housing Market Bubble Brewing in the United States?," Working Papers 202023, University of Pretoria, Department of Economics.
    8. Huang, MeiChi, 2025. "Time-varying impacts of monetary policies on state-level housing markets: Evidence from the Covid-19 period," The Quarterly Review of Economics and Finance, Elsevier, vol. 100(C).
    9. Martin Iseringhausen, 2024. "The housing supply channel of monetary policy," Working Papers 59, European Stability Mechanism, revised 05 Feb 2024.
    10. Adra, Samer & Menassa, Elie, 2022. "The Fed’s dual shocks and the housing market," Economics Letters, Elsevier, vol. 218(C).
    11. Luisa Corrado & Stefano Grassi & Enrico Minnella, 2021. "The Transmission Mechanism of Quantitative Easing: A Markov-Switching FAVAR Approach," CEIS Research Paper 520, Tor Vergata University, CEIS, revised 21 Oct 2021.
    12. Martin Groiss & Nicolas Syrichas, 2025. "Monetary Policy, Property Prices and Rents: Evidence from Local Housing Markets," Berlin School of Economics Discussion Papers 0058, Berlin School of Economics.
    13. Mats Wilhelmsson, 2020. "What Role Does the Housing Market Play for the Macroeconomic Transmission Mechanism?," JRFM, MDPI, vol. 13(6), pages 1-17, June.
    14. Huang, MeiChi, 2024. "A greater crisis? Investigating MSA-level housing markets during the COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 71(C).

  29. Niko Hauzenberger & Maximilian Bock & Michael Pfarrhofer & Anna Stelzer & Gregor Zens, 2018. "Implications of macroeconomic volatility in the Euro area," Papers 1801.02925, arXiv.org, revised Jun 2018.

    Cited by:

    1. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    2. Śmiech, Sławomir & Papież, Monika & Shahzad, Syed Jawad Hussain, 2020. "Spillover among financial, industrial and consumer uncertainties. The case of EU member states," International Review of Financial Analysis, Elsevier, vol. 70(C).
    3. Śmiech, Sławomir & Papież, Monika & Dąbrowski, Marek A., 2019. "How important are different aspects of uncertainty in driving industrial production in the CEE countries?," Research in International Business and Finance, Elsevier, vol. 50(C), pages 252-266.

  30. 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 & Rossini, Luca, 2025. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," International Journal of Forecasting, Elsevier, vol. 41(1), pages 361-376.
    2. 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.
    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. Anna Pajor & Justyna Wróblewska & Łukasz Kwiatkowski & Jacek Osiewalski, 2024. "Hybrid SV‐GARCH, t‐GARCH and Markov‐switching covariance structures in VEC models—Which is better from a predictive perspective?," International Statistical Review, International Statistical Institute, vol. 92(1), pages 62-86, April.

Articles

  1. Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2025. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Empirical Economics, Springer, vol. 68(2), pages 535-553, February.
    See citations under working paper version above.
  2. Pfarrhofer, Michael & Stelzer, Anna, 2025. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Macroeconomic Dynamics, Cambridge University Press, vol. 29, pages 1-1, January.
    See citations under working paper version above.
  3. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    See citations under working paper version above.
  4. Huber, Florian & Onorante, Luca & Pfarrhofer, Michael, 2024. "Forecasting euro area inflation using a huge panel of survey expectations," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1042-1054.
    See citations under working paper version above.
  5. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2024. "Investigating Growth-at-Risk Using a Multicountry Nonparametric Quantile Factor Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(4), pages 1302-1317, October.
    See citations under working paper version above.
  6. Pfarrhofer, Michael, 2023. "Measuring International Uncertainty Using Global Vector Autoregressions with Drifting Parameters," Macroeconomic Dynamics, Cambridge University Press, vol. 27(3), pages 770-793, April.
    See citations under working paper version above.
  7. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2023. "Tail Forecasting With Multivariate Bayesian Additive Regression Trees," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 979-1022, August.
    See citations under working paper version above.
  8. Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2023. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Journal of Econometrics, Elsevier, vol. 232(1), pages 52-69.
    See citations under working paper version above.
  9. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2023. "General Bayesian time‐varying parameter vector autoregressions for modeling government bond yields," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 69-87, January.

    Cited by:

    1. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    2. Hauzenberger Niko & Huber Florian & Koop Gary, 2024. "Dynamic Shrinkage Priors for Large Time-Varying Parameter Regressions Using Scalable Markov Chain Monte Carlo Methods," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 201-225, April.
    3. Nicolas Hardy & Dimitris Korobilis, 2025. "Learning from crises: A new class of time-varying parameter VARs with observable adaptation," Papers 2512.03763, arXiv.org.

  10. Martin Feldkircher & Florian Huber & Gary Koop & Michael Pfarrhofer, 2022. "APPROXIMATE BAYESIAN INFERENCE AND FORECASTING IN HUGE‐DIMENSIONAL MULTICOUNTRY VARs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1625-1658, November.
    See citations under working paper version above.
  11. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    See citations under working paper version above.
  12. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2021. "Measuring the effectiveness of US monetary policy during the COVID‐19 recession," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 287-297, July.
    See citations under working paper version above.
  13. Florian Huber & Michael Pfarrhofer, 2021. "Dynamic shrinkage in time‐varying parameter stochastic volatility in mean models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(2), pages 262-270, March.
    See citations under working paper version above.
  14. 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.
  15. Niko Hauzenberger & Michael Pfarrhofer, 2021. "Bayesian State‐Space Modeling for Analyzing Heterogeneous Network Effects of US Monetary Policy," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(4), pages 1261-1291, October.
    See citations under working paper version above.
  16. Manfred M. Fischer & Florian Huber & Michael Pfarrhofer & Petra Staufer‐Steinnocher, 2021. "The Dynamic Impact of Monetary Policy on Regional Housing Prices in the United States," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 49(4), pages 1039-1068, December.
    See citations under working paper version above.
  17. 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.
    See citations under working paper version above.
  18. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2021. "The regional transmission of uncertainty shocks on income inequality in the United States," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 887-900.
    See citations under working paper version above.
  19. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 911-926, September.
    See citations under working paper version above.

Chapters

  1. Massimiliano Marcellino & Michael Pfarrhofer, 2024. "Bayesian nonparametric methods for macroeconomic forecasting," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 5, pages 90-125, Edward Elgar Publishing.
    See citations under working paper version above.Sorry, no citations of chapters recorded.
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