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Bayesian Vector Autoregressions with Stochastic Volatility

Citations

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Cited by:

  1. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2007. "Estimating Macroeconomic Models: A Likelihood Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1059-1087.
  2. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
  3. Rodriguez, Abel & Puggioni, Gavino, 2010. "Mixed frequency models: Bayesian approaches to estimation and prediction," International Journal of Forecasting, Elsevier, vol. 26(2), pages 293-311, April.
  4. Marek Jarocinski, 2010. "Responses to monetary policy shocks in the east and the west of Europe: a comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 833-868.
  5. Rozina Shaheen, 2019. "Impact of Fiscal Policy on Consumption and Labor Supply under a Time-Varying Structural VAR Model," Economies, MDPI, vol. 7(2), pages 1-15, June.
  6. Loddo, Antonello & Ni, Shawn & Sun, Dongchu, 2011. "Selection of Multivariate Stochastic Volatility Models via Bayesian Stochastic Search," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 342-355.
  7. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
  8. Punzi, Maria Teresa, 2016. "Financial cycles and co-movements between the real economy, finance and asset price dynamics in large-scale crises," FinMaP-Working Papers 61, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
  9. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
  10. Nasir, Muhammad Ali & Naidoo, Lutchmee & Shahbaz, Muhammad & Amoo, Nii, 2018. "Implications of oil prices shocks for the major emerging economies: A comparative analysis of BRICS," Energy Economics, Elsevier, vol. 76(C), pages 76-88.
  11. Roberto Leon-Gonzalez & Blessings Majoni, 2023. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," GRIPS Discussion Papers 23-07, National Graduate Institute for Policy Studies.
  12. Soyer, Refik & Tanyeri, Kadir, 2006. "Bayesian portfolio selection with multi-variate random variance models," European Journal of Operational Research, Elsevier, vol. 171(3), pages 977-990, June.
  13. Kriwoluzky, Alexander, 2008. "Matching theory and data: Bayesian vector autoregression and dynamic stochastic general equilibrium models," SFB 649 Discussion Papers 2008-060, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  14. Deschamps, Philippe J., 2011. "Bayesian estimation of an extended local scale stochastic volatility model," Journal of Econometrics, Elsevier, vol. 162(2), pages 369-382, June.
  15. Mark Bognanni, 2018. "A Class of Time-Varying Parameter Structural VARs for Inference under Exact or Set Identification," Working Papers (Old Series) 1811, Federal Reserve Bank of Cleveland.
  16. Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
  17. Chen, Yufeng & Yang, Shuo, 2021. "Time-varying effect of international iron ore price on China’s inflation: A complete price chain with TVP-SVAR-SV model," Resources Policy, Elsevier, vol. 73(C).
  18. Chan, Joshua C.C. & Yu, Xuewen, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
  19. Pami Dua, 2023. "Macroeconomic Modelling and Bayesian Methods," Springer Books, in: Pami Dua (ed.), Macroeconometric Methods, chapter 0, pages 19-37, Springer.
  20. Guney, Selin, 2015. "An evaluation of price forecasts of the cattle market under structural changes," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205109, Agricultural and Applied Economics Association.
  21. Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2024. "Large Order-Invariant Bayesian VARs with Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 825-837, April.
  22. Abel Rodriguez & Enrique ter Horst, 2008. "Measuring expectations in options markets: An application to the SP500 index," Papers 0901.0033, arXiv.org.
  23. Minchul Shin & Molin Zhong, 2020. "A New Approach to Identifying the Real Effects of Uncertainty Shocks," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 367-379, April.
  24. Abel Rodr�guez & Enrique ter Horst, 2011. "Measuring expectations in options markets: an application to the S&P500 index," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1393-1405, July.
  25. Njindan Iyke, Bernard, 2016. "Are Monetary Policy Disturbances Important in Ghana? Some Evidence from Agnostic Identification," MPRA Paper 70205, University Library of Munich, Germany.
  26. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility with Bayesian dynamic linear models," Papers 0802.0214, arXiv.org.
  27. Kleppe, Tore Selland & Liesenfeld, Roman & Moura, Guilherme Valle & Oglend, Atle, 2022. "Analyzing Commodity Futures Using Factor State-Space Models with Wishart Stochastic Volatility," Econometrics and Statistics, Elsevier, vol. 23(C), pages 105-127.
  28. K. Triantafyllopoulos, 2011. "Time-varying vector autoregressive models with stochastic volatility," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(2), pages 369-382, September.
  29. Víctor Peña & Kaoru Irie, 2022. "On the Relationship between Uhlig Extended and beta‐Bartlett Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 147-153, January.
  30. Zheng Liu & Daniel F. Waggoner & Tao Zha, 2009. "Sources of the Great Moderation: shocks, frictions, or monetary policy?," FRB Atlanta Working Paper 2009-03, Federal Reserve Bank of Atlanta.
  31. Moura, Guilherme V. & Noriller, Mateus R., 2019. "Maximum likelihood estimation of a TVP-VAR," Economics Letters, Elsevier, vol. 174(C), pages 78-83.
  32. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
  33. Daniel J Lewis, 2021. "Identifying Shocks via Time-Varying Volatility [First Order Autoregressive Processes and Strong Mixing]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(6), pages 3086-3124.
  34. Scott R. Baker & Tucker S. McElroy & Xuguang S. Sheng, 2020. "Expectation Formation Following Large, Unexpected Shocks," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 287-303, May.
  35. Billio, Monica & Casarin, Roberto & Costola, Michele & Iacopini, Matteo, 2024. "COVID-19 spreading in financial networks: A semiparametric matrix regression model," Econometrics and Statistics, Elsevier, vol. 29(C), pages 113-131.
  36. Jin, Xin & Maheu, John M., 2016. "Bayesian semiparametric modeling of realized covariance matrices," Journal of Econometrics, Elsevier, vol. 192(1), pages 19-39.
  37. Karlsson, Sune & Mazur, Stepan, 2020. "Flexible Fat-tailed Vector Autoregression," Working Papers 2020:5, Örebro University, School of Business.
  38. Hartwig, Benny, 2020. "Robust inference intime-varying structural VAR models: The DC-Cholesky multivariate stochasticvolatility model," Discussion Papers 34/2020, Deutsche Bundesbank.
  39. Arratibel, Olga & Michaelis, Henrike, 2013. "The Impact of Monetary Policy and Exchange Rate Shocks in Poland: Evidence from a Time-Varying VAR," Discussion Papers in Economics 21088, University of Munich, Department of Economics.
  40. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
  41. Katz, Harrison & Brusch, Kai Thomas & Weiss, Robert E., 2024. "A Bayesian Dirichlet auto-regressive moving average model for forecasting lead times," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1556-1567.
  42. Farmer, Roger E.A. & Waggoner, Daniel F. & Zha, Tao, 2011. "Minimal state variable solutions to Markov-switching rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 2150-2166.
  43. Hwang, Youngjin, 2025. "Information content in yield curve dynamics: Implications for monetary policy," Journal of Macroeconomics, Elsevier, vol. 83(C).
  44. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
  45. NAKAJIMA, Jouchi, 2025. "Time-varying Local Projections with Stochastic Volatility," Discussion Paper Series 761, Institute of Economic Research, Hitotsubashi University.
  46. Uhlig, H.F.H.V.S., 1999. "What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure," Other publications TiSEM 2e0fa8dd-ead5-4c6b-97cb-1, Tilburg University, School of Economics and Management.
  47. Juan F. Rubio-Ramirez & Daniel F. Waggoner & Tao Zha, 2005. "Markov-switching structural vector autoregressions: theory and application," FRB Atlanta Working Paper 2005-27, Federal Reserve Bank of Atlanta.
  48. K. Triantafyllopoulos, 2007. "Covariance estimation for multivariate conditionally Gaussian dynamic linear models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(8), pages 551-569.
  49. Charles Bos & Neil Shephard, 2006. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 219-244.
  50. William W. Chow, 2004. "An outlier robust hierarchical Bayes model for forecasting: the case of Hong Kong," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 99-114.
  51. Almeida, Thiago Ramos, 2024. "Estimating time-varying factors’ variance in the string-term structure model with stochastic volatility," Research in International Business and Finance, Elsevier, vol. 70(PA).
  52. Joshua Chan & Eric Eisenstat & Xuewen Yu, 2022. "Large Bayesian VARs with Factor Stochastic Volatility: Identification, Order Invariance and Structural Analysis," Papers 2207.03988, arXiv.org.
  53. 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.
  54. Kang, Sang Hoon & Islam, Faridul & Kumar Tiwari, Aviral, 2019. "The dynamic relationships among CO2 emissions, renewable and non-renewable energy sources, and economic growth in India: Evidence from time-varying Bayesian VAR model," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 90-101.
  55. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2023. "Vector autoregression models with skewness and heavy tails," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
  56. Dahem, Ahlem & Skander, Slim & Fatma, Siala Guermazi, 2017. "Time Varying VAR Analysis for Disaggregated Exchange Rate Pass-through in Tunisia," MPRA Paper 79759, University Library of Munich, Germany, revised 2017.
  57. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pintér, Gábor, 2017. "Forecasting with VAR models: Fat tails and stochastic volatility," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1124-1143.
  58. Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023. "Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
  59. Korobilis, D & Yilmaz, K, 2018. "Measuring Dynamic Connectedness with Large Bayesian VAR Models," Essex Finance Centre Working Papers 20937, University of Essex, Essex Business School.
  60. Tevfik Aktekin & Nicholas G. Polson & Refik Soyer, 2020. "A family of multivariate non‐gaussian time series models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 691-721, September.
  61. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
  62. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility using state space models," Papers 0802.0223, arXiv.org.
  63. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
  64. Mark Bognanni & Edward P. Herbst, 2014. "Estimating (Markov-Switching) VAR Models without Gibbs Sampling: A Sequential Monte Carlo Approach," Working Papers (Old Series) 1427, Federal Reserve Bank of Cleveland.
  65. H. F. Lopes & R. E. McCulloch & R. S. Tsay, 2014. "Parsimony Inducing Priors for Large Scale State-Space Models," Business and Economics Working Papers 205, Unidade de Negocios e Economia, Insper.
  66. Sánchez, Marcelo, 2008. "Oil shocks and endogenous markups: results from an estimated euro area DSGE model," Working Paper Series 860, European Central Bank.
  67. Mark Glickman, 2001. "Dynamic paired comparison models with stochastic variances," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(6), pages 673-689.
  68. K. Triantafyllopoulos, 2012. "Multi‐variate stochastic volatility modelling using Wishart autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(1), pages 48-60, January.
  69. Deschamps, Philippe J., 2011. "Bayesian estimation of an extended local scale stochastic volatility model," Journal of Econometrics, Elsevier, vol. 162(2), pages 369-382, June.
  70. Jungsuk Kim & Mengxi Wang & Donghyun Park & Cynthia Castillejos Petalcorin, 2021. "Correction to: Fiscal policy and economic growth: some evidence from China," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 157(4), pages 1003-1004, November.
  71. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2008. "How Structural Are Structural Parameters?," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 83-137, National Bureau of Economic Research, Inc.
  72. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
  73. Mayer, Walter J. & Dorsey, Robert E., 1998. "Maximum score estimation of disequilibrium models and the role of anticipatory price-setting," Journal of Econometrics, Elsevier, vol. 87(1), pages 1-24, August.
  74. Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).
  75. Moura, Guilherme V. & Santos, André A.P. & Ruiz, Esther, 2020. "Comparing high-dimensional conditional covariance matrices: Implications for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 118(C).
  76. Daniel F. Waggoner & Tao Zha, 2000. "A Gibbs simulator for restricted VAR models," FRB Atlanta Working Paper 2000-3, Federal Reserve Bank of Atlanta.
  77. Vasyl Golosnoy & Jens Hogrefe, 2013. "Signaling NBER turning points: a sequential approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 438-448, February.
  78. Lopes, Hedibert F. & McCulloch, Robert E. & Tsay, Ruey S., 2022. "Parsimony inducing priors for large scale state–space models," Journal of Econometrics, Elsevier, vol. 230(1), pages 39-61.
  79. Xinyu Huang & Weihao Han & David Newton & Emmanouil Platanakis & Dimitrios Stafylas & Charles Sutcliffe, 2023. "The diversification benefits of cryptocurrency asset categories and estimation risk: pre and post Covid-19," The European Journal of Finance, Taylor & Francis Journals, vol. 29(7), pages 800-825, May.
  80. repec:hum:wpaper:sfb649dp2008-060 is not listed on IDEAS
  81. Legrand, Romain, 2018. "Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean," MPRA Paper 88925, University Library of Munich, Germany.
  82. Marcelo Sánchez, 2011. "Oil shocks and endogenous markups: results from an estimated euro area DSGE model," International Economics and Economic Policy, Springer, vol. 8(3), pages 247-273, September.
  83. Charles Bos & Neil Shephard, 2006. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 219-244.
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