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Bayesian Vector Autoregressions with Stochastic Volatility

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Cited by:

  1. 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.
  2. 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).
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. Daniel F. Waggoner & Tao Zha, 2000. "A Gibbs simulator for restricted VAR models," FRB Atlanta Working Paper 2000-3, Federal Reserve Bank of Atlanta.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. Moura, Guilherme V. & Noriller, Mateus R., 2019. "Maximum likelihood estimation of a TVP-VAR," Economics Letters, Elsevier, vol. 174(C), pages 78-83.
  23. Jin, Xin & Maheu, John M., 2016. "Bayesian semiparametric modeling of realized covariance matrices," Journal of Econometrics, Elsevier, vol. 192(1), pages 19-39.
  24. 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.
  25. 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.
  26. Zheng Liu & Daniel F. Waggoner & Tao Zha, 2009. "Sources of the Great Moderation: shocks, friction, or monetary policy?," Working Paper Series 2009-01, Federal Reserve Bank of San Francisco.
  27. 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.
  28. Sánchez, Marcelo, 2008. "Oil shocks and endogenous markups: results from an estimated euro area DSGE model," Working Paper Series 860, European Central Bank.
  29. Jungsuk Kim & Mengxi Wang & Donghyun Park & Cynthia Castillejos Petalcorin, 2021. "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(3), pages 555-582, August.
  30. 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.
  31. 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).
  32. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
  33. 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.
  34. 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.
  35. 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.
  36. Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2021. "Large Order-Invariant Bayesian VARs with Stochastic Volatility," Papers 2111.07225, arXiv.org.
  37. Hartwig, Benny, 2020. "Robust inference intime-varying structural VAR models: The DC-Cholesky multivariate stochasticvolatility model," Discussion Papers 34/2020, Deutsche Bundesbank.
  38. 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.
  39. 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.
  40. Legrand, Romain, 2018. "Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean," MPRA Paper 88925, University Library of Munich, Germany.
  41. Alexander Kriwoluzky, 2008. "Matching Theory and Data: Bayesian Vector Autoregression and Dynamic Stochastic General Equilibrium Models," SFB 649 Discussion Papers SFB649DP2008-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  42. 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.
  43. Abel Rodriguez & Enrique ter Horst, 2008. "Measuring expectations in options markets: An application to the SP500 index," Papers 0901.0033, arXiv.org.
  44. Karlsson, Sune & Mazur, Stepan, 2020. "Flexible Fat-tailed Vector Autoregression," Working Papers 2020:5, Örebro University, School of Business.
  45. 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.
  46. 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.
  47. Mark Glickman, 2001. "Dynamic paired comparison models with stochastic variances," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(6), pages 673-689.
  48. 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).
  49. Njindan Iyke, Bernard, 2015. "Assessing the Effects of Housing Market Shocks on Output: The Case of South Africa," MPRA Paper 69610, University Library of Munich, Germany, revised 01 Feb 2016.
  50. Kim, Dukpa, 2014. "Maximum likelihood estimation for vector autoregressions with multivariate stochastic volatility," Economics Letters, Elsevier, vol. 123(3), pages 282-286.
  51. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
  52. 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).
  53. 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.
  54. 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.
  55. 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.
  56. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility using state space models," Papers 0802.0223, arXiv.org.
  57. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
  58. 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.
  59. 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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