Forecasting with Medium and Large Bayesian VARs

Citations

Cited by:

1. Fuentes-Albero, Cristina & Melosi, Leonardo, 2013. "Methods for computing marginal data densities from the Gibbs output," Journal of Econometrics, Elsevier, vol. 175(2), pages 132-141.
   • Cristina Fuentes-Albero & Leonardo Melosi, 2011. "Methods for Computing Marginal Data Densities from the Gibbs Output," Departmental Working Papers 201131, Rutgers University, Department of Economics.
2. Koop, Gary & Korobilis, Dimitris, 2016. "Model uncertainty in Panel Vector Autoregressive models," European Economic Review, Elsevier, vol. 81(C), pages 115-131.
   • Gary Koop & Dimitris Korobilis, 2014. "Model Uncertainty in Panel Vector Autoregressive Models," Working Paper series 39_14, Rimini Centre for Economic Analysis.
   • Gary Koop & Dimitris Korobilis, 2015. "Model Uncertainty in Panel Vector Autoregressive Models," Working Paper series 15-35, Rimini Centre for Economic Analysis.
   • Koop, Gary & Korobilis, Dimitris, 2014. "Model Uncertainty in Panel Vector Autoregressive Models," MPRA Paper 58131, University Library of Munich, Germany.
   • Gary Koop & Dimitris Korobilis, 2014. "Model uncertainty in panel vector autoregressive models," Working Papers 1408, University of Strathclyde Business School, Department of Economics.
   • Koop, Gary & Korobilis, Dimitris, 2014. "Model Uncertainty in Panel Vector Autoregressive Models," SIRE Discussion Papers 2014-011, Scottish Institute for Research in Economics (SIRE).
   • Gary Koop & Dimitris Korobilis, 2014. "Model uncertainty in panel vector autoregressive models," Working Papers 2014_10, Business School - Economics, University of Glasgow.
3. Eva F. Janssens & Robin L. Lumsdaine, 2024. "Sectoral slowdowns in the United Kingdom: Evidence from transmission probabilities and economic linkages," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 22-40, January.
4. Grant, Angelia L. & Chan, Joshua C.C., 2017. "Reconciling output gaps: Unobserved components model and Hodrick–Prescott filter," Journal of Economic Dynamics and Control, Elsevier, vol. 75(C), pages 114-121.
   • Joshua C.C. Chan & Angelia L. Grant, 2016. "Reconciling output gaps: unobserved components model and Hodrick-Prescott filter," CAMA Working Papers 2016-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
5. Kyriakos Drivas & Claire Economidou & Konstantinos N. Konstantakis & Panayotis G. Michaelides, 2022. "Technological Leaders, Laggards and Spillovers: A Network GVAR Analysis," Open Economies Review, Springer, vol. 33(2), pages 231-269, April.
6. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2016. "Does joint modelling of the world economy pay off? Evaluating global forecasts from a Bayesian GVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 86-100.
   • Dovern, Jonas & Feldkircher, Martin & Huber , Florian, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 0590, University of Heidelberg, Department of Economics.
   • Jonas Dovern & Martin Feldkircher & Florian Huber, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 200, Oesterreichische Nationalbank (Austrian Central Bank).
7. Anastasios Evgenidis & Stephanos Papadamou, 2021. "The impact of unconventional monetary policy in the euro area. Structural and scenario analysis from a Bayesian VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5684-5703, October.
8. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
9. Florian Huber & Gary Koop, 2023. "Subspace shrinkage in conjugate Bayesian vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 556-576, June.
   • Florian Huber & Gary Koop, 2021. "Subspace Shrinkage in Conjugate Bayesian Vector Autoregressions," Papers 2107.07804, arXiv.org.
10. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
11. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
12. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2020. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 934-943, September.
    • Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," CAMA Working Papers 2019-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
13. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1403-1417, September.
    • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," Working Papers 21-02R, Federal Reserve Bank of Cleveland, revised 09 Aug 2021.
    • 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.
    • Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea & Mertens, Elmar, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," CEPR Discussion Papers 15964, C.E.P.R. Discussion Papers.
14. Kenneth Beauchemin & Saeed Zaman, 2011. "A medium scale forecasting model for monetary policy," Working Papers (Old Series) 1128, Federal Reserve Bank of Cleveland.
15. James Morley & Benjamin Wong, 2020. "Estimating and accounting for the output gap with large Bayesian vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 1-18, January.
    • James Morley & Benjamin Wong, 2017. "Estimating and accounting for the output gap with large Bayesian vector autoregressions," CAMA Working Papers 2017-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Morley, James & Wong, Benjamin, 2018. "Estimating and Accounting for the Output Gap with Large Bayesian Vector Autoregressions," Working Papers 2018-04, University of Sydney, School of Economics, revised Feb 2019.
16. Kamber, Güneş & Theodoridis, Konstantinos & Thoenissen, Christoph, 2017. "News-driven business cycles in small open economies," Journal of International Economics, Elsevier, vol. 105(C), pages 77-89.
    • Güneş Kamber & Konstantinos Theodoridis & Christoph Thoenissen, 2014. "News-Driven Business Cycles in Small Open Economies," Working Papers 2014017, The University of Sheffield, Department of Economics.
    • Gunes Kamber & Konstantinos Theodoridis & Christoph Thoenissen, 2014. "News-driven business cycles in small open economies," CAMA Working Papers 2014-02, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
17. Kuo‐Hsuan Chin, 2022. "Forecast evaluation of DSGE models: Linear and nonlinear likelihood," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1099-1130, September.
18. Igan, Deniz & Kabundi, Alain & De Simone, Francisco Nadal & Tamirisa, Natalia, 2017. "Monetary policy and balance sheets," Journal of Policy Modeling, Elsevier, vol. 39(1), pages 169-184.
    • Ms. Deniz O Igan & Alain N. Kabundi & Mr. Francisco d Nadal De Simone & Ms. Natalia T. Tamirisa, 2013. "Monetary Policy and Balance Sheets," IMF Working Papers 2013/158, International Monetary Fund.
    • Alain Kabundi & Deniz Igan & Francisco N. de Simone & Natalia Tamirisa, 2013. "Monetary Policy and Balance Sheets," Working Papers 364, Economic Research Southern Africa.
19. Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019. "Bayesian nonparametric sparse VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
    • Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse VAR models," Papers 1608.02740, arXiv.org, revised Oct 2018.
20. Демешев Борис Борисович & Малаховская Оксана Анатольевна, 2016. "Макроэкономическое Прогнозирование С Помощью Bvar Литтермана," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 20(4), pages 691-710.
21. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
22. Louzis Dimitrios P., 2016. "Steady-state priors and Bayesian variable selection in VAR forecasting," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(5), pages 495-527, December.
    • Dimitrios P. Louzis, 2015. "Steady-state priors and Bayesian variable selection in VAR forecasting," Working Papers 195, Bank of Greece.
23. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    • Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
    • Tim Oliver Berg & Steffen Henzel, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," ifo Working Paper Series 155, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    • Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
24. Chan, Joshua C.C., 2023. "Comparing stochastic volatility specifications for large Bayesian VARs," Journal of Econometrics, Elsevier, vol. 235(2), pages 1419-1446.
    • Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
25. 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).
    • Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
26. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic forecast accuracy in a data‐rich environment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1050-1072, November.
    • Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
27. Auer, Simone, 2019. "Monetary policy shocks and foreign investment income: Evidence from a large Bayesian VAR," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 142-166.
    • Dr. Simone Auer, 2014. "Monetary Policy Shocks and Foreign Investment Income: Evidence from a large Bayesian VAR," Working Papers 2014-02, Swiss National Bank.
    • Simone Auer, 2014. "Monetary policy shocks and foreign investment income: evidence from a large Bayesian VAR," Globalization Institute Working Papers 170, Federal Reserve Bank of Dallas.
28. Nicoletta Pashourtidou & Christos Papamichael & Charalampos Karagiannakis, 2018. "Forecasting economic activity in sectors of the Cypriot economy," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 12(2), pages 24-66, December.
29. Tallman, Ellis W. & Zaman, Saeed, 2020. "Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy," International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
    • Ellis W. Tallman & Saeed Zaman, 2018. "Combining Survey Long-Run Forecasts and Nowcasts with BVAR Forecasts Using Relative Entropy," Working Papers (Old Series) 1809, Federal Reserve Bank of Cleveland.
30. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
31. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using hierarchical aggregation constraints to nowcast regional economic aggregates," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-04, Economic Statistics Centre of Excellence (ESCoE).
32. Emmanuel Mamatzakis & Mike G. Tsionas, 2021. "Testing for persistence in US mutual funds’ performance: a Bayesian dynamic panel model," Annals of Operations Research, Springer, vol. 299(1), pages 1203-1233, April.
33. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2016. "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1371-1391, November.
34. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    • Giannone, Domenico & Bańbura, Marta & Lenza, Michele, 2014. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," Working Paper Series 1733, European Central Bank.
    • Giannone, Domenico & Banbura, Marta & Lenza, Michele, 2014. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," CEPR Discussion Papers 9931, C.E.P.R. Discussion Papers.
    • Martha Banbura & Domenico Giannone & Michèle Lenza, 2014. "Conditional Forecasts and Scenario Analysis with Vector Autoregressions for Large Cross-Sections," Working Papers ECARES ECARES 2014-15, ULB -- Universite Libre de Bruxelles.
35. Gianluca Cubadda & Marco Mazzali, 2024. "The vector error correction index model: representation, estimation and identification," The Econometrics Journal, Royal Economic Society, vol. 27(1), pages 126-150.
    • Gianluca Cubadda & Marco Mazzali, 2023. "The Vector Error Correction Index Model: Representation, Estimation and Identification," CEIS Research Paper 556, Tor Vergata University, CEIS, revised 04 Apr 2023.
36. Verbrugge, Randal & Zaman, Saeed, 2024. "Improving inflation forecasts using robust measures," International Journal of Forecasting, Elsevier, vol. 40(2), pages 735-745.
    • Randal J. Verbrugge & Saeed Zaman, 2022. "Improving Inflation Forecasts Using Robust Measures," Working Papers 22-23R, Federal Reserve Bank of Cleveland, revised 30 May 2023.
37. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
38. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.
    • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 2016_09, Business School - Economics, University of Glasgow.
    • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103R, Brandeis University, Department of Economics and International Business School, revised Apr 2016.
    • Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2017. "Bayesian Compressed Vector Autoregressions," Working Paper series 17-32, Rimini Centre for Economic Analysis.
39. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
40. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 791-897, Elsevier.
    • Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
41. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2021. "No‐arbitrage priors, drifting volatilities, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 495-516, August.
    • Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," Working Papers 20-27, Federal Reserve Bank of Cleveland.
42. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-07, Economic Statistics Centre of Excellence (ESCoE).
    • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Discussion Papers in Economics 19/05, Division of Economics, School of Business, University of Leicester.
43. Rubio-Ramírez, Juan Francisco & Petrella, Ivan & Antolin-Diaz, Juan, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," CEPR Discussion Papers 16613, C.E.P.R. Discussion Papers.
    • Juan Antolin-Diaz & Ivan Petrella & Juan F. Rubio-Ramirez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," FRB Atlanta Working Paper 2021-25, Federal Reserve Bank of Atlanta.
    • Juan Antolín-Díaz & Ivan Petrella & Juan F. Rubio-Ramírez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," Working Papers 2021-14, FEDEA.
44. Panagiotelis, Anastasios & Athanasopoulos, George & Hyndman, Rob J. & Jiang, Bin & Vahid, Farshid, 2019. "Macroeconomic forecasting for Australia using a large number of predictors," International Journal of Forecasting, Elsevier, vol. 35(2), pages 616-633.
    • Bin Jiang & George Athanasopoulos & Rob J Hyndman & Anastasios Panagiotelis & Farshid Vahid, 2017. "Macroeconomic forecasting for Australia using a large number of predictors," Monash Econometrics and Business Statistics Working Papers 2/17, Monash University, Department of Econometrics and Business Statistics.
45. Berger, Tino & Richter, Julia & Wong, Benjamin, 2022. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    • Tino Berger & Julia Richter & Benjamin Wong, 2020. "Financial factors and the business cycle," CAMA Working Papers 2020-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Berger, Tino & Richter, Julia & Wong, Benjamin, 2021. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," University of Göttingen Working Papers in Economics 415, University of Goettingen, Department of Economics.
    • Tino Berger & Julia Richter & Benjamin Wong, 2021. "A Unified Approach for Jointly Estimating the Business and Financial Cycle, and the Role of Financial Factors," Monash Econometrics and Business Statistics Working Papers 4/21, Monash University, Department of Econometrics and Business Statistics.
    • Berger, Tino & Richter, Julia & Wong, Benjamin, 2021. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," Working Papers 02/2021, German Council of Economic Experts / Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung.
46. Churm, Rohan & Joyce, Mike & Kapetanios, George & Theodoridis, Konstantinos, 2015. "Unconventional monetary policies and the macroeconomy: the impact of the United Kingdom's QE2 and Funding for Lending Scheme," Bank of England working papers 542, Bank of England.
47. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
48. Heather Anderson & Giovanni Caggiano & Farshid Vahid & Benjamin Wong, 2020. "Sectoral Employment Dynamics in Australia," Monash Econometrics and Business Statistics Working Papers 20/20, Monash University, Department of Econometrics and Business Statistics.
    • Heather Anderson & Giovanni Caggiano & Farshid Vahid & Benjamin Wong, 2020. "Sectoral employment dynamics in Australia," CAMA Working Papers 2020-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
49. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2018. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-14, Economic Statistics Centre of Excellence (ESCoE).
    • Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
50. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2016. "Structural analysis with Multivariate Autoregressive Index models," Journal of Econometrics, Elsevier, vol. 192(2), pages 332-348.
    • Marcellino, Massimiliano & Kapetanios, George & Carriero, Andrea, 2015. "Structural Analysis with Multivariate Autoregressive Index Models," CEPR Discussion Papers 10801, C.E.P.R. Discussion Papers.
51. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
52. Marco Centoni & Gianluca Cubadda, 2015. "Common Feature Analysis of Economic Time Series: An Overview and Recent Developments," CEIS Research Paper 355, Tor Vergata University, CEIS, revised 05 Oct 2015.
53. Malte Knuppel & Fabian Kruger & Marc-Oliver Pohle, 2022. "Score-based calibration testing for multivariate forecast distributions," Papers 2211.16362, arXiv.org, revised Dec 2023.
    • Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
54. Knotek, Edward S. & Zaman, Saeed, 2019. "Financial nowcasts and their usefulness in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1708-1724.
    • Edward S. Knotek & Saeed Zaman, 2017. "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series) 1702, Federal Reserve Bank of Cleveland.
55. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "How Sensitive Are VAR Forecasts to Prior Hyperparameters? An Automated Sensitivity Analysis," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 229-248, Emerald Group Publishing Limited.
    • Joshua C.C. Chan & Liana Jacobi & Dan Zhu, 2018. "How sensitive are VAR forecasts to prior hyperparameters? An automated sensitivity analysis," CAMA Working Papers 2018-25, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
56. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Large Vector Autoregressions with Asymmetric Priors," Working Papers 759, Queen Mary University of London, School of Economics and Finance.
    • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Large Vector Autoregressions with Asymmetric Priors," Working Papers 759, Queen Mary University of London, School of Economics and Finance.
57. Chan, Joshua C.C. & Eisenstat, Eric & Koop, Gary, 2016. "Large Bayesian VARMAs," Journal of Econometrics, Elsevier, vol. 192(2), pages 374-390.
    • Joshua C C Chan & Eric Eisenstat & Gary Koop, 2014. "Large Bayesian VARMAs," Working Papers 1409, University of Strathclyde Business School, Department of Economics.
    • Joshua Chan & Eric Eisenstat & Gary Koop, 2015. "Large Bayesian VARMAs," Working Paper series 15-36, Rimini Centre for Economic Analysis.
    • Chan, Joshua C.C. & Eisenstat, Eric & Koop, Gary, 2014. "Large Bayesian VARMAs," SIRE Discussion Papers 2015-06, Scottish Institute for Research in Economics (SIRE).
    • Joshua C.C. Chan & Eric Eisenstat & Gary Koop, 2014. "Large Bayesian VARMAs," Working Paper series 40_14, Rimini Centre for Economic Analysis.
58. Konstantakis, Konstantinos N. & Soklis, George & Michaelides, Panayotis G., 2017. "Tourism expenditures and crisis transmission: A general equilibrium GVAR analysis with network theory," Annals of Tourism Research, Elsevier, vol. 66(C), pages 74-94.
    • Konstantakis, Konstantinos N. & Soklis, George & Michaelides, Panayotis G., 2017. "Tourism expenditures and crisis transmission: a general equilibrium GVAR analysis with network theory," LSE Research Online Documents on Economics 83531, London School of Economics and Political Science, LSE Library.
59. Juan Solorzano-Margain & Serafin Martinez-Jaramillo & Fabrizio Lopez-Gallo, 2013. "Financial contagion: extending the exposures network of the Mexican financial system," Computational Management Science, Springer, vol. 10(2), pages 125-155, June.
60. Petrova, Katerina, 2022. "Asymptotically valid Bayesian inference in the presence of distributional misspecification in VAR models," Journal of Econometrics, Elsevier, vol. 230(1), pages 154-182.
61. Koop, Gary & Korobilis, Dimitris, 2013. "Large time-varying parameter VARs," Journal of Econometrics, Elsevier, vol. 177(2), pages 185-198.
    • Koop, Gary & Korobilis, Dimitris, 2012. "Large time-varying parameter VARs," MPRA Paper 38591, University Library of Munich, Germany.
    • Koop, Gary & Korobilis, Dimitris, 2012. "Large Time-Varying Parameter VARs," SIRE Discussion Papers 2012-14, Scottish Institute for Research in Economics (SIRE).
    • Gary Koop & Dimitris Korobilis, 2012. "Large Time-Varying Parameter VARs," Working Paper series 11_12, Rimini Centre for Economic Analysis.
    • Gary Koop & Dimitris Korobilis, 2012. "Large time-varying parameter VARs," Working Papers 2012_04, Business School - Economics, University of Glasgow.
62. Mr. Jorge A Chan-Lau, 2017. "Variance Decomposition Networks: Potential Pitfalls and a Simple Solution," IMF Working Papers 2017/107, International Monetary Fund.
63. Kaabia, Olfa & Abid, Ilyes & Guesmi, Khaled, 2013. "Does Bayesian shrinkage help to better reflect what happened during the subprime crisis?," Economic Modelling, Elsevier, vol. 31(C), pages 423-432.
    • Olfa Kaabia & Ilyes Abid & Khaled Guesmi, 2012. "Does Bayesian Shrinkage Help to Better Reflect What Happened during the Subprime Crisis?," EconomiX Working Papers 2012-46, University of Paris Nanterre, EconomiX.
    • Ilyes Abid & Khaled Guesmi & Olfa Kaabia, 2013. "Does Bayesian Shrinkage Help to Better Reflect What Happened During the Subprime Crisis?," Post-Print hal-01410575, HAL.
    • Ilyes Abid & Khaled Guesmi & Olfa Kaabia, 2012. "Does Bayesian Shrinkage Help to Better Reflect What Happened During the Subprime Crisis?," Post-Print hal-01410674, HAL.
64. Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
    • Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
65. Tomasz Wozniak, 2016. "Rare Events and Risk Perception: Evidence from Fukushima Accident," Department of Economics - Working Papers Series 2021, The University of Melbourne.
66. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
67. repec:hum:wpaper:sfb649dp2014-004 is not listed on IDEAS
68. Gary Koop, 2012. "Using VARs and TVP-VARs with Many Macroeconomic Variables," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(3), pages 143-167, September.
    • Gary Koop, 2013. "Using VARs and TVP-VARs with Many Macroeconomic Variables," Working Papers 1303, University of Strathclyde Business School, Department of Economics.
    • Gary, Koop, 2013. "Using VARs and TVP-VARs with Many Macroeconomic Variables," SIRE Discussion Papers 2013-35, Scottish Institute for Research in Economics (SIRE).
69. Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
70. Korobilis, Dimitris, 2016. "Prior selection for panel vector autoregressions," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 110-120.
    • Korobilis, Dimitris, 2015. "Prior selection for panel vector autoregressions," SIRE Discussion Papers 2015-73, Scottish Institute for Research in Economics (SIRE).
    • Dimitris Korobilis., 2015. "Prior selection for panel vector autoregressions," Working Papers 2015_10, Business School - Economics, University of Glasgow.
    • Korobilis, Dimitris, 2015. "Prior selection for panel vector autoregressions," MPRA Paper 64143, University Library of Munich, Germany.
71. Niko Hauzenberger & Florian Huber & Luca Onorante, 2021. "Combining shrinkage and sparsity in conjugate vector autoregressive models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 304-327, April.
    • Niko Hauzenberger & Florian Huber & Luca Onorante, 2020. "Combining Shrinkage and Sparsity in Conjugate Vector Autoregressive Models," Papers 2002.08760, arXiv.org, revised Aug 2020.
72. Chan, Joshua C.C., 2021. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1212-1226.
    • Joshua C. C. Chan, 2019. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," CAMA Working Papers 2019-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
73. Antonio Pacifico, 2021. "Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," Econometrics, MDPI, vol. 9(2), pages 1-35, May.
74. Schnücker, Annika, 2016. "Restrictions Search for Panel VARs," VfS Annual Conference 2016 (Augsburg): Demographic Change 145566, Verein für Socialpolitik / German Economic Association.
75. Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.
76. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
77. Michael W. McCracken & Joseph T. McGillicuddy, 2019. "An empirical investigation of direct and iterated multistep conditional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 181-204, March.
    • Michael W. McCracken & Joseph McGillicuddy, 2017. "An Empirical Investigation of Direct and Iterated Multistep Conditional Forecasts," Working Papers 2017-40, Federal Reserve Bank of St. Louis.
78. Raputsoane, Leroi, 2018. "Targeting financial stress as opposed to the exchange rate," MPRA Paper 84865, University Library of Munich, Germany.
79. Berg Tim Oliver, 2017. "Forecast accuracy of a BVAR under alternative specifications of the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(2), pages 1-29, April.
    • Tim Oliver Berg, 2015. "Forecast Accuracy of a BVAR under Alternative Specifications of the Zero Lower Bound," ifo Working Paper Series 203, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
80. Morley, James & Rodríguez-Palenzuela, Diego & Sun, Yiqiao & Wong, Benjamin, 2023. "Estimating the euro area output gap using multivariate information and addressing the COVID-19 pandemic," European Economic Review, Elsevier, vol. 153(C).
    • Morley, James & Palenzuela, Diego Rodriguez & Sun, Yiqiao & Wong, Benjamin, 2022. "Estimating the Euro Area output gap using multivariate information and addressing the COVID-19 pandemic," Working Paper Series 2716, European Central Bank.
81. Barbara Rossi, 2019. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
    • Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    • Rossi, Barbara, 2020. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," CEPR Discussion Papers 14472, C.E.P.R. Discussion Papers.
82. 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.
    • 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.
    • 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.
83. Jean Boivin & Marc P. Giannoni & Dalibor Stevanović, 2020. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 272-284, April.
    • Jean Boivin & Marc Giannoni & Dalibor Stevanovic, 2013. "Dynamic effects of credit shocks in a data-rich environment," Staff Reports 615, Federal Reserve Bank of New York.
    • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2016. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2016s-55, CIRANO.
    • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2013s-11, CIRANO.
    • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Cahiers de recherche 1324, CIRPEE.
    • Giannoni, Marc & Boivin, Jean & Stevanovic, Dalibor, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CEPR Discussion Papers 9470, C.E.P.R. Discussion Papers.
84. Tim Oliver Berg, 2016. "Multivariate Forecasting with BVARs and DSGE Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(8), pages 718-740, December.
    • Berg, Tim Oliver, 2015. "Multivariate Forecasting with BVARs and DSGE Models," MPRA Paper 62405, University Library of Munich, Germany.
85. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
86. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2022. "The global component of inflation volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 700-721, June.
    • Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2018. "The global component of inflation volatility," Temi di discussione (Economic working papers) 1170, Bank of Italy, Economic Research and International Relations Area.
    • Marcellino, Massimiliano & Carriero, Andrea & Corsello, Francesco, 2019. "The Global Component of Inflation Volatility," CEPR Discussion Papers 13470, C.E.P.R. Discussion Papers.
87. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
    • Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
    • Giannone, Domenico & Reichlin, Lucrezia & Bańbura, Marta & Modugno, Michele, 2013. "Now-casting and the real-time data flow," Working Paper Series 1564, European Central Bank.
    • Martha Banbura & Domenico Giannone & Michèle Modugno & Lucrezia Reichlin, 2012. "Now-Casting and the Real-Time Data Flow," Working Papers ECARES ECARES 2012-026, ULB -- Universite Libre de Bruxelles.
88. G. Cubadda & S. Grassi & B. Guardabascio, 2022. "The Time-Varying Multivariate Autoregressive Index Model," Papers 2201.07069, arXiv.org.
    • Gianluca Cubadda & Stefano Grassi & Barbara Guardabascio, 2024. "The Time-Varying Multivariate Autoregressive Index Model," CEIS Research Paper 571, Tor Vergata University, CEIS, revised 10 Jan 2024.
89. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
90. Joshua C.C. Chan & Eric Eisenstat, 2015. "Efficient estimation of Bayesian VARMAs with time-varying coefficients," CAMA Working Papers 2015-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
91. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers 2014-25, Federal Reserve Bank of St. Louis.
    • Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers (Old Series) 1413, Federal Reserve Bank of Cleveland.
92. Andrejs Bessonovs, 2015. "Suite of Latvia's GDP forecasting models," Working Papers 2015/01, Latvijas Banka.
93. Knotek, Edward S. & Zaman, Saeed, 2021. "Asymmetric responses of consumer spending to energy prices: A threshold VAR approach," Energy Economics, Elsevier, vol. 95(C).
    • Edward S. Knotek & Saeed Zaman, 2020. "Asymmetric Responses of Consumer Spending to Energy Prices: A Threshold VAR Approach," Working Papers 20-17, Federal Reserve Bank of Cleveland.
94. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    • Kashif Yousuf & Serena Ng, 2019. "Boosting High Dimensional Predictive Regressions with Time Varying Parameters," Papers 1910.03109, arXiv.org.
95. Didier Nibbering & Richard Paap & Michel van der Wel, 2016. "A Bayesian Infinite Hidden Markov Vector Autoregressive Model," Tinbergen Institute Discussion Papers 16-107/III, Tinbergen Institute, revised 13 Oct 2017.
96. Kyle E. Binder & Mohsen Pourahmadi & James W. Mjelde, 2020. "The role of temporal dependence in factor selection and forecasting oil prices," Empirical Economics, Springer, vol. 58(3), pages 1185-1223, March.
97. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Bayesian VARs: Specification Choices and Forecast Accuracy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 46-73, January.
    • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2011. "Bayesian VARs: specification choices and forecast accuracy," Working Papers (Old Series) 1112, Federal Reserve Bank of Cleveland.
    • Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2011. "Bayesian VARs: Specification Choices and Forecast Accuracy," CEPR Discussion Papers 8273, C.E.P.R. Discussion Papers.
98. Stefański, Maciej, 2022. "Macroeconomic effects and transmission channels of quantitative easing," Economic Modelling, Elsevier, vol. 114(C).
99. Konstantakis, Konstantinos & Michaelides, Panayotis G., 2014. "Combining Input-Output (IO) analysis with Global Vector Autoregressive (GVAR) modeling: Evidence for the USA (1992-2006)," MPRA Paper 67111, University Library of Munich, Germany.
100. Eric Eisenstat & Joshua C. C. Chan & Rodney W. Strachan, 2016. "Stochastic Model Specification Search for Time-Varying Parameter VARs," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1638-1665, December.
     • Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2014. "Stochastic Model Specification Search for Time-Varying Parameter VARs," CAMA Working Papers 2014-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
     • Eric Eisenstat & Joshua C.C. Chan & Rodney Strachan, 2014. "Stochastic Model Specification Search for Time-Varying Parameter VARs," Working Paper series 44_14, Rimini Centre for Economic Analysis.
101. Koop, Gary, 2014. "Forecasting with dimension switching VARs," International Journal of Forecasting, Elsevier, vol. 30(2), pages 280-290.
102. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
     • Gregor Kastner & Florian Huber, 2017. "Sparse Bayesian vector autoregressions in huge dimensions," Papers 1704.03239, arXiv.org, revised Dec 2019.
103. Chin, Kuo-Hsuan & Li, Xue, 2019. "Bayesian forecast combination in VAR-DSGE models," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 278-298.
104. Kaabia, Olfa & Abid, Ilyes & Mkaouar, Farid, 2016. "The dark side of the black gold shock onto Europe: One stock's joy is another stock's sorrow," Economic Modelling, Elsevier, vol. 58(C), pages 642-654.
105. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
     • Joshua C. C. Chan & Aubrey Poon & Dan Zhu, 2023. "High-Dimensional Conditionally Gaussian State Space Models with Missing Data," Papers 2302.03172, arXiv.org.
106. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Large Vector Autoregressions with Stochastic Volatility and Flexible Priors," Working Papers (Old Series) 1617, Federal Reserve Bank of Cleveland.
107. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05r, Department of Economics, University of Birmingham.
108. 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.
     • 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.
109. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
110. Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2017. "Have Standard VARS Remained Stable Since the Crisis?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 931-951, August.
     • Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2014. "Have standard VARs remained stable since the crisis?," Working Paper 2014/13, Norges Bank.
     • Marcellino, Massimiliano & Aastveit, Knut Are & Carriero, Andrea & Clark, Todd, 2016. "Have Standard VARs Remained Stable Since the Crisis?," CEPR Discussion Papers 11558, C.E.P.R. Discussion Papers.
     • Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2014. "Have Standard VARs Remained Stable since the Crisis?," Working Papers (Old Series) 1411, Federal Reserve Bank of Cleveland.
111. Joshua C.C. Chan & Eric Eisenstat, 2013. "Gibbs Samplers for VARMA and Its Extensions," ANU Working Papers in Economics and Econometrics 2013-604, Australian National University, College of Business and Economics, School of Economics.
112. 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.
113. Cubadda, Gianluca & Guardabascio, Barbara, 2019. "Representation, estimation and forecasting of the multivariate index-augmented autoregressive model," International Journal of Forecasting, Elsevier, vol. 35(1), pages 67-79.
     • Gianluca Cubadda & Barbara Guardabascio, 2017. "Representation, Estimation and Forecasting of the Multivariate Index-Augmented Autoregressive Model," CEIS Research Paper 397, Tor Vergata University, CEIS, revised 13 Jul 2018.
114. Bernardini, Emmanuela & Cubadda, Gianluca, 2015. "Macroeconomic forecasting and structural analysis through regularized reduced-rank regression," International Journal of Forecasting, Elsevier, vol. 31(3), pages 682-691.
     • Emmanuela Bernardini & Gianluca Cubadda, 2013. "Macroeconomic forecasting and structural analysis through regularized reduced-rank regression," CEIS Research Paper 289, Tor Vergata University, CEIS, revised 03 Oct 2013.
115. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
116. Boubaker, Sabri & Gounopoulos, Dimitrios & Nguyen, Duc Khuong & Paltalidis, Nikos, 2017. "Assessing the effects of unconventional monetary policy and low interest rates on pension fund risk incentives," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 35-52.
117. Joshua C. C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2020. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 692-711, September.
     • Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility," Working Paper Series 44, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
     • Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
118. Ralf Brüggemann & Christian Kascha, 2017. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2017-06, Department of Economics, University of Konstanz.
     • Bertsche, Dominik & Brüggemann, Ralf & Kascha, Christian, 2019. "Directed Graph and Variable Selection in Large Vector Autoregressive Models," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203656, Verein für Socialpolitik / German Economic Association.
     • Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2018. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2018-08, Department of Economics, University of Konstanz.
119. Raffaella Giacomini & Barbara Rossi, 2015. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 207-229, August.
     • Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in nonstationary environments: What works and what doesn't in reduced-form and structural models," Economics Working Papers 1476, Department of Economics and Business, Universitat Pompeu Fabra.
     • Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
120. Edward S. Knotek & Saeed Zaman, 2014. "The Slowdown in Residential Investment and Future Prospects," Economic Commentary, Federal Reserve Bank of Cleveland, issue May.
121. Everett Grant & Julieta Yung, 2017. "The Double-Edged Sword of Global Integration: Robustness, Fragility & Contagion in the International Firm Network," Globalization Institute Working Papers 313, Federal Reserve Bank of Dallas.
     • Everett Grant, 2018. "The Double-Edged Sword of Global Integration: Robustness, Fragility \& Contagion in the International Firm Network," 2018 Meeting Papers 506, Society for Economic Dynamics.
122. Camehl, Annika, 2023. "Penalized estimation of panel vector autoregressive models: A panel LASSO approach," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1185-1204.
123. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
     • Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Domenico Sartore, 2018. "A scoring rule for factor and autoregressive models under misspecification," Working Papers 2018:18, Department of Economics, University of Venice "Ca' Foscari".
124. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
     • Joshua C.C. Chan & Rodney W. Strachan, 2020. "Bayesian state space models in macroeconometrics," CAMA Working Papers 2020-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
125. Mikhail Mamonov & Anna Pestova, 2021. ""Sorry, You're Blocked." Economic Effects of Financial Sanctions on the Russian Economy," CERGE-EI Working Papers wp704, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
126. Huang, Y-F., 2012. "Forecasting Chinese inflation and output: A Bayesian vector autoregressive approach," MPRA Paper 41933, University Library of Munich, Germany.
127. Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
     • Joshua C. C. Chan, 2019. "Asymmetric conjugate priors for large Bayesian VARs," CAMA Working Papers 2019-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
     • Joshua C. C. Chan, 2021. "Asymmetric Conjugate Priors for Large Bayesian VARs," Papers 2111.07170, arXiv.org.
128. Heather Anderson & Giovanni Caggiano & Farshid Vahid & Benjamin Wong, 2020. "Sectoral Employment Dynamics in Australia and the COVID‐19 Pandemic," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 53(3), pages 402-414, September.
129. Tino Berger & Lorenzo Pozzi, 2023. "Cyclical consumption," Tinbergen Institute Discussion Papers 23-064/VI, Tinbergen Institute.
130. Joshua C. C. Chan, 2020. "Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 68-79, January.
     • Joshua C.C. Chan, 2015. "Large Bayesian VARs: A flexible Kronecker error covariance structure," CAMA Working Papers 2015-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
131. Pestova, Anna (Пестова, Анна) & Mamonov, Mikhail (Мамонов, Михаил), 2016. "Estimating the Influence of Different Shocks on Macroeconomic Indicators and Developing Conditional Forecasts on the Basis of BVAR Model for the Russian Economy [Оценка Влияния Различных Шоков На Д," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 4, pages 56-92, August.
132. Gächter, Martin & Huber, Florian & Meier, Martin, 2022. "A shot for the US economy," Finance Research Letters, Elsevier, vol. 47(PA).
133. Michele Campolieti & Deborah Gefang & Gary Koop, 2013. "Technical appendix to: a new look at variation in employment growth in Canada," Working Papers 26145533, Lancaster University Management School, Economics Department.
134. Petrova, Katerina, 2019. "A quasi-Bayesian local likelihood approach to time varying parameter VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 286-306.
135. Bin Jiang & Anastasios Panagiotelis & George Athanasopoulos & Rob Hyndman & Farshid Vahid, 2016. "Bayesian Rank Selection in Multivariate Regression," Monash Econometrics and Business Statistics Working Papers 6/16, Monash University, Department of Econometrics and Business Statistics.
136. Benati, Luca & Chan, Joshua & Eisenstat, Eric & Koop, Gary, 2020. "Identifying noise shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
     • Joshua Chan & Luca Benati & Eric Eisenstat & Gary Koop, 2018. "Identifying Noise Shocks," Working Paper Series 41, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
137. Tsionas, Efthymios G. & Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2016. "Bayesian GVAR with k-endogenous dominants & input–output weights: Financial and trade channels in crisis transmission for BRICs," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 1-26.
138. Ashwin Madhou & Tayushma Sewak & Imad Moosa & Vikash Ramiah, 2017. "GDP nowcasting: application and constraints in a small open developing economy," Applied Economics, Taylor & Francis Journals, vol. 49(38), pages 3880-3890, August.
139. Carriero, Andrea & Galvão, Ana Beatriz & Kapetanios, George, 2019. "A comprehensive evaluation of macroeconomic forecasting methods," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1226-1239.
     • Andrea Carriero & Galvao, Ana Beatriz & Kapetanios, George, 2016. "A comprehensive evaluation of macroeconomic forecasting methods," EMF Research Papers 10, Economic Modelling and Forecasting Group.
140. Cross, Jamie L. & Hou, Chenghan & Poon, Aubrey, 2020. "Macroeconomic forecasting with large Bayesian VARs: Global-local priors and the illusion of sparsity," International Journal of Forecasting, Elsevier, vol. 36(3), pages 899-915.
141. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
142. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
143. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
144. Lütkepohl, Helmut, 2014. "Structural vector autoregressive analysis in a data rich environment: A survey," SFB 649 Discussion Papers 2014-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
     • Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," Discussion Papers of DIW Berlin 1351, DIW Berlin, German Institute for Economic Research.
145. Erlan Konebayev, 2023. "Forecasting a Commodity-Exporting Small Open Developing Economy Using DSGE and DSGE-BVAR," International Economic Journal, Taylor & Francis Journals, vol. 37(1), pages 39-70, January.
     • Erlan Konebayev, 2022. "Forecasting a commodity-exporting small open developing economy using DSGE and DSGE-BVAR," NAC Analytica Working Paper 24, NAC Analytica, Nazarbayev University, revised May 2022.
146. Moramarco, Graziano, 2024. "Financial-cycle ratios and medium-term predictions of GDP: Evidence from the United States," International Journal of Forecasting, Elsevier, vol. 40(2), pages 777-795.
     • Graziano Moramarco, 2021. "Financial-cycle ratios and medium-term predictions of GDP: Evidence from the United States," Papers 2111.00822, arXiv.org, revised Jan 2024.
147. Lai, Wei-Ting & Chen, Ray-Bing & Chen, Ying & Koch, Thorsten, 2022. "Variational Bayesian inference for network autoregression models," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
148. Alex Bara & Pierre Le Roux, 2017. "South Africa's Financial Spillover Effects on Growth and Financial Development in the Southern African Development Community," International Journal of Economics and Financial Issues, Econjournals, vol. 7(5), pages 400-412.
149. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2022. "An automated prior robustness analysis in Bayesian model comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 583-602, April.
     • Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "An automated prior robustness analysis in Bayesian model comparison," CAMA Working Papers 2019-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
150. Raputsoane, Leroi, 2018. "Monetary policy reaction function pre and post the global financial crisis," MPRA Paper 84866, University Library of Munich, Germany.
151. Ankargren, Sebastian & Jonéus, Paulina, 2021. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Econometrics and Statistics, Elsevier, vol. 19(C), pages 97-113.
     • Sebastian Ankargren & Paulina Jon'eus, 2019. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Papers 1907.01075, arXiv.org.
152. Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
     • Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
153. George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019. "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1027-1049, November.
     • Marcellino, Massimiliano & Kapetanios, George & Venditti, Fabrizio, 2016. "Large Time-Varying Parameter VARs: A Non-Parametric Approach," CEPR Discussion Papers 11560, C.E.P.R. Discussion Papers.
     • George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
154. Maciej Stefański, 2021. "Macroeconomic Effects of Quantitative Easing Using Mid-sized Bayesian Vector Autoregressions," KAE Working Papers 2021-068, Warsaw School of Economics, Collegium of Economic Analysis.
155. Ms. Adina Popescu & Ms. Alina Carare, 2011. "Monetary Policy and Risk-Premium Shocks in Hungary: Results from a Large Bayesian VAR," IMF Working Papers 2011/259, International Monetary Fund.
156. Bańbura, Marta & Bobeica, Elena & Martínez Hernández, Catalina, 2023. "What drives core inflation? The role of supply shocks," Working Paper Series 2875, European Central Bank.
157. Carriero, Andrea & Clements, Michael P. & Galvão, Ana Beatriz, 2015. "Forecasting with Bayesian multivariate vintage-based VARs," International Journal of Forecasting, Elsevier, vol. 31(3), pages 757-768.
158. Pestova, Anna & Mamonov, Mikhail, 2019. "Should we care? : The economic effects of financial sanctions on the Russian economy," BOFIT Discussion Papers 13/2019, Bank of Finland, Institute for Economies in Transition.
159. Michaelides, Panayotis G. & Tsionas, Efthymios G. & Konstantakis, Konstantinos N., 2018. "Debt Crisis in Europe (2001-2015): A Network General Equilibrium GVAR approach," MPRA Paper 89998, University Library of Munich, Germany.
160. Gil-Alana, Luis A. & Gupta, Rangan & Olubusoye, Olusanya E. & Yaya, OlaOluwa S., 2016. "Time series analysis of persistence in crude oil price volatility across bull and bear regimes," Energy, Elsevier, vol. 109(C), pages 29-37.
     • Luis A. Gil-Alana & Rangan Gupta & Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2015. "Time Series Analysis of Persistence in Crude Oil Price Volatility across Bull and Bear Regimes," Working Papers 201580, University of Pretoria, Department of Economics.
161. Joshua C.C. Chan & Eric Eisenstat & Rodney W. Strachan, 2018. "Reducing dimensions in a large TVP-VAR," CAMA Working Papers 2018-49, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
     • Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2018. "Reducing Dimensions in a Large TVP-VAR," Working Paper series 18-37, Rimini Centre for Economic Analysis.
     • Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2018. "Reducing Dimensions in a Large TVP-VAR," Working Paper Series 43, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
162. Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Tsionas, Efthymios G. & Minou, Chrysanthi, 2015. "System estimation of GVAR with two dominants and network theory: Evidence for BRICs," Economic Modelling, Elsevier, vol. 51(C), pages 604-616.
163. Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
164. Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
165. Thomas Horvath & Peter Huber & Ulrike Huemer & Helmut Mahringer & Philipp Piribauer & Mark Sommer & Stefan Weingärtner, 2022. "Mittelfristige Beschäftigungsprognose für Österreich und die Bundesländer. Berufliche und sektorale Veränderungen 2021 bis 2028," WIFO Studies, WIFO, number 70720, April.
166. Karamanis, Dimitrios & Kechrinioti, Alexandra, 2023. "The Greek-Turkish rivalry: A Bayesian VAR approach," MPRA Paper 116827, University Library of Munich, Germany.
167. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore & Wing-Keung Wong, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
     • Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore & Wing-Keung Wong, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," International Association of Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
     • Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Domenico Sartore, 2018. "A scoring rule for factor and autoregressive models under misspecification," Working Papers 2018:18, Department of Economics, University of Venice "Ca' Foscari".
168. Korobilis, Dimitris, 2015. "Prior selection for panel vector autoregressions," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-73, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
169. Mihaela Simionescu, 2016. "Foreign Direct Investment and Sustainable Development. A Regional Approach for Romania," Working Papers of Macroeconomic Modelling Seminar 162702, Institute for Economic Forecasting.
170. Gefang, Deborah, 2014. "Bayesian doubly adaptive elastic-net Lasso for VAR shrinkage," International Journal of Forecasting, Elsevier, vol. 30(1), pages 1-11.
171. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
172. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2024. "Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates," International Journal of Forecasting, Elsevier, vol. 40(2), pages 626-640.
     • Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates," Working Papers 22-06, Federal Reserve Bank of Cleveland.
173. Marian Fink & Thomas Horvath & Peter Huber & Ulrike Huemer & Christoph Lorenz & Helmut Mahringer & Philipp Piribauer & Mark Sommer, 2019. "Mittelfristige Beschäftigungsprognose für Österreich und die Bundesländer. Berufliche und sektorale Veränderungen 2018 bis 2025," WIFO Studies, WIFO, number 66159, April.
174. 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.
175. Marian Fink & Thomas Horvath & Peter Huber & Ulrike Huemer & Mathias Kirchner & Helmut Mahringer & Philipp Piribauer, 2017. "Mittelfristige Beschäftigungsprognose für Österreich und die Bundesländer. Berufliche und sektorale Veränderungen 2016 bis 2023," WIFO Studies, WIFO, number 60948, April.
176. Nguyen, BH & Zhang, Bo, 2022. "Forecasting oil Prices: can large BVARs help?," Working Papers 2022-04, University of Tasmania, Tasmanian School of Business and Economics.
177. Annika Schnücker, 2016. "Restrictions Search for Panel VARs," Discussion Papers of DIW Berlin 1612, DIW Berlin, German Institute for Economic Research.
178. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
179. Emmanuel Mamatzakis & Mike Tsionas, 2018. "A Bayesian dynamic model to test persistence in funds' performance," Working Paper series 18-23, Rimini Centre for Economic Analysis.
180. Till Weigt & Bernd Wilfling, 2021. "An approach to increasing forecast‐combination accuracy through VAR error modeling," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 686-699, July.
     • Till Weigt & Bernd Wilfling, 2018. "An approach to increasing forecast-combination accuracy through VAR error modeling," CQE Working Papers 6818, Center for Quantitative Economics (CQE), University of Muenster.
181. Joshua C. C. Chan & Eric Eisenstat, 2018. "Bayesian model comparison for time‐varying parameter VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 509-532, June.
     • Joshua C.C. Chan & Eric Eisenstat, 2015. "Bayesian model comparison for time-varying parameter VARs with stochastic volatility," CAMA Working Papers 2015-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
182. Prüser, Jan, 2023. "Data-based priors for vector error correction models," International Journal of Forecasting, Elsevier, vol. 39(1), pages 209-227.
183. Kazeem Abimbola Sanusi & Zandri Dickason-Koekemoer, 2024. "Trade Openness, Financial Development and Economic Growth in Lesotho: BVAR and Time-varying VAR Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 14(3), pages 66-75, May.
184. Churm, Rohan & Joyce, Michael & Kapetanios, George & Theodoridis, Konstantinos, 2021. "Unconventional monetary policies and the macroeconomy: The impact of the UK's QE2 and funding for lending scheme," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 721-736.
185. Omar, Haytham & Klibi, Walid & Babai, M. Zied & Ducq, Yves, 2023. "Basket data-driven approach for omnichannel demand forecasting," International Journal of Production Economics, Elsevier, vol. 257(C).
186. Calvo-Pardo, Hector & Mancini, Tullio & Olmo, Jose, 2021. "Granger causality detection in high-dimensional systems using feedforward neural networks," International Journal of Forecasting, Elsevier, vol. 37(2), pages 920-940.
187. Mikhail Mamonov & Anna Pestova, 2023. "The Price of War: Macroeconomic and Cross-Sectional Effects of Sanctions on Russia," CERGE-EI Working Papers wp756, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
188. Lomivorotov, Rodion, 2015. "Bayesian estimation of monetary policy in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 41-63.
189. Ross Doppelt & Keith O'Hara, 2018. "Bayesian Estimation of Fractionally Integrated Vector Autoregressions and an Application to Identified Technology Shocks," 2018 Meeting Papers 1212, Society for Economic Dynamics.
190. Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2023. "Directed graphs and variable selection in large vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 223-246, March.
191. Jamie L. Cross & Chenghan Hou & Gary Koop, 2021. "Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs," Working Papers No 04/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
192. 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.
193. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
194. Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.
195. Boubaker, Sabri & Gounopoulos, Dimitrios & Nguyen, Duc Khuong & Paltalidis, Nikos, 2015. "Assessing the effects of unconventional monetary policy on pension funds risk incentives," MPRA Paper 73398, University Library of Munich, Germany, revised Aug 2016.
     • Sabri Boubaker & Dimitrios Gounopoulos & Duc Khuong Nguyen & Nikos Paltalidis, 2016. "Assessing the Effects of Unconventional Monetary Policy on Pension Funds Risk Incentives," Working Papers 2016-005, Department of Research, Ipag Business School.
196. Fu, Bowen, 2023. "Measuring the trend real interest rate in a data-rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
197. Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse seemingly unrelated regression model (SUR)," Working Papers 2016:20, Department of Economics, University of Venice "Ca' Foscari".
198. Scheffel, Eric Michael, 2012. "Political uncertainty in a data-rich environment," MPRA Paper 37318, University Library of Munich, Germany.
199. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Apr 2023.
200. repec:zbw:bofitp:2019_013 is not listed on IDEAS
201. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019. "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, vol. 212(1), pages 137-154.
202. De Gooijer, Jan G. & Zerom, Dawit, 2019. "Semiparametric quantile averaging in the presence of high-dimensional predictors," International Journal of Forecasting, Elsevier, vol. 35(3), pages 891-909.
203. Maiorova, Ksenia & Fokin, Nikita, 2020. "Наукастинг Темпов Роста Стоимостных Объемов Экспорта И Импорта По Товарным Группам [Nowcasting the growth rates of the export and import by commodity groups]," MPRA Paper 109557, University Library of Munich, Germany.
204. Damian Stelmasiak & Grzegorz Szafrański, 2016. "Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 21-42, March.
205. Ji, Kan & Qian, Zongxin, 2015. "Does tax policy affect credit spreads? Evidence from the US and UK," Journal of Macroeconomics, Elsevier, vol. 43(C), pages 318-329.
206. Joseph, Andreas & Kalamara, Eleni & Kapetanios, George & Potjagailo, Galina & Chakraborty, Chiranjit, 2021. "Forecasting UK inflation bottom up," Bank of England working papers 915, Bank of England, revised 27 Sep 2022.
207. Cobb, Marcus P A, 2017. "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper 76849, University Library of Munich, Germany.
208. Ping Wu & Gary Koop, 2022. "Fast, Order-Invariant Bayesian Inference in VARs using the Eigendecomposition of the Error Covariance Matrix," Working Papers 2310, University of Strathclyde Business School, Department of Economics.
209. Pestova, Anna & Mamonov, Mikhail, 2019. "Should we care? The economic effects of financial sanctions on the Russian economy," BOFIT Discussion Papers 13/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
210. Dallakyan, Aramayis & Kim, Rakheon & Pourahmadi, Mohsen, 2022. "Time series graphical lasso and sparse VAR estimation," Computational Statistics & Data Analysis, Elsevier, vol. 176(C).
211. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
     • Roberto Casarin & Daniel Felix Ahelegbey & Monica Billio, 2014. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Working Papers 2014:29, Department of Economics, University of Venice "Ca' Foscari".
212. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
213. Paci, Lucia & Consonni, Guido, 2020. "Structural learning of contemporaneous dependencies in graphical VAR models," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
214. Olfa Kaabia & Ilyes Abid & Khaled Guesmi, 2012. "Does Bayesian Shrinkage Help to Better Reflect What Happened during the Subprime Crisis?," Working Papers hal-04141032, HAL.
215. Swamy, Vighneswara, 2020. "Macroeconomic transmission of Eurozone shocks to India—A mean-adjusted Bayesian VAR approach," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 126-150.
216. Dimitris P. Louzis, 2014. "Macroeconomic and credit forecasts in a small economy during crisis: A large Bayesian VAR approach," Working Papers 184, Bank of Greece.
217. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Nov 2024.
218. Ovielt Baltodano L'opez & Roberto Casarin, 2022. "A Dynamic Stochastic Block Model for Multi-Layer Networks," Papers 2209.09354, arXiv.org.
219. 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.