IDEAS home Printed from https://ideas.repec.org/r/qmw/qmwecw/767.html
   My bibliography  Save this item

Inference on Multivariate Heteroscedastic Time Varying Random Coefficient Models

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Giraitis, Liudas & Kapetanios, George & Marcellino, Massimiliano, 2021. "Time-varying instrumental variable estimation," Journal of Econometrics, Elsevier, vol. 224(2), pages 394-415.
  2. Chronopoulos, Ilias & Kapetanios, George & Petrova, Katerina, 2021. "Kernel-based Volatility Generalised Least Squares," Econometrics and Statistics, Elsevier, vol. 20(C), pages 2-11.
  3. Gustavo Fruet Dias & Marcelo Fernandes & Cristina M. Scherrer, 2016. "Component shares in continuous time," CREATES Research Papers 2016-25, Department of Economics and Business Economics, Aarhus University.
  4. Klein, Mathias & Linnemann, Ludger, 2020. "The time-varying effect of fiscal policy on inflation: Evidence from historical US data," Economics Letters, Elsevier, vol. 186(C).
  5. Y. Dendramis & G. Kapetanios & M. Marcellino, 2020. "A similarity‐based approach for macroeconomic forecasting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 801-827, June.
  6. Foroni, Claudia & Marcellino, Massimiliano & Stevanovic, Dalibor, 2022. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," International Journal of Forecasting, Elsevier, vol. 38(2), pages 596-612.
  7. Alonso-Alvarez, Irma & Di Nino, Virginia & Venditti, Fabrizio, 2022. "Strategic interactions and price dynamics in the global oil market," Energy Economics, Elsevier, vol. 107(C).
  8. Philippe Goulet Coulombe, 2020. "The Macroeconomy as a Random Forest," Papers 2006.12724, arXiv.org, revised Mar 2021.
  9. Giacomo Bormetti & Fulvio Corsi, 2021. "A Lucas Critique Compliant SVAR model with Observation-driven Time-varying Parameters," Papers 2107.05263, arXiv.org, revised Feb 2022.
  10. Chang, Yoosoon & Kwak, Boreum, 2017. "U.S. monetary-fiscal regime changes in the presence of endogenous feedback in policy rules," IWH Discussion Papers 15/2017, Halle Institute for Economic Research (IWH).
  11. 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.
  12. 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.
  13. Riccardo Lucchetti & Francesco Valentini, 2023. "Kernel-based time-varying IV estimation: handle with care," Empirical Economics, Springer, vol. 65(6), pages 3001-3026, December.
  14. Kapetanios, George & Millard, Stephen & Price, Simon & Petrova, Katerina, 2018. "Time varying cointegration and the UK Great Ratios," Essex Finance Centre Working Papers 23320, University of Essex, Essex Business School.
  15. Zongwu Cai & Xiyuan Liu, 2021. "Solving the Price Puzzle Via A Functional Coefficient Factor-Augmented VAR Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202106, University of Kansas, Department of Economics, revised Jan 2021.
  16. Laura Liu & Christian Matthes & Katerina Petrova, 2022. "Monetary Policy Across Space and Time," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 37-64, Emerald Group Publishing Limited.
  17. Baillie, Richard T. & Cho, Dooyeon, 2016. "Assessing Euro crises from a time varying international CAPM approach," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 197-208.
  18. Richard T. Baillie & Fabio Calonaci & George Kapetanios, 2019. "Hierarchical Time Varying Estimation of a Multi Factor Asset Pricing Model," Working Papers 879, Queen Mary University of London, School of Economics and Finance.
  19. Kapetanios, George & Zikes, Filip, 2018. "Time-varying Lasso," Economics Letters, Elsevier, vol. 169(C), pages 1-6.
  20. Yayi Yan & Jiti Gao & Bin Peng, 2020. "A Class of Time-Varying Vector Moving Average Models: Nonparametric Kernel Estimation and Application," Papers 2010.01492, arXiv.org.
  21. Philippe Goulet Coulombe, 2024. "The macroeconomy as a random forest," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 401-421, April.
  22. Magnus Reif, 2022. "Time‐Varying Dynamics of the German Business Cycle: A Comprehensive Investigation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(1), pages 80-102, February.
  23. Philippe Goulet Coulombe, 2021. "The Macroeconomy as a Random Forest," Working Papers 21-05, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  24. Dias, Gustavo Fruet & Fernandes, Marcelo & Scherrer, Cristina Mabel, 2017. "Improving on daily measures of price discovery," Textos para discussão 444, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
  25. Kapetanios, George & Millard, Stephen & Petrova, Katerina & Price, Simon, 2020. "Time-varying cointegration with an application to the UK Great Ratios," Economics Letters, Elsevier, vol. 193(C).
  26. Yayi Yan & Jiti Gao & Bin peng, 2020. "A Class of Time-Varying Vector Moving Average (infinity) Models," Monash Econometrics and Business Statistics Working Papers 39/20, Monash University, Department of Econometrics and Business Statistics.
  27. Yu Bai & Massimiliano Marcellino & George Kapetanios, 2023. "Mean Group Instrumental Variable Estimation of Time-Varying Large Heterogeneous Panels with Endogenous Regressors," Monash Econometrics and Business Statistics Working Papers 13/23, Monash University, Department of Econometrics and Business Statistics.
  28. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Apr 2023.
  29. Camba-Méndez, Gonzalo, 2020. "On the inflation risks embedded in sovereign bond yields," Working Paper Series 2423, European Central Bank.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.