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Estimation of vector error correction models with mixed-frequency data

Author

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  • Byeongchan Seong
  • Sung K. Ahn
  • Peter A. Zadrozny

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  • Byeongchan Seong & Sung K. Ahn & Peter A. Zadrozny, 2013. "Estimation of vector error correction models with mixed-frequency data," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(2), pages 194-205, March.
    • Handle: RePEc:bla:jtsera:v:34:y:2013:i:2:p:194-205
    DOI: jtsa.12001
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    Cited by:

    1. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.
    2. Ines Fortin & Jaroslava Hlouskova & Leopold Sögner, 2023. "Financial and economic uncertainties and their effects on the economy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(2), pages 481-521, May.
    3. Peter Fuleky & Carl Bonham, 2010. "Forecasting Based on Common Trends in Mixed Frequency Samples," Working Papers 2010-17R1, University of Hawaii Economic Research Organization, University of Hawaii at Manoa, revised Jul 2013.
    4. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2016. "Testing for Granger causality with mixed frequency data," Journal of Econometrics, Elsevier, vol. 192(1), pages 207-230.
    5. Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).
    6. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation of Non-Stationary Large Approximate Dynamic Factor Models," Papers 1910.09841, arXiv.org.
    7. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    8. Seong, Byeongchan, 2020. "Smoothing and forecasting mixed-frequency time series with vector exponential smoothing models," Economic Modelling, Elsevier, vol. 91(C), pages 463-468.
    9. Francisco Corona & Pilar Poncela & Esther Ruiz, 2020. "Estimating Non-stationary Common Factors: Implications for Risk Sharing," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 37-60, January.
    10. Peter Fuleky & Carl, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 2013-5, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    11. Nusair, Salah A. & Olson, Dennis, 2021. "Asymmetric oil price and Asian economies: A nonlinear ARDL approach," Energy, Elsevier, vol. 219(C).
    12. Chambers, Marcus J., 2016. "The estimation of continuous time models with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 390-404.
    13. Thomas B. Götz & Alain Hecq & Jean-Pierre Urbain, 2013. "Testing for Common Cycles in Non-Stationary VARs with Varied Frequency Data," Advances in Econometrics, in: VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims, volume 32, pages 361-393, Emerald Group Publishing Limited.
    14. Paola Arce & Jonathan Antognini & Werner Kristjanpoller & Luis Salinas, 2019. "Fast and Adaptive Cointegration Based Model for Forecasting High Frequency Financial Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 99-112, June.
    15. Cuixia Jiang & Tingting Zhao & Qifa Xu & Dan Hu, 2024. "An unrestricted MIDAS ordered logit model with applications to credit ratings," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 2722-2739, July.
    16. Zhou, Xinquan & Bagnarosa, Guillaume & Gohin, Alexandre & Pennings, Joost M.E. & Debie, Philippe, 2023. "Microstructure and high-frequency price discovery in the soybean complex," Journal of Commodity Markets, Elsevier, vol. 30(C).

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