Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2209.05998.html
   My bibliography  Save this paper

Interpreting and predicting the economy flows: A time-varying parameter global vector autoregressive integrated the machine learning model

Author

Listed:
  • Yukang Jiang
  • Xueqin Wang
  • Zhixi Xiong
  • Haisheng Yang
  • Ting Tian
Abstract
The paper proposes a time-varying parameter global vector autoregressive (TVP-GVAR) framework for predicting and analysing developed region economic variables. We want to provide an easily accessible approach for the economy application settings, where a variety of machine learning models can be incorporated for out-of-sample prediction. The LASSO-type technique for numerically efficient model selection of mean squared errors (MSEs) is selected. We show the convincing in-sample performance of our proposed model in all economic variables and relatively high precision out-of-sample predictions with different-frequency economic inputs. Furthermore, the time-varying orthogonal impulse responses provide novel insights into the connectedness of economic variables at critical time points across developed regions. We also derive the corresponding asymptotic bands (the confidence intervals) for orthogonal impulse responses function under standard assumptions.

Suggested Citation

  • Yukang Jiang & Xueqin Wang & Zhixi Xiong & Haisheng Yang & Ting Tian, 2022. "Interpreting and predicting the economy flows: A time-varying parameter global vector autoregressive integrated the machine learning model," Papers 2209.05998, arXiv.org.
    • Handle: RePEc:arx:papers:2209.05998
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2209.05998
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2021. "Deep Neural Networks for Estimation and Inference," Econometrica, Econometric Society, vol. 89(1), pages 181-213, January.
    2. Niko Hauzenberger & Michael Pfarrhofer, 2021. "Bayesian State‐Space Modeling for Analyzing Heterogeneous Network Effects of US Monetary Policy," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(4), pages 1261-1291, October.
    3. Georgiadis, Georgios, 2015. "Examining asymmetries in the transmission of monetary policy in the euro area: Evidence from a mixed cross-section global VAR model," European Economic Review, Elsevier, vol. 75(C), pages 195-215.
    4. Kilian,Lutz & Lütkepohl,Helmut, 2018. "Structural Vector Autoregressive Analysis," Cambridge Books, Cambridge University Press, number 9781107196575.
    5. Pesaran M.H. & Schuermann T. & Weiner S.M., 2004. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 129-162, April.
    6. Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2010. "Stochastic model specification search for Gaussian and partial non-Gaussian state space models," Journal of Econometrics, Elsevier, vol. 154(1), pages 85-100, January.
    7. Lütkepohl, Helmut & Staszewska-Bystrova, Anna & Winker, Peter, 2020. "Constructing joint confidence bands for impulse response functions of VAR models – A review," Econometrics and Statistics, Elsevier, vol. 13(C), pages 69-83.
    8. Kok, Christoffer & Gross, Marco, 2013. "Measuring contagion potential among sovereigns and banks using a mixed-cross-section GVAR," Working Paper Series 1570, European Central Bank.
    9. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    10. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
    11. Robert Tibshirani, 2011. "Regression shrinkage and selection via the lasso: a retrospective," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(3), pages 273-282, June.
    12. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Timo Bettendorf, 2019. "Spillover effects of credit default risk in the euro area and the effects on the Euro: A GVAR approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 296-312, January.
    2. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian Vector Autoregressions," The Warwick Economics Research Paper Series (TWERPS) 1159, University of Warwick, Department of Economics.
    3. Kenneth F. Wallis & Jan P. A. M. Jacobs, 2005. "Comparing SVARs and SEMs: two models of the UK economy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 209-228.
    4. Alexander Chudik & M. Hashem Pesaran, 2016. "Theory And Practice Of Gvar Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, February.
    5. Chisiridis, Konstantinos & Mouratidis, Kostas & Panagiotidis, Theodore, 2022. "The north-south divide, the euro and the world," Journal of International Money and Finance, Elsevier, vol. 121(C).
    6. Ong, Sheue Li & Sato, Kiyotaka, 2018. "Regional or global shock? A global VAR analysis of Asian economic and financial integration," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 232-248.
    7. Jacobs, Jan P.A.M. & Wallis, Kenneth F., 2010. "Cointegration, long-run structural modelling and weak exogeneity: Two models of the UK economy," Journal of Econometrics, Elsevier, vol. 158(1), pages 108-116, September.
    8. Skouralis, Alexandros, 2021. "The role of systemic risk spillovers in the transmission of Euro Area monetary policy," ESRB Working Paper Series 129, European Systemic Risk Board.
    9. Victor Pontines, 2021. "The real effects of loan-to-value limits: empirical evidence from Korea," Empirical Economics, Springer, vol. 61(3), pages 1311-1350, September.
    10. Capasso, Salvatore & D'Uva, Marcella & Fiorelli, Cristiana & Napolitano, Oreste, 2023. "Cross-border Italian sovereign risk transmission in EMU countries," Economic Modelling, Elsevier, vol. 126(C).
    11. repec:hal:spmain:info:hdl:2441/27od5pb99881folvtfs8s3k16l is not listed on IDEAS
    12. Lombardi, Marco J. & Galesi, Alessandro, 2009. "External shocks and international inflation linkages: a global VAR analysis," Working Paper Series 1062, European Central Bank.
    13. Vadim Napalkov & Anna Novak & Andrey Shulgin, 2021. "Variations in the Effects of a Single Monetary Policy: The Case of Russian Regions," Russian Journal of Money and Finance, Bank of Russia, vol. 80(1), pages 3-45, March.
    14. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, October.
    15. Anna Sznajderska, 2019. "The role of China in the world economy: evidence from a global VAR model," Applied Economics, Taylor & Francis Journals, vol. 51(15), pages 1574-1587, March.
    16. repec:spo:wpmain:info:hdl:2441/27od5pb99881folvtfs8s3k16l is not listed on IDEAS
    17. Dées, Stéphane & Galesi, Alessandro, 2021. "The Global Financial Cycle and US monetary policy in an interconnected world," Journal of International Money and Finance, Elsevier, vol. 115(C).
    18. Stefan Schiman-Vukan & Harald Badinger, 2020. "Measuring Monetary Policy with Residual Sign Restrictions at Known Shock Dates," WIFO Working Papers 608, WIFO.
    19. Roko Pedisic, 2022. "Cointegration Analysis of Financial Market Indices During Financial Shocks. Focus on Global Financial Crisis and COVID-19 ?andemic Crisis," Bulletin of Applied Economics, Risk Market Journals, vol. 9(2), pages 59-78.
    20. Ouerk, Salima, 2023. "ECB unconventional monetary policy and volatile bank flows: Spillover effects on emerging market economies," International Economics, Elsevier, vol. 173(C), pages 175-211.
    21. Castrén, Olli & Dées, Stéphane & Zaher, Fadi, 2010. "Stress-testing euro area corporate default probabilities using a global macroeconomic model," Journal of Financial Stability, Elsevier, vol. 6(2), pages 64-78, June.
    22. Jacobs, Jan P.A.M. & Wallis, Kenneth F., 2010. "Cointegration, long-run structural modelling and weak exogeneity: Two models of the UK economy," Journal of Econometrics, Elsevier, vol. 158(1), pages 108-116, September.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2209.05998. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.