IDEAS home Printed from https://ideas.repec.org/p/pre/wpaper/202002.html
   My bibliography  Save this paper

Time-Varying Spillover of US Trade War on the Growth of Emerging Economies

Author

Listed:
  • Oguzhan Cepni

    (Central Bank of the Republic of Turkey, Anafartalar Mah. Istiklal Cad. No:10 06050 Ankara, Turkey)

  • David Gabauer

    (Business and Management, Webster Vienna Private University, Praterstraße 23, 1020 Vienna, Austria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Khuliso Ramabulana

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

Abstract

In the wake of an unprecedented increase in the trade policy-related uncertainty of the US since 2017, we analyze the ability of a newspaper-based trade policy uncertainty index of the US in predicting the growth rate of emerging market economies using a novel multivariate time-varying causality framework. We provide overwhelming evidence of the role of trade uncertainty in negatively impacting the growth of emerging markets in a statistically significant manner, with the effect being on the rise since the Great Recession. Our results are robust to the usage of an alternative econometric methodology, metric of trade uncertainty, and also over an out-of-sample forecasting exercise. Policy conclusions of our results are discussed.

Suggested Citation

  • Oguzhan Cepni & David Gabauer & Rangan Gupta & Khuliso Ramabulana, 2020. "Time-Varying Spillover of US Trade War on the Growth of Emerging Economies," Working Papers 202002, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202002
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    2. Rossi, Barbara, 2005. "Optimal Tests For Nested Model Selection With Underlying Parameter Instability," Econometric Theory, Cambridge University Press, vol. 21(5), pages 962-990, October.
    3. Rangan Gupta & Chi Keung Marco Lau & Mark E. Wohar, 2019. "The impact of US uncertainty on the Euro area in good and bad times: evidence from a quantile structural vector autoregressive model," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 353-368, May.
    4. Caldara, Dario & Iacoviello, Matteo & Molligo, Patrick & Prestipino, Andrea & Raffo, Andrea, 2020. "The economic effects of trade policy uncertainty," Journal of Monetary Economics, Elsevier, vol. 109(C), pages 38-59.
    5. Martin Ruzima & Micheal Kofi Boachie, 2018. "Exchange rate uncertainty and private investment in BRICS economies," Asia-Pacific Journal of Regional Science, Springer, vol. 2(1), pages 65-77, April.
    6. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    7. Vasilios Plakandaras & Rangan Gupta & Luis A. Gil-Alana & Mark E. Wohar, 2019. "Are BRICS exchange rates chaotic?," Applied Economics Letters, Taylor & Francis Journals, vol. 26(13), pages 1104-1110, July.
    8. Grossman, Valerie & Mack, Adrienne & Martínez-García, Enrique, 2014. "A New Database of Global Economic Indicators," Journal of Economic and Social Measurement, IOS Press, issue 3, pages 163-197.
    9. Shuping Shi & Peter C. B. Phillips & Stan Hurn, 2018. "Change Detection and the Causal Impact of the Yield Curve," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 966-987, November.
    10. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    11. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    12. Marco Del Negro & Giorgio E. Primiceri, 2015. "Time Varying Structural Vector Autoregressions and Monetary Policy: A Corrigendum," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1342-1345.
    13. Mr. Christian H Ebeke & Jesse Siminitz, 2018. "Trade Uncertainty and Investment in the Euro Area," IMF Working Papers 2018/281, International Monetary Fund.
    14. Clark, Todd E. & McCracken, Michael W., 2006. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1127-1148, August.
    15. Dario Caldara & Matteo Iacoviello & Patrick Molligo & Andrea Prestipino & Andrea Raffo, 2019. "Does Trade Policy Uncertainty Affect Global Economic Activity?," FEDS Notes 2019-09-04, Board of Governors of the Federal Reserve System (U.S.).
    16. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    17. Joshua C.C. Chan & Eric Eisenstat, 2017. "Efficient estimation of Bayesian VARMAs with time†varying coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1277-1297, November.
    18. Barbara Rossi & Yiru Wang, 2019. "VAR-Based Granger-Causality Test in the Presence of Instabilities," Working Papers 1083, Barcelona School of Economics.
    19. Jean Boivin & Marc P. Giannoni, 2006. "Has Monetary Policy Become More Effective?," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 445-462, August.
    20. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    21. Rangan Gupta & Godwin Olasehinde-Williams & Mark E. Wohar, 2018. "The Impact of US Uncertainty Shocks on a Panel of Advanced and Emerging Market Economies: The Role of Exchange Rate, Trade and Financial Channels," Working Papers 201857, University of Pretoria, Department of Economics.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Çepni, Oğuzhan & Gül, Selçuk & Hacıhasanoğlu, Yavuz Selim & Yılmaz, Muhammed Hasan, 2020. "Global uncertainties and portfolio flow dynamics of the BRICS countries," Research in International Business and Finance, Elsevier, vol. 54(C).
    2. Layal Mansour-Ichrakieh, 2021. "The Impact of Israeli and Saudi Arabian Geopolitical Risks on the Lebanese Financial Market," JRFM, MDPI, vol. 14(3), pages 1-24, February.

    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. Edmond Berisha & David Gabauer & Rangan Gupta & Chi Keung Marco Lau, 2021. "Time-varying influence of household debt on inequality in United Kingdom," Empirical Economics, Springer, vol. 61(4), pages 1917-1933, October.
    2. Mehmet Balcilar & Gizem Uzuner & Festus Victor Bekun & Mark E. Wohar, 2023. "Housing price uncertainty and housing prices in the UK in a time-varying environment," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(2), pages 523-549, May.
    3. Semei Coronado & Rangan Gupta & Saban Nazlioglu & Omar Rojas, 2023. "Time‐varying causality between bond and oil markets of the United States: Evidence from over one and half centuries of data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2239-2247, July.
    4. David Gabauer & Rangan Gupta & Jacobus Nel & Woraphon Yamaka, 2021. "Time-Varying Predictability of Labor Productivity on Inequality in United Kingdom," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(3), pages 771-788, June.
    5. Yiru Wang & Barbara Rossi, 2019. "VAR-based Granger-causality test in the presence of instabilities," Economics Working Papers 1642, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Barbara Rossi & Yiru Wang, 2019. "Vector autoregressive-based Granger causality test in the presence of instabilities," Stata Journal, StataCorp LP, vol. 19(4), pages 883-899, December.
    7. 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.
    8. Christou, Christina & Gabauer, David & Gupta, Rangan, 2020. "Time-Varying impact of uncertainty shocks on macroeconomic variables of the united kingdom: Evidence from over 150 years of monthly data," Finance Research Letters, Elsevier, vol. 37(C).
    9. Mehmet Balcilar & Edmond Berisha & Oğuzhan Çepni & Rangan Gupta, 2022. "The predictive power of the term spread on inequality in the United Kingdom: An empirical analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1979-1988, April.
    10. Gu, Xin & Zhu, Zixiang & Yu, Minli, 2021. "The macro effects of GPR and EPU indexes over the global oil market—Are the two types of uncertainty shock alike?," Energy Economics, Elsevier, vol. 100(C).
    11. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    12. Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
    13. Arigoni, Filippo & Lenarčič, Črt, 2020. "The impact of trade policy uncertainty shocks on the Euro Area," MPRA Paper 100832, University Library of Munich, Germany.
    14. Samuel F. Onipede & Nafiu A. Bashir & Jamaladeen Abubakar, 2023. "Small open economies and external shocks: an application of Bayesian global vector autoregression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1673-1699, April.
    15. Gnangnon, Sèna Kimm, 2023. "Duration of membership in the world trade organization and investment-oriented remittances inflows," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 258-277.
    16. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2023. "Vector autoregression models with skewness and heavy tails," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    17. Gnangnon, Sèna Kimm, 2022. "Duration of WTO Membership and Investment-Oriented Remittances Flows," EconStor Preprints 251274, ZBW - Leibniz Information Centre for Economics.
    18. Hännikäinen Jari, 2017. "Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    19. Kang, Wensheng & Ratti, Ronald. A. & Vespignani, Joaquin, 2017. "Global commodity prices and global stock volatility shocks: effects across countries," Working Papers 2017-05, University of Tasmania, Tasmanian School of Business and Economics.
    20. Ganics, Gergely & Odendahl, Florens, 2021. "Bayesian VAR forecasts, survey information, and structural change in the euro area," International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.

    More about this item

    Keywords

    Trade Policy Uncertainty of the United States; Time-Varying Multivariate Causality; Emerging Market Economies;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:pre:wpaper:202002. 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: Rangan Gupta (email available below). General contact details of provider: https://edirc.repec.org/data/decupza.html .

    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.