IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v580y2021ics0378437121004192.html
   My bibliography  Save this article

Detecting lag linkage effect between economic policy uncertainty and crude oil price: A multi-scale perspective

Author

Listed:
  • He, Huizi
  • Sun, Mei
  • Gao, Cuixia
  • Li, Xiuming

Abstract

This paper proposes a new compound model to investigate the linkage effect between economic policy uncertainty (EPU) and West Texas Intermediate (WTI) crude oil future price from 1985 to 2018. Two main steps are involved in this proposed model: multi-scale analysis and time delay cross correlation analysis. Considering nonlinear and nonstationary characteristics of crude oil price, the long-term, medium-term, and short-term trends of WTI price are correspondingly obtained by decomposition and reconstruction. To capture the linked characteristics in different periods, we segment the sample data into 14 periods. Finally, we analyze the linkage effect between EPU index and crude oil price based on direction of link, time lag and association strength. The results indicate that information will be transmitted from EPU index to crude oil price regardless of the time scale, but the transmission capacity is different. The period of reverse linkage between oil price and EPU index accounts for 63% of the sample interval, whereas the same linkage mainly occurs when oil price rises. The linkage lag and association strength of EPU index and oil price have obvious dissimilarity in different periods. Potential application value for energy policy makers and oil related investors are presented.

Suggested Citation

  • He, Huizi & Sun, Mei & Gao, Cuixia & Li, Xiuming, 2021. "Detecting lag linkage effect between economic policy uncertainty and crude oil price: A multi-scale perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    • Handle: RePEc:eee:phsmap:v:580:y:2021:i:c:s0378437121004192
    DOI: 10.1016/j.physa.2021.126146
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437121004192
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2021.126146?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xiuwen Chen & Xiaolei Sun & Jianping Li, 2020. "How does economic policy uncertainty react to oil price shocks? A multi-scale perspective," Applied Economics Letters, Taylor & Francis Journals, vol. 27(3), pages 188-193, February.
    2. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2014. "Dynamic Spillovers of Oil Price Shocks and Policy Uncertainty," Department of Economics Working Paper Series 166, WU Vienna University of Economics and Business.
    3. Wang, Minggang & Chen, Ying & Tian, Lixin & Jiang, Shumin & Tian, Zihao & Du, Ruijin, 2016. "Fluctuation behavior analysis of international crude oil and gasoline price based on complex network perspective," Applied Energy, Elsevier, vol. 175(C), pages 109-127.
    4. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2017. "Oil price shocks and policy uncertainty: New evidence on the effects of US and non-US oil production," Energy Economics, Elsevier, vol. 66(C), pages 536-546.
    5. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2017. "Forecasting the real prices of crude oil using forecast combinations over time-varying parameter models," Energy Economics, Elsevier, vol. 66(C), pages 337-348.
    6. You, Wanhai & Guo, Yawei & Zhu, Huiming & Tang, Yong, 2017. "Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression," Energy Economics, Elsevier, vol. 68(C), pages 1-18.
    7. Yang, Lu, 2019. "Connectedness of economic policy uncertainty and oil price shocks in a time domain perspective," Energy Economics, Elsevier, vol. 80(C), pages 219-233.
    8. Li, Xiuming & Sun, Mei & Gao, Cuixia & He, Huizi, 2019. "The spillover effects between natural gas and crude oil markets: The correlation network analysis based on multi-scale approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 306-324.
    9. Zhang, Yue-Jun & Zhang, Lu, 2015. "Interpreting the crude oil price movements: Evidence from the Markov regime switching model," Applied Energy, Elsevier, vol. 143(C), pages 96-109.
    10. Yaneer Bar-Yam, 2016. "From Big Data To Important Information," Papers 1604.00976, arXiv.org.
    11. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    12. Zhang, Xun & Lai, K.K. & Wang, Shou-Yang, 2008. "A new approach for crude oil price analysis based on Empirical Mode Decomposition," Energy Economics, Elsevier, vol. 30(3), pages 905-918, May.
    13. Raza, Syed Ali & Shah, Nida & Shahbaz, Muhammad, 2018. "Does economic policy uncertainty influence gold prices? Evidence from a nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 57(C), pages 61-68.
    14. Tang, Ling & Zhang, Chengyuan & Li, Ling & Wang, Shouyang, 2020. "A multi-scale method for forecasting oil price with multi-factor search engine data," Applied Energy, Elsevier, vol. 257(C).
    15. Ftiti, Zied & Hadhri, Sinda, 2019. "Can economic policy uncertainty, oil prices, and investor sentiment predict Islamic stock returns? A multi-scale perspective," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 40-55.
    16. Jaroslaw Kwapien & Pawel Oswiecimka & Stanislaw Drozdz, 2015. "Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations," Papers 1506.08692, arXiv.org, revised Nov 2015.
    17. Yan, Lei & Irwin, Scott H. & Sanders, Dwight R., 2018. "Mapping algorithms, agricultural futures, and the relationship between commodity investment flows and crude oil futures prices," Energy Economics, Elsevier, vol. 72(C), pages 486-504.
    18. Zhang, Yue-Jun & Wang, Jin-Li, 2019. "Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models," Energy Economics, Elsevier, vol. 78(C), pages 192-201.
    19. Zhang, Xun & Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method," Energy Economics, Elsevier, vol. 31(5), pages 768-778, September.
    20. Wang, Minggang & Zhao, Longfeng & Du, Ruijin & Wang, Chao & Chen, Lin & Tian, Lixin & Eugene Stanley, H., 2018. "A novel hybrid method of forecasting crude oil prices using complex network science and artificial intelligence algorithms," Applied Energy, Elsevier, vol. 220(C), pages 480-495.
    21. Baum, Christopher F. & Zerilli, Paola, 2016. "Jumps and stochastic volatility in crude oil futures prices using conditional moments of integrated volatility," Energy Economics, Elsevier, vol. 53(C), pages 175-181.
    22. Hailemariam, Abebe & Smyth, Russell & Zhang, Xibin, 2019. "Oil prices and economic policy uncertainty: Evidence from a nonparametric panel data model," Energy Economics, Elsevier, vol. 83(C), pages 40-51.
    23. repec:eee:finlet:v:24:y:2018:i:c:p:56-63 is not listed on IDEAS
    24. Chiarella, Carl & Kang, Boda & Nikitopoulos, Christina Sklibosios & Tô, Thuy-Duong, 2013. "Humps in the volatility structure of the crude oil futures market: New evidence," Energy Economics, Elsevier, vol. 40(C), pages 989-1000.
    25. Diaz, Elena Maria & de Gracia, Fernando Perez, 2017. "Oil price shocks and stock returns of oil and gas corporations," Finance Research Letters, Elsevier, vol. 20(C), pages 75-80.
    26. Liu, Li & Zhang, Tao, 2015. "Economic policy uncertainty and stock market volatility," Finance Research Letters, Elsevier, vol. 15(C), pages 99-105.
    27. Ling Tang & Shuai Wang & Kaijian He & Shouyang Wang, 2015. "A novel mode-characteristic-based decomposition ensemble model for nuclear energy consumption forecasting," Annals of Operations Research, Springer, vol. 234(1), pages 111-132, November.
    28. Yan, Lei & Irwin, Scott H. & Sanders, Dwight R., "undated". "The Relationship between Commodity Investment Flows and Crude Oil Futures Prices: Real or Spurious?," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235933, Agricultural and Applied Economics Association.
    29. Kang, Wensheng & Perez de Gracia, Fernando & Ratti, Ronald A., 2017. "Oil price shocks, policy uncertainty, and stock returns of oil and gas corporations," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 344-359.
    30. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2014. "Dynamic spillovers of oil price shocks and economic policy uncertainty," Energy Economics, Elsevier, vol. 44(C), pages 433-447.
    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. Liu, Ying Lin & Zhang, Jing Jie & Fang, Yan, 2023. "The driving factors of China's carbon prices: Evidence from using ICEEMDAN-HC method and quantile regression," Finance Research Letters, Elsevier, vol. 54(C).
    2. He, Huizi & Sun, Mei & Li, Xiuming & Mensah, Isaac Adjei, 2022. "A novel crude oil price trend prediction method: Machine learning classification algorithm based on multi-modal data features," Energy, Elsevier, vol. 244(PA).
    3. Yan Ding & Yue Liu & Pierre Failler, 2022. "The Impact of Uncertainties on Crude Oil Prices: Based on a Quantile-on-Quantile Method," Energies, MDPI, vol. 15(10), pages 1-35, May.
    4. Sheng Cheng & Wei Liu & Qisheng Jiang & Yan Cao, 2023. "Multi–Scale Risk Connectedness Between Economic Policy Uncertainty of China and Global Oil Prices in Time–Frequency Domains," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1593-1616, April.

    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. Wang, Yilei & Cheng, Sheng & Cao, Yan, 2022. "How does economic policy uncertainty respond to the global oil price fluctuations? Evidence from BRICS countries," Resources Policy, Elsevier, vol. 79(C).
    2. Badshah, Ihsan & Demirer, Riza & Suleman, Muhammad Tahir, 2019. "The effect of economic policy uncertainty on stock-commodity correlations and its implications on optimal hedging," Energy Economics, Elsevier, vol. 84(C).
    3. Rasool Dehghanzadeh Shahabad & Mehmet Balcilar, 2022. "Modelling the Dynamic Interaction between Economic Policy Uncertainty and Commodity Prices in India: The Dynamic Autoregressive Distributed Lag Approach," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
    4. Qin, Yun & Chen, Jinyu & Dong, Xuesong, 2021. "Oil prices, policy uncertainty and travel and leisure stocks in China," Energy Economics, Elsevier, vol. 96(C).
    5. Apostolakis, George N. & Floros, Christos & Gkillas, Konstantinos & Wohar, Mark, 2021. "Financial stress, economic policy uncertainty, and oil price uncertainty," Energy Economics, Elsevier, vol. 104(C).
    6. Yingce Yang & Junjie Guo & Ruihong He, 2023. "The Asymmetric Impact of the Oil Price and Disaggregate Shocks on Economic Policy Uncertainty: Evidence From China," SAGE Open, , vol. 13(2), pages 21582440231, June.
    7. Ioannis Dokas & Georgios Oikonomou & Minas Panagiotidis & Eleftherios Spyromitros, 2023. "Macroeconomic and Uncertainty Shocks’ Effects on Energy Prices: A Comprehensive Literature Review," Energies, MDPI, vol. 16(3), pages 1-35, February.
    8. Mokni, Khaled, 2021. "When, where, and how economic policy uncertainty predicts Bitcoin returns and volatility? A quantiles-based analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 65-73.
    9. Cao, Yan & Cheng, Sheng & Li, Xinran, 2023. "How economic policy uncertainty affects asymmetric spillovers in food and oil prices: Evidence from wavelet analysis," Resources Policy, Elsevier, vol. 86(PB).
    10. Raza, Syed Ali & Masood, Amna & Benkraiem, Ramzi & Urom, Christian, 2023. "Forecasting the volatility of precious metals prices with global economic policy uncertainty in pre and during the COVID-19 period: Novel evidence from the GARCH-MIDAS approach," Energy Economics, Elsevier, vol. 120(C).
    11. Huang, Jianbai & Dong, Xuesong & Chen, Jinyu & Zhong, Meirui, 2022. "Do oil prices and economic policy uncertainty matter for precious metal returns? New insights from a TVP-VAR framework," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 433-445.
    12. Wen, Jun & Khalid, Samia & Mahmood, Hamid & Zakaria, Muhammad, 2021. "Symmetric and asymmetric impact of economic policy uncertainty on food prices in China: A new evidence," Resources Policy, Elsevier, vol. 74(C).
    13. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2017. "Oil price shocks and policy uncertainty: New evidence on the effects of US and non-US oil production," Energy Economics, Elsevier, vol. 66(C), pages 536-546.
    14. Xiaohui Zhao, 2020. "Do the stock returns of clean energy corporations respond to oil price shocks and policy uncertainty?," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-16, December.
    15. Sheng Cheng & Wei Liu & Qisheng Jiang & Yan Cao, 2023. "Multi–Scale Risk Connectedness Between Economic Policy Uncertainty of China and Global Oil Prices in Time–Frequency Domains," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1593-1616, April.
    16. Kang, Wensheng & de Gracia, Fernando Perez & Ratti, Ronald A., 2019. "The asymmetric response of gasoline prices to oil price shocks and policy uncertainty," Energy Economics, Elsevier, vol. 77(C), pages 66-79.
    17. Claudiu Tiberiu Albulescu, 2020. "Coronavirus and oil price crash," Working Papers hal-02507184, HAL.
    18. Zhang, Yue-Jun & Yan, Xing-Xing, 2020. "The impact of US economic policy uncertainty on WTI crude oil returns in different time and frequency domains," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 750-768.
    19. Qin, Meng & Su, Chi-Wei & Hao, Lin-Na & Tao, Ran, 2020. "The stability of U.S. economic policy: Does it really matter for oil price?," Energy, Elsevier, vol. 198(C).
    20. Ivanovski, Kris & Hailemariam, Abebe, 2022. "Time-varying geopolitical risk and oil prices," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 206-221.

    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:eee:phsmap:v:580:y:2021:i:c:s0378437121004192. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.