IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v130y2024ics0140988324000331.html
   My bibliography  Save this article

Technology shocks and crude oil market connection: The role of climate change

Author

Listed:
  • Salisu, Afees A.
  • Isah, Kazeem
  • Oloko, Tirimisiyu O.

Abstract

We study the connection between global technology shocks (TS) and the crude oil market from 1880 to 2018. Our study utilizes newly constructed global TS datasets that cover OECD countries and 164 countries, while also considering the role of climate change using temperature anomalies. We use the GARCH-MIDAS framework to account for mixed data frequencies and statistical properties of the variables. Our findings show that the link between TS and oil return volatility is episodic, with the relationship becoming apparent after the great depression of the 1930s. Technological innovations appear to moderate oil return volatility. We also estimate the effect of climate change-augmented TS on oil volatility and find that it reduces the potential of technology shocks to lessen oil return volatility. We also find that the out-of-sample forecast gains are realized from observing TS and climate change in the predictability of oil return volatility. Nonetheless, a more general definition of global TS (with 164 countries) offers higher forecast gains than a more restricted global TS (with OECD countries only). Finally, we document the implications of our findings for policy and practice.

Suggested Citation

  • Salisu, Afees A. & Isah, Kazeem & Oloko, Tirimisiyu O., 2024. "Technology shocks and crude oil market connection: The role of climate change," Energy Economics, Elsevier, vol. 130(C).
  • Handle: RePEc:eee:eneeco:v:130:y:2024:i:c:s0140988324000331
    DOI: 10.1016/j.eneco.2024.107325
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988324000331
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2024.107325?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. Salisu, Afees A. & Gupta, Rangan & Demirer, Riza, 2022. "Global financial cycle and the predictability of oil market volatility: Evidence from a GARCH-MIDAS model," Energy Economics, Elsevier, vol. 108(C).
    2. Chen, Xian & Li, Yang & Xiao, Jihong & Wen, Fenghua, 2020. "Oil shocks, competition, and corporate investment: Evidence from China," Energy Economics, Elsevier, vol. 89(C).
    3. Salisu, Afees A. & Gupta, Rangan & Bouri, Elie & Ji, Qiang, 2020. "The role of global economic conditions in forecasting gold market volatility: Evidence from a GARCH-MIDAS approach," Research in International Business and Finance, Elsevier, vol. 54(C).
    4. Leonid Kogan & Dimitris Papanikolaou, 2014. "Growth Opportunities, Technology Shocks, and Asset Prices," Journal of Finance, American Finance Association, vol. 69(2), pages 675-718, April.
    5. Lin, Boqiang & Raza, Muhammad Yousaf, 2020. "Analysis of energy security indicators and CO2 emissions. A case from a developing economy," Energy, Elsevier, vol. 200(C).
    6. O-Chia Chuang & Chenxu Yang, 2022. "Identifying the Determinants of Crude Oil Market Volatility by the Multivariate GARCH-MIDAS Model," Energies, MDPI, vol. 15(8), pages 1-14, April.
    7. Narayan, Seema, 2013. "Foreign exchange markets and oil prices in Asia," Journal of Asian Economics, Elsevier, vol. 28(C), pages 41-50.
    8. Smith, L. Vanessa & Tarui, Nori & Yamagata, Takashi, 2021. "Assessing the impact of COVID-19 on global fossil fuel consumption and CO2 emissions," Energy Economics, Elsevier, vol. 97(C).
    9. Naeem, Muhammad Abubakr & Peng, Zhe & Suleman, Mouhammed Tahir & Nepal, Rabindra & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency connectedness among oil shocks, electricity and clean energy markets," Energy Economics, Elsevier, vol. 91(C).
    10. Alanya-Beltran, Willy, 2022. "Modelling stock returns volatility with dynamic conditional score models and random shifts," Finance Research Letters, Elsevier, vol. 45(C).
    11. Tumala, Mohammed M. & Salisu, Afees A. & Atoi, Ngozi V., 2022. "Oil-growth nexus in Nigeria: An ADL-MIDAS approach," Resources Policy, Elsevier, vol. 77(C).
    12. Xiuwen Chen & Xiaolei Sun & Jun Wang, 2019. "Dynamic Spillover Effect Between Oil Prices and Economic Policy Uncertainty in BRIC Countries: A Wavelet-Based Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(12), pages 2703-2717, September.
    13. Hamilton, James D., 2003. "What is an oil shock?," Journal of Econometrics, Elsevier, vol. 113(2), pages 363-398, April.
    14. Liu, Li & Wang, Yudong & Wu, Chongfeng & Wu, Wenfeng, 2016. "Disentangling the determinants of real oil prices," Energy Economics, Elsevier, vol. 56(C), pages 363-373.
    15. 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.
    16. Sharma, Susan Sunila & Narayan, Paresh Kumar, 2022. "Technology shocks and stock returns: A long-term perspective," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 67-83.
    17. Kong, Dongmin & Yang, Xiandong & Xu, Jian, 2020. "Energy price and cost induced innovation: Evidence from China," Energy, Elsevier, vol. 192(C).
    18. Cristiana Tudor & Andrei Anghel, 2021. "The Financialization of Crude Oil Markets and Its Impact on Market Efficiency: Evidence from the Predictive Ability and Performance of Technical Trading Strategies," Energies, MDPI, vol. 14(15), pages 1-19, July.
    19. Narayan, Paresh Kumar & Gupta, Rangan, 2015. "Has oil price predicted stock returns for over a century?," Energy Economics, Elsevier, vol. 48(C), pages 18-23.
    20. Hakan Yilmazkuday, 2021. "COVID-19 and Daily Oil Price Pass-Through," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 2(1), pages 1-6.
    21. Afees A. Salisu & Juncal Cuñado & Kazeem Isah & Rangan Gupta, 2021. "Oil Price and Exchange Rate Behaviour of the BRICS," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(7), pages 2042-2051, May.
    22. Afees A. Salisu & Rangan Gupta & Elie Bouri & Qiang Ji, 2022. "Mixed‐frequency forecasting of crude oil volatility based on the information content of global economic conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 134-157, January.
    23. Nonejad, Nima, 2021. "The price of crude oil and (conditional) out-of-sample predictability of world industrial production," Journal of Commodity Markets, Elsevier, vol. 23(C).
    24. Bampinas Georgios & Panagiotidis Theodore, 2015. "On the relationship between oil and gold before and after financial crisis: linear, nonlinear and time-varying causality testing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 657-668, December.
    25. Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
    26. Bonato, Matteo, 2019. "Realized correlations, betas and volatility spillover in the agricultural commodity market: What has changed?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 184-202.
    27. Howard Kung & Lukas Schmid, 2015. "Innovation, Growth, and Asset Prices," Journal of Finance, American Finance Association, vol. 70(3), pages 1001-1037, June.
    28. Le, Thai-Ha & Boubaker, Sabri & Bui, Manh Tien & Park, Donghyun, 2023. "On the volatility of WTI crude oil prices: A time-varying approach with stochastic volatility," Energy Economics, Elsevier, vol. 117(C).
    29. Kim, Myung Suk, 2018. "Impacts of supply and demand factors on declining oil prices," Energy, Elsevier, vol. 155(C), pages 1059-1065.
    30. Watanabe, Shingo, 2016. "Technology Shocks and the Great Depression," The Journal of Economic History, Cambridge University Press, vol. 76(3), pages 909-933, September.
    31. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    32. Shuping Shi & Stan Hurn & Peter C B Phillips, 2020. "Causal Change Detection in Possibly Integrated Systems: Revisiting the Money–Income Relationship [Energy Consumption and Economic Growth in the United States]," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(1), pages 158-180.
    33. Kolodziej, Marek & Kaufmann, Robert K. & Kulatilaka, Nalin & Bicchetti, David & Maystre, Nicolas, 2014. "Crude oil: Commodity or financial asset?," Energy Economics, Elsevier, vol. 46(C), pages 216-223.
    34. Yaya, OlaOluwa S. & Ogbonna, Ahamuefula E. & Vo, Xuan Vinh, 2022. "Oil shocks and volatility of green investments: GARCH-MIDAS analyses," Resources Policy, Elsevier, vol. 78(C).
    35. Munir, Qaiser & Lean, Hooi Hooi & Smyth, Russell, 2020. "CO2 emissions, energy consumption and economic growth in the ASEAN-5 countries: A cross-sectional dependence approach," Energy Economics, Elsevier, vol. 85(C).
    36. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Lasisi, Lukman & Olaniran, Abeeb, 2022. "Geopolitical risk and stock market volatility in emerging markets: A GARCH – MIDAS approach," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    37. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    38. Hsu, Po-Hsuan, 2009. "Technological innovations and aggregate risk premiums," Journal of Financial Economics, Elsevier, vol. 94(2), pages 264-279, November.
    39. Smyth, Russell & Narayan, Paresh Kumar, 2018. "What do we know about oil prices and stock returns?," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 148-156.
    40. Fenghua Wen & Jihong Xiao & Xiaohua Xia & Bin Chen & Zhengyan Xiao & Jinyi Li, 2019. "Oil Prices and Chinese Stock Market: Nonlinear Causality and Volatility Persistence," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(6), pages 1247-1263, May.
    41. Li, Zeyun & Qadus, Abdul & Maneengam, Apichit & Mabrouk, Fatma & Shahid, Muhammad Sadiq & Timoshin, Anton, 2022. "Technological innovation, crude oil volatility, and renewable energy dimensions in N11 countries: Analysis based on advance panel estimation techniques," Renewable Energy, Elsevier, vol. 191(C), pages 204-212.
    42. Korotayev, Andrey & Bilyuga, Stanislav & Belalov, Ilya & Goldstone, Jack, 2018. "Oil prices, socio-political destabilization risks, and future energy technologies," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 304-310.
    43. Hou, Aijun & Suardi, Sandy, 2012. "A nonparametric GARCH model of crude oil price return volatility," Energy Economics, Elsevier, vol. 34(2), pages 618-626.
    44. Guillouzouic-Le Corff, Arthur, 2018. "Did oil prices trigger an innovation burst in biofuels?," Energy Economics, Elsevier, vol. 75(C), pages 547-559.
    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. Hu, Jinyan & Wang, Kai-Hua & Su, Chi Wei & Umar, Muhammad, 2022. "Oil price, green innovation and institutional pressure: A China's perspective," Resources Policy, Elsevier, vol. 78(C).
    2. Harrison, Andre & Liu, Xiaochun & Stewart, Shamar L., 2023. "Structural sources of oil market volatility and correlation dynamics," Energy Economics, Elsevier, vol. 121(C).
    3. Afees A. Salisu & Riza Demirer & Rangan Gupta, 2023. "Technological Shocks and Stock Market Volatility Over a Century: A GARCH-MIDAS Approach," Working Papers 202308, University of Pretoria, Department of Economics.
    4. Kumeka, Terver Theophilus & Uzoma-Nwosu, Damian Chidozie & David-Wayas, Maria Onyinye, 2022. "The effects of COVID-19 on the interrelationship among oil prices, stock prices and exchange rates in selected oil exporting economies," Resources Policy, Elsevier, vol. 77(C).
    5. Lu, Xinjie & Ma, Feng & Wang, Tianyang & Wen, Fenghua, 2023. "International stock market volatility: A data-rich environment based on oil shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 184-215.
    6. Salisu, Afees A. & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil prices over 150 years: The role of tail risks," Resources Policy, Elsevier, vol. 75(C).
    7. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Gupta, Rangan & Bouri, Elie, 2024. "Energy-related uncertainty and international stock market volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 280-293.
    8. Arshad, Shaista & Rizvi, Syed Aun R. & Haroon, Omair & Mehmood, Fahad & Gong, Qiang, 2021. "Are oil prices efficient?," Economic Modelling, Elsevier, vol. 96(C), pages 362-370.
    9. Ayinde, Taofeek O. & Olaniran, Abeeb O. & Abolade, Onomeabure C. & Ogbonna, Ahamuefula Ephraim, 2023. "Technology shocks - Gold market connection: Is the effect episodic to business cycle behaviour?," Resources Policy, Elsevier, vol. 84(C).
    10. Hanif, Waqas & Hadhri, Sinda & El Khoury, Rim, 2024. "Quantile spillovers and connectedness between oil shocks and stock markets of the largest oil producers and consumers," Journal of Commodity Markets, Elsevier, vol. 34(C).
    11. Nonejad, Nima, 2020. "A comprehensive empirical analysis of the predictive impact of the price of crude oil on aggregate equity return volatility," Journal of Commodity Markets, Elsevier, vol. 20(C).
    12. Bhagavatula Aruna & H. Rajesh Acharya, 2020. "Do Different Types of Oil Price Shocks Affect the Indian Stock Returns Differently at Firm-level? A Panel Structural Vector Autoregression Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 238-249.
    13. Nonejad, Nima, 2022. "Understanding the conditional out-of-sample predictive impact of the price of crude oil on aggregate equity return volatility," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    14. Hong, Yanran & Cao, Shijiao & Xu, Pengfei & Pan, Zhigang, 2024. "Interpreting the effect of global economic risks on crude oil market: A supply-demand perspective," International Review of Financial Analysis, Elsevier, vol. 91(C).
    15. Aharon, David Y. & Azman Aziz, Mukhriz Izraf & Kallir, Ido, 2023. "Oil price shocks and inflation: A cross-national examination in the ASEAN5+3 countries," Resources Policy, Elsevier, vol. 82(C).
    16. Adeosun, Opeoluwa Adeniyi & Tabash, Mosab I. & Anagreh, Suhaib, 2022. "Oil price and economic performance: Additional evidence from advanced economies," Resources Policy, Elsevier, vol. 77(C).
    17. Wong, Jin Boon & Hasan, Mostafa Monzur, 2021. "Oil shocks and corporate payouts," Energy Economics, Elsevier, vol. 99(C).
    18. Golab, Anna & Bannigidadmath, Deepa & Pham, Thach Ngoc & Thuraisamy, Kannan, 2022. "Economic policy uncertainty and industry return predictability – Evidence from the UK," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 433-447.
    19. Rehman, Mobeen Ur & Vo, Xuan Vinh & McIver, Ron & Kang, Sang Hoon, 2022. "Sensitivity of US sectoral returns to energy commodities under different investment horizons and market conditions," Energy Economics, Elsevier, vol. 108(C).
    20. Ray Ball & Gil Sadka & Ayung Tseng, 2022. "Using accounting earnings and aggregate economic indicators to estimate firm-level systematic risk," Review of Accounting Studies, Springer, vol. 27(2), pages 607-646, June.

    More about this item

    Keywords

    Technology shocks; Crude oil market; Climate change; Predictability; GARCH-MIDAS;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • N7 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

    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:eee:eneeco:v:130:y:2024:i:c:s0140988324000331. 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.elsevier.com/locate/eneco .

    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.