Oil Prices and Economic Growth in China: A Time-Frequency Analysis

Main Article Content

Thuy Tien Ho
Nguyen Mau Ba Dang
Ngo Thai Hung


This study analyses the inherent evolution dynamics of economic activity and global oil prices in China using the tools of wavelet and wavelet-based VAR-GARCH-BEKK model. Besides, the Wavelet-Granger causality test of Olayeni (2016) provides us further insights into the magnitude and direction of causal connectedness between oil prices and economic activity in China over time and across different frequencies simultaneously. We find that the spillover effects between China’s economic activity and global oil prices are time-varying in different time and frequencies in terms of direction and strength. More accurately, the prices and volatility spillovers between them are significant in the short and medium run but eventually neutral toward the long run. The Wavelet-Granger causality provides us further insights into the lead-lag relationships between oil prices and China’s economic activity from an economic perspective. The dynamic time-frequency association findings suggest crucial implications that might assist policymakers and other market participants in mitigating risk.

Article Details

How to Cite
Thuy Tien Ho, Nguyen Mau Ba Dang, & Ngo Thai Hung. (2024). Oil Prices and Economic Growth in China: A Time-Frequency Analysis. Asian Academy of Management Journal, 29(1), 25–54. https://doi.org/10.21315/aamj2024.29.1.2
Original Articles


Ahmed, F., Osama Daudpota, M., & Kashif, M. (2017). Oil price shocks and industry level production using vector autoregression: Empirical evidence from Pakistan. Global Journal of Business Research, 11(3), 13−25.

Allen, D. E., Amram, R., & McAleer, M. (2013). Volatility spillovers from the Chinese stock market to economic neighbours. Mathematics and Computers in Simulation, 94, 238−257. https://doi.org/10.1016/j.matcom.2013.01.001

Aloui, C., Hkiri, B., Hammoudeh, S., & Shahbaz, M. (2018). A multiple and partial wavelet analysis of the oil price, inflation, exchange rate, and economic growth nexus in Saudi Arabia. Emerging Markets Finance and Trade, 54(4), 935−956. https://doi.org/10.1080/1540496X.2017.1423469

Awartani, B., Maghyereh, A., & Ayton, J. (2020). Oil price changes and industrial output in the MENA region: Nonlinearities and asymmetries. Energy, 196, 117043. https://doi.org/10.1016/j.energy.2020.117043

Baz, K., Xu, D., Ali, H., Ali, I., Khan, I., Khan, M. M., & Cheng, J. (2020). Asymmetric impact of energy consumption and economic growth on ecological footprint: Using asymmetric and nonlinear approach. Science of the Total Environment, 718, 137364. https://doi.org/10.1016/j.scitotenv.2020.137364

Benhmad, F. (2013). Dynamic cyclical comovements between oil prices and US GDP: A wavelet perspective. Energy Policy, 57, 141−151. https://doi.org/10.1016/j.enpol.2013.01.017

Chen, J., Zhu, X., & Li, H. (2020). The pass-through effects of oil price shocks on China’s inflation: A time-varying analysis. Energy Economics, 86, 104695. https://doi.org/10.1016/j.eneco.2020.104695

Chen, J. Y., Zhu, X. H., & Zhong, M. R. (2021). Time‐varying effects and structural change of oil price shocks on industrial output: Evidence from China’s oil industrial chain. International Journal of Finance and Economics, 26(3), 3460−3472. https://doi.org/10.1002/ijfe.1970

Chen, X., Sun, X., & Wang, J. (2019). Dynamic spillover effect between oil prices and economic policy uncertainty in BRIC countries: A wavelet-based approach. Emerging Markets Finance and Trade, 55(12), 2703−2717. https://doi.org/10.1080/1540496X.2018.1564904

Cobo-Reyes, R., & Quirós, G. P. (2005). The effect of oil price on industrial production and on stock returns. Working Paper 05/18, Universidad de Granada.

Cross, J., & Nguyen, B. H. (2017). The relationship between global oil price shocks and China’s output: A time-varying analysis. Energy Economics, 62, 79−91. https://doi.org/10.1016/j.eneco.2016.12.014

Cuñado, J., & de Gracia, F. P. (2003). Do oil price shocks matter? Evidence for some European countries. Energy Economics, 25(2), 137−154. https://doi.org/10.1016/S0140-9883(02)00099-3

Dong, M., Chang, C. P., Gong, Q., & Chu, Y. (2019). Revisiting global economic activity and crude oil prices: A wavelet analysis. Economic Modelling, 78, 134−149. https://doi.org/10.1016/j.econmod.2018.08.012

Elder, J. (2018). Oil price volatility: Industrial production and special aggregates. Macroeconomic Dynamics, 22(3), 640−653. https://doi.org/10.1017/S136510051600047X

Engle, R., & Kroner, F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11(1), 122−150. https://doi.org/10.1017/S0266466600009063

Eryiğit, M. (2012). The dynamical relationship between oil price shocks and selected macroeconomic variables in Turkey. Economic Research-Ekonomska Istraživanja, 25(2), 263−276. https://doi.org/10.1080/1331677X.2012.11517507

Jo, S. (2014). The effects of oil price uncertainty on global real economic activity. Journal of Money, Credit and Banking, 46(6), 1113−1135. https://doi.org/10.1111/jmcb.12135

Jo, S., Karnizova, L., & Reza, A. (2019). Industry effects of oil price shocks: A re- examination. Energy Economics, 82, 179−190. https://doi.org/10.1016/j.eneco.2018.12.010

Hamilton, J. D. (1983). Oil and the macroeconomy since World War II. Journal of Political Economy, 91(2), 228−248. https://doi.org/10.1086/261140

Hamilton, J. D. (2011). Nonlinearities and the macroeconomic effects of oil prices. Macroeconomic Dynamics, 15, 364–378. https://doi.org/10.1017/S1365100511000307

Hatemi-J, A. (2012). Asymmetric causality tests with an application. Empirical Economics, 43(1), 447−456. https://doi.org/10.1007/s00181-011-0484-x

He, Z. (2020). Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect. International Review of Economics and Finance, 66, 131−153. https://doi.org/10.1016/j.iref.2019.11.004

Herrera, A. M., Lagalo, L. G., & Wada, T. (2011). Oil price shocks and industrial production: Is the relationship linear? Macroeconomic Dynamics, 15(S3), 472−497. https://doi.org/10.1017/S1365100511000290

Hooker, M. A. (1996). What happened to the oil price-macroeconomy relationship? Journal of Monetary Economics, 38(2), 195−213. https://doi.org/10.1016/S0304-3932(96)01281-0

Huang, B. N., Hwang, M. J., & Peng, H. P. (2005). The asymmetry of the impact of oil price shocks on economic activities: An application of the multivariate threshold model. Energy Economics, 27(3), 455−476. https://doi.org/10.1016/j.eneco.2005.03.001

Hung, N. T. (2019). An analysis of CEE equity market integration and their volatility spillover effects. European Journal of Management and Business Economics, 29(1), 23−40. https://doi.org/10.1108/EJMBE-01-2019-0007

Hung, N. T. (2020). Time-frequency nexus between Bitcoin and developed stock markets in the Asia-Pacific. The Singapore Economic Review, 1−26. https://doi.org/10.1142/S0217590820500691

Hung, N. T. (2021). Volatility behaviour of the foreign exchange rate and transmission among Central and Eastern European countries: Evidence from the EGARCH model. Global Business Review, 22(1), 36−56. https://doi.org/10.1177/0972150918811713

Hung, N. T. (2022a). Time-frequency co-movements between biomass energy consumption and human development in Brics countries. Problemy Ekorozwoju, 17(1), 196−210.

Hung, N. T. (2022b). Asymmetric connectedness among S&P 500, crude oil, gold and Bitcoin. Managerial Finance, 48(4), 587−610. https://doi.org/10.1108/MF-08-2021-0355

Kilian L., & Vigfusson R. (2011). Nonlinearities in the oil price-output relationship. Macroeconomic Dynamics, 15(3), 337−363. https://doi.org/10.1017/S1365100511000186

Lardic, S., & Mignon, V. (2008). Oil prices and economic activity: An asymmetric cointegration approach. Energy Economics, 30(3), 847−855. https://doi.org/10.1016/j.eneco.2006.10.010

Lee, C. C., Lee, C. C., & Li, Y. Y. (2021). Oil price shocks, geopolitical risks, and green bond market dynamics. The North American Journal of Economics and Finance, 55, 101309. https://doi.org/10.1016/j.najef.2020.101309

Mehrara, M., & Sarem, M. (2009). Effects of oil price shocks on industrial production: Evidence from some oil‐exporting countries. OPEC Energy Review, 33(3−4), 170−183. https://doi.org/10.1111/j.1753-0237.2009.00167.x

Olayeni, O. R. (2016). Causality in continuous wavelet transform without spectral matrix factorization: Theory and application. Computational Economics, 47(3), 321−340. https://doi.org/10.1007/s10614-015-9489-4

Peng, Y., Chen, W., Wei, P., & Yu, G. (2020). Spillover effect and Granger causality investigation between China’s stock market and international oil market: A dynamic multiscale approach. Journal of Computational and Applied Mathematics, 367, 112460. https://doi.org/10.1016/j.cam.2019.112460

Raza, S. A., Shahbaz, M., Amir-ud-Din, R., Sbia, R., & Shah, N. (2018). Testing for wavelet based time-frequency relationship between oil prices and US economic activity. Energy, 154, 571−580. https://doi.org/10.1016/j.energy.2018.02.037

Reboredo, J. C., Rivera-Castro, M. A., & Ugolini, A. (2017). Wavelet-based test of co-movement and causality between oil and renewable energy stock prices. Energy Economics, 61, 241−252. https://doi.org/10.1016/j.eneco.2016.10.015

Rua, A. (2013). Worldwide synchronization since the nineteenth century: A wavelet-based view. Applied Economics Letters, 20(8), 773−776. https://doi.org/10.1080/13504 851.2012.744129

Sakashita, Y., & Yoshizaki, Y. (2016). The effects of oil price shocks on IIP and CPI in emerging countries. Economies, 4(4), 20. https://doi.org/10.3390/economies4040020

Santini, D. (1985). The energy-squeeze model: Energy price dynamics in US business cycles. International Journal of Energy Systems, 5, 18−25.

Scholtens, B., & Yurtsever, C. (2012). Oil price shocks and European industries. Energy Economics, 34(4), 1187−1195. https://doi.org/10.1016/j.eneco.2011.10.012

Shahbaz, M., Van Hoang, T. H., Mahalik, M. K., & Roubaud, D. (2017). Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis. Energy Economics, 63, 199−212. https://doi.org/10.1016/j.eneco.2017.01.023

Shi, S., Hurn, S., & Phillips, P. C. (2020). Causal change detection in possibly integrated systems: Revisiting the money–income relationship. Journal of Financial Econometrics, 18(1), 158−180. https://doi.org/10.1093/jjfinec/nbz004

Tang, W., Wu, L., & Zhang, Z. (2010). Oil price shocks and their short-and long-term effects on the Chinese economy. Energy Economics, 32, S3−S14. https://doi.org/10.1016/j.eneco.2010.01.002

Taspinar, N. Azin, V., & Gokmenoglu, K. (2015). The relationship between industrial production, GDP, inflation and oil price: The case of Turkey. Procedia Economics and Finance, 25, 497−503. https://doi.org/10.1016/S2212-5671(15)00762-5

Tiwari, A. K., Olayeni, R. O., Olofin, S. A., & Chang, T. (2019). The Indian inflation-growth relationship revisited: Robust evidence from time-frequency analysis. Applied Economics, 51(51), 5559−5576. https://doi.org/10.1080/00036846.2019.1616065

Tugcu, C. T., Ozturk, I., & Aslan, A. (2012). Renewable and non-renewable energy consumption and economic growth relationship revisited: Evidence from G7 countries. Energy Economics, 34(6), 1942−1950. https://doi.org/10.1016/j.eneco.2012.08.021

Yıldırım, E., & Öztürk, Z. (2014). Oil price and industrial production in G7 countries: Evidence from the asymmetric and non-asymmetric causality tests. Procedia- Social and Behavioral Sciences, 143, 1020−1024. https://doi.org/10.1016/j.sbspro.2014.07.547

Yu, L., Zha, R., Stafylas, D., He, K., & Liu, J. (2019). Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR- BEKK-GARCH models. International Review of Financial Analysis, 68, 101280. https://doi.org/10.1016/j.irfa.2018.11.007