Fractional Integration Analysis of Rare Earth Material Price Dynamics for Mechanical System Design and Sustainable Manufacturing
DOI:
https://doi.org/10.31181/rme584Keywords:
Rare Earth Elements, Price Persistence, Fractional Integration, Long Memory, Energy TransitionAbstract
Rare earth elements (REEs) are strategic resources essential for defense mechanical systems, digital industries, and clean energy technologies. This study examines the persistence and long-term dynamics of REE prices from September 2012 to May 2022 using the ARFIMA mechanical model, which captures both short- and long-memory behavior. Additionally, descriptive statistics and fractional integration analysis are employed to evaluate distributional characteristics and interrelationships among REE prices. The descriptive findings reveal notable heterogeneity across elements, with neodymium, praseodymium, terbium, and dysprosium exhibiting higher mean values, greater volatility, and positive skewness, indicating higher sensitivity to market shocks. The ARFIMA results show that most REE prices are fractionally integrated and mean-reverting, suggesting that shocks are largely transitory. However, neodymium, praseodymium, terbium, and dysprosium display high persistence and near unit-root behavior, implying that shocks may have permanent effects. These findings highlight the importance of critical REEs for supply chain resilience, risk management, and sustainable energy transition policies.
References
Abo-Khalil, A. G. (2024). Integrating sustainability into higher education challenges and opportunities for universities worldwide. Heliyon, 10(9). https://doi.org/10.1016/j.heliyon.2024.e29946
Akaike, H. (1979). A Bayesian extension of the minimum AIC procedure of autoregressive model fitting. Biometrika, 66(2), 237-242. https://doi.org/10.1093/biomet/66.2.237
Apergis, E., & Apergis, N. (2017). The role of rare earth prices in renewable energy consumption: The actual driver for a renewable energy world. Energy Economics, 62, 33-42. https://doi.org/10.1016/j.eneco.2016.12.015
Chung, R. C., Ip, W., & Chan, S. L. (2009). An ARIMA-intervention analysis model for the financial crisis in China's manufacturing industry. International Journal of Engineering Business Management, 1, 5. https://doi.org/10.5772/6785
Claudio-Quiroga, G., Gil-Alana, L. A., & Maiza-Larrarte, A. (2023). Mineral prices persistence and the development of a new energy vehicle industry in China: A fractional integration approach. Resources Policy, 82, 103433. https://doi.org/10.1016/j.resourpol.2023.103433
Deng, S., Prodius, D., Nlebedim, I. C., Huang, A., Yih, Y., & Sutherland, J. W. (2021). A dynamic price model based on supply and demand with application to techno-economic assessments of rare earth element recovery technologies. Sustainable Production and Consumption, 27, 1718-1727. https://doi.org/10.1016/j.spc.2021.04.013
Diebold, F. X., & Rudebusch, G. D. (1991). Forecasting output with the composite leading index: A real-time analysis. Journal of the American Statistical Association, 86(415), 603-610. https://doi.org/10.1080/01621459.1991.10475085
Ding, Z., Granger, C. W., & Engle, R. F. (1993). A long memory property of stock market returns and a new model. Journal of empirical finance, 1(1), 83-106. https://doi.org/10.1016/0927-5398(93)90006-D
Dziubaniuk, O., Ivanova-Gongne, M., & Nyholm, M. (2023). Learning and teaching sustainable business in the digital era: a connectivism theory approach. International journal of educational technology in Higher education, 20(1), 20. https://doi.org/10.1186/s41239-023-00390-w
Fan, J. H., Omura, A., & Roca, E. (2023). Geopolitics and rare earth metals. European Journal of Political Economy, 78, 102356. https://doi.org/10.1016/j.ejpoleco.2022.102356
Ferreira, G., & Critelli, J. (2022). China’s global monopoly on rare-earth elements. The US Army War College Quarterly: Parameters, 52(1), 57-72. https://doi.org/10.55540/0031-1723.3129
García, M. V. R., Krzemień, A., del Campo, M. Á. M., García-Miranda, C. E., & Lasheras, F. S. (2018). Rare earth elements price forecasting by means of transgenic time series developed with ARIMA models. Resources Policy, 59, 95-102. https://doi.org/10.1016/j.resourpol.2018.06.003
Haque, N., Hughes, A., Lim, S., & Vernon, C. (2014). Rare earth elements: Overview of mining, mineralogy, uses, sustainability and environmental impact. Resources, 3(4), 614-635. https://doi.org/10.3390/resources3040614
Hassler, U., & Wolters, J. (1994). On the power of unit root tests against fractional alternatives. Economics letters, 45(1), 1-5. https://doi.org/10.1016/0165-1765(94)90049-3
Issler, J. V., Rodrigues, C., & Burjack, R. (2014). Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons. Journal of international money and Finance, 42, 310-335. https://doi.org/10.1016/j.jimonfin.2013.08.017
Jowitt, S. M. (2022). Mineral economics of the rare-earth elements. MRS Bulletin, 47(3), 276-282. https://doi.org/10.1557/s43577-022-00289-3
Larson, A. M., Balema, T. A., Zahl, P., Schilling, A. C., Stacchiola, D. J., & Sykes, E. C. H. (2020). Hypothetical Efficiency of Electrical to Mechanical Energy Transfer during Individual Stochastic Molecular Switching Events. ACS nano, 14(12), 16558-16564. https://doi.org/10.1021/acsnano.0c04082
Malhotra, R., Massoudi, M., & Jindal, R. (2023). Shifting from traditional engineering education towards competency-based approach: The most recommended approach-review. Education and Information Technologies, 28(7), 9081-9111. https://doi.org/10.1007/s10639-022-11568-6
Mancheri, N. A. (2016). An overview of Chinese rare earth export restrictions and implications. Rare Earths Industry, 21-36. https://doi.org/10.1016/B978-0-12-802328-0.00002-4
Pawar, G., & Ewing, R. C. (2022). Recent advances in the global rare-earth supply chain. MRS Bulletin, 47(3), 244-249. https://doi.org/10.1557/s43577-022-00305-6
Sowell, F. (1992). Maximum likelihood estimation of stationary univariate fractionally integrated time series models. Journal of econometrics, 53(1-3), 165-188. https://doi.org/10.1016/0304-4076(92)90084-5
Wei, L., Zhang, W., & Lin, C. (2023). The study of the effectiveness of design-based engineering learning: the mediating role of cognitive engagement and the moderating role of modes of engagement. Frontiers in psychology, 14, 1151610. https://doi.org/10.3389/fpsyg.2023.1151610
Wood, S. A. (1990). The aqueous geochemistry of the rare-earth elements and yttrium: 1. Review of available low-temperature data for inorganic complexes and the inorganic REE speciation of natural waters. Chemical Geology, 82, 159-186. https://doi.org/10.1016/0009-2541(90)90080-Q
Zheng, B., Zhang, Y. W., Qu, F., Geng, Y., & Yu, H. (2022). Do rare earths drive volatility spillover in crude oil, renewable energy, and high-technology markets?—A wavelet-based BEKK-GARCH-X approach. Energy, 251, 123951. https://doi.org/10.1016/j.energy.2022.123951
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Reports in Mechanical Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.