Monetary Policy, Commodity Prices and the MYR/USD Exchange Rate: Evidence from a Nonlinear ARDL Model
Authors
Centre for Economic Development and Policy, Universiti Malaysia Sabah, Malaysia\Faculty of Business, Economics and Accountancy, Universiti Malaysia Sabah, Malaysia (Malaysia)
Centre for Economic Development and Policy, Universiti Malaysia Sabah, Malaysia\Faculty of Business, Economics and Accountancy, Universiti Malaysia Sabah, Malaysia (Malaysia)
Centre for Economic Development and Policy, Universiti Malaysia Sabah, Malaysia\Faculty of Business, Economics and Accountancy, Universiti Malaysia Sabah, Malaysia (Malaysia)
Centre for Economic Development and Policy, Universiti Malaysia Sabah, Malaysia\Faculty of Business, Economics and Accountancy, Universiti Malaysia Sabah, Malaysia (Malaysia)
Faculty of Economics, Universitas Sarjanawiyata Tamansiswa, Indonesia (Indonesia)
Faculty of Economics, Universitas Sarjanawiyata Tamansiswa, Indonesia (Indonesia)
Article Information
DOI: 10.47772/IJRISS.2026.1015EC0073
Subject Category: Education
Volume/Issue: 10/15 | Page No: 1018-1032
Publication Timeline
Submitted: 2026-07-08
Accepted: 2026-07-13
Published: 2026-07-27
Abstract
This study examines the effects of monetary policy rates and commodity prices on the MYR/USD exchange rate using monthly data from January 2015 to December 2025. The explanatory variables are the Malaysian Overnight Policy Rate, the United States effective federal funds rate, Brent crude oil prices, and gold prices. A nonlinear autoregressive distributed lag model is applied to assess whether positive and negative changes in these variables produce different exchange rate responses. The Akaike Information Criterion selects the NARDL (2,0,0,1,1) specification. The results indicate strong persistence in MYR/USD movements. Changes in Brent crude oil and gold prices produce significant short-run effects, while changes in the Malaysian Overnight Policy Rate and the United States federal funds rate are statistically insignificant. The Wald tests do not identify significant differences between the positive and negative effects of the explanatory variables. The bounds test also does not provide robust evidence of a stable long-run relationship. The findings suggest that short-run movements in international commodity prices are more closely associated with MYR/USD fluctuations than direct changes in Malaysian and United States policy rates.
Keywords
MYR/USD exchange rate, monetary policy, Brent crude oil price, gold price, nonlinear autoregressive distributed lag model
Downloads
References
1. Butt, S., Ramakrishnan, S., Loganathan, N., & Chohan, M. A. (2020). Evaluating the exchange rate and commodity price nexus in Malaysia: Evidence from the threshold cointegration approach. Financial Innovation, 6, Article 22. https://doi.org/10.1186/s40854-020-00181-6 [Google Scholar] [Crossref]
2. Butt, S., Ramzan, M., Wong, W. K., Chohan, M. A., & Ramakrishnan, S. (2023). Unlocking the secrets of exchange rate determination in Malaysia: A game-changing hybrid model. Heliyon, 9(8), e19140. https://doi.org/10.1016/j.heliyon.2023.e19140 [Google Scholar] [Crossref]
3. Jamal, A., & Bhat, M. A. (2022). COVID-19 pandemic and the exchange rate movements: Evidence from six major COVID-19 hot spots. Future Business Journal, 8, Article 17. https://doi.org/10.1186/s43093-022-00126-8 [Google Scholar] [Crossref]
4. Johari, M. S., Habibullah, M. S., Yusop, Z., & Lee, C. (2017). The study of exchange rates behavior in Malaysia by using NATREX model. Journal of Fundamental and Applied Sciences, 9(3S), 697–715. https://doi.org/10.4314/jfas.v9i3s.55 [Google Scholar] [Crossref]
5. Kok, S. C., Pinjaman, S., & Geetha, C. The Predictability of The Ringgit Malaysia Against the United States Dollar Exchange Rate. International Journal of Research and Innovation in Social Science, 9(15), 1018-1026. [Google Scholar] [Crossref]
6. Mohd Ali, M. F., Syed Mohamad, S. F., Mohammad Yusof, A. S., Ismail, S., & Ibrahim, N. A. (2022). A GARCH study on exchange rate determinants: A case of Malaysia. Journal of Statistical Modeling and Analytics, 4(1), 72–84. https://doi.org/10.22452/josma.vol4no1.6 [Google Scholar] [Crossref]
7. Ng, M. C., & Geetha, C. (2020). The impact of monetary variables on exchange rate in Malaysia from 2013 until 2015. Malaysian Journal of Business and Economics, 7(2), 215–243. https://doi.org/10.51200/mjbe.vi.2893 [Google Scholar] [Crossref]
8. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. https://doi.org/10.1002/jae.616 [Google Scholar] [Crossref]
9. Pinjaman, S., & Kogid, M. (2020). Macroeconomic determinants of house prices in Malaysia. Jurnal Ekonomi Malaysia, 54(1), 153-165. [Google Scholar] [Crossref]
10. Pinjaman, S., Kok, S. C., Aralas, S., Basuki, A. T., Hadi, S., Nugraha, P., & Darsono, S. N. A. C. (2026). Pandemic shocks and time-varying weak-form efficiency in ASEAN foreign exchange markets: An empirical investigation. Optimum: Jurnal Ekonomi dan Pembangunan, 16(1), 138-147. [Google Scholar] [Crossref]
11. Pinjaman, S., Thani, M. A. M., Bakar, M., & Hadi, S. (2025). The Nexus between Governance Quality and Economic Growth of Malaysia: Short-And Long-Run Analyses. International Journal of Research and Innovation in Social Science, 9(15), 115-129. [Google Scholar] [Crossref]
12. Quadry, M. O., Mohamad, A., & Yusof, Y. (2017). On Malaysian Ringgit exchange rate determination and recent depreciation. International Journal of Economics, Management and Accounting, 25(1), 1–26. https://doi.org/10.31436/ijema.v25i1.366 [Google Scholar] [Crossref]
13. Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles and W. C. Horrace (Eds.), Festschrift in honor of Peter Schmidt: Econometric methods and applications (pp. 281–314). Springer. https://doi.org/10.1007/978-1-4899-8008-3_9 [Google Scholar] [Crossref]
14. Taasim, S. I., Pinjaman, S., & Albani, A. (2021). Does energy consumption and trade openness contribute to economic growth in the East Asian growth area?. International Journal of Energy Economics and Policy, 11(2), 23-29. [Google Scholar] [Crossref]
15. Udeagha, M.C. & Ngepah, N. (2021). The asymmetric effect of trade openness on economic growth in South Africa: a nonlinear ARDL approach. Economic Change and Restructuring, 54(2):491-540. [Google Scholar] [Crossref]
16. Yilmazkuday, H. (2022). COVID-19 and exchange rates: Spillover effects of U.S. monetary policy. Atlantic Economic Journal, 50, 67–84. https://doi.org/10.1007/s11293-022-09747-4 [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- Assessment of the Role of Artificial Intelligence in Repositioning TVET for Economic Development in Nigeria
- Teachers’ Use of Assure Model Instructional Design on Learners’ Problem Solving Efficacy in Secondary Schools in Bungoma County, Kenya
- “E-Booksan Ang Kaalaman”: Development, Validation, and Utilization of Electronic Book in Academic Performance of Grade 9 Students in Social Studies
- Analyzing EFL University Students’ Academic Speaking Skills Through Self-Recorded Video Presentation
- Major Findings of The Study on Total Quality Management in Teachers’ Education Institutions (TEIs) In Assam – An Evaluative Study