The Predictive Power of Monthly Interest Rate Differential (IRD) Changes on USD/PHP Exchange Rate Movements (2014–2024)

Rustum D Gevero and Daryl T Buenavista
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Rustum D Gevero: School of Business and Management, Xavier University – Ateneo de Cagayan, Cagayan de Oro City, Philippines.
Daryl T Buenavista: School of Business and Management, Xavier University – Ateneo de Cagayan, Cagayan de Oro City, Philippines.

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Abstract: Background: Fluctuations in the USD/PHP exchange rate influence investment decisions, trade competitiveness, and financial market stability in the Philippines. Understanding how Interest Rate Differentials (IRD) affect these exchange rate movements, including possible delayed effects, is therefore important for investors, businesses, and policymakers managing foreign currency exposure. Aims: This study examines the predictive power of monthly changes in the Interest Rate Differential (IRD) between the Philippines and the United States on USD/PHP exchange rate movements from 2014 to 2024. Study Design: Quantitative, correlational, and regression-based research using monthly data. Place and Duration of Study: Philippines and United States, January 2014 to December 2024. Methodology: Monthly data on Philippine and U.S. interest rates and the USD/PHP exchange rate were analyzed using Pearson correlation and simple linear regression across seven lag structures (0–6 months). Forecast accuracy was evaluated using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). Results: Changes in the IRD showed a statistically significant but weak relationship with USD/PHP movements only at the four-month lag (B = −1.211, P = .003, R² = .069). All other lag structures were not significant. The four-month lag model yielded the lowest forecast errors (MAE = .549; RMSE = .762). Conclusion: IRD has a delayed but weak predictive effect on USD/PHP exchange rate movements, with the four-month lag producing the strongest and only statistically significant result. IRD should be treated as a supplementary indicator rather than a standalone forecasting tool.

Date: 2026-05-26
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Published in Asian Journal of Economics, Business and Accounting, 2026, 26 (6), pp.24-31. ⟨10.9734/ajeba/2026/v26i62287⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05635347

DOI: 10.9734/ajeba/2026/v26i62287

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