Structural Fragmentation and Monetary Policy Transmission: Evidence from Pakistan's Dual Security-Energy Shock

Abstract

This study examines whether structural fragmentation alters monetary policy transmission in Pakistan. Unlike conventional approaches that treat geopolitical risk as an episodic disturbance, the study conceptualizes fragmentation as a persistent condition arising from security pressures and energy-corridor vulnerabilities. Using monthly data and an autoregressive distributed lag framework, the analysis investigates the transmission of changes in the State Bank of Pakistan's policy rate to market interest rates, the exchange rate, and import prices. The results indicate that monetary policy significantly affects market interest rates and exchange-rate dynamics; however, the strength of transmission varies with the level of structural fragmentation. Security and energy fragmentation weaken the pass-through from the policy rate to market interest rates, while energy fragmentation increases exchange-rate pressure and amplifies exchange-rate pass-through to import prices. These findings suggest that monetary policy becomes less predictable during prolonged security and energy disruption. The study contributes to the emerging literature on geopolitical fragmentation by distinguishing persistent structural pressures from temporary geopolitical shocks and by demonstrating their implications for monetary-policy effectiveness in an energy-importing emerging economy.

References

Ahmad, B., Dawood, M. N., Waheed, M., Abrar, A., & Bibi, N. (2025). The central bankers’ role and monetary policy: A comparative case study of the ECB, Federal Reserve, and State Bank of Pakistan during crisis periods. International Journal of Business and Management Sciences, 6(1), 572–586.

Al Kium, A., Sarker, S., Shikha, S. A., Kamal, M. A. T., Jabed, M. I. K., Munifa, N. K., ... & John, D. B. (2023). Health equity and digital disparities in cancer screening and cardiovascular care across socioeconomic and ethnic groups: A systematic review. Vascular and Endovascular Review, 6(2), 35–44.

Caldara, D., & Iacoviello, M. (2022). Measuring geopolitical risk. American Economic Review, 112(4), 1194–1225. https://doi.org/10.1257/aer.20191823

Dawn, S., Vadlamudi, B., Vital, M. L. N., Das, S. S., Rao, K. D., Al Mansur, A., & Ustun, T. S. (2026). Enhancing grid stability and sustainability in electrical markets: A review on the synergy of renewable energy and electric vehicles. Energy Exploration & Exploitation, 44(2), 1021–1066. https://doi.org/10.1177/01445987251383177

Hamid, N., & Syed, M. (2026). Monetary policy in a balance-of-payments-constrained economy: Fiscal dominance, external vulnerability, and the case for caution in Pakistan. In Policy challenges for macroeconomic management and growth in Pakistan (p. 49).

Hanif, M. N. (2014). Monetary policy experience of Pakistan.

Hasan, M. A., Khan, A. H., Pasha, H. A., Rasheed, M. A., & Husain, A. M. (1995). What explains the current high rate of inflation in Pakistan? [With comments]. The Pakistan Development Review, 34(4), 927–943.

Ijaz, T., Hafiz, Z. A., & Khan, A. M. (2019). Contextualization of IMF in Pakistan: A discourse analysis of print media. Journal of the Research Society of Pakistan, 56(2), 219.

Iqbal, U. (2025). AI-powered supplier risk intelligence: Predicting financial and geopolitical supply chain disruptions in US critical industries. Journal of Engineering and Computational Intelligence Review, 3(2), 173–193.

Jabed, M. I. K. (2024). Stock market price prediction using machine learning techniques. American International Journal of Sciences and Engineering Research, 7(1), 1–6.

Jabed, M. I. K., Sirazy, M. R. M., Mandal, S., Akter, S. A., Hassan, A., & Esa, H. (2026). Developing AI-based financial forecasting and cybersecurity systems for the US digital economy. Frontiers in Computer Science and Artificial Intelligence, 5(5), 30–38.

Jordà, Ò. (2005). Estimation and inference of impulse responses by local projections. American Economic Review, 95(1), 161–182. https://doi.org/10.1257/0002828053828518

Mahmood, A. (2025). Monetary policy transmission mechanism in Pakistan: What we know and what we need to know?

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

Rahman, M. A., Devnath, R. K., Niloy, S. B., Mehedi, C. M., Chowdhury, T. H., & Jabed, M. I. K. (2025, October). A stacking ensemble framework for predicting employee turnover: Explainable AI with SHAP. In 2025 IEEE 2nd International Conference on Computing, Applications and Systems (COMPAS) (pp. 1–6). IEEE.

Renzhi, N., & Beirne, J. (2025). Global shocks and monetary policy transmission in emerging markets. Emerging Markets Finance and Trade, 61(3), 786–803. https://doi.org/10.1080/1540496X.2024.2443621

Rizvi, M., & Hussain, A. (2026). Projecting agency: Pakistan’s geoeconomic discourse in an era of great power competition. St. Antony’s International Review, 21(1).

State Bank of Pakistan. (2026). Monetary policy report: February 2026. State Bank of Pakistan.