Gulf Shock Transmission and Macroeconomic Fragility in Developing Economies: A Bayesian-Calibrated Monte Carlo Vulnerability Assessment

This dataset supports the research paper titled “Gulf Shock Transmission and Macroeconomic Fragility in Developing Economies: A Bayesian-Calibrated Monte Carlo Vulnerability Assessment.” The study examines how a Gulf-centred geopolitical shock may transmit to selected developing economies through GCC remittance exposure, energy-import pressure, shipping and logistics disruption, external-demand compression, foreign-exchange stress, inflation, reserve loss, policy-rate response, growth vulnerability and governance-fiscal fragility. The dataset covers six economies: Pakistan, Bangladesh, Sri Lanka, India, the Philippines and Bhutan. It includes raw remittance source files, processed remittance exposure files, macroeconomic and structural exposure inputs, recursive simulation outputs, Bayesian-calibrated Monte Carlo results, final tables, figures, audit files and R scripts used to reproduce the analysis. GCC remittance exposure is calculated as GCC-origin remittances divided by total recipient-country remittances, using Saudi Arabia, United Arab Emirates, Kuwait, Qatar, Oman and Bahrain as GCC source economies. The research develops a recursive Macroeconomic Vulnerability Index (MVI) and applies symmetric and asymmetric Gulf-shock scenarios. The Bayesian-calibrated Monte Carlo layer uses 10,000 draws to generate median vulnerability estimates, 90% credible intervals, uncertainty widths and rank-probability matrices. The results show a stable but intensity-sensitive vulnerability hierarchy, with Pakistan and Sri Lanka emerging as the highest-vulnerability cases under the extreme-combined scenario, followed by Bangladesh, India, the Philippines and Bhutan. The dataset is organised to allow replication of the paper’s tables, figures and Monte Carlo results. The R scripts can be run from the IRANPAK project folder to reproduce the cleaned remittance architecture, scenario-simulation outputs, Bayesian uncertainty tables, figures and audit logs. The files are provided for transparency, verification and future extension of the study, including possible full-panel macroeconomic modelling, alternative governance-fiscal amplification structures and robustness analysis. Data sources include public central-bank remittance publications, World Bank remittance and macroeconomic data, IMF and UNCTAD policy sources, and processed scenario-simulation files generated by the authors. Users should cite the original public data sources where relevant and cite this dataset when using the processed replication files, simulation outputs or R scripts.