Economic policy transmission and economic misery in Nigeria

This dataset supports the empirical investigation of whether economic policy shocks and their transmission mechanisms significantly influence economic misery in Nigeria. The study hypothesizes that changes in monetary policy, exchange rate volatility, and economic policy uncertainty transmit shocks across the macroeconomic system and affect economic misery. The dataset contains annual observations for the Economic Policy Uncertainty Index (EPUI), Exchange Rate Volatility (EXRV), Monetary Policy Rate (MPR), Oil Price (OILP), and Economic Misery Index (MISERY) over the study period. The data were compiled from publicly available and reputable secondary sources, with the respective sources identified in the accompanying documentation and research article. Exchange rate volatility was derived from exchange rate data using the specified volatility estimation procedure, while the Economic Misery Index was constructed from its underlying macroeconomic components according to the methodology adopted in the study. The remaining variables were obtained from their respective official or established data sources. The dataset was used to examine the dynamic interactions and transmission of shocks among economic policy variables and economic misery. The analysis shows that economic policy shocks are interconnected rather than operating independently. In particular, exchange rate volatility emerges as an important transmitter of shocks, while economic policy uncertainty predominantly absorbs shocks from other variables. Monetary policy also participates in shock transmission, although its role is comparatively weaker. These findings indicate that macroeconomic instability in Nigeria is influenced by interconnected policy and market shocks, with exchange rate conditions playing a particularly important role. Researchers can use the dataset to replicate the empirical analysis, examine the relationships among economic policy shocks and economic misery, or conduct further time-series and connectedness analyses. Variable names and measurements should be interpreted according to the definitions and methodology provided in the accompanying study.