Examining the Quantile Effects of Political Risk and Crude Oil Price Volatility on Macroeconomic Indicators in Iran

Abstract

Since the energy crisis of the 1970s, significant attention has been directed to the impact of crude oil shocks on the economy. Crude oil price volatility, particularly in 2008, has generated more severe disruptions. Oil shocks or fluctuations in oil prices are considered one of the main causes of many economic crises among both oil-importing and oil-exporting countries. For oil-exporting countries, revenues from oil sales constitute a highly important source of fiscal and foreign exchange income for governments. The dependence of these revenues on global oil prices, and in other words, their exogenous nature, can be regarded as a source of uncertainty and instability in economic policymaking. Therefore, it can be argued that any fluctuation or instability in the global oil market may lead to disequilibrium and even crises, unless proper policies are adopted by governments to address such volatility. The present article examines the quantile effects of political risk and crude oil price volatility on macroeconomic indicators in Iran. This study is classified as applied research and, in terms of nature, it is analytical–descriptive. From the perspective of data collection, it falls under the category of ex-post facto research. The statistical population of the study concerns Iran, covering the time period between 1991 and 2023. As the results and quantile regression estimates indicate, in the lower quantiles (first and second), crude oil price volatility and financial crises have a negative effect, while political stability, rule of law, government effectiveness, regulatory quality, and PSOP have a positive effect on gross domestic product. From the third and fourth quantiles onward, the intensity of these effects decreases. In other words, the studied indices in the first (Q25) and second (Q50) quantiles exhibit a positive temporal correlation with gross domestic product. However, as lagged components move toward the third (Q75) and fourth (Q95) quantiles, the correlation between the studied indices and gross domestic product decreases. Furthermore, the results and quantile regression estimates in the income inequality model show that in the lower quantiles (first and second), crude oil price volatility and financial crises exert a positive effect, while political stability, rule of law, government effectiveness, regulatory quality, and PSOP exert a negative effect on income inequality. From the third and fourth quantiles onward, the intensity of these effects decreases. In other words, the studied indices in the first (Q25) and second (Q50) quantiles have a positive temporal correlation with income inequality. However, as lagged components move toward the third (Q75) and fourth (Q95) quantiles, the correlation between the studied indices and income inequality diminishes.