Oil Price Implications for the Petroleum and Pharmaceutical Industry: the Quantile Regression Approach

In the study, quantile regression (QR) is employed as the primary research tool, with ordinary least squares (OLS) regression used for comparison purposes. The motivation for this research stems from conflicting findings in existing literature regarding the spillover effects of Brent crude oil prices for the pharmaceutical industry. Findings from the QR analysis indicate that more substantial spillover effects occur in the tail quantiles, specifically during periods of economic crisis and prosperity. Recommendations for future research should focus on gaining a deeper understanding of the mechanisms underlying the differential responses of oil and pharmaceutical companies to oil price fluctuations, as well as identifying additional factors that may moderate these effects. In light of the study's findings, it is recommended to consider different regulatory approaches that could help reduce the sensitivity of oil companies to oil price oscillations. Additionally, support for business diversification strategies is advised to mitigate potential economic risks for both industries.