IMPACT OF OIL SHOCKS ON THE OIL, AGRICULTURAL AND FOOD INDUSTRY - QUANTILE AND OLS REGRESSION

Sanja Bakić

doi:10.59267/ekoPolj2401293B

Authors

Sanja Bakić Phd student, Faculty of Economics, University of Novi Sad, Novi Sad, Serbia https://orcid.org/0000-0003-2706-519X

DOI:

https://doi.org/10.59267/ekoPolj2401293B

Keywords:

oil, oil industry, agriculture, OLS, quantile regression

Abstract

This paper determines the impact of Brent oil shocks on the price of shares of companies from the oil, agricultural and food industries that includes the period of the COVID-19 pandemic. For this purpose, they use a quantile regression approach and compare its findings with a standard Ordinary Least Squares (OLS) regression model. Moreover, in this research they use quantile regression, which enables them to analyze different quantiles of share prices of companies from the oil industry, the agricultural industry, and the food industry. They observe three different periods - a period of recession, a normal period and a period of expansion. Finally, empirical evaluations using quantile regression and OLS models show us that shocks from the oil market are more pronounced in companies from the oil industry compared to companies from the agricultural and food industries. The findings of this research provide important information for investors, economic policy makers, and other parties.

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