Document Type

Article

Publication Date

Spring 5-5-2017

Advisor

William duPont

Abstract

Though a large body of literature analyzes commodity markets in general as well as the crude oil market, little work looks at the determinants of gasoline price shocks and which variables contributed to specific historical shocks. Using a structural vector autoregression (SVAR) model, one can determine how gasoline prices typically respond to shocks in price determinants, how much each variable, on average, contributes to the variation in gasoline, and which variables influenced gasoline prices during particular shocks. This paper proposes a simple SVAR model of the gasoline market and uses the model to determine what caused gasoline prices to decline between June 2014 and February 2015.

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