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Estimating the Elasticity of Demand for Gasoline
Professor Pushan Dutt
The graph below shows the evolution of the price of oil (adjusted for inflation) since
1957. Note a couple of sharp jumps and collapses in the price of oil.
1.
2.
3.

1973: : 2.75 % of global production was withheld; Prices in nominal terms jumped from $3.5 a barrel to $10 a barrel
1979: 5.68 % of global production withheld; Prices in nominal terms jumped from $15 to $32 a barrel.
2007: Oil prices increase from $60 to reach a peak of $128, followed by a rapid collapse Why do we observe such sharp swings in oil prices? The answer lies in the elasticity of demand and supply. For this exercise we will focus on the demand side and estimate the price elasticity of demand for oil. We will focus on the US and use time-series data to estimate this demand function.
Here are the somewhat modest goals of the assignment:
1. To convince you that demand functions and elasticities are measurable, rather than purely abstract concepts.
2. To provide practice in manipulating and interpreting demand functions particularly constant-elasticity demand functions
3. To motivate your study of linear regression in UDJ by providing an example of an application.
I will lead you through the steps without explaining the statistical methods of regression.
Such methods are not part of this course but you will see them in detail in your UDJ core course. © INSEAD

Step 1: Write a Model
The first, and perhaps the most important step, is to understand the determinants of gasoline demand in a country.
Two immediate candidates would be the price of gasoline and income. Other determinants could be the price of new cars, the price of used cars, perhaps some macroeconomic factors such as the interest rate and/or unemployment rate. However, we will keep things simple and estimate demand as a function

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