Hurricane Sandy: Supply, Demand and Appropriate Responses to the Gas Shortage

https://hbsp.harvard.edu/import/1170966

1. Read the case carefully and determine the issue.
2. With the help of appropriate demand and supply graphs, show that was it a demand issue or supply issue or both? What would have happened to equilibrium price and quantity?
3. How supplier responded to demand? Why did some people think that price gouging was happening? Do you agree with this statement?
4. What the government did, and do you think it was an appropriate response?
5. What are the future lessons for people and government to deal with these types of supply/demand issues?

Estimation of Energy Demand Function

Use the dataset “assignment-data” available on LMS. It has a data by year on US gasoline consumption

(G), gasoline prices (PG), per-capita income (Y), price of new cars (PNC), price of used cars (PUC), and population (POP). By using the data, perform the following tasks:

1. Calculate gasoline per capita consumption (GPC) and draw a line graph and interpret the trend.

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Economic theory suggest the following, in relation to a demand function for the gasoline:

GPC = f(PG, Y, PNC, PUC)

With a regression model in log form as follows:

log GPC = logA + B1 log PG + B2 log Y + B3 log PNC + B4 log PUC

(1)

1. Determine the signs of regression coefficients using economic theory and provide reasoning
2. Run a simple regression model (by using equation 1 above) and interpret regression coefficients and elasticities and provide reasoning for each coefficient. Are the regression coefficients similar to the economic theory? If not, what could be the reason? Consult some academic literature.

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1. Now create previous year gasoline consumption (LPrevGPC) variable as an independent variable and re-run regression model (equation 2) as follows:

log GPC = logA+B1 log PG+B2 log Y +B3 log PNC+B4 log PUC+B5 log PrevGPC,

(2)

Where the expression B1/(1 − B5) is in fact long run elasticity of demand. Calculate this long run elasticity of demand and interpret the number by comparing it with short run price elasticity. What conclusion would you draw from these estimates?

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• What sort of recommendations you would make as an analyst to an energy firm operating in the USA in relation to the pricing and disposable income in particular.

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