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The Impact of Fossil Fuel Prices on Alternative Energy Stocks

By Roman Milioti

The purpose of this paper is to determine if fossil fuel price fluctuations can influence the price alternative energy stock valuations. Employing a Lag Augmented VAR analysis, the research analyzes how natural gas and WTI oil prices impact the price of an alternative energy index. The analysis reveals that neither the price of natural gas nor the price of WTI have a statistically significant positive impact of the price of the alternative energy index. The results are attributed to natural gas and alternative energy acting as both substitutes and compliments given renewable
energy intermittency.

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Advisor: Gale Boyd | JEL Codes: G12, Q42

The Effects of Global Oil Price on Government Investment the Nigerian Agricultural Sector

By Chuka Obiofuma

Nigeria’s heavy dependence on oil makes it a prime target for the resource curse. The occurance of this phenomenon in Nigeria could mean that there is capital flight from the agricultural sectors of the economy when the oil sector increases in profitability. This would disproportionately hurt the poor of Nigeria who depend on agriculture for their livelihood. This work investigates whether or not the Nigerian government, the largest investor into the Agricultural sector, tends to increase or decrease its investment in the agricultural sector as global oil prices rise. Using data from the years 1978-2014, the results of this paper show that as oil prices increase so too does the Nigerian government’s investment in its agricultural sector.

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Advisor: Alison Hagy, Gale Boyd | JEL Codes: I28, O13, Q43 | Tagged:  Agriculture, Energy, Government Policy

Identifying Supply and Demand Elasticities of Iron Ore

By Zhirui zhu

This paper utilizes instrumental variables and joint estimation to construct efficiently identified estimates of supply and demand equations for the world iron ore market under the assumption of perfect competition. With annual data spanning 1960-2010, I found an upward sloping supply curve and a downward sloping demand curve. Both of the supply and demand curves are efficiently identified using a 3SLS model. The instruments chosen are strong and credible. Point estimation of the long-run price elasticities of supply and demand are 0.45 and -0.24 respectively, indicating inelastic supply and demand market dynamics. Back-tests and forecasts were done with Monte Carlo simulations. The results indicate that 1) the predicted prices are consistent with the historical prices, 2) world GDP growth rate is the determining factor in the forecasting of iron ore prices.

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Advisor: Gale Boyd | JEL Codes: C30, Q31 | Tagged: Demand, Iron Ore, Supply, Simulation, Simultaneous Equation

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