Agricultural Economics Department

 

First Advisor

Lilyan E. Fulginiti

Date of this Version

3-2013

Document Type

Dissertation

Citation

A dissertaton presented to the faculty of the Graduate College at the University of Nebraska in partial fulfillment of requirements for the degree of Doctor of Philosophy

Major: Agricultural Economics

Under the supervision of Professor Lilyan E. Fulginiti

Lincoln, Nebraska, March, 2013

Comments

Copyright 2013, Kepifri Alpha Lakoh

Abstract

This dissertation studies three main issues related to renewable energy in the United States and in Sub Sahara Africa.

The first chapter seeks to provide answers to a very fundamental question for second generation biofuels: “How much crop residue can farmers harvest from their fields for sale to cellulosic ethanol companies without affecting current levels of production? The model developed is applied to 101 counties from four Midwestern states in the United States (Colorado, Iowa, Nebraska and Wyoming). Results show that soil organic matter significantly contributes to explaining changes in technical efficiency and total factor productivity. Furthermore, average crop residue harvest potentials were 33%, 53%, 35% and 8% in Colorado, Iowa, Nebraska and Wyoming respectively.

The second chapter analyzes the market and welfare effects of foreign biofuel investments in Sierra Leone. A log-linear comparative static displacement model was used to carry out the analysis and a 30% demand shock was introduced into the system to represent an increase in biofuel demand. Results revealed large welfare enhancing gains for consumers of inedible biofuels but resulted in welfare losses in the staples and edible biofuel consumer markets. Producers generally reported welfare gains by virtue of owning factor inputs (land and other). Equilibrium quantities of inedible biofuels, edible biofuels and food increased by about 8.8%, decreased by 0.22% and increased by 0.6% respectively. Prices for both inputs and outputs increased while quantities of inputs also increased.

The third chapter determines the degree of responsiveness of farm energy input prices and corn prices to changes in crude oil prices using time series techniques. An Error Correction Model (ECM) and a VAR (vector autoregressive model) was fitted. The VAR was used to deduced variance decompositions for the six variables considered (prices of crude oil, diesel, gasoline, natural gas, electricity and corn) to determine the various contributions to the respective error variances. Results showed that the variables converged to a long run stable equilibrium. The strongest relationship was estimated for crude oil prices and diesel and gasoline prices. Prices for natural gas, electricity and corn had small and negative association with crude oil prices.

Advisor: Lilyan E. Fulginiti.

Share

COinS