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The overall purpose of this study is to estimate how the rise in grain prices (especially corn prices) induced by ethanol production impacts U.S. catfish industry. Using monthly data from January 1996 to December 2007, an ARDL model and bounds testing procedure were used. The existence of cointegration between the feed price and its regressors and between the farm price and its regressors was found. Results show that the short- and long-run feed price elasticity with respect to corn prices were 0.224 and 0.075, respectively. It was found that energy is more important to catfish feed production than to farm level catfish production, and is more important to processor level production than to farm level production. Results further showed that catfish farmers will lose net returns because the estimated farm price elasticity with respect to feed prices was smaller than the necessary change that would keep net returns the same. The overall purpose of this study is to estimate how the rise in grain prices (especially corn prices) induced by ethanol production impacts catfish feed prices and catfish prices at the farm level. Using monthly data from January 1996 to December 2007, an ARDL model and bounds testing procedure were used to test the existence of cointegration between the variables of interest. The existence of cointegration between the feed price and its regressors and between the farm prices and its regressors was found. Estimation results show that the short- and long-run feed price elasticity with respect to corn prices were 0.224 and 0.075, respectively. Feed and farm price elasticities with respect to energy prices were highlighted. The results show that energy is more important to catfish feed production than to catfish production at the farm level, and energy is more important to catfish production at the processor level than to production at the farm level.

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This dissertation examines the role of asset prices to act as a transmission and amplification mechanism. Specifically, it looks at how changes in asset prices can help transmit and amplify technology shocks through the credit channel by changing the supply of loanable funds, or changing the supply of deposits, or both. Using a modified version of the Kiyotaki-Moore credit cycles model with concave utility and decreasing returns to scale production function, the dissertation illustrates that asset prices can as a credible amplification and transmission mechanism. Using concave utility and decreasing returns to scale production function allows the incorporation risk aversion into the credit cycles model. The model can help explain the gap between observed magnitude of shocks, and the corresponding changes in economic activity. The behavior of a heterogeneous agent economy in response to a technology shock is simulated using computer programs. The simulations show that a one percent technology shock translates into a more than four percent change in capital held by the constrained agents by moving capital from one agent type to the other. This moves the economy away from a first-best equilibrium. If the technology shock is positive there is an increased demand of capital from the more productive agents, and thus a more than proportionate increase in output. If the technology shock is negative, the opposite path is followed, and economic activity falls more than proportionately. There are credit constraints built into the model. Agents' access to credit is determined by the value of collateral on oer, which in turn depends on asset prices. Technology shocks change demand for assets, their prices, their value as collateral, and hence agents' access to credit. Further, since prices are forward looking, a shock in one period propagates through time. These simulations show that the effects of the shock can be felt up to 13 periods after it has hit. An event analysis with housing price data from 18 countries spanning a period of more than four decades is also performed. It shows that there is strong co-movement of housing prices and economic activity. In particular, larger changes in housing prices have been accompanied by qualitatively similar changes in economic activity. The period leading up to the peak of a real estate cycle is accompanied by a more than proportionate increase in private sector lending, and once the peak has been crested, there is a more than proportionate fall in nominal private sector lending. This evidence is in sync with the earlier observation that changes in asset prices influence agents' access to credit and contribute to the persistence of the effects of the shock far into the future. Further, the preferred measure of economic health, the rate of inflation, sees no measurable change in periods leading up to a real estate peak, and beyond. This throws up the need for some other measure of economic health that is better able to capture the events in asset markets. Policy makers have been paying more attention to this channel in the aftermath of the sub-prime mortgage crisis in the United States. There have been multiples changes in regulatory policy across the world, and specific steps are being taken to dampen exuberance in the real estate market. Only time can tell if these measures turn out to be effective, but at least a step has been taken towards realizing that housing market can lead to a wider economic and banking crisis. / Economics

Price and inventory decisions are key levers of profit for firms. A manager needs to understand the impacts of pricing, ordering and stocking decisions not only on today's operations but also on future demand. In this dissertation we investigate these intertwining decisions by incorporating inter-temporal effects of pricing decisions through reference prices. We introduce three significant extensions to reference price models to provide more meaningful insight into pricing, inventory and ordering decisions. We first present a threshold reference model. The threshold model incorporates zones of insensitivity around expected price that moderate the reference impacts on demand. This provides a rigourous model that is flexible enough to handle different pricing strategies such as single everyday low pricing (EDLP), high-low pricing (HiLo) and other general price cycles. We develop two solution approaches and provide computational results. We next introduce a reference model with stochastic demand. There is considerable previous research supporting the consideration of variability in pricing and inventory decisions and this is especially true in the context of inter-temporal demand interactions based on pricing decisions. We find that the introduction of stochastic elements can actually increase or decrease the length of the price cycle for some consumers in a reference model depending on the parameters of the model. This extends the stochastic demand model and bridges to reference models for improved managerial insight. The final model presented is the dynamic lot sizing model. When prices and production decisions or order quantities are determined simultaneously the interactions need to be considered to optimize profits. The reference model incorporates the inter-temporal price effects to provide a clearer picture of the optimal decision. The inclusion of reference effects does change the optimal decision. / Thesis / Doctor of Philosophy (PhD)