This dissertation targets at studying the cause and implication of empirical grounded industry facts using multiple methodologies, including analytical model, statistical model, and agent-based simulation. Basically, this dissertation investigates two main research objects, the U.S. beef industry and restructured electricity market.

Beef is the single largest sector within United States agricultural production, accounting for a fifth of farm market revenues.Unlike other animal products, only a small share of output is produced under vertically integrated arrangements. Beef production also differs from other sectors because of the long production lags and the opportunity to utilize forage from lower quality land. The sector divides between grass-based cow-calf operations during the first year

of a beef animal's life and grain-based feeder operations during the months preceding slaughter. The two sub-sectors also differ in regards to financial performance. Empirical data shows that cow-calf sector has strong positive autocorrelation in returns over time while the feeding sector return is close to white noise. Using the notion of Ricardian rent this study extends existing dynamic models of beef market equilibrium to rationalize this dierence. Time series data are tested where preliminary tests provide evidence in favor of the theory proposed by this study. The results are important in explaining why the cattle feeding sector is relatively immune from demand and supply-side shocks whereas cow-calf operations are more exposed.

The second part of the dissertation turns focus on the restructured electricity market. In April 2003, the U.S. Federal Energy Regulatory Commission (FERC) proposed a new market design for U.S. wholesale power markets. Core features of this design include oversight of operations by some form of Independent System Operator (ISO), a two-settlement system consisting of a day-ahead market supported by a parallel real-time market to ensure continual balancing

of supply and demand for power, and management of grid congestion by means of locational marginal pricing. The restructuring of electricity market stays in the layer of wholesale market while the retail market still remains highly regulated by the state government. To alleviate the disconnection between wholesale and retail market, ISO propels demand response program to encourage retail customers join the wholesale market which is supposed to pass wholesale market price signal to the final customers. To investigate the impact of this connecting attempt on current power system performance in terms of both market and physical operation, this dissertation conducts agent-based simulation experiments on three topics that are closely related with demand response and price-sensitive bidding behavior. Specific studied issues include: a close-loop simulation study of two-settlement market with price-sensitive customers and intelligent load serving entity, a multi-agent simulation study of demand response provider baseline inflation behavior and generator company investment decisions under high penetration level of DR resource with a market framework requested by new FERC Order 745, an agent-based simulation study of LSE strategic price sensitive bidding behavior under three different market clearing mechanisms. To carry out this research, a flexible simulation framework is developed independently with a major extension of the AMES wholesale power market test bed to include two-settlement system, Unit Commitment system, smart device, intelligent LSE, multi-task ISO and capacity market.