This paper presents economic models for resource management and scheduling in Grid computing. Peer-to-Peer (P2P) and Grid computing are emerging as next-generation computing platforms, enabling the creation of Virtual Enterprises (VE) for sharing globally distributed resources. However, resource management, application development, and usage models in these environments are complex due to the geographic distribution of resources owned by different organizations or peers. Each resource owner has different usage policies, cost models, and availability. To address these challenges, the authors propose a computational economy framework for resource allocation and regulating supply and demand in Grid environments. This framework provides mechanisms for optimizing resource provider and consumer objective functions through trading and brokering services. In real-world markets, various economic models are used to set service prices based on supply and demand and their value to users, including commodity markets, posted prices, tenders, and auctions. The paper discusses the application of these models for interaction between Grid components to determine resource service value and the necessary infrastructure to implement each model. In addition to standard Grid services, infrastructure is needed for interaction protocols, allocation mechanisms, currency, secure banking, and enforcement services. The authors briefly discuss existing technologies that provide some of these services and their use in developing the Nimrod-G grid resource broker. They also demonstrate the effectiveness of some economic models in resource trading and scheduling using the Nimrod/G resource broker with deadline and cost-constrained scheduling on the World Wide Grid (WWG) testbed, which has resources distributed across five continents.This paper presents economic models for resource management and scheduling in Grid computing. Peer-to-Peer (P2P) and Grid computing are emerging as next-generation computing platforms, enabling the creation of Virtual Enterprises (VE) for sharing globally distributed resources. However, resource management, application development, and usage models in these environments are complex due to the geographic distribution of resources owned by different organizations or peers. Each resource owner has different usage policies, cost models, and availability. To address these challenges, the authors propose a computational economy framework for resource allocation and regulating supply and demand in Grid environments. This framework provides mechanisms for optimizing resource provider and consumer objective functions through trading and brokering services. In real-world markets, various economic models are used to set service prices based on supply and demand and their value to users, including commodity markets, posted prices, tenders, and auctions. The paper discusses the application of these models for interaction between Grid components to determine resource service value and the necessary infrastructure to implement each model. In addition to standard Grid services, infrastructure is needed for interaction protocols, allocation mechanisms, currency, secure banking, and enforcement services. The authors briefly discuss existing technologies that provide some of these services and their use in developing the Nimrod-G grid resource broker. They also demonstrate the effectiveness of some economic models in resource trading and scheduling using the Nimrod/G resource broker with deadline and cost-constrained scheduling on the World Wide Grid (WWG) testbed, which has resources distributed across five continents.