Grid computing is a promising technology for future computing platforms. Here, the task of scheduling computing resources proves difficult as resources are geographically distributed and owned by individuals with different access and cost policies. This paper addresses the idea of applying economic models to the scheduling task. To this end a scheduling infrastructure and a market-economic method is presented. The efficiency of this approach in terms of response- and waittime minimization as well as utilization is evaluated by simulations with real workload traces. The evaluations show that the presented economic scheduling algorithm provides similar or even better average weighted response-times as common algorithms like backfilling. This is especially promising as the presented economic models have additional advantages as e.g. support for different price models, optimization objectives, access policies or quality of service demands.