Airline delays lead to a tremendous loss of time and resources and cost billions of dollars every year in the United States. To explore solutions for reducing delay, it is essential to understand factors causing flight delays and also the network impact of delays at one airport in the National Airspace System (NAS). For air transportation planning and policy purposes, this study concentrates on providing answers from a macroscopic point of view without being distracted by volatile operational details. A set of multivariate equations is proposed to model daily average arrival delay at one airport, and another for the rest of the NAS. The model for the single airport considers independent variables such as deterministic arrival queuing delay, delay at other airports in the NAS, adverse weather (convective and local), and different demand management regimes. The model for the rest of the NAS considers arrival delay as a function of deterministic arrival queuing delay, arrival delay at the single airport, adverse weather (convective and local), and other factors. Observation of the interactions between these two models shows that they can be regressed with an econometric technique: two-stage least squares. This macroscopic framework of delay impact analysis can be used to investigate the network effect of capacity improvement or new demand management strategies at a single airport. Hypothetical scenarios are generated and the systemwide delay reduction is calculated. This is a powerful decision support tool for stakeholders to use in deciding how to allocate resources optimally and to reduce delays.