‘Outdegree’ from directed graph theory is used to measure the salience of individual locations in the transmission of Covid-19 morbidity through the spatiotemporal network of contagion and their salience in the spatiotemporal diffusion of vaccination rollout. A spatial econometric model in which morbidity varies inversely with vaccination rollout, and vaccination rollout varies directly with morbidity is used to calculate dynamic auto-outdegrees for morbidity, and dynamic cross-outdegrees for the effect of vaccination on morbidity. The former identifies hot spots of contagion, and the latter identifies locations in which vaccination rollout is particularly effective in reducing national morbidity. These outdegrees are calculated analytically rather than simulated numerically.   

We present an economic definition of cascading effects of a disaster on the labor market over the medium to long term. Cascading effects are considered events that alter local amenities. In the context of the labor market, the standard conception of a cascade as a sequence of events that alter the capital stock, may not be very instructive as the immediate time horizon is not the relevant economic timeframe. We outline some of the theoretical implications arising from this definition and give them some intuition based on an agent based simulation model. The model is used to simulate two cascade-type scenarios following an earthquake in the city of Jerusalem. Results indicate that a strong cascading effect in the labor market depends on serious functional change in the physical environment i.e. land-use change. Flow-related changes in labor and population movement are less likely to create effects that cascade into other sub-markets. Implications of these findings point to the key role of labor mobility as workers seek solutions outside the area struck by disaster.