The Impact of Tech Demand During COVID-19: A Local Optimization Utility-Based Human Migration Model

Abstract

Over the past two years, COVID-19 has dramatically disrupted the movement of hu- mans across the United States but its impact on society long-term is still unclear. In this paper, I present a locally optimized utility model for a single migration class influenced by tech demand during the pandemic. I derive a formulation for net city utility associated with factors of the labor market, primarily wage differentials, the cost of living, job availabil- ity, and other benefits, and solve the maximization problem for utility at a city at a given time. I then apply the model to a numerical analysis to quantitatively determine the im- pact of tech demand during COVID-19 on human migration in the top 10 most populous cities across the United States, and compare those trends to those determined by the util- ity model with migration numbers reported throughout the pandemic over a period of ten months. This work is a contribution to the theory of local migration models as well as an extension to the literature on optimizing system-wide human migration in the presence of regulations.