New York City Mobility Analytics Index and the Relationship with Economic Activity

Alternative data sources, such as transit data and Google searches, can be used to quantify the physical movement of populations within a region. We hypothesize that an increase in mobility in New York City is correlated with an increase in economic activity as measured by traditional economic data sources. By aggregating and analyzing data from multiple alternative data sources, an index that quantitatively demonstrates the amount of movement within New York City can be constructed. We present a data analytics framework that (1) collects data from the Metropolitan Transportation Authority (MTA) and (2) investigates the relationship between mobility and the unemployment rate in New York City. Experimental results indicate that there is a relationship between the number of people utilizing public transit and the unemployment rate. The preliminary results suggest that MTA data sources have the potential to be one of the predictive features of unemployment. This experimental framework could be used as a supplement to traditional tools used by city officials, policymakers, and businesses to inform decision-making and planning.