Earlier this fall, Michigan State University’s Institute for Public Policy and Social Research released the State Networks dataset, a compilation of state-to-state relational variables. This data consists of economic, political, and geographic ties between state pairs (http://ippsr.msu.edu/public-policy/state-networks).
Using this data, I analyzed how similar the Midwestern states are in terms of travel, migration, and trade. I used the U.S. Census’ determination of the Midwestern states to include Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. In the State Networks dataset, I am using the variables called IncomingFlights, ACS_Migration, and Imports.
The first figure shows the incoming flights among Midwestern states. The flights in the data represent a 10% sample of flights and comes from the Airline Origin and Destination Survey implemented by the Bureau of Transportation. The circles are labeled according to which state they represent and are sized by the number of incoming flights to that state from all other Midwestern states. The arrows between each state represent the flights being sent from one state to the other, and they are sized according to the number of flights being sent.
Illinois receives the most incoming flights from the Midwestern states. The thicker lines between Ohio and Illinois, Minnesota and Ohio, Missouri and Ohio, and Wisconsin and Ohio show that there are a lot of flights between those state pairs. The top 3 states receiving flights are Illinois, Minnesota, and Missouri. South Dakota, Kansas, and North Dakota receive the fewest flights.
Next, I made a figure showing migration among the Midwestern states. This data comes from the U.S. Census American Community Survey and indicates the number of people moving from one state to another in 2017. In this figure, the circles are sized by the magnitude of the growth or loss in people the state experiences from other Midwestern states. The green circles indicate that state is experiencing a net gain in people moving to the state from other Midwestern states. The reddish color indicates the state is experiencing a net loss; people are moving out of the state into other Midwestern states at a higher rate than they are moving to that state. Again, the thickness of the arrows between the states is dependent on the amount of people moving from that state to the state at the receiving end.
Notably, Illinois stands out as having a sizeable negative net migration. Illinois experienced the greatest loss, as a lot of people were moving from Illinois to other Midwestern states. South Dakota, Ohio, Kansas, Nebraska, and Iowa also experienced a loss from residents moving to other Midwestern states in 2017. The Midwestern state to which people moved to the most in 2017 was Indiana, followed by Missouri, Wisconsin, Minnesota, Michigan, and North Dakota.
Lastly, I explored trade between the Midwestern states by using the value of trade between each state in 2017 from the Commodity Flow Survey implemented by the Bureau of Transportation Statistics. Again, circles are sized by the total value of Midwestern imports to that state. The thickness of the arrows indicates the value of the imports from the sending state to the receiving state.
Indiana received the greatest value of imports from the Midwestern states in 2017. Ohio, Wisconsin, and Michigan follow Indiana in highest values of imports. Not shown in the figure is the amount of exports sent to other Midwestern states. In order, Minnesota, Illinois, Michigan, and North Dakota sent the highest values of exports to other Midwestern states. We can see that Michigan is one of the top senders of goods throughout the Midwest and one of the top receivers of trade from the Midwest.
These figures show some of the analyses we can complete from the State Networks dataset, and there are many state-level indicators within the data that may help us understand some of these state-pair relationships, such as state ideology, partisanship, demographics, borders, regions, and gross state product.
Shayla Olson is a second-year doctoral student in the Department of Political Science at MSU. Her work as an IPPSR Policy Fellow involves building and maintaining the State Networks database. She studies American political behavior, public opinion, and political communication in the context of religion and race.
