A New Tool for Sub-State Modeling of Energy and Climate Policy: The Indiana Scalable Energy and Economy Model
*Names in bold indicate Presenter
The Indiana Scalable Economic and Energy Model (IN-SEEM) is a data-intensive, dynamic, simultaneous econometric model that shows the relationship between the energy system and the economy at two geographic scales: the state level and for sub-state, multi-county regions. Using data from the BEA, BLS, Census, NOAA, and the EIA—along with an allocation model that estimates energy consumption at the sub-state level—the model describes the energy sector using prices and consumption of electricity, natural gas, and motor gasoline across residential, commercial, industrial, and transportation end-uses. Employment and earnings in ten economic sectors, as well as gross state and regional product, unemployment, and non-wage income, comprise the economic component of the model. The “scalable” aspect of IN-SEEM refers to the ability of researchers to adapt the definition of sub-state regions according to the needs of policy analysis; this iteration of the model presents ten sub-state regions defined by contiguous counties with shared economic characteristics. The relationships between energy and economic variables are captured by 300 unique equations that capture historic relationships within each region; thirty additional identities aggregate the regional endogenous variables to represent state-wide effects. The structure of the model allows estimates at the state level to feed back into the regional equations, an important feature given the significant relationship state-level activity plays in the economic performance of certain sectors in certain regions.
This paper mainly serves as a “proof-of-concept” of a sub-state energy and economic modeling, though we also illustrate its usefulness for policy analysis by simulating an increase in motor gasoline prices driven by a national policy of allowing crude oil exports. The policy analysis produces a set of results describing the effect of such a policy at the state and sub-state level on energy consumption and broader economic indicators. From this analysis, we can draw several lessons that inform policy design and anticipate both intended and unintended consequences.