Author
Listed:
- Mo Li
- João Pedro Ferreira
- Christa D. Court
- David Meyer
- Mengming Li
- Wesley W. Ingwersen
Abstract
Subnational input–output (IO) tables capture industry- and region-specific production, consumption, and trade of commodities and serve as a common basis for regional and multi-regional economic impact analysis. However, subnational IO tables are not made available by national statistical offices, especially in the United States (US), nor have they been estimated with transparent methods for reproducibility or updated regularly for public availability. In this article, we describe a robust StateIO modeling framework to develop state and two-region IO models for all 50 states in the US using national IO tables and state industry and trade data from reliable public sources such as the US Bureau of Economic Analysis. We develop 2012-2017 state IO models and two-region IO models at the BEA summary level. The two regions are state of interest and rest of the US. All models are validated by a series of rigorous checks to ensure the results are balanced at state and national levels. We then use these models to calculate a 2012–2017 time series of macro economic indicators and highlight results for 11 states that have distinct economies with respect to size, geography, and industry structure. We also compare selected indicators to state IO models created by popular licensed and open-source software. Our StateIO modeling framework is consolidated in an open-source R package, stateior , to ensure transparency and reproducibility. Our StateIO models are US-focused, which may not be transferrable to international accounts, and form the economic base of state versions of the US environmentally-extended IO models.
Suggested Citation
Mo Li & João Pedro Ferreira & Christa D. Court & David Meyer & Mengming Li & Wesley W. Ingwersen, 2023.
"StateIO - Open Source Economic Input-Output Models for the 50 States of the United States of America,"
International Regional Science Review, , vol. 46(4), pages 428-481, July.
Handle:
RePEc:sae:inrsre:v:46:y:2023:i:4:p:428-481
DOI: 10.1177/01600176221145874
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