stateior is an R package for building multi-regional economic input-output (MRIO) tables of states in the United States, refered to as StateIO models.
Currently, stateior is capable of creating IO tables for each US state and building two-region MRIO models based on those state IO tables at the BEA Summary level of resolution in the US for all years from 2012-2020.
The two regions are State of Interest (SoI) and Rest of the US (RoUS).
stateior was initially conceived in support of creating state-specific versions of USEEIO models, but may be used for other purposes where state input-output tables are used.
The methodology used to build the StateIO models is described in a paper in International Regional Science Review.
The package is intended to add transparency and reproducibility to the complex process of generating subnational input-output tables, which are not compiled by any statistical agency.
stateior implements a robust commodity-industry modeling framework that models supply, use and trade of commodities by industries and final users in 50 U.S. states plus the District of Columbia and includes international import and export.
stateior offers various functions for building, validating, visualizing, writing, and loading StateIO models.
stateior is in a beta development state while the complete methodology and StateIO data products are under external peer-review.
See the Wiki for advanced uses, details about modeling approach, data and metadata, and how to contribute to stateior.
There are two primary ways to use stateior.
- To access the final data products in an R environment. This usage is the most simple and rapid and all that is required where the intention is only to review and use the two-region Make and Use tables.
- To study, run, modify the source code for any or all of the model building steps, from raw data acquisition to final two-region table assembly. This is a developer use.
Install the most recent release version of stateior and attach it to the current R session. See Releases for all previously released versions. Note these steps will automatically install other R packages required by devtools and stateior.
install.packages("devtools")
devtools::install_github("USEPA/stateior")
library(stateior)# For a specific release:
devtools::install_github("USEPA/[email protected]")Load desired StateIO data. See One Region Data and Two Region Data for names and details of one- and two-region MRIO data sets that are currently available, respectively.
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# One-Region Data #
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# Load the state one-region (state only) domestic Use tables for 2012 for all states.
# This will download the data product from a remote server and load it into your R session as an R list.
OneRegionDomesticUse_2012 <- loadStateIODataFile("State_Summary_DomesticUse_2012")
# Select the Georgia Use table.
# This will put this table into a standard R data frame named 'GA_DomesticUse_2012'.
GA_DomesticUse_2012 <- OneRegionDomesticUse_2012[["Georgia"]]
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# Two-Region Data #
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# Load the two-region domestic Use tables for 2012 for all states.
# This will download the data product from a remote server and load it into your R session as an R list.
TwoRegionDomesticUse_2012 <- loadStateIODataFile("TwoRegion_Summary_DomesticUse_2012")
# Select the two-region Use table for Georgia and Rest of the US.
# This will put this table into a standard R data frame named 'GA_TwoRegionDomesticUse_2012'.
GA_TwoRegionDomesticUse_2012 <- TwoRegionDomesticUse_2012[["Georgia"]]If viewing either one-region or two-region data of a specific state in Excel spreadsheet is preferred, export it to a csv file in a given outputfolder.
# Export 2012 Georgia Use tables to a csv file.
writeStateIODatatoCSV <- ("State_Summary_DomesticUse_2012", "Georgia", outputfolder)
# Export 2012 two-region Use table for Georgia and Rest of the US to a csv file.
writeStateIODatatoCSV <- ("TwoRegion_Summary_DomesticUse_2012", "Georgia", outputfolder)For studying, replicating or modify the code, users will want to clone or copy the source code and review the code in R. See more in Instructions for Developers.
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