Getting Started: WiNDC 2.0
Note that this page refers to WiNDC Version 2.0, released in August 2019. For details of the current version, see Getting Started: WiNDC Build Stream.
Utilities and Dataset Description
The WiNDC build routine is a collection of GAMS programs for producing subnational economic accounts for input-output or computable general equilibrium models of the United States economy. All code and data necessary for producing subnational accounts are provided in this repository. Currently, the routine can produce state level accounts.
We begin with the national input-output table of the Bureau of Economic Analysis (BEA) and downscale to the regional level using publicly available economic statistics from governmental agencies. We use additional data from the BEA on regional gross product and consumer expenditures and data from the Census Bureau on foreign trade, bilateral trade and state government expenditures. We show how to combine publicly avialable data from these sources and other government agencies to compile a database that serves as input data for the WiNDC build stream. The WiNDC build stream generates the core WiNDC database. The database contains multisectoral subnational economic datasets for the years 1997 to 2016.
In addition to the core WiNDC database, we offer two modules: the energy-environment module, called blueNOTE, and a basic agricultural module, called NASS.
Downloads
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The WiNDC build stream package, including a GDX file with all data sources and the GAMS file
build.gmsthat generates the core WiNDC database: windc_build-2.0.zip (13.8 MB).
Note that the files are described in the paper. - The pre-compiled core WiNDC database: in GDX format (44.6 MB) and JSON format (76 MB).
- The datasources files (153.6 MB). Note that a GDX file with a compilation of all datasources is part of the WiNDC build stream package.
Step-By-Step Instructions
These instructions refer to the build of WiNDC 2.0. For details on WiNDC 1.0, see Getting Started: WiNDC 1.0.
If you are interested only in the core WiNDC database, you can download it in GDX format (44.6 MB) and JSON format (76 MB). If you are interested in details of the build, the source datasets and the modules, please follow the steps outlined below.
- Download the WiNDC build stream package: windc_build.zip (163 MB).
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Unzipping the file will create a directory called
windc_buildwith the subdirectorybuild_files, and the GAMS filesbuild.gms,disagg.gmsandrecalibrate.gms. These GAMS files perform the build, disaggregation, and ultimate re-calibration. We implemented this modular design to give users maximal flexibility for customization. The directorybuild_filescontains all GAMS subroutines and the input data in GDX format. If you are interested in details of the input data, see Getting Started: WiNDC 2.0 Data Stream. -
If you have a local version of GAMS and have access to the relevant licenses,
navigate in your command line or terminal to the
windc_builddirectory and run the GAMS filebuild.gmsby simply typing the following command:Note that this build will work in both, Windows and UNIX/LINUX environments. See the paper for a description of all subroutines within the build stream.gams build.gms -
The core WiNDC database,
WiNDCdatabase.gdx, will be generated locally in a directory calledbuilt_datasets. It contains data for all US states and 71 (summary) sectors from 1997-2016. -
If you don't have access to a GAMS license including needed solver licenses,
you can generate the database locally using
NEOS.
To run the model on NEOS, type the following command:
gams build.gms --neos=yes - Once the database is created, it can be loaded into a general equilibrium model in GAMS. If a dataset is generated without any optional recalibration, it includes data for all years. Here is an example of how to read the core data file into GAMS in a simple general equilibrium model and verify benchmark consistency in the underlying dataset. Note that this model contains no customizations aside from sectoral aggregation.
Modules: blueNOTE and NASS
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Disaggregate
The core WiNDC database can be disaggregated into specific year and sector data. This is performed with the filedisagg.gms.
For example, the following command will generate a disaggregated data file of key energy sectors for a particular year:Note that the flaggams disagg.gms --aggr=bluenote --year=2016 [--neos=yes]
--neos=yesis optional. If the year is not specified, it will automatically be set to 2016. This command generates the fileWiNDC_disagg_bluenote.gdxand places it in the directorybuilt_datasets.
To disaggregate the core WiNDC database for the agricultural sector, use the following command:This command generates the filegams disagg.gms --aggr=nass --year=2012 [--neos=yes]
WiNDC_disagg_nass.gdxand places it in the directorybuilt_datasets. Note that for the agricultural sector only the year 2012 is available.
The set mappings that control the disaggregation are in the directorybuild_files/user_defined_schemes. Examples for both blueNOTE and NASS are included with the core distribution. Users are encouraged to customize this based on their specific modeling framework. Please contact us if you have questions about how to build your own disaggregation schemes.
Note: The fileWiNDCdatabase.gdxmust exist in the directorybuilt_datasetsfor the routinedisagg.gmsto run successfully. -
Recalibrate
To recalibrate the disaggregated blueNOTE dataset, run the following command:As before, again, the NEOS flag is optional in case you wish to solve the model remotely on the NEOS system. The resulting recalibrated database is calledgams recalibrate.gms --aggr=bluenote --year=2016 [--neos=yes]WiNDC_cal_2016_bluenote.gdxand it is placed in the directorybuilt_datasets.
To recalibrate the disaggregated NASS dataset, run the following command:The resulting recalibrated database is calledgams recalibrate.gms --satdata=nass --year=2012 [--neos=yes]WiNDC_cal_2012_nass.gdxand it is placed in the directorybuilt_datasets.
Note: In order to successfully runrecalibrate.gms, the fileWiNDC_disagg_*.gdxmust exist in the directorybuilt_datasets.