Mission
The mission of the Wisconsin National Data Consortium (WiNDC) is to provide open source multisectoral economic datasets to enable quantitative policy analysis, lower the barrier of entry to the development of general equilibrium models, and foster collaboration among researchers and policymakers.
Vision
We want to make it easy for researchers and policymakers to access and use high-quality economic data and models. All of our data methods, data, and models are open source and free to use with attribution.
We encourage researchers using our data to open source their code and models, and we provide a platform for sharing these resources. We also aim to create a community of researchers and policymakers to improve the quality of economic analysis and policy decisions.
We believe that science should be replicable and transparent, and we strive to make our datasets and models accessible to all.
The WiNDC team is available to answer questions and provide support to our users. If you have questions about our data, models, making your code be open source, or other questions, please contact us .
If you find errors in our datasets or models, either raise an issue on our github issues page or contact us . We are committed to continuous improvement and welcome feedback on our datasets, models, and resources.
About WiNDC
The Wisconsin National Data Consortium (WiNDC) facilitates the creation and documentation of open source multisectoral economic datasets for US states. These datasets are created by open source computer programs which can be run on NEOS . The datasets are provided together with canonical general equilibrium models which can provide the starting point for quantitative policy analysis.
The first version of the open-source dataset (WiNDC 1.0) was a byproduct of a research project conducted by Thomas F. Rutherford and Andrew Schreiber (both at that time at the University of Wisconsin-Madison) with Gökçe Akin-Olçum (from the Environmental Defense Fund ) and Christoph Böhringer (from the University of Oldenburg).