Regional Growth and Cultural Tourism Development Scenarios Associated with the Bears Ears National Monument Cultural Center
Principal Investigator(s): View help for Principal Investigator(s) Jordan W. Smith, Utah State University
Version: View help for Version V1
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Project Citation:
Smith, Jordan W. Regional Growth and Cultural Tourism Development Scenarios Associated with the Bears Ears National Monument Cultural Center. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-03-20. https://doi.org/10.3886/E223702V1
Project Description
Summary:
View help for Summary
Overview
The Jupyter notebook (Bears_Ears_Economic_Impact.pynb) includes all Python code to process data and create all figures reported in the manuscript. The code can also be accessed via Google Colab here (https://colab.research.google.com/drive/19QptKut-FHMs0OIG6N9O7_C9qr_pSZC8?usp=sharing). All code is heavily commented and should be interpretable.
Bureau of Labor Statistics Data and Analyses
All Bureau of Labor Statistics data were acquired from the agency’s Quarterly Census on Employment and Wages online data portal (https://www.bls.gov/cew/downloadable-data-files.htm). These data are provided in the ‘BLS.zip’ file. You can extract these data and place them in a local drive, access the files via the Python code provided, and proceed through the creation of the figures.
Economic Impact Data
Economic impact data, provided after the analyses for each scenario was run, are provided in both the ‘Economic_Impact_and_Tax_Revenues_Results.xlsx’ and ‘economic_indicators_data.csv’ files. The former is more interpretable for humans, the latter is called by the Python code provided to create the figures shown in the paper. The latter file will need to be placed in a local drive before executing the Python code which calls it.
Comments or Questions
Please direct any questions to Dr. Jordan W. Smith (jordan.smith@usu.edu).
The Jupyter notebook (Bears_Ears_Economic_Impact.pynb) includes all Python code to process data and create all figures reported in the manuscript. The code can also be accessed via Google Colab here (https://colab.research.google.com/drive/19QptKut-FHMs0OIG6N9O7_C9qr_pSZC8?usp=sharing). All code is heavily commented and should be interpretable.
Bureau of Labor Statistics Data and Analyses
All Bureau of Labor Statistics data were acquired from the agency’s Quarterly Census on Employment and Wages online data portal (https://www.bls.gov/cew/downloadable-data-files.htm). These data are provided in the ‘BLS.zip’ file. You can extract these data and place them in a local drive, access the files via the Python code provided, and proceed through the creation of the figures.
Economic Impact Data
Economic impact data, provided after the analyses for each scenario was run, are provided in both the ‘Economic_Impact_and_Tax_Revenues_Results.xlsx’ and ‘economic_indicators_data.csv’ files. The former is more interpretable for humans, the latter is called by the Python code provided to create the figures shown in the paper. The latter file will need to be placed in a local drive before executing the Python code which calls it.
Comments or Questions
Please direct any questions to Dr. Jordan W. Smith (jordan.smith@usu.edu).
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