Projected income data under different shared socioeconomic pathways for Washington state

Area of Science:

• Climate Science
• Socioeconomic Modeling
• Geospatial Analysis

Background:

• High-resolution income projections are crucial for climate change adaptation and mitigation strategies.
• Existing methods lack the granular detail needed for localized planning.

Purpose of the Study:

• To develop and validate a methodology for downscaling state-level income projections to the census block level for Washington state.
• To provide accurate income data essential for climate change research and policy-making.

Main Methods:

• Utilized state-level GDP per capita projections and converted them to household income.
• Employed the Longitudinal Origin-Destination Employment Statistics (LODES) dataset for downscaling to census block-level.
• Validated the methodology by downscaling historical income data and comparing it with actual LODES and American Community Survey data.

Main Results:

• Achieved strong agreement between downscaled and reference income data, with average R-squared values of 0.67 (block-level), 0.8 (block group-level), and 0.99 (county-level).
• Validated the accuracy of the downscaling methodology across different geographic granularities.

Conclusions:

• The developed methodology provides a reliable approach for generating high-resolution income projections.
• This approach is transferable to other states and beneficial for demographic analysis, economic research, and urban planning.