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California Dream Index

Visualizing and Analyzing Economic Mobility in California

Overview

The California Dream Index (CDI) is a web tool created by economic equity-focused organization California Forward. The tool depicts county-level scores of economic mobility across ten indicators from 2010 to 2019. 

Presented here is a capstone project performed by two master's candidates at NYU CUSP leveraging publicly accessible data to build on the CDI tool in the form of two core deliverables: 

 

1.) Re-creating the CDI's statewide interactive visualizations at a lower granularity (tract level)


2.) Performing a series of clustering analyses for each decade from 1990 to 2019, creating resident economic archetype profiles for comparison over time and providing rich insights on connections among CDI indicators, income, demographics and location

 

10 Indicators of Economic Mobility

Drawing on insights from previous research, the California Forward team selected these ten indicators. The capstone project team employed all of these indicators for the visualization deliverable, eight of them for a single-year clustering analysis and three of them for a multi-decade clustering analysis.

College Degree /

CTE Attainment

Early Childhood Education

Income Above Cost of Living

Rent Burden

Home Ownership

Broadband Access

Short Commutes

Prosperous Neighborhoods

Clean Drinking Water

Air Quality

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to Overview
to Methods

 Methods + Results

Visualizations

For their first deliverable, this capstone team created a series of statewide, tract-level interactive visualizations using Python for data processing and Datawrapper for map construction.

 

Maps were created for each of the ten indicators, as well as a composite of them ("Overall CDI Score") for 2019, 2010 and their differences.

 

Three examples are shown below, and a document with links to the rest is available here.

Clustering Analyses

The capstone team's second deliverable was a series of clustering analyses on California residents using some of the ten CDI indicators as features.

The first analysis focused on the year 2019 and was based on the eight indicators that were available within the IPUMS census microdata archives. Seven clusters were produced and compared here, and this analysis is referred to as the 2019 Comprehensive Clustering.

The second analysis was a decadal series of clustering exercises spanning 1990 to 2019 and relying on three of the CDI indicators as features. Four clusters were produced for each decade. This analysis is referred to as the Multi-Year Clustering.

2019 Comprehensive Clustering

Cluster Income Table

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Cluster Ranking Radar Chart

The radar chart depicts cluster rankings in each feature category. Strong feature scores result in higher rankings, which here result in smaller polygons, as rank 7 is on the outside of the axis and the top ranks are on the inside.

 

When compared to the cluster income table, the chart reveals that higher feature rankings correlate with higher incomes.

Multi-Year Clustering

Insights

Insights

Visualization

Creating visualizations on census tract granularity has allowed California Forward to investigate economic mobility on a local level. These granular visualizations are intended for the organization's internal use and will be used by California Forward to inform stakeholders including local-level policymakers. For example, the organization facilitated a meeting between the capstone team and Tahoe Prosperity Center. The team's plots in the Tahoe area revealed surprising shifts in home ownership over the last ten years, as well as other findings that this organization can now take into account in their work. The statewide plots revealed particularly dramatic changes in the Early Childhood Education and Affordable Rent categories. To inspect any of the statewide maps, click here.

Clustering

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The clustering analyses resulted in rich depictions of economic archetypes in California. The Comprehensive 2019 analysis proved most of the available CDI indicators to be strong indicators of economic status, as residents in clusters with high feature rankings had higher median incomes. The one exception to this was commute time, which seems to have been skewed by numerous residents reporting 0-minute work commutes. In all analyses, housing and education were particularly strong indicators of economic status. The Multi-Year analysis revealed that the housing-income connection grew progressively stronger each decade from 1990 to 2019. Cluster makeups remained very consistent each year until a shift in 2019, For more detailed findings as well as demographic insights, see the project GitHub repository and paper.

to Data

Data Sources

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Census Data

American Community Survey Data from:

https://www.census.gov

Census Microdata

U.S. Census and American Community Survey microdata  from:

https://www.ipums.org

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CA Map Shapefiles

California Geographic Boundaries from:

https://data.ca.gov

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United Way Data

Data on Cost of Living in California from:

https://www.unitedwaysca.org

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Air Quality Data

Air Quality Data from:

https://oehha.ca.gov

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Water Board Data

Drinking water data from:

https://www.waterboards.ca.gov

About Us

Team

Mike Carper

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Aren Kabarajian

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Mentor & Sponsor

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Dr. Eric Corbett

Mentor

NYU CUSP Smart Cities Postdoctoral Associate

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Patrick Atwater

Sponsor 

Senior Research Analyst at California Forward

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About Us
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