jobs housing fit in the bay area

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JOBS HOUSING FIT IN THE BAY AREA Chris Benner, University of California Davis 1

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Jobs Housing Fit in the Bay Area. Chris Benner, University of California Davis. From jobs-housing balance to fit. First systematic studies in the late 1980s Found that commute distance was affected by a multitude of factors Low-income workers given special consideration - PowerPoint PPT Presentation

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Page 1: Jobs Housing Fit in the Bay Area

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JOBS HOUSING FIT IN THE BAY AREAChris Benner, University of California Davis

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From jobs-housing balance to fit

First systematic studies in the late 1980s Found that commute distance was

affected by a multitude of factors Low-income workers given special

consideration Appropriate “fit” between jobs and

housing often discussed but never explicitly studied

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Issues and opportunities

Why should we care? VMT, GHG, and equity

Current conditions versus projections

Appropriate geography of analysis

Prototype jobs-housing fit analysis(Sacramento Area Council of

Governments)

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Data

Jobs Longitudinal Employer-Household Dynamics http://onthemap.ces.census.gov/ Any geography possible Low-wage ≤ $1250/month

Affordable rental units American Community Survey Census Summary File 1 Rent ≤ $750/month Margins of error (places vs. tracts)

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Method

Jurisdiction level Linked to political process and decisions

regarding affordable housing provision Tract/buffer level

More closely linked to VMT Avoids problems with arbitrary boundaries

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mappingregionalchange.ucdavis.edu

Red = Severe shortage of affordable rental units

Blue = Excess of affordable rental units in relation to available low-wage jobs

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Multiple Silicon Valley Cities with JHFit > 5

Multiple Eastern Suburbs with

JHFit > 10

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Tract/buffer level results

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Buffer definition

• Sidestep problems with arbitrary jurisdictional boundaries

• Test different sizes using travel data

• Highlights small geographies with poor fit

Example buffer definition

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Commute performanceby Alex Karner

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Bay Area VMT

Data from activity-based microsimulation of daily travel patterns in 2010

Allows analysis of low-wage VMT attracted to each zone

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Bay Area VMT

Census Tract 15

Low-wage worker 115 mile one-way commute

Low-wage worker 212 mile one-way commute

Low-wage worker 322 mile one-way commute

Total work VMT attracted = 49Total workers = 3

Attracted work VMT per worker= 49/3 = 16.3

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Bay Area VMT

JH fit category

0 – 2.2 2.2 – 4 > 4

VMT attracted

7.10 7.61 10.4

JH fit category

Coefficient p-value

2.2 – 4 0.51 0.005

> 4 3.31 < 0.001

N = 1592, R2 = 0.24

Model results

Mean VMT attracted by JH fit category

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Bay Area VMT

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Conclusions

New method to calculate and track changes in jobs-housing fit over time using public data

Highlights opportunities for affordable housing provision and economic development

Clear implications for low-income commute performance

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Contact

CollaboratorsBidita TithiAlex KarnerJonathan LondonCatherine Garoupa-White

AdvocatesFelicity GasserSam Tepperman-GelfantLisa Hershey

Acknowledgements

Chris [email protected]://regionalchange.ucdavis.edu http://mappingregionalchange.ucdavis.edu