Developing a new methodology for analyzing potential displacement

415 Pages·2017·14.87 MB·English

Developing a New
Methodology for Analyzing
Potential Displacement

University of California, Berkeley

Principal Investigator:
Karen Chapple

Co-Principal Investigators:
Paul Waddell
Daniel Chatman

With Miriam Zuk 

University of California, Los Angeles

Principal Investigator:
Anastasia Loukaitou-Sideris

Co-Principal Investigator:
Paul Ong

With Silvia R. Gonzalez, Chhandara Pech, and Karolina Gorska

Prepared for the California Air Resources Board and the California Environmental Protection Agency
By the University of California, Berkeley and the University of California, Los Angeles

ARB Agreement No. 13‐310
March 24, 2017
The statements and conclusions in this Report are those of the contractor and not necessarily
those of the California Air Resources Board. The mention of commercial products, their
source, or their use in connection with material reported herein is not to be construed as
actual or implied endorsement of such products.
Acknowledgements

This Report was submitted in fulfillment of ARB Agreement No. 13-310 by the University of
California, Berkeley under the partial sponsorship of the California Air Resources.
Board. Work was completed as of 10/9/15.

Chapter 2 and 5:

The UC-Berkeley team is grateful for the advice of its advisory committee at MTC/ABAG, including
Vikrant Sood, Carlos Romero, Peter Cohen, Gen Fujioka, Wayne Chen, Bob Allen, Duane Bay, Jennifer
Martinez, and Johnny Jaramillo. Our case study research (groundtruthing and policy) in East Palo
Alto, Chinatown, Marin City, the Mission, and San Jose benefited deeply from the participation of
local community groups, including San Francisco Organization Project/Peninsula Interfaith Action,
Chinatown Community Development Center, Marin Grassroots, PODER, and Working Partnerships.

Chapter 3:

Development of UrbanSim has been previously supported by the National Science Foundation
Grants CMS-9818378, EIA-0090832, EIA-0121326, IIS- 0534094, IIS-0705898, IIS-0964412, and
IIS-0964302 and by grants from the U.S. Federal Highway Administration, U.S. Environmental
Protection Agency, European Research Council, Maricopa Association of Governments, Puget
Sound Regional Council, Oahu Metropolitan Planning Organization, Lane Council of Governments,
Southeast Michigan Council of Governments, Metropolitan Transportation Commission and the
contributions of many users. The application of UrbanSim to the San Francisco Bay Area was funded
by the Metropolitan Transportation Commission (MTC).

The following persons participated in the development of the research to adapt UrbanSim to
address displacement issues in its application to the San Francisco Bay Area:
Paul Waddell, City and Regional Planning, University of California Berkeley
Samuel Maurer, City and Regional Planning, University of California Berkeley
Samuel Blanchard, City and Regional Planning, University of California Berkeley

This project has been done in close collaboration with the staff of the Metropolitan Transportation
Commission (MTC) and of the Association of Bay Area Governments (ABAG). In particular, we
wish to acknowledge the leadership of Mike Reilly at MTC, with additional assistance from Aksel
Olsen at ABAG. Many other staff at MTC and at ABAG have participated in the development of the
data, the scenarios and the analysis described in this report.

Chapter 4:

Many thanks to those who provided assistance with NHTS and CHTS confidential data, and the
remote system for using the CHTS, including Brennan Borlaug, Evan Burton, Jeff Gonder, Susan Liss,
Jasmy Methipara, and Adella Santos. Thanks also to Karen Chapple for helpful comments that
improved the paper, and for a large set of comments from numerous anonymous reviewers,
organized by the California Air Resources Board.
Table of Contents

List of Tables………………………………………………………………………… .……i
List of Figures………………………………………………………………………..… …iii
Abstract………………………………………………………………………………..… …v
Executive Summary……………………………………………………………….. …..vi
Introduction…………………………………………………………………………. ……1
Chapter 1: Literature Review of Gentrification, Displacement, and
the Role of Public Investment……………..……………………. ……3
Chapter 2: Analysis of Historic Patterns of Neighborhood Change…. ….45
Chapter 3: Developing Tools for Analyzing Potential Displacement
Impacts in SCS…………………………………………….…………. ….93
Chapter 4: Effects on Auto Use of Household Displacement from
Rail Station Areas……………………….…………………………..… 156
Chapter 5: Anti-Displacement Policy Analysis…………………………….. ..181
Conclusions…………………………………………………………………………..… 262
References………………………………………………………………………………. 263
Appendices………………………………………………………………………………. 285
Appendix A: Summary of Racial Transition and Succession
Studies…………………………………………………………. ..285
Appendix B: Summary of the Impact of Rail Transit Facilities on
Residential and Commercial Property Values………… 291
Appendix C: Summary of Studies on TOD and Gentrification……… 295
Appendix D: TOD Impacts in Los Angeles………………………………. .297
Appendix E: Summary of Simulation Models of Gentrification……. 302
Appendix F: Census Tract Datasets………………………………………… 304
Appendix G: Parcel-Level Datasets………………………………………… 308
Appendix H: Data Cleaning Protocol for DataQuick Assessor
and Transaction Data………………………………………… 314

12/01/16 DRAFT
Appendix I: Sources and Definitions of Affordable Housing
Data for Section 2E.2………………………………………… .317
Appendix J: Ground-Truthing Methodology for the SF Bay Area… 318
Appendix K: Los Angeles Ground-Truthing Neighborhoods…….... .333
Appendix L: Detailed Ground-Truthing Methodology for Los
Angeles……………………………………………………………. 336
Appendix M: Survey Instruments in Los Angeles……………………… 339
Appendix N: Interview Protocol for Los Angeles………………………. 348
Appendix O: Detailed Assessments for LA Ground-Truthing
Case Studies…………………………………………………..… 352
Appendix P: Bay Area UrbanSim Models as Used in Plan Bay
Area……………………………………………………………..… 361
Appendix Q: SCAG PECAS Estimated Aggregated TOD Impacts.…. .381
Appendix R: In- and Out-Migration Regression Results………….…. .389
Appendix S: Average Daily VMT by Income and Rail Access………. .391
Appendix T: Anti-Displacement Strategies and Sources…………..… 399
Appendix U: Policies adopted by each LA County City…………….…. 401
Appendix V: Challenges Facing Inclusionary Zoning……………….… 402

12/01/16 DRAFT
List of Tables

Table 1.1 Indicators and Data Sources for Analyzing Gentrification and Displacement ......................... 36
Table 2A.1: Common Neighborhood-level Datasets Collected for Both Regions ........................................ 49
Table 2A.2: Common Address-level Datasets Collected for Both Regions ..................................................... 49
Table 2C.1: Summary Statistics for Transit Station Types in the Bay Area (Means) ................................. 53
Table 2C.2: TOD Tracts, Gentrified With/Without Development for Los Angeles County ..................... 54
Table 2C.3: Summary Statistics for Transit Station Types in the Bay Area (Means) ................................. 55
Table 2C.4: TODs, Gentrification, and Residential Development for the 9-County Bay Area ................ 56
Table 2D.1: In-Out Migration, Parsimonious Multivariate Regressions ......................................................... 61
Table 2D.2: Bivariate Analysis by Subgroups, LA County and the Bay Area, 2009-2013 ........................ 62
Table 2D.3: Modeling Share of In-Movers by Subgroups, Multivariate Regressions for Los Angeles
County, 2009-2013 ............................................................................................................................................................... 63
Table 2D.4: Modeling Share of In-Movers by Subgroups, Multivariate Regressions for the Bay Area,
2009-2013 ................................................................................................................................................................................ 64
Table 2E.1: Gentrification Criteria for Los Angeles, County Averages ............................................................ 65
Table 2E.2: Gentrification Criteria, Medians for the Nine-County Bay Area ................................................. 67
Table 2E.3: Logit Regressions of Gentrification, 1990-2000 and 2000-2013, Los Angeles ................... 70
Table 2E.4: Logit Regressions of Gentrification, 1990-2000 and 2000-2013, Bay Area ......................... 71
Table 2E.5: Changes in Affordable Housing1, Linear Regressions (Los Angeles), ...................................... 72
Table 2E.6: Changes in Affordable Housing, Linear Regressions (Bay Area) ............................................... 73
Table 2E.7: Evictions and Condominium Conversions, Linear Regressions, San Francisco................... 73
Table 2E.8: Change of Low-income Households, Linear Regressions (Bay Area) ...................................... 75
Table 2F.1: Changes in Neighborhood Characteristics, LA County, 2000-2013* ........................................ 76
Table 2F.2: Table 2F.2: Neighborhood Change Multivariate Regressions, LA County, 2000-2013*... 77
Table 2F.3: Changes in Neighborhood Characteristics, SF Bay Area, 2000-2013*..................................... 78
Table 2F.4: Neighborhood Change Multivariate Regressions, SF Bay Area, 2000-2013 ......................... 79
Table 2G.1: Regression Results for Los Angeles ....................................................................................................... 81
Table 2H.1: Comparisons of Secondary Data and Ground-truthing Data in Three Case Study
Areas ........................................................................................................................................................................................... 84
Table 2H.2: Count of Parcels and Blocks Surveyed in Los Angeles ................................................................... 85
Table 2H.3: Comparison of Indicators of Neighborhood Change in Los Angeles Case Studies ............. 87
Table 2H.4: Percent land use matched in Los Angeles Case Study Areas ...................................................... 88
Table 2H.5: Estimated Housing Units from Assessor and Census Data in Los Angeles Study ............... 89
Table 2H.6: Percent of Major improvements for Observed and Assessor Parcels in Los Angeles
Study Areas .............................................................................................................................................................................. 89
Table 2H.7: Percent of Constructions for Observed and Assessor Parcels in Los Angeles Study ........ 90
Table 3A.1: Key Features of UrbanSim…………………………………………………………………………………….. 102
Table 3A.2: Specification of UrbanSim Model Components Using Parcel Data Structure .................... 103
Table 3A.3: Data Inputs and Outputs of UrbanSim ............................................................................................... 106
Table 3A.4: Hedonic Regression Estimation Results for Rental Listings .................................................... 110
Table 3A.5: Relocation Choice Model Estimation Results for Renters ......................................................... 113
Table 3A.6: Location Choice Model Estimation Results for Renters in Income Quartile 1 .................. 114

1 We ran an analysis looking at the change in public housing units in TOD and non-TOD areas and found that
changes in TOD areas are essentially the same as in non-TOD areas (the difference in proportion is not statistically
different). From 2000 to 2013, non-TOD areas lost 5.8% of their public housing units, whereas non-TOD areas lost
6%.
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Table 3A.7: Location Choice Model Estimation Results for Renters in Income Quartile 2 .................. 115
Table 3A.8: Location Choice Model Estimation Results for Renters in Income Quartile 3 .................. 115
Table 3A.9: Location Choice Model Estimation Results for Renters in Income Quartile 4 .................. 116
Table 3B.1: Dwelling type categories in the SCAG PECAS Model.................................................................... 124
Table 3B.2: Household Categories in the SCAG PECAS Model ......................................................................... 125
Table 3B.3: Rent modifier Coefficients in the SCAG PECAS model for the distance to Transit Station
.................................................................................................................................................................................................... 128
Table 3B.4: Effects of neighborhood characteristics on neighborhood change ....................................... 133
Table 3B.5: Legend of measured effects from Table 3B.4.................................................................................. 134
Table 3B.6: Metrics used to calibrate TOD scenario ............................................................................................ 136
Table 3B.7: Results of the parameter test scenarios ............................................................................................ 138
Table 3B.8: Effect of parameter changes compared to the empirical targets ........................................... 138
Table 3B.9: Change resulting from the optimal parameters ............................................................................ 139
Table 3B.10: Changes in Zone Constants .................................................................................................................. 139
Table 3B.11: SCAG PECAS Enhancement Options ................................................................................................. 147
Table 3C.1: Actual versus Predicted Gentrification in Los Angeles Tracts ................................................. 152
Table 3C.2: Actual versus Predicted Gentrification in Bay Area Tracts ....................................................... 154
Table 3C.3: Actual versus Predicted Loss of Low Income Households in Bay Area Tracts ................. 155
Table 4.1: Average Daily VMT by Income Category and Rail Access, metropolitan areas only, NHTS
2009, and CHTS 2010-2012 ........................................................................................................................................... 166
Table 4.2: Tobit Model of Household Daily VMT for NHTS 2009 Data and CHTS 2010-2012 Data
(Metropolitan areas, San Francisco Bay Area, and Los Angeles Area) ......................................................... 170
Table 4.3: Tobit Model of Household Daily VMT for all Metropolitan Areas, Bay Area, LA Area (NHTS
and CHTS data) .................................................................................................................................................................... 174
Table 4.4: Example scenarios showing estimated change in VMT in selected gentrifying census
tracts ........................................................................................................................................................................................ 178
Table 5.1: Affordable Housing and Anti-Displacement Strategies ................................................................. 187
Table 5.2: Federal and State Funding Available for Affordable Rental ........................................................ 197
Table 5.3: Anti-Displacement Policies in the Bay Area and Los Angeles ..................................................... 201
Table 5.4: Anti-Displacement Policies/Programs by County ........................................................................... 202
Table 5.5: Annual Average Housing Unit Construction per 10,000 People, Bay Area Cities, by
Affordable Housing Production Strategy .................................................................................................................. 203
Table 5.6: Projected housing demand, supply, and shortfall for the nine-county ................................... 204
Table 5.7: LA County Cities that have instigated 3 or more Anti-Displacement and Housing
Affordability Policies ......................................................................................................................................................... 205
Table 5.8: Existing Los Angeles Plans with TOD sections .................................................................................. 213
Table 5.9: Inclusionary Housing Units Produced (1999-2006) ...................................................................... 220
Table 5.10: Inclusionary Housing Units Produced (1998-2005) .................................................................... 221
Table 5.11: Cities in the Bay Area with Rent Stabilization/Control Ordinances ...................................... 226
Table 5.12: Chinatown, LA Demographics ............................................................................................................... 248
Table 5.13: Hollywood/Western Demographics ................................................................................................... 252
Table 5.14: 103rd St/Watts Towers Demographics ............................................................................................ 257

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List of Figures

Figure 1.1 “Some Conditions Resulting in Displacement in Urban Neighborhoods” ................................ 26
Figure 2C.1: Map of 2010 TOD tracts ............................................................................................................................ 51
Figure 2C.2: TOD Areas in the Bay Area ....................................................................................................................... 52
Figure 2C.3: Development Tracts in LA County (L) and Gentrified Tracts in LA County (R) ................. 54
Figure 2C.4: Development Tracts in the Bay Area (L) and Gentrified Tracts in the Bay Area (R) ............. 56
Figure 2D.1: In- and Out-Migration Rates Calculations ......................................................................................... 58
Figure 2D.2: Bivariate Analysis, In- and Out-Migration Rates for Los Angeles, 2009-2013 .................. 59
Figure 2D.3: Bivariate Analysis, In- and Out-Migration Rates for Los Angeles (L) and the SF
Bay Area (R), 2009-2013 ...................................................................................................................................................... 59
Figure 2D.4: Per-Capita Income, LA County and 9-County Bay Area (adjusted to 2013 dollars) .............. 63
Figure 2E.1: Gentrified/Gentrifying census Tracts, LA County 1990-2013 ........................................................ 66
Figure 2E.2: Gentrified/Gentrifying census Tracts, SF Bay Area 1990-2013 .................................................... 68
Figure 2G.1: Estimated Number of Housing Units for LA County ..................................................................... 82
Figure 2H.1: Gentrifying and Gentrified Census Tracts, Los Angeles County, 1990-2013 ........................... 86
Figure 3A.1: UrbanSim Model Flow: Employment Focus .................................................................................. 104
Figure 3A.2: UrbanSim Model Flow: Household Focus ....................................................................................... 104
Figure 3A.3: UrbanSim Model Flow: Real Estate Focus ...................................................................................... 105
Figure 3A.4: Computation Process in UrbanSim Choice Models ..................................................................... 108
Figure 3A.5: Rent per Square Foot from Craigslist Rental Listings ............................................................... 110
Figure 3A.6: Square Footage per Unit from Craigslist Rental Listings ......................................................... 111
Figure 3A.7: Rent Burdens for Bay Area Households .......................................................................................... 112
Figure 3B.1: Information flows in the PECAS framework ................................................................................. 123
Figure 3B.2: Shifted Exponential Function used in Transit Local Rent Modifier ..................................... 127
Figure 3B.3: Change in number of households <10k, 2 or less person .............................................................. 141
Figure 3B.4: Change in Households by Category and Zone ............................................................................... 142
Figure 3B.5: Relative change in rent in Luxury Single Family Dwelling space (ResType 3) ............... 143
Figure 3B.6: Relative change in rent in Economy Single Family Dwelling space (ResType 4) .......... 143
Figure 4.1: Average Daily VMT by Income and Rail Access in All Californian Metropolitan Areas
(NHTS data) .......................................................................................................................................................................... 167
Figure 4.2: Average Daily VMT by Income and Rail Access in All Californian Metropolitan Areas
(CHTS data) ........................................................................................................................................................................... 167
Figure 4.3: Net Effect of Household Income on VMT (NHTS, Based on Models in Table 4.2)............. 172
Figure 4.4: Net effect of rail proximity on VMT, by income category – threshold models ................... 175
Figure 5.1: State and Federal Investment in Affordable Housing (from the California Housing
Partnership Corporation) ............................................................................................................................................... 198
Figure 5.2: Number of Anti-Displacement Policies by City ............................................................................... 202
Figure 5.3: Comparison of the Proportion of Bay Area and Los Angeles Cities with Anti-
Displacement Policies ....................................................................................................................................................... 206
Figure 5.4: Per Capita Opportunity Bay Area Grant Funding By Number of Anti-Displacement
Policies, Bay Area Cities ................................................................................................................................................... 211
Figure 5.5: Distribution of Units by Income Level and Age of Inclusionary Program............................ 217
Figure 5.6: Inclusionary-Development Units by Income Target ..................................................................... 217
Figure 5.7: Inclusionary Zoning in Bay Area Cities ............................................................................................... 219
Figure 5.8: Condominium Conversion Policies in Bay Area Cities ................................................................. 224
Figure 5.9: Rent Control Policies in the Bay Area ................................................................................................. 227
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Figure 5.10: Census Tracts at Risk for Gentrification/Displacement in 1990 and 2000, but did not
experience gentrification between 2000 2013 ...................................................................................................... 230
Figure 5.11: Tract 113, Chinatown, and Greater Chinatown ............................................................................ 231
Figure 5.12: Change in Median Rent in Chinatown (Tract 113) and Surrounding Tracts ................... 233
Figure 5.13: Instances of No-Fault Evictions and Percentage of Rent-Controlled Units in San
Francisco by Census Tract and Chinatown and Surroundings ........................................................................ 235
Figure 5.14: East Palo Alto and Case Study Area ................................................................................................... 237
Figure 5.15: Case Study Area Map (Census Tract 5019) .................................................................................... 242
Figure 5.16: Race/Ethnicity and Population Change, 1990-2013 .................................................................. 244
Figure 5.17: Rent Stabilized Units in Tract 5019, San Jose ............................................................................... 245
Figure 5.18: Chinatown, LA Study Area by Census Tract (2010 Boundaries) ........................................... 247
Figure 5.19: Hollywood/Western Study Area by Census Tract (2010 Boundaries) .............................. 251
Figure 5.20: 103rd St/Watts Towers Study Area by Census Tract (2010 Boundaries) ........................ 256

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Abstract

In 2008, California passed Senate Bill 375, requiring metropolitan planning organizations to
develop Sustainable Communities Strategies as part of their regional transportation planning
process. While the implementation of these strategies has the potential for environmental and
economic benefits, there are also potential negative social equity impacts, as rising land costs in
infill development areas may result in the displacement of low-income residents. This report
examines the relationship between fixed-rail transit neighborhoods and displacement in Los
Angeles and the San Francisco Bay Area, modeling patterns of neighborhood change in relation to
transit-oriented development, or TOD. Overall, we find that TOD has a significant impact on the
stability of the surrounding neighborhood, leading to increases in housing costs that change the
composition of the area, including the loss of low-income households. We found mixed evidence as
to whether gentrification and displacement in rail station areas would cause an increase in auto
usage and vehicle miles traveled (VMT). The report also examines the effectiveness of anti-
displacement strategies. The results can be adapted into existing regional models (PECAS and
UrbanSim) to analyze different investment scenarios. The project includes an off-model tool that
will help practitioners identify the potential risk of displacement.
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