Meaningful Action: Evaluating Local Government Plans to Affirmatively Further Fair Housing in California

Figures & data

Figure 1. Regional and internal segregation by race for cities in Southern California with between 40,000 and 500,000 residents.

Source: US Census Bureau (2022).

Table 1. Selected characteristics of eight case study municipalities and southern California median.

Municipality	Population (000s)	Median household income (000s)	Percent homeowner	Percent Non-Hispanic White	Dissimilarity index (% White, blocks)	2021 Regional Housing Needs Allocation/2014 Housing capacity^a
Chula Vista	275	93	60	16	0.23	0.5
Culver City	41	105	54	47	0.43	1.9
Downey	114	78	49	14	0.23	4.7
Fontana	208	83	66	13	0.31	1.1
Montebello	63	67	44	6	0.41	23.7
Pasadena	139	90	42	34	0.33	3.8
Santa Monica	93	100	29	63	0.28	2.4
Simi Valley	127	103	71	58	0.21	0.9
Median municipality^b	52	82	59	33	0.28	1.5

Source: Authors with US Census Bureau (2022), California Department of Housing and Community Development (2021b), and Monkkonen et al. (2024).

Notes: ^aThe ratio of 2021 Regional Housing Needs Allocation (RHNA) to 2014 housing capacity reflects the scale of the challenge cities face in accommodating expectations for housing production in their existing zoning. ^bSouthern California refers to the seven counties that comprise the regions of the Southern California Association of Governments and San Diego County Association of Governments.

Table 2. Summary of housing element characteristics for case study cities.

City	Consultant	Date certified	Number of drafts^a	Length (pages)	Length of appendices (pages)
Chula Vista	Veronica Tam and Associates^b	October 28, 2022	3	90	305
Culver City	Veronica Tam and Associates	October 10, 2022	4	114	182
Downey	MIG	October 14, 2022	3	178	48
Fontana	Kimley-Horn	August 9, 2022	2	244	106
Montebello	Rangwala Associates	July 11, 2022	3	146	0
Pasadena	Veronica Tam and Associates	March 10, 2023	4	82	236
Santa Monica	John Douglas	October 14, 2022	3	173	1,432
Simi Valley	Rincon Consultants	May 18, 2023	3	104	40

Source: California Department of Housing and Community Development (n.d.), City of Chula Vista (2022), City of Culver City (2021), City of Downey (2021), City of Fontana (2021), City of Montebello (2021), City of Pasadena (2022), City of Santa Monica (2021), and City of Simi Valley (2022).

Notes: ^aBased on the number of California Department of Housing and Community Development review letters. ^bVeronica Tam and Associates only assisted with the AFFH section, not the other components of the housing element.

Table 3. Nine sectors of Affimatively Furthering Fair Housing programs.

Sector	Description
Education and outreach	Programs that spread awareness, coordinate with other agencies, or host meetings.
Required by state law	Programs in most categories that are driven in direct response to state law. This does not include strategies to meet the Regional Housing Needs Allocation.
Vague future actions	Programs without specific goals, metrics, or implementation plans, or programs containing the word "may."
Place-based investment	Programs focused on investing in lower-income/environmental justice neighborhoods. Typically related to infrastructure and maintenance.
Assistance to lower-income households	Subsidies, technical assistance to lower-income households, preservation of existing low-income housing stock.
Infrastructure and maintenance	General improvement of infrastructure, not necessarily place based or aimed at lower-resourced neighborhoods.
Housing production	Programs aimed at spurring or incentivizing new housing production. This program does not include housing programs directly required by state law, but would include strategies used to meet the RHNA.
Information strategy	Programs to create and organize data, generally to be used internally.
Preservation of existing affordable housing	Programs geared toward preserving and maintaining affordable housing stock, rather than the construction of new units.

Table 4. Evaluation of fair housing analysis.

City	Conditions in low-income areas	Affordable housing in affluent areas	Clarity	Constraints	Other factors	Sites inventory evaluation	Summary score (% of total)
Chula Vista	3	2	2	1	2	2	63
Culver City	3	3	3	1	3	2	79
Downey	2	3	2	3	2	2	74
Fontana	3	2	2	3	3	2	79
Montebello	3	3	3	2	3	2	84
Pasadena	3	3	3	2	1	2	74
Santa Monica	3	3	3	2	3	3	89
Simi Valley	2	2	3	3	2	2	74

Source: Authors with City of Chula Vista (2022), City of Culver City (2021), City of Downey (2021), City of Fontana (2021), City of Montebello (2021), City of Pasadena (2022), City of Santa Monica (2021), and City of Simi Valley (2022).

Table 5. Summary of Affirmatively Furthering Fair Housing program characteristics by municipality.

City	Number of Affirmatively Furthering Fair Housing programs or actions	Programs with Affirmatively Furthering Fair Housing component (%)	Metrics
			Have timeline (%)	Have objectives (%)	New (%)
Chula Vista	23^a	35	57	57	61
Culver City	39	80	95	97	61
Downey	28	42	100	96	74
Fontana	29	29	90	58	48
Montebello	15^a	33	44	62	71
Pasadena	45	70	100	91	29
Santa Monica	23	38	87	74	61
Simi Valley	30	62	91	83	65
Total	232	53	88	81	56

Source: Authors with City of Chula Vista (2022), City of Culver City (2021), City of Downey (2021), City of Fontana (2021), City of Montebello (2021), City of Pasadena (2022), City of Santa Monica (2021), and City of Simi Valley (2022).

Notes: ^aThese cities had one Affirmatively Furthering Fair Housing “program” with many actions.

Table 6. Share of programs by Affirmatively Furthering Fair Housing goal.

City	Affirmatively Furthering Fair Housing Goal
	Housing disparities (%)	Integration (%)	Transforming neighborhoods (%)	Anti-discrimination (%)
Chula Vista	62	13	4	21
Culver City	61	16	8	15
Downey	65	0	13	22
Fontana	48	0	29	23
Montebello	43	24	12	21
Pasadena	47	13	18	22
Santa Monica	57	30	0	13
Simi Valley	60	9	9	22
Average	56	12	12	20

Source: Authors with City of Chula Vista (2022), City of Culver City (2021), City of Downey (2021), City of Fontana (2021), City of Montebello (2021), City of Pasadena (2022), City of Santa Monica (2021), and City of Simi Valley (2022).

Table 7. Meaningful impact of Affirmatively Furthering Fair Housing programs by municipality.

City	Number of programs	Number of meaningful programs	Summary program score^a	Average program score
Chula Vista	23	2	51	2.2
Culver City	39	4	87	2.2
Downey	28	8	86	3.1
Fontana	29	3	58	2.0
Montebello	15	2	39	2.6
Pasadena	45	7	120	2.7
Santa Monica	23	8	81	3.5
Simi Valley	30	5	73	2.4

Source: Authors with City of Chula Vista (2022), City of Culver City (2021), City of Downey (2021), City of Fontana (2021), City of Montebello (2021), City of Pasadena (2022), City of Santa Monica (2021), and City of Simi Valley (2022).

Note: ^aTo calculate the summary program score, we assign meaningful programs a value of six, medium-impact programs a three, and low-impact programs a one, and sum them. The average also uses this scoring system.

Table 8. Distribution of sites for new housing and existing zoning.

	Fair Housing Land Use Score				Other measures
City	All sites	Lower-income sites	All rezoned sites	Existing multi-family zoning^a	Dissimilarity index (all sites)	Share of Regional Housing Needs Allocation met with rezoning (%)
Chula Vista	−0.06	−0.13	NA	−0.46	0.68	0
Culver City	−0.01	−0.15	−0.01	−0.21	0.17	256
Downey	−0.28	−0.24	−0.24	−0.46	0.43	68
Fontana	0.17	0.00	0.10	0.05	0.48	42
Montebello	0.25	0.28	0.32	−0.39	0.45	81
Pasadena	−0.42	−0.30	NA	−0.52	0.57	0
Santa Monica	−0.46	−0.50	−0.49	−0.34	0.48	100
Simi Valley	−0.75	−0.76	−0.71	−0.39	0.78	55

Source: Authors with City of Chula Vista (2022), City of Culver City (2021), City of Downey (2021), City of Fontana (2021), City of Montebello (2021), City of Pasadena (2022), City of Santa Monica (2021), City of Simi Valley (2022), and California Department of Housing and Community Development (2021b).

Notes: NA: not applicable. ^aThe multi-family zoning score does not incorporate planned rezoning in the housing element, and excludes mixed-use zones.

U.S. Census Bureau. (2022). 2017-2021 American Community Survey 5-year estimates. Retrieved via the Census API.

 Google Scholar

California Department of Housing and Community Development (HCD). (2021b). Regional housing needs allocation. Retrieved January 24, 2024, from https://www.hcd.ca.gov/planning-and-community-development/regional-housing-needs-allocation

 Google Scholar

Monkkonen, P., Manville, M., & Lens, M. (2024). Built out cities? A new approach to measuring land use regulation. Journal of Housing Economics, 63, 101982. https://doi.org/10.1016/j.jhe.2024.101982

 Web of Science ®Google Scholar

City of Chula Vista. (2022). Housing element of the general plan 2021-2029.

 Google Scholar

City of Culver City. (2021). Housing element of the general plan 2021-2029.

 Google Scholar

City of Downey. (2021). Housing element of the general plan 2021-2029.

 Google Scholar

City of Fontana. (2021). Housing element of the general plan 2021-2029.

 Google Scholar

City of Montebello. (2021). Housing element of the general plan 2021-2029.

 Google Scholar

City of Pasadena. (2022). Housing element of the general plan 2021-2029.

 Google Scholar

City of Santa Monica. (2021). Housing element of the general plan 2021-2029.

 Google Scholar

City of Simi Valley. (2022). Housing element of the general plan 2021-2029.

 Google Scholar