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HomeMy WebLinkAbout7.1 Regional Housing Needs Alloc Update C I T Y C LE R K File # D[3]~QJ-[z]~ AGENDA STATEMENT CITY COUNCIL MEETING DATE: January 16, 2007 SUBJECT: ATTACHMENTS: RECOMMEiON: ~ FINANCIAL STATEMENT: None. PROJECT DESCRIPTION: Background Update on Regional Housing Needs Allocation (RHNA) Methodology for Income Allocations for the 2007-2014 Housing Element Cycle Report prepared by Mamie R. Nuccio, Associate Planner 1) 2) City Council Agenda Statement dated December 19,2006. Association of Bay Area Governments Memo dated January 4, 2007 regarding Alternative Income Allocation Method. Draft letter to ABAG regarding the proposed alternative income allocation methodology. 3) 1) Receive report and direct Staff to forward comments (Attachment 3) to ABAG regarding the proposed Alternative Income Allocation Methodology for the 2007-2014 Housing Element cycle, OR Accept the proposed Alternative Income Allocation Methodology for the 2007-2014 Housing Element cycle. 2) On November 16,2006, the Association of Bay Area Governments (ABAG) Executive Board adopted a Resolution authorizing the release of the proposed Regional Housing Needs Allocation (RHNA) methodology for public review and comment. The comment period is still currently open and will close on January 18, 2007. The ABAG Executive Board will also meet on January 18th to adopt the final RHNA methodology. At the December 19, 2006 City Council meeting, Staff presented an informational report on the RHNA methodology and the City Council accepted the proposed methodology. The methodology included the allocation of the regional housing need as well as the allocatioJ). of housing units by income level (See COPY TO: Page 1 of 4 ITEMNO.~ G:\General Plan\Housing Element\RHNA 2007-2014\01-16-07 CCSR RHNA Method Alternatives.doc G Attachment 1). The proposed methodologies for the 2007-2014 RHNA period were as follows (See Tables 1 and 2 below): Committee Recommendation for the RHNA Methodolo Household Growth from 2007-2014 Existing Em loyment in 2007 Em loyment Growth from 2007-2014 Household Growth near transit from 2007-2014 Employment Growth near transit from 2007-2014 40% 20% 20% 10% 10% Table 2. Recommended Re ional Income Allocation based on Affordabili Very Low Income Low Income Moderate Income Above Moderate Income Total U to 50% AMI 50%-80% AMI 80%-120% AMI Above 120% AMI 23% 16% 19% 42% 100% Housing Methodology Committee (HMC) Meeting of January 4, 2007 Since the opening of the public review and comment period, ABAG has received comments from various jurisdictions regarding the proposed RHNA methodology. Allocation ofthe Region's Total Housing Need The most prevalent concern expressed by local jurisdictions regarding the proposed methodology for allocating the region's total housing need was regarding the transit factor. The proposed methodology includes two transit factors: household growth near transit and employment growth near transit. Both factors are weighted at 10% (See Table 1 above). Local jurisdictions expressed concern regarding the use of both existing and planned transit as factors in the methodology based on a belief that this would unfairly burden those jurisdictions with either existing or planned transit and those cities with multiple transit stations. In response to these comments, ABAG staff developed several new alternative methodologies for consideration. The HMC reviewed these new alternatives at the January 4, 2007 meeting and by majority vote recommended that the proposed methodology remain unchanged (See Table 1 above). Allocation of Housing Units by Income Level Local jurisdictions also expressed concern to ABAG regarding the allocation of housing units by income level. Some jurisdictions believe that by applying the "equal share" concept, the methodology does not do enough to alleviate existing concentrations of lower income housing. These jurisdictions indicated that they would be unfairly burdened with additional lower income housing further perpetuating regional, social and economic inequities. In response to these comments, ABAG staff prepared several new alternative methodologies for consideration (See Attachment 2). The HMC reviewed the new alternatives and by majority vote recommended a new methodology that takes into consideration existing concentrations of lower income housing. ANALYSIS: Since the HMC did not recommend to ABAG any modifications to the proposed methodology for the allocation of total housing units, which the City Council reviewed at the December 19, 2006 meeting, Page 2 of 4 Staffs analysis focuses only on the proposed changes to the methodology for allocating units by income level. Allocation of Housing Units by Income Level The previously proposed methodology for the allocation of housing units by income level applied an "equal share" approach whereby all jurisdictions within the region would be required to provide the same percentage of lower income housing based on the distribution of lower income households within the region (See Table 2 above). By taking the "equal share" approach, every jurisdiction would contribute to the region's need for lower income housing; however, this approach did not take into consideration existing concentrations of lower income housing. The proposed alternative methodology attempts to factor into the allocation existing concentrations of lower income housing. . Census 2000 data for local household income distribution and regional household income distribution would be used by ABAG to determine where existing concentrations of lower income housing currently exist and where additional lower income housing is needed. A comparison of a jurisdiction's existing household income distribution to the region's household income distribution would determine whether the jurisdiction has more, or less, lower income households than the region as a whole. If a jurisdiction has more lower income households (i.e. Oakland), then they would be assigned a smaller percentage of lower income housing units for the 2007-2014 RHNA cycle. If a jurisdiction has less lower income households (i.e. Piedmont), they would be assigned a larger percentage of lower income housing units for the 2007-2014 RHNA cycle. For example, under the previously proposed methodology, Oakland and Piedmont would both be required to set aside 23% of their housing unit allocation for very-low income households. Under the currently proposed methodology, Oakland would be assigned 13% (to correct for existing concentrations of lower income housing) whereas Piedmont would be assigned 33% (to compensate for an existing lack of lower income housing). The actual number of lower income housing units assigned to a jurisdiction would be a percentage of that jurisdiction's total housing unit allocation. The multiplier used by ABAG in calculating the proposed alternative methodology is 175%. This means that each jurisdiction is allocated 175% of the difference between its 2000 household income distribution and the 2000 regional household income distribution. Other multipliers of 100%, 125% or 150% could also be used to address existing concentrations of low income housing. ABAG proposed a multiplier of 150% to the HMC; however, this was not supported by a majority. Implications for Dublin Under the previously proposed methodology, Dublin would have been required to provide the following: Very Low Income Low Income Moderate Income Above Moderate Income Previous Proposed Methodology 23% 16% 19% 42% Currently Proposed Methodology 33% 20% 19% 28% Based on the proposed alternative methodology now recommended by the HMC, which utilizes a 175% multiplier, Dublin's percentage of very low and low income units would increase by 10% and 4% respectively, an increase of 343 very low income units and 121 low income units (please note that the number of units stated are provided for illustrative purposes only and do not necessarily reflect the actual Page 3 of 4 allocation); the percentage of moderate income units would remain proportionately the same; and, above moderate income units would be reduced by 14% (See Table 3 below). Total Need Dublin 3,440* Percentage of Total *The Total Need number reflects the 1999-2006 RHNA and is not the official RHNA number for the 2007-2014 RHNA cycle. Similarly, the numbers shown for very low, low, moderate and above moderate incomes are based on the 1999-2006 RHNA and are used for illustrative purposes only; they do not reflect Dublin's actual allocation for the 2007-2014 RHNA. 569* 16% 661* 19% 1,432* 42% 690* 20% 669* 19% The most significant impact of the newly proposed alternative methodology to Dublin would be providing 1,121 very low income units (343 additional units from the previously proposed methodology) within the 2007-2014 RHNA cycle. While Staff supports the methodology in concept, it may be unrealistic to expect that such a large number of very low income units could be provided within a short 7 year time frame. Additionally, the types of support services utilized most frequently by lower income households are currently located within the more urban areas ofthe region and not in the Tri-Valley area. Therefore, Staff recommends that the City Council forward a letter (Attachment 3) to ABAG requesting consideration of the use of a different multiplier to achieve more realistic goals for 2007-2014 RHNA cycle while continuing to take into consideration existing concentrations of lower income housing. As shown in Attachment 2, ABAG has calculated an alternative methodology using a 150% multiplier which would increase Dublin's percentage of very low and low income units by 6% and 3% respectively; an increase of 235 very low income units and 79 low income units (please note that the number of units stated are provided for illustrative purposes only and do not necessarily reflect the actual allocation). While this results in a slightly lower income allocation for very low and low income units, it is still somewhat aggressive. Staffs recommendation is that ABAG consider using a less aggressive multiplier of 100% or 125% thereby taking a more incremental approach to addressing existing concentrations of lower income housing which is more realistic and more likely to be achievable. It would also give service providers more of an opportunity to redirect resources to the outlying suburban areas of the region as the service population grows. NEXT STEPS: Since the public review and comment period for the 2007-2014 RHNA methodology closes on January 18,2007, Staff has prepared a draft letter to ABAG for the City Council's consideration which expresses concern over the proposed alternative methodology for the allocation of housing units by income level (See Attachment 3). STAFF RECOMMENDATION: Staff recommends that the City Council: 1) Receive report and direct Staff to forward comments (Attachment 3) to ABAG regarding the proposed Alternative Income Allocation Methodology for the 2007-2014 Housing Element cycle, OR 2) Accept the proposed Alternative Income Allocation Methodology for the 2007-2014 Housing Element cycle. Page 4 of 4 \ Db '..h.D CITY CLERK File # DOO(C]-~CJ AGENDA STATEMENT CITY COUNCIL MEETING DATE: December 19,2006 SUBJECT: ATTACHMENTS: RECOMMENDATION: . 1) ,/I ~ ,).",- r:J( '1 ~',j\ FINANCIAL STATEMENT: PROJECT DESCRIPTION: Background Informational Report on the Regional Housing Needs Allocation (RHNA) Methodology for the 2007-2014 Housing Element Cycle Report prepared by Mamie R. Nuccio, Associate Planner 1) Association of Bay Area Governments (ABAG) memo to the ABAG Executive Board dated October 26, 2006 regarding Draft Regional Housing Needs Allocation Methodology. Association of Bay Area Governments (ABAG) memo to the Housing Methodology Committee (HMC) dated October 11, 2006 regarding Scenarios for Allocating Units by Income 2) 2) Receive report and accept the 2007-2014 RHNA methodology for the allocation of total housing units and allocation of units by income level, OR Direct Staff to forward comments to ABAG regarding the methodology. None. State law requires that all governing bodies (i.e. the City Council) adopt a comprehensive, long term General Plan for the physical development of the City. The General Plan must include the 7 State mandated elements; one of which is the Housing Element. The Housing Element establishes specific goals, policies and objectives to meet the current and future housing needs of the City. The Housing Element must be updated approximately every 5 years and submitted for review to the State Department of Housing and Community Development (HCD) for compliance with State law. The City completed the most recent update to the Housing Element in June 2003 and received State certification in July 2003. The next update to the Housing Element is due in June 2009. COPY TO: ------------------------------------------------------------------------------------------------------------- Page 1 of7 /--/!t'1II<t!J1 ' < 7.1 Attachme {Y G:\General Plan\Housing Element\RHNA 2007-20]4\12-] 9-06 CCSR RHNA Methodology.doc -.---. ZDbY-LD The updating of the Housing Element begins with the State issuing Regional Housing Needs Allocation (RHNA) numbers to the local Council of Governments. The Association of Bay Area Governments (ABAG) is the Council of Governments for the 9 county San Francisco Bay Area region. In accordance with State law, ABAG is required to determine the existing and projected housing need for the San Francisco Bay Area and to develop a methodology by which to allocate the region's housing need to individual counties and cities within the region. The State, in collaboration with ABAG, assigns the RHNA numbers which must then be incorporated into each jurisdictions Housing Element update. 1999-2006 RHNA Period Regional Housing Need The methodology adopted by ABAG for allocating the regions total housing need during the 1999-2006 Housing Element cycle included two factors, 1) Household Growth and 2) Employment Growth. Both factors were weighted equally at 50% (See Table 1 below). Table 1. 1999-2006 RHNA Methodolo Factor Household Growth from 1999-2006 Em loyment Growth from 1999-2006 Total Percent e 50% 50% 100% The number of housing units allocated to each jurisdiction was based on the projected growth in households and employment for the 1999-2006 RHNA period. Based on this methodology, the City of Dublin was assigned a RHNA of 5,436 housing units. State law requires that local jurisdictions remove constraints and adequately zone land to allow for the construction of their RHNA. During the 1999-2006 RHNA period, the City of Dublin successfully zoned land to allow for the construction of over 5,436 housing units. While local jurisdictions are not required to actually construct their allocation of housing units, the City issued building permits for the construction of 3,585 new housing units during the 1999-2006 RHNA period. Dublin's success in enabling the construction of new housing units surpasses that of many jurisdictions within the Bay Area. Affordabi1ity In addition to adopting a methodology for allocating the regions total housing need to individual jurisdictions, ABAG also adopts a methodology for the distribution of affordable housing units. When allocating affordable housing units, the methodology attempts to ensure that all communities contribute equally in providing affordable housing and responding to existing needs for affordable housing without over concentrating lower income households within a particular community. In an effort to move the Bay Area region towards a more equitable distribution of affordable housing units, the methodology adopted for the 1999-2006 RHNA period started with each jurisdictions existing income distribution and then moved it 50% towards the regional average. Based on this methodology, the City of Dublin received an allocation of 796 very low income units, 531 low income units, 1,441 moderate income units, and 2,668 above moderate income units (see Table 2 below). Page 2 of7 Table 2. Ci of Dublin 1999-2006 RHNA Income 1Jj~l!1 1999-2006 RHNA ** 30:04lo Very Low Income ( <50% AMI* Low Income >50% to <80% AMI* ) Moderate Income (>80% to <120% AMI*) Above Moderate Income (> 120% AMI* Total 5,436 3,585 * AMI: Area Median Income. The Area Median Income for a family of four living in Alameda County in 2006 is $86,300. **Local jurisdictions are required by State law to remove constraints and adequately zone land to allow for the construction of their housing unit allocations. ***Permitted is defmed as the issuance of Building Permits for the construction of a residential unit. 796 T otalT:Jni 1999-20fJ6iJlfll1iflik 257 (32%) 531 239 (45%) 1,441 369 (26%) 2,668 2,720 (102%) 2007-2014 RHNA Period In order to determine how to allocate the Bay Area's share of housing need for the 2007-2014 RHNA period, ABAG assembled a Housing Methodology Committee (HMC) comprised of elected officials, city and county members and stakeholder representatives to advise ABAG staff on a methodology for the allocation. City Staff attended the HMC meetings which were held monthly from May to October 2006. ABAG discussed with the HMC various methodologies and a variety of factors were considered including, household growth; existing employment; employment growth; household growth near transit; and, employment growth near transit. In all, the HMC reviewed 10 different methodologies. The HMC was also asked to recommend a methodology for determining the Regional Income Allocations. The Regional Income Allocations set forth the number of RHNA housing units which must be set aside for very low, low, moderate and above moderate income levels. Regional Housing Need The HMC recommended that the following five RHNA factors be used in allocating the regional housing need: 1) Household Growth; 2) Existing Employment; 3) Employment Growth; 4) Household Growth near Transit; and 5) Employment Growth near Transit (See Table 3 below). Projections 2007 is used to determine what each jurisdictions household growth and employment growth will be for the 2007-2014 RHNA period. Because Projections 2007 looks at data in 5 year increments (i.e. 2005,2010, 2015, etc.) ABAG will look at growth between 2005 and 2010 and between 2010 and 2015 and average the growth on a yearly basis to estimate the 2007 and 2014 numbers. For example, Dublin's number of households in 2005 was 13,440 and is projected to be 16,600 in 2010 for a total household growth of 3,160 households. By dividing the household growth (3,160 households) by 5 (the number of years between 2005 and 2010) you obtain an estimated yearly household growth rate of 632 households. In order to estimate Dublin's 2007 household population you would add the total number of households in 2005 (13,440) plus 632 households for 2006 and another 632 households for 2007. The result is an Page 3 of7 estimated 14,704 households for 2007. The same formula would be used to e~~~~old population in 2014 as well as existing employment and employment growth. Each factor is weighted based upon the relative importance ofthe factor. For example, the HMC felt that household growth over the next 7 years (2007-2014) should receive the greatest weighting at 40% since this factor directly affects the need for additional housing units. Existing Employment in 2007 is included as a factor and weighted 20% in order to improve the existing jobs/housing balance within the region. Employment Growth is also included as a factor and weighted 20% in order to maintain a jobs/housing balance over the next 7 years. Lastly, the HMC felt that Household Growth and Employment Growth near Transit were important factors to include but gave them a lower weighting of 10% each. To determine Household Growth and Employment Growth near Transit, ABAG will focus on growth within a 12 mile radius of existing or planned transit stations. Including growth near transit as a factor is intended to focus future development near transit stations to help alleviate traffic congestion within the region. Table 3. HMC Recommendation for the RHNA Methodolo Factor Household Growth from 2007-2014 Existin Em 10 ent in 2007 Em 10 ent Growth from 2007-2014 Household Growth near transit from 2007-2014 Em 10 ent Growth near transit from 2007-2014 Percenta e 40% 20% 20% 10% 10% Once the State of California releases the regional housing needs number in March 2007, ABAG will apply the methodology shown in Table 3 above to distribute the housing units among the individual counties and cities within the region. Affordability ABAG presented the HMC with four different scenarios for allocating housing units by income level (Attachment 2). However, the HMC did not recommend any of these scenarios because they felt that the allocation of housing units by income level based on the regional income distribution was the best solution (See Table 4 below). The regional income distribution is proposed to be based on household income data from Census 2000 or data from the U.S. Department of Housing and Urban Development that specifies household incomes by household size. Table 4. Recommended Re ional Income Allocation based on Affordabili Income Level Area Median Income* (AM Ve Low Income U to 50% AMI Low Income 50%-80% AMI Moderate Income 80%-120% AMI Above Moderate Income Above 120% AMI Total *In 2006, the Area Median Income for a family of four living in Alameda County is $86,300. Percenta e 23% 16% 19% 42% 100% By assigning each community an equal share of the region's affordable housing units, the methodology recognizes that the need for affordable housing is a problem that is shared by the region as a whole and it is consistent with the idea that every jurisdiction must contribute its "fair share" to providing affordable housing. The proposed methodology also promotes a more equitable income distribution by moving each jurisdiction to the same standardized income distribution and is more likely to avoid the over concentration of income groups within a particular jurisdiction. Page 40f7 ABA G Executive Board Meeting 5" C!b4la At the October 26, 2006 ABAG Executive Board Meeting, ABAG staff presented the HMC's recommendation for the RHNA methodology and the Regional Income Allocation methodology (See Tables 3 and 4 above). The Executive Board adopted a Resolution authorizing the release of the draft methodology for public review and comment. The public review and comment period is November 16, 2006 to January 18, 2007. On January 18th, ABAG staff will return to the Executive Board with a recommendation on the final methodology including responses to all comments received during the public review and comment period. ANALYSIS: 2007-2014 Regional Housing Need Allocation (RHNA) Based on the recommended methodology (See Table 3 above), and if the total RHNA were the same as last cycle, City Staff estimates that Dublin's total housing allocation would be reduced by approximately 39% from the previous 1999-2006 Housing Element cycle. Because the RHNA numbers for the 2007- 2014 period have not been released yet by the State of California, and in order to illustrate the proposed methodology, ABAG has applied the draft methodology to the total 1999-2006 RHNA resulting in a hypothetical allocation of3,326 housing units (See Table 5 below). Table 5. Comparison of RHNA for 1999-2006 and 2007-2014 RHNA Period 1999-2006 2007-2014 *Not the official RHNA number for 2007-2014. Housinl! Units 5,436 3,326* The primary reason for the anticipated reduction in RHNA is based on the new methodology which has been designed to direct growth to the more urbanized areas ofthe region (i.e. San Francisco, Oakland, and San Jose) and by including existing employment centers as a factor and not just employment growth. By taking into consideration existing employment centers, jurisdictions which currently have a greater imbalance between jobs and housing would be assigned a larger number of housing units in order to try and correct the imbalance. Since Dublin currently has a jobs/housing balance of approximately 1.39 jobs per housing unit and planned future development that will provide both jobs and housing, Dublin is not anticipated to have a tremendous imbalance. 2007-2014 Regional Income Allocation based on Affordability One of the goals of the RHNA process is to ensure that local governments consider the housing needs of persons at all income levels. In allocating affordable units to individual jurisdictions, the idea is that each locality must contribute their fair share in planning for some of the region's need for very low and low income units and at the same time avoiding or mitigating the over concentration of income groups in a jurisdiction. To meet these goals, the proposed methodology for the 2007-2014 period would assign each jurisdiction's need based on the regional average. In order to illustrate this, ABAG applied the proposed methodology (See Table 3 above) to the 1999-2006 RHNA numbers (See Table 6 below). Page 5 of7 Table 6. Com arison of RHNA b Income Cate or 1999-2006 RHNA La ~ t..\ l.D 2007-2014 RHNA Income Level Dwellin Units % of total Dwellin Units Ve Low Income 796 15% 765* Low Income 531 9% 532* Moderate Income 1,441 26% 632* Above Moderate Income 2,668 50% 1,397* Total 5,436 100% 3,326* *These numbers are based on the 1999-2006 RHNA and are not the official RHNA numbers for 2007-2014. % of total 23% 16% 19% 42% 100% Again, it should be noted that the number of total housing units and corresponding breakdown of units by income category are illustrative only. Until the State determines the overall housing need for the entire Bay Area region, Staffwill not know what Dublin's allocation will be. While Dublin's total allocation of housing units for the 2007-2014 RHNA cycle is anticipated to be 39% less than the previous RHNA, the percentage of very low and low income units is expected to be higher in order to meet the region's need for housing units in these income categories. Though the percentage of very low and low income units may be higher, the actual dwelling unit count in these categories is expected to be relatively the same as the previous RHNA. Conversely, the percentage of moderate and above moderate units is expected to be lower and the actual dwelling unit count significantly less than the previous RHNA in these income categories. NEXT STEPS: Regional Housing Needs Allocation Timeline (See Table 7) As mentioned previously in this report, the public review and comment period for the 2007-2014 RHNA methodology will end on January 18, 2007. Also, on January 18th ABAG staff will return to the ABAG Executive Board to present the final methodology and all comments received during the public review and comment period. It is expected that the State of California will release the draft RHNA numbers to ABAG in March 2007 and ABAG anticipates issuing the draft RHNA numbers to individual jurisdiction's by June 30, 2007. Following the release of the draft RHNA numbers there will be a revision period at which time local jurisdictions will have an opportunity to review and request changes to their allocations. At the close of the revision period, the fmal allocations will be assigned and an appeal period begins (approximately from November 2007 to April 2008). It is expected that the final RHNA numbers will be allocated by ABAG no later than June 30, 2008. The RHNA timeline is set forth in Table 7 below. Table 7. RHNA Timeline Date November 16, 2006 November 16,2006 - Janua January 18, 2007 March I, 2007 June 30, 2007 June 2007 - October 2007 November 2007 - A ri12008 June 30, 2008 June 30, 2009 ABAG Executive Board releases proposed methodology for ub1ic review and comment 60-da Public Review and Comment Period on methodolo ABAG Executive Board to ado t final methodology State of California determination of regional housing need ABAG issues draft RHNA numbers Revision Period A eals Period Final RHNA numbers issued b ABAG Housin Element U date due to State of California Page 60f7 CONCLUSION: ., ool..\~ The allocation of RHNA marks the beginning of the next Housing Element update and the methodology, which will be adopted by the ABAG Executive Board on January 18, 2007, will determine how the 2007- 2014 RHNA is distributed to local jurisdictions. ABAG is currently accepting comments on the methodology for the allocation of total housing units and affordable housing units. Staff recommends that the five proposed factors used for the methodology - household growth, existing employment, employment growth, household growth near transit and employment growth near transit - be accepted because the factors consider expected household and employment growth as well as existing employment to ensure an adequate jobslhousing balance for the region. Staff also recommends that the use of the regional income allocations to distribute affordable housing units to individual jurisdictions be accepted because the methodology recognizes that the need for affordable housing is a problem that is shared by the region as a whole and requires that all jurisdictions contribute to providing affordable housing in order to reduce the over concentration of affordable units within a particular jurisdiction. STAFF RECOMMENDATION: Staff recommends that the City Council: 1) Receive report and accept the 2007-2014 RHNA methodology for the allocation oftotal housing units and allocation of units by income level, OR 2) Direct Staff to forward comments to ABAG regarding the methodology. Page 70f7 ~~4-to u ASSOCIA nON OF BAY AREA GOVERNMENTS o Representing City and County Governments of the San Francisco Bay Area ASAG MEMO To: From: Date: Re: ABAG Executive Board ABAG Staff October 26, 2006 Draft Regional Housing Needs Allocation Methodology Recommendation Staff recommends that the ABAG Executive Board adopt Resolution 13-06 authorizing release of the Housing Methodology Committee's recommendation for a proposed Regional Housing Needs Allocation Methodology (RHNA) for the 2007-2014 period. Upon release, a not less than 60-day public comment period on the methodology will begin. The comment period will close on January 18,2007. On that date, staff will bring to the Executive Board recommendations for the final methodology. The fmal methodology shall include responses to all comments received on the draft RHNA methodology and reasons for any significant changes. Background As the region's Council of Governments, ABAG is responsible for allocating the state-defermined regional housing need to all jurisdictions in the Bay Area. The HMC was established in May 2006 to assist staff in developing a recommended methodology for allocating the regional need for adoption by the ABAG Executive Board. The HMC was comprised of local elected officials, city and county staff, and stakeholder representatives. Regional Housing Needs Allocation Process The Regional Housing Needs (RHN) process is a state mandate regarding planning for housing in Califomia. The state, regional and local governments each have a role to play. Local governments have autonomy in planning for exactly how and where housing will be developed in their individual communities. The amount of housing cities and counties must plan for, however, is determined through the interplay of state, regional and local housing policy. The State of California requires that all jurisdictions in the state update the Housing Elements of their General Plans. Housing Elements serve as the local plan for how a jurisdiction win meet its share of the region's housing need. The State of California, via the Housing and Community Development Department (HCD), determines each region's need for housing, primarily based on estimated population growth. COGs then allocate that need, for all income groups, amongst jurisdictions. jurisdictions then plan for that need in their housing elements, which are state-certified by HCD. RHNA Methodology Recommendation The regional housing needs allocation methodology is the tool used to assign each jurisdiction in the Bay Area its share of the region's total housing need. The actual tool is a mathematical equation that consists of weighted factors. There are also a set of "rules" that dictate how units will be allocated by income, within spheres of influence, voluntary transfer of units, and subregions. The HMC's recommendation encompasses these distinct components of the methodology. In their recommendation, the HMC members considered local land use plans and policies, regional growth policies and the state's housing polices, as expressed in the state mandated RHNA objectives. Additional information on how these recommendations were derived is contained in the attached report. /2-./Q-OI.,d <t.t' Attachment 1 ~ croYlo ~\ _ ..,.....". 1, v Draft RHNA Allocation Methodology 10/26/06 Page 2 1. Weighted Factors Factors in the allocation methodology are the mathematical variables that allocate shares of the regional housing need (RHN). The factors reflect: 1) state mandated RHNA objectives; 2) RHNA statutory requirements; 3) local policy and 4) regional policy. In the methodology, each factor is given priority relative to the others. Priority is established through "weighting" in the formula. For example, if one of the factors, household growth, is determined to be more important than another factor, e.g., transit, the methodology can give household growth a higher weight than transit in the formula. The methodology may also equally weight the factors, therefore ensuring that all the factors are of equal priority. A. Household Growth, 40 Percent Each local jurisdiction should plan for housing according to regionally projected household growth within its boundaries during the RHNA planning period (2007 - 2014). Household growth should be weighted 40 percent in the allocation. Household growth is used as a factor, as opposed to existing households or total households, to ensure that additional housing is not allocated where there are existing concentrations of homes in the region, but rather where growth is anticipated to occur. In this way household growth as a factor in the methodology ensures that the allocation is consistent with both local plans for growth and with regional growth policies, as those areas that are planning for household growth would receive a higher allocation than those areas not planning for growth. Household growth in ABAG's Projections is most influenced by local land use plans and policies, including planned and protected agricultural lands, open space and parks, city-centered growth policies, urban growth boundaries, and any physical or geological constraints. Regional policies have been incorporated into Projections since 2002, are assumed to go into effect by 2010, and therefore have some effect on regional housing growth estimates in the 2007-2014 RHNA period. Regional policies assume that there will be increased housing growth in existing urbanized areas, near transit stations and along major public transportation corridors. These regional policies are consistent with state housing policies to promote infill development, environmental and agricultural protection and efficient development patterns. B. Existing Employment, 20 Percent; Employment Growth, 20 Percent Each local jurisdiction should plan for housing to accommodate existing employment (2007) and regionally projected employment growth within its boundaries during the RHNA planning period (2007 - 2014). This would ensure that the need allocation gives jurisdictions with both existing concentrations of jobs and planned job growth a share of the regional housing need. This would direct housing to existing job centers and to areas with anticipated employment growth. These jobs allocation factors may address regional jobs-housing imbalance and facilitate access by proximity, for housing would be directed to communities with jobs and planned jobs, which may reduce vehicle miles traveled due to reduced inter- and intra-regional commuting. C. Household Growth near Transit, 10 Percent; Employment Growth near Transit, 10 Percent Each local jurisdiction with an existing or planned transit station should plan for more housing near such stations. Current regional policy places incrementally more growth along major transportation corridors and at transit stations. Therefore, a housing need allocation that uses regional housing growth and employment as factors would be inclusive of "transit" as a policy issue. Using transit as a \0 ~ '4tD, u Draft RHNA Allocation Methodology 10/26/06 Page 3 direct factor in the methodology would give transit a greater .degree of policy weight. Those jurisdictions with transit, existing and planned, would receive a relatively higher proportion of the housing needs allocation than those jurisdictions without existing or planned transit. The inclusion of "planned" transit in the methodology could potentially give a relatively higher allocation to an area where the planned transit does not materialize. However, if housing is built at appropriate densities before transit is put in place, the transit investment may become more financially feasible, for projected ridership would be higher. 2. Regional Income Allocations Each local jurisdiction should plan for income-based housing in the same ratio as the regional average income distnbution. A methodology that assigns each jurisdiction's regional housing need based on the regional average income distribution would be an "equal share" approach because it applies the same income distribution to each jurisdiction. Although considered an equitable approach, it does not consider existing concentrations of poverty. 3. Spheres of Influence Each local jurisdiction with the land-use permitting authority in a "Sphere of Influence" should plan for the housing needed to accommodate housing growth, existing employment and employment growth in such "Sphere of Influence" areas. A 100 percent allocation of the housing need to the jurisdiction that has land use control over the area would ensure that the jurisdiction that plans for accommodating the housing units also receives credit for any built units during the RHNA period. 4. Transfer of Units After the initial allocation of the regional housing need, a local jurisdiction may request approval to transfer units with willing partner(s), in a way that maintains total need allocation amongst all transfer parties, maintains income distribution of both retained and transferred units, and includes package of incentives to facilitate production of housing units. This transfer rule would allow the transfer of allocated housing need between willing jurisdictions in conjunction with fmancial resources, while maintaining the integrity of the state's RHNA objectives by preventing any jurisdiction from abdicating its responsibility to plan for housing across all income categories. Transfers done in this manner may facilitate increased housing production in the region. 5. Subregions The County of San Mateo, in partnership with all twenty cities in the county, has formed a subregion, as allowed by state statute. ABAG .will assign a share of the regional need to the subregion "in a proportion consistent with the distribution of households" in Projections 2007. The subregion is then responsible for completing its own RHNA process that is parallel to, but separate from, the regional RHNA process. The subregion will create its own methodology, issue draft allocations, handle the revision and appeal processes, and then issue fmal allocations to the members of the subregion. The rules on how to handle the subregion allocation in the event the subregion fails are contained in the attached RHNA technical document. \ \ D:b 4lD J- Planning Housing in the San Francisco Bay Area I'M _~__........ _.. "ft'.l<~ ...,," llU l.m ilf ~~ '" Draft Regional Housing Needs Allocation Methodology, 4th Revision Technical Documentation November 2007 o ABAG , '2- oa 4-lc ,..,1 u Introduction The Regional Housing Needs Allocation (RHNA) process is a state mandate on planning for housing in California. The state, regional and local governments each have a role to play. Local governments have autonomy in planning for exactly how and where housing will be developed in their individual communities. The amount of housing cities and counties must plan for, however, is determined through the interplay of state, regional and local housing policy. Periodically, the State of California requires that all jurisdictions in the state update the Housing Element of their General Plans. Within these Housing Elements, the state mandates that local governments plan for their share of the region's housing need, for people of all income categories. In the case of the San Francisco Bay Area, ABAG, as the region's Council of Governments, and the State Housing and Community Development Department (RCD), determines the region's need for housing. This determination of need is primarily based on estimated population growth. ABAG then allocate that need, for all income groups, amongst jurisdictions. The jurisdictions then plan for that need in their local housing elements, which are eventually state-certified by HCD. This technical document details the process for developing the draft Regional Housing Needs Allocation, describes the Housing Methodology Committee's allocation methodology recommendations and rationale for each component, and offers information on ABAG's Projections. I. RHNA Schedule II. RHNA State Goals & Regional Policy Ill. Statutory Factors & Survey of Factors IV. The Housing Methodology Committee V. Draft Allocation Methodology VI. Regional Projections San Francisco Bay Area \3OCY-1o '-Ie U- Draft Regional Housing Needs Allocation, 4th Revision I. RHNA Schedule On September 29, 2006, ABAG received approval of a two-year extension for completing the RHNA process from the Department of Housing and Community Development (HCD). The following milestones are consistent with that two-year extension: · November 16,2006: Adoption of draft allocation methodology by ABAG Executive Board; start of a 60-day public comment period · January 18, 2007: ABAG Executive Board adopts [mal methodology . March 1, 2007: Determination of regional housing need . June 30,2007: Release of draft allocations . June 30,2008: Release offmal allocations . June 30, 2009: Housing element revisions due to HCD II. RHN A State Goals & Regional Policy There are four statutory objectives of RHNA. As shown below, these objectives include increasing housing supply, affordability, and housing types; encouraging efficient development and infill; promoting jobs-housing balance; and reducing concentrations of poverty . These objectives are consistent with the Bay Area's regional policies regarding growth. Following the Smart Growth Strategy/Regional Livability Footprint Project that was completed in 2002, ABAG's Executive Board resolved to use theses regional policies as the basis for Projections. Since that decision, Projections assumes that, over time, local land use policies will move the region closer toward regional policies. The shift to policy-based Projections has important implications for growth and development in the region. Projections now forecasts more growth in existing urbanized areas and near transit, and less in agricultural areas. This is consistent with the RHNA objectives that call for an increase in the supply of housing, jobs-housing balance, more infill development, and protection of the environment, and efficient development patterns. Since the Projections forecast is the basis for the RHNA allocations, these same regional policies will influence how housing units are distributed within the region. RHNA Objectives (1) Increase the housing supply and the mix of housing types, tenure, and affordability in all cities and counties within the region in an equitable manner, which shall result in each jurisdiction receiving an allocation of units for low and very low income households. (2) Promote infill development and socioeconomic equity, the protection of environmental and agricultural resources, and the encouragement of efficient development patterns. (3) Promote an improved intraregional relationship November 2006, Page 2 Regional Policies · Support existing communities · Create compact, healthy communities with a diversity of housing, jobs, activities, and services to meet the daily needs of residents · Increase housing affordability, supply and choices · Increase transportation efficiency and choices · Protect and steward natural habitat, open space, and agricultural land · Improve social and economic equity \4eo4to I'D San Francisco Bay Area Draft Regional Housing Needs Allocation, 4th Revision between jobs and housing. (4) Allocate a lower proportion of housing need to an income category when a jurisdiction already has a disproportionately high share of households in that income category, as compared to the countywide distribution of households in that category from the most recent decennial United States census. · Promote economic and fiscal health · Conserve resources, promote sustainabiJity, and improve environmental quality · Protect public health and safety TII. Statutory Factors & Survey of Factors 1. Statutory Factors The RHNA statutes delineate specific factors that the HMC had to consider for inclusion in the allocation methodology, including: . Water and sewer capacity · Land suitable for urban development or conversion to residential use · Protected open space - lands protected by state and federal government · County policies to protect prime agricultura1land · Distribution of household growth · Market demand for housing · City-centered growth policies · Loss of affordable units contained in assisted housing · High housing cost burdens · Housing needs of farm workers · Impact of universities and colleges on housing needs in a community With the advice of the HMC, ABAG staff considered how to incorporate the statutory factors into the allocation methodology, how to allocate units by income, and how to address issues such as spheres of influence, the relationship to subregions, and voluntary transfers of housing units between jurisdictions. Their goal has been to develop an allocation methodology that is consistent with the RHNA objectives and statutory requirements while also reflecting local conditions and the regional goals for growth. See Section IV. 1. Weighted Factors for a detailed description of how the factors are included in the recommended methodology. 2. Survey of Factors On September 15, 2006, ABAG sent a memorandum and survey form to each planning director of every local jurisdiction in the region. The memorandum explained the use of factors in the RHNA allocation methodology, described the status of the HM:C's deliberations, set forth the criteria for using a factor in the methodology, and solicited local input on the statutory factors and suggestions for additional factors. ABAG received responses from 42 local jurisdictions (A detailed summary of survey responses is available at http://W\vw.abag.ca.l!.ov/planning/housingneeds or by contacting ABAG staff.) November 2006, Page 3 \5q,4Lc .. u San Francisco Bay Area Draft Regional Housing Needs Allocation, 4th Revision The Governor signed AB 2572 into law on September 29, 2006. The legislation adds a statutory factor: housing needs generated by the presence of a private university or a campus of the Califomia State University or the University of California. The HMC concluded that student populations need not be added as an explicit factor in the allocation methodology. The reason is that the existence of universities and resulting student populations are included in ABAG's household population estimates. Therefore, ABAG will circulate its explanation of the effects of this factor and a survey form for this factor during the review period of the draft methodology. Responses will be due in time for ABAG staff to evaluate them and to make any necessary changes to the methodology. The 42 survey responses varied widely. Many commented on the HMC deliberations, supporting or opposing specific measures under consideration, and offering alternative methodological approaches. Others commented on the existing and near-term market conditions for housing in their jurisdictions. The comments that focused on how specific factors should be explicitly considered in the methodology can be summarized as follows: s s ummarv urvev ResDonses 1. Jobs/Housing Relationship (a) use employed residents to. measure jobs/housing balance 3 (b) take into account home based businesses/employment 1 (c) use commute shed to assess jobslhousing balance 2 2. Constraints due to SewerlWater/Land Capacity (a) respondents identified specific sewer/water constraints 2 3. Public TransitITransportation Infrastructure (a) respondents confirmed they were planning for TOO 5 4. Market Demand for Housing 0 5. City-Centered Development (a) described local city-centered policies 6 (b) described specific policies, agreements, etc. on development in spheres of influence 7 (SOl) (c) stated there were no written agreements on SOls 1 6. Loss of Assisted Housing Units (a) identified at risk units at varying degrees of specificity 10 (b) do not use as a factor 1 7. High Housing Cost Burden (a) use CHAS data 1 8. Housing Needs of Fannworkers (a) identified local efforts for farmworker housing 4 9. Others (a) use congestion levels 1 (b) reward past performance in meeting RHNA goals 1 (c) RHNA allocation should at least equal planned growth 1 November 2006, Page 4 lLD 00 l.h~ u San Francisco Bay Area Draft Regional Housing Needs Allocation, 4U1 Revision Several of the possible allocation factors proposed in the surveys were considered by the HMC, but not explicitly incorporated in the draft methodology. These factors include those related to: . Jobs-housingbalance: l(a)-(c) Sewer/water constraints: 2 City-centered development: Sea) - (c) Loss of assisted housing units: 6 High housing cost burdens: 7 Housing needs of farm workers: 8 · Traffic congestion: 9(a) Rewards for past RHNA performance: 9(b) . . . . . . The HMC has included the following suggested REINA factors as explicit components of the draft methodology but may not have used them in precisely the way suggested by the respondents: . Public transit/transportation infrastructure: 3 The HMC did not consider 9( c). In each instance where a respondent described specific localized data in support of its response to a survey question, e.g. 2, 6(a) and 8(a), the respondent did not identify sources for comparable data for other jurisdictions. Therefore, staff could not conclude that the proffered factor met the statutory requirement for comparability and availability. Consequently, the proposed factor was not used. IV. Housing Methodology Committee As the region's Council of Governments, ABAG is responsible for allocating the state- determined regional housing need to all jurisdictions in the Bay Area. The lIMC was established in May 2006 to assist staff in developing a recommended methodology for allocating the regional need for adoption by the ABAG Executive Board. The HMC was comprised of local elected officials, city and county staff, and stakeholder representatives from each county in the region. It includes members from each county so that it adequately represents the entire region. The members of the Housing Methodology Committee were: Barbara Kondylis, Supervisor, District 1 (Solano), ABAG Executive Board Scott Haggerty, Supervisor, District I (Alameda), ABAG Executive Board Jerffery Levine, Housing Department, City of Oakland, Alameda Jennifer Hosterman, Mayor, City of Pleasant on, Alameda Dan Marks, Director of Planning & Development, City of Berkeley, Alameda Julie Pierce, Council Member, City of Clayton, Contra Costa Phillip Woods, Principal Planner, City of Concord, Contra Costa Gwen Regalia, Council Member, City of Walnut Creek, Contra Costa Linda Jackson, Principal Planner, City of San Rafael, Marin Paul Kennoyan, Community Development Dir., City of Sausalito, Marin November 2006, Page 5 \1 Ob4Lo,r- ~ -, 1 San Francisco Bay Area Draft Regional Housing Needs Allocation, 4th Revision Stacy Lauman, Assistant Planner, County of Marin, Marin Jean Hasser, Senior Planner, City of Napa, Napa Diane Dillon, Supervisor, County of Napa, Napa Howard Siegel, Community Partnership Mgr., County of Napa, Napa Amit Ghosh, Assistant Planning Director, San Francisco, San Francisco Doug Shoemaker, Mayor's Office of Housing, City of San Francisco, San Francisco Amy Tharp, Director of Planning, City of San Francisco, San Francisco Duane Bay, Housing Director, San Mateo County, San Mateo Andrea Ouse, City Planner, Town of Co 1m a, San Mateo Mark Duino, Planner, San Mateo County, San Mateo Laurel Prevetti Deputy Dir., Planning, Building and Code Enforcement, City of San Jose, Santa Clara Regina Brisco, Housing Planner, City of Gilroy, Santa Clara Steve Piasecki, Planning Director, City of Cupertino, Santa Clara Matt Walsh, Principal Planner, Solano County, Solano Chuck Dimmick, Councilmember (Vacaville) Solano City/County Coord. Council, Solano Eve Somjen, Assistant Director, City of Fairfield, Solano Mike Moore, Community Development Dir., City ofPetaluma, Sonoma Jake MacKenzie, Council Member, City of Rohnert Park, Sonoma Jennifer Barrett, Deputy Director - Planning, County of Sonoma, Sonoma Geeta Rao, Policy Director, Nonprofit Housing of Northern California, Stakeholder Kate O'Hara, Regional Issues Organizer, Greenbelt Alliance, Stakeholder Margaret Gordon, Community Liaison, West Oakland Indicators Project, Stakeholder Andrew Michael, Vice President, Bay Area Council, Stakeholder Paul B. Campos, VP, Govt. Affairs & Gen. Counsel, Home Builders Association, Stakeholder V. The Regional Needs Allocation Methodology The RENA methodology assigns each jurisdiction in the Bay Area its share of the region's total housing need. The methodology includes an allocation tool that is a mathematical equation that consists of weighted factors. There are also "rules" regarding allocation of units by income, how to handle units in spheres of influence, voluntary transfers of units, and subregions. The draft methodology encompasses these distinct components of the methodology. In their recommendation, the HMC members considered local land use plans and policies, regional growth policies and the state's housing polices, as expressed in the state mandated RHNA objectives. 1. Weighted Factors Factors in the allocation methodology are the mathematical variables that partly determine how the regional housing need (RHN) is allocated to local jurisdictions. The factors reflect: 1) state mandated RHNA objectives; 2) RHNA statutory requirements; 3) local policy and 4) regional policy. In the methodology, each factor is given priority relative to the others. Priority is established through "weighting" in the formula. For example, if one of the factors, e.g., household growth, is determined to be more important than another factor, e.g., transit, the methodology can give household growth a higher weight than transit in the formula. The methodology may also equally weight the factors, therefore ensuring that all the factors are of equal priority. November 2006, Page 6 \ ~ oc,4la -u San Francisco Bay Area Draft Regional Housing Needs Allocation, 4th Revision The factors and weights (expressed in parenthesis) recommend by the HMC are: . Household growth (40%) Existing employment (20%) Employment growth (20%) Household growth near existing and planned transit (10%) . Employment growth near existing and planned transit (10%) . . . . Household growth, existing employment, and employment growth are estimated in ABAG's regional household and employment forecasts, Projections. A. Household Growth, 40 percent Each local jurisdiction should plan for housing according to regionally projected household growth within its boundaries during the RHNA planning period (2007 - 2014). Household growth should be weighted 40 percent in the allocation. The use of housing as a RHNA factor represents consistency with local, regional, and state policies regarding where housing growth will and should occur in the region. Where and how much housing growth will occur in the region is estimated by ABAG's forecasting model, as documented in Projections. Specifically, household growth is based on: 1) local land use policies and plans; 2) demographic and economic trends, such as migration, birth and death rates, housing prices, and travel costs; and 3) regional growth policies. Household growth in ABAG's Projections is most influenced by local land use plans and policies, including planned and protected agricultural lands, open space and parks, city- centered growth policies, urban growth boundaries, and any physical or geological constraints. Regional policies incorporated into Projections since 2002, are assumed to go into effect by 2010, and therefore have some effect on regional housing growth estimates in the 2007-2014 RHNA period. Regional policies assume that there will be increased housing growth in existing urbanized areas, near transit stations and along major public transportation corridors. These regional policies are consistent with state housing policies to promote infill development, environmental and agricultural protection and efficient development patterns. The impacts of regional policy assumptions in Projections are: a) potential environmental and agricultural resource protection by directing growth away from existing open and agricultural lands; b) the encouragement of efficient development patterns through increased infill development and higher densities in existing communities; and c) the potential for increased transportation choices, e.g. walking and public transit, through more housing development near transit and jobs. The household estimates in Projections account for all people living in housing units, including students. Thus, the portion of the student population that occupies part of a local jurisdiction's housing stock is counted as such and as a source of future household formation. The portion of the student population that occupies "group quarters," such as college dormitories, are not included in household population counts. This is consistent with state policy regarding RHNA that excludes "group quarters" from being counted as housing units. November 2006, Page 7 \C1 OQl.\LD ") 1-'1 .A LJ San Francisco Bay Area Draft Regional Housing Needs Allocation, 4d\ Revision Household growth is used as a factor, as opposed to existing units or total units, to ensure that additional housing is not planned where there are existing concentrations of homes in the region, but rather where growth is anticipated to occur. In this way household growth as a factor in the methodology ensures that the allocation is consistent with both local plans for growth and with regional growth policies, as those areas that are planning for household growth would receive a higher allocation than those areas not planning for growth. B. Employment, 40 percent (Existing Employment, 20 percent; Growth, 20 percent) Each local jurisdiction should plan for housing to accommodate existing employment (2007) and regionally projected employment growth (2007-2014) within its boundaries during the RHNA planning period. This would ensure that the need allocation gives jurisdictions with both existing concentrations of jobs and planned job growth a share of the regional housing need. This would direct housing to existing job centers and to areas with anticipated employment growth. These jobs allocation factors may be effective in addressing regional jobs-housing imbalance. These factors would also facilitate access by proximity, for housing would be directed to communities with jobs and planned jobs, which may reduce vehicle miles traveled due to reduced inter- and intra-regional commuting. As a factor, employment has the ability to assign regional housing needs to jurisdictions in a way that provides a better balance between housing and employment. In the Bay Area, as in many metropolitan areas, employment centers have historically not produced enough housing to match job growth. Limited housing production near existing jobs and in areas with continued employment growth has escalated Bay Area housing costs and has triggered increased housing production in outlying Bay Area communities and in surrounding counties, including San Joaquin, Stanislaus, and San Benito. This has led to longer commutes on increasingly congested freeways, inefficient use of public transportation infrastructure and land capacity, and negative impacts on health, equity, air quality, the environment and overall quality ofIife in the Bay Area. In the allocation methodology, employment can be used in varying degrees of aggressiveness to address regional jobs-housing imbalance. The HMC considered three options: 1) employment growth, 2) existing jobs (2007) and 3) total jobs in the RHNA period (existing jobs in 2007 and growth from 2007 to 2014). Employment growth as a factor would assure that jurisdictions that are planning for employment growth also plan for commensurate housing. However, this would be ineffective in addressing historic regional jobs-housing imbalances, and therefore it is the least aggressive option. Existing jobs as an allocation factor would give relatively higher allocations to existing job centers and would therefore be the most aggressive toward historic jobs-housing imbalances; however it does not take into account future job growth. Total jobs as a factor would give relatively higher allocations to both jurisdictions that are currently job centers and those with planned job growth. Therefore, this is a moderately aggressive approach relative to the other two options. The HMC recommends a balance between the least and most aggressive options by separately weighting employment growth and existing employment. This would attempt to address historic jobs-housing imbalances and would seek to avert future imbalances. While an aggressive approach, it is relatively less aggressive than the use of total jobs as a factor. A total jobs factor would primarily direct growth to existing job centers, which would receive November 2006, Page 8 20lYoY-~ . , v- San Francisco Bay Area Draft Regional Housing Needs Allocation, 4th Revision the entire 40 percent weight for employment, as opposed to the 20 percent recommended weight. Existing Employment, 20 Percent The location and amount of existing jobs in the region is estimated by ABAG's forecasting model, as documented in Projections. Specifically, existing employment is based on: 1) existing regional and local job data, and 2) regional and local economic trends, attractiveness of commercial/industriallocations, including labor force costs, housing prices, travel costs, access to potential employees, markets, and similar businesses. The inclusion of existing employment as a RHNA factor ensures that regional housing need is allocated in a manner consistent with regional policies and state RHNA objectives. Planning for more housing in communities with existing jobs can address historic jobs- housing imbalances. More housing in existing job centers may also encourage infill and efficient development pattems through higher densities in existing communities. There is also the potential for reduced 'inter- and intra-regional vehicle miles traveled and shorter commutes, as more housing would be planned in proximity to existing jobs. More housing near jobs may also encourage alternative modes of travel, including walking and public transportation, as most existing jobs centers in the region are also transit rich. Planning for housing near existing jobs also places less development pressure on outlying areas, especially in rural areas with agricultural lands and protected open space. Employment Growth, 20 Percent The location and amount of employment growth in the region is projected by ABAG's forecasting model, as documented in Projections. Specifically, employment growth is based on: 1) local land use policies and plans; 2) economic trends, such as national and regional industrial assumptions, attractiveness of commercial/industrial locations, including labor force costs, housing prices, travel costs, access to potential employees, markets, and similar businesses; and 3) regional policy. Inclusion of local land use policies and plans and economic trends in ABAG's employment growth forecast ensures that the use of employment growth as a RHN A factor is consistent with local policies, plans, and local capacity for job growth. Employment growth in Projections considers all the land protection and growth policies, physical constraints, and the employment-related factors identified by the state and the HMC for inclusion in the allocation methodology, including existing jobs centers, home-based businesses, employed residents, housing prices, household income and employment at private universities, and campuses of the California State University and the University of California. The inclusion of employment growth as a RHNA factor ensures that the regional housing need is allocated to areas where job growth is forecasted to occur during the RHNA period. These areas would have the responsibility of providing housing for the additional jobs that are added to the region. These areas are typically served by the region's transit infrastructure. Matching housing to jobs would still have the potential for reducing vehicle miles traveled and. encouraging alternative modes of travel. This employment factor would place housing in exi~ting communities, but would place less of the housing in the most urbanized cities in the regIon. As with household growth, inclusion of regional policies in ABAG' s Projections ensures that the use of employment growth as a RHNA factor is consistent with both state and regional polices regarding growth, infill development, and efficient use of land. This is because November 2006, Page 9 21 DD4~.! u San Francisco Bay Area Draft Regional Housing Needs Allocation, 4th Revision regional policies in Projections assume that relatively more job growth will occur in existing urbanized communities and near transit, while less growth is projected in outlying communities with no transit infrastructure, including those with agricultural areas and open space. In addition, regional assumptions would promote greater use of public transportation through increased job development near transit. C. Household Growth near Transit, 10 Percent; Employment Growth near Transit, 10 Percent Each local jurisdiction with an existing or planned transit station should plan for more housing near such stations. As a factor, "household growth near transit" allocates 10 percent of the regional housing need to jurisdictions based on their forecasted household growth near existing or planned transit stations. As a factor, "employment growth near transit" allocates 10 percent of the regional housing need to jurisdictions based on their forecasted employment growth near existing or planned transit stations. Transit is defined as areas with fIXed-alignment public transit, both existing and planned. The transit services included are: Altamont Commuter Express (ACE), Bay Area Rapid Transit (BART), Caltrain, San Francisco MUNI light rail, and Santa Clara Valley Transportation Authority (VT A) light rail, and ferries. Planned transit stations include all fixed transit stations in the Metropolitan Transportation Commission's Regional Transportation Plan, Track One. Growth near transit is defined as household or employment growth within one-half mile of an existing or planned transit station, but eliminating any overlap between stations located within one mile of each other. Incorporating a transit factor directly into the methodology would, in effect, give extra weight to this state and regional objective. This is because a transit-based policy is already incorporated into ABAG's policy-based Projections. Current regional policy places incrementally more growth along major transportation corridors and at transit stations. Therefore, a housing need allocation that uses regional housing growth and employment as factors would indirectly include "transit" as a policy issue in the allocation methodology. Using transit as a direct factor in the methodology would give transit a greater degree of policy weight. Those jurisdictions with transit stations, existing and planned, would receive a relatively higher proportion of the housing needs allocation than those jurisdictions without existing or planned transit stations. Despite some objections, the HMC recommends that transit be used as a direct factor. This was due, in part, to the expectation that impacts of the policy assumptions in Projections will not begin to take effect until 2010. Directing growth to areas with public transit in the allocation methodology would ensure that this regional policy influences development patterns during the 2007-2014 RHNA period. Use of these factors would address the state RHNA objectives and regional goals of encouraging the use of public transit and the efficient use of transportation infrastructure. Directing housing need to areas near transit would also promote infill development, as existing transit stations are primarily in existing urbanized areas in the region. The effect of the addition of planned transit stations in the allocation methodology is that a relatively higher share of the regional allocation is given to jurisdictions that will receive November 2006, Page 10 2:2. oe4~-- u San Francisco Bay Area Draft Regional Housing Needs Allocation, 4th Revision investments for public transportation. Inclusion of planned stations gives communities that will have new transit stations an opportunity to ensure that they plan sufficient housing to support the extension of transit services. In addition, given the long time-frame for implementation of service extensions, it makes sense to begin the land use planning around proposed stations before the transit stations are put in place. This is in support of both state and regional policies to ensure efficient use of transportation infrastructure and to encourage increased transit use. There is a multitude of data supporting the theory that higher population densities have a net positive impact on transit ridership. The HMC was divided in its support for including a transit, and particularly planned transit, as part of tp.e allocation methodology. Many of the committee members believed that the regional growth policies embedded in Projections sufficiently addressed both state and regional policies promoting transit use and efficient use of transportation infrastructure. It was felt by some members that having transit as a direct factor would give too much weight to transit and would also unfairly burden communities with both existing and planned transit. Planned transit was also contentious because some of the planned transit stations included in MTC's Regional Transportation Plan may not be built, including many of the e-BART stations planned for eastern Contra Costa County. However, others on the HMC felt that if housing is built at appropriate densities before transit is put in place, the transit investment may become more financially feasible, for projected ridership would be higher. D. The Allocation Formula The household growth, employment and transit factors are weighted together to create an allocation formula. Each factor describes a jurisdiction's "share" of a regional total. For example, if the region expects to grow by 100 households, and one city in the region is to grow by 10 households in the same period, then that city's "share" of the region's growth is 10 percent. A jurisdiction's share of the Regional Housing need is assigned according to its percentage share of regional: (Household Growth x .40) + (Employment Growth x .20) + (Existing Employment x .20) + (Household Growth near Transit x .10) + (Employment Growth near Transit x .10) Growth is during the RHNA planning period (2007 - 2014). The transit factors refer to growth that occurs within Y2 mile of planned or existing fixed transit stations in the jurisdiction. Planned stations are those in the RTP 2005 - Track 1. 2. Regional Allocations of Housing Units based on Affordability There are two primary goals of the RHNA process: 1) increase the supply of housing and 2) ensure that local governments consider the housing needs of persons at all income levels. The HMC recommends that each local jurisdiction should plan for income-based housing in the same ratio as the regional average income distribution (as described by the 2000 Census). A methodology that allocates each jurisdiction's regional housing need based on the regional average income distribution would be an "equal share" approach because it applies the same income distribution to each jurisdiction. Although considered an equitable approach, it does not consider existing concentrations of poverty. November 2006, Page 11 23 004LP._ U'" San Francisco Bay Area Draft Regional Housing Needs Allocation, 4th Revision The following income allocation of regional housing needs to jurisdictions is recommended: . Very Low, 23 Percent Households with income up' to 50 percent of the county's area median income (AMI) Low, 16 Percent Households with income between 50 and 80 percent of the county's AMI Moderate, 19 Percent Households with income between 80 and 120 percent of the county's AMI Above-Moderate, 42 Percent Households with income above 120 percent of the county's AMI . . . This recommendation is based on the recognition that the need for affordable housing is a problem shared by the region as a whole, and is not localized to specific jurisdictions. By assigning every community an equal share of the regional need for affordable units, the methodology promotes the idea that every jurisdiction should do its "fair share" to provide housing. During the discussion of the income-based allocation, some HMC members expressed concern that a potential drawback of the proposed "equal share" strategy is that it might allocate affordable housing to jurisdictions that are less likely to build the units. If this were the case, the income allocation would therefore hinder the region's ability to provide enough housing affordable to meet the region's housing needs. However, there was general agreement that the benefits of this approach outweighed the potential negative impact. In addition, the HMC members felt that this issue could be worked out through the provisions in the methodology that allow for voluntary transfer agreements between individual jurisdictions. The liMC discussed the possibility of using the proportion of households with a high housing cost burden in a jurisdiction to adjust the income allocation for each jurisdiction. As a result, areas with higher numbers of households with a cost burden would receive a larger share of affordable units. This factor is based on the premise that directing more affordable housing units to these jurisdictions would provide more housing options to residents in those areas. However, the liMC was opposed to adjusting allocations based on high housing cost burdens because there was concern that, as noted above, including a factor based on existing conditions in a jurisdiction would ultimately lead to the over-concentration of low-income households in an area. In addition, committee members were committed to the idea that the need for affordable housing is a regional problem that each local government should have an equal share in addressing. 3. Spheres of Influence Every city in the Bay Area has a "sphere of influence (SOl)". A city's SOl can be either contiguous with or beyond the city's boundaries. It is the areas that the city is responsible for planning, as it is the probable future boundary of the city, including areas that may eventually be annexed by the city. The SOl is designated by the county Local Area Formation Commission (LAFCO). The LAFCO influences how government responsibilities are divided among jurisdictions and service districts within a county. If there is planned household or employment growth within the unincorporated portion of an SOl during the RHNA period, the allocation methodology must include a rule for allocating housing needs to the affected city or county. November 2006, Page 12 "2 '--l OOLfLo - , v San Francisco Bay Area Draft Regional Housing Needs Allocation, 4th Revision Therefore, the HMC recommends that each local jurisdiction with the land-use permitting authority in a SOl should plan for the housing needed to accommodate housing growth, existing employment and employment growth in such areas. A 100 percent allocation of the housing need to the jurisdiction that has land use control over the area would ensure that the jurisdiction that plans for accommodating the housing units also receives credit for any built units during the RHNA period. There are differences in whether a city or county has jurisdiction over land use and development within unincorporated SOls. In response to these variations, the HMC recommends the following SOl rules: 1. In Napa, Santa Clara, Solano, and Sonoma Counties, the allocation of housing need generated by the unincorporated SOl will be assigned to the cities. 2. In Alameda, Contra Costa, and Marin Counties, the allocation of housing need generated by the unincorporated SOl will be assigned to the county. ) The HMC recognizes that, although these guidelines reflect the general approaches to SOls in each county, adjustments may be needed to better reflect local conditions. Requests for SOl allocation adjustments may arise during the RHNA comment or revision period. Therefore, the HMC recommends that the methodology include the following criteria for handling such requests: 1. Adjustments to SOl allocations shall be consistent with any pre-existing written agreement between the city and county that allocates such units, or 2. In the absence of a written agreement, the requested adjustment would allocate the units to the jurisdiction that has permitting authority over future development in the SOL 4. Transfer of Units After the initial allocation, each local jurisdiction may request that it be allowed to transfer units with willing partner(s), in a way that maintains total need allocation amongst all transfer parties, maintains income distribution of both retained and transferred units, and includes a package of incentives to facilitate production of housing units. This transfer rule would allow the transfer of allocated housing need between willing jurisdictions in conjunction with financial and non-financial resources, while maintaining the integrity of the state's RHNA objectives by preventing any jurisdiction from abdicating its responsibility to plan for housing across all income categories. Transfers done in this manner may facilitate increased housing production in the region. The HMC recommends the following criteria for responding to requests for revisions that transfer units among local jurisdictions: 1. Transfer requests must have at least two willing partners and the total number of units within the group requesting the transfer cannot be reduced. 2. Transfers must include units at all income levels in the same proportion as initially allocated. I The County of San Mateo (formed a RHNA subregion) and the City and County of San Francisco (irrelevant) have been omitted. November 2006, Page 13 z6 00 4l.P .~ u San Francisco Bay Area Draft Regional Housing Needs Allocation, 4th Revision 3. All members of the transfer group must retain some allocation of very low and low income units. 4. The proposed transfer must include a specifically defined package of incentives and/or resources that will enable the jurisdiction(s) receiving an increased allocation to provide more housing choices than would otherwise occur absent the transfer and the accompanying incentives or resources. 5. If the transfer results in a greater concentration of very low or low income units in the receiving jurisdiction, the effect must be offset by findings by the members of the transfer group that address the RHNA objectives. For example, the findings might include (a) there is such an urgent need for more housing choices in those income categories that the opportunity to effect more housing choices in these categories offsets the impacts of over-concentration, or (b) the package of incentives and/or resources are for mixed income projects, or (c) the package of incentives and/or resources are for "transitional" housing for very low or low income households being relocat~d for rehabilitation of existing very low or low income units, or (d) the package of incentives and/or resources are for additional units that avoid displacement or "gentrification" of existing communities. 6. For the transfer of very low and low income units, there are restrictions that ensure the long-term affordability of the transferred units. 7. Transfers must comply with all other statutory constraints and be consistent with the RHNA objectives. In addition to guaranteeing that transfers meet the RHNA statutory objectives, these criteria 'promote regional policies to increase housing supply and provide more housing choices. The criteria state that the transfer must include the resources necessary to improve housing choices and, specifically, in a way that would not otherwise be possible without the transfer. The long-term affordability restrictions on very low and low income transferred units ensure that these units will contribute to a fundamental increase in affordable housing choices. The criteria also emphasize development of affordable units and are therefore consistent with the state RHNA objective that every jurisdiction does its "fair share" to provide affordable housing. The requirement that jurisdictions must retain some very low and low income units and the stipulation that transfers must maintain the same income distribution as is initially allocated ensure that a jurisdiction cannot abdicate its responsibility to provide affordable units. The criteria also ensure that the benefits created by the transfer outweigh any possible negative effects of an over-concentration oflower income households. 5. Subregions The County of San Mateo, in partnership with all twenty cities in the county, has formed a subregion, as allowed by state statute. The subregion has designated the City/County Association of Governments (C/CAG) as the entity responsible for coordinating and implementing the subregional RHNA process. As required by statute, ABAG will assign a share of the regional need to the San Mateo subregion "in a proportion consistent with the distribution of households" in Projections 2007. The subregion is responsible for completing its own RHNA process that is parallel to, but separate from, the regional RHNA process. The subregion will create its own methodology, issue draft allocations, handle the revision and appeal processes, and then issue final allocations to members of the subregion. November 2006, Page 14 'Zlo ~ '-\Lo IIJ/ San Francisco Bay Area Draft Regional Housing Needs Allocation, 4th Revision Although the subregion is working independently of the regional RHNA process, ABAG is ultimately responsible for ensuring that all of the region's housing need is allocated. Thus, if the subregion fails at any point in its attempt to develop a final RHNA allocation for the subregion, ABAG must complete the allocation process for the members of the subr~gion. In the event that the San Mateo subregion fails to complete the RHNA process, the HMC recommends the methodology include the following guidelines for handling the allocation of units to jurisdictions within the subregion: 1. If the members of the subregion adopts a "default allocation," ABAG will allocate using the default allocation. A "default allocation" is the allocation which a member of the San Mateo RHNA subregion receives if it "opts out" of the subregion. 2. If the subregion fails before ABAG has made any allocation, ABAG combines the subregional share with the rest of the regional need and allocates the total regional need to the entire region using ABAG's RHNA methodology. 3. If the subregion fails after ABAG has made its initial allocation, ABAG separately allocates the subregional share among only the members of the subregion. ABAG uses its RHNA methodology to do so. This approach is recommended by the HMC because it minImiZeS the extent of any reallocations that could occur as a result of subregional failure and preserves the integrity of the respective efforts of ABAG and C/CAG. Keeping San Mateo separated once ABAG has completed its initial allocation also provides the most certainty to all jurisdictions about what their allocation will be. VI. Regional Projections Every two years, ABAG produces a long-run regional forecast called Projections. The Projections forecast provides specific information for population, households, employment and other related variables. In Projections 2007, values are reported for year 2000, and then for each five year increment to 2035. Several related models are used to perform the forecast. The economic model balances demand for the production of goods and services with the supply of productive capacity. The demographic model uses birth rates, death rates and migration data to forecast future population using a cohort-survival model. A great deal of data is required by the models, including information on economic relationships and trends, population-related information like births, deaths and migration, as well as land use and land use policy data. Since Projections 2003, ABAG has assumed the "Network of Neighborhoods" land use pattern, as developed through the Smart Growth Strategy/Regional Livability Footprint Project. This pattern expects higher levels of housing production. It also assumes that an increasing proportion of regional growth occurs near transit and in existing urban areas. In the Projections 2007 forecast, additional housing production and a shift in the pattern of development primarily occurs in the later part of the forecast. Earlier in the forecast, population growth is generally consistent with the California Department of Finance (DOF) forecast. The distribution of growth is generally consistent with local general plans. November 2006, Page 15 2., DO 4{p ....., - v San Francisco Bay Area Draft Regional Housing Needs Allocation, 4'h Revision ABAG has continually collected information on local land use as part of its modeling efforts. The forecast is produced for nearly 1400 census tracts in the region and shows the existing land use and the capacity of each tract to support additional population or economic activities. Because the forecast is based on local land use information, forecasted growth occurs in locations that are consistent with local plans. However, even with 1400 census tracts, only so much detailed information can be included. We may know that moderate growth can occur in an area without specifically understanding that a portion of that area is a nature preserve. We may know that growth should not occur in an area, but it may not be clear whether it is due to a physical limitation, or a general plan policy. November 2006, Page 16 2:B ~L.\lD Draft Regional Housing Needs Allocation: Example Calculation u Committee PrevIous Proposal RHNA 11/6/06 12:21 PM Regional Need 2Jq,~'!4:: , 230 743 , ALAMEDA 2,182 2,162 ALBANY 260 277 BERKELEY 2,983 1,269 DUBLIN 3,326 5,436 EMERYVILLE 1,786 777 FREMONT 5,693 6,708 HAYWARD 3,537 2,835 LIVERMORE 3,564 5,107 NEWARK 928 1,250 OAKLAND 19,698 7,733 PIEDMONT 37 49 PLEASANTON 3,402 5,059 SAN LEANDRO 2,423 870 UNION CITY 2,135 1,951 UNINCORPORATED 1,938 5,310 ALAMEDA COUNTY 43,335 46,793 ANTIOCH 2,334 4,459 BRENTWOOD 2,895 4,073 CLAYTON 162 446 CONCORD 3,474 2,319 DANVILLE 550 1,110 EL CERRITO 626 185 HERCULES 427 792 LAFAYETTE 378 194 MARTINEZ 1,066 1,341 MORAGA 221 214 OAKLEY 749 1,208 ORINDA 233 221 PINOLE 304 288 PITTSBURG 2,237 2,513 PLEASANT HILL 588 714 RICHMOND 2,828 2,603 SAN PABLO 280 494 SAN RAMON 3,263 4,447 WALNUT CREEK 2,660 1,653 UNINCORPORATED 3,209 5,436 CONTRA COSTA CNTY 28,295 34,710 BELVEDERE 24 10 CORTE MADERA 227 179 FAIRFAX 65 64 LARKSPUR 701 303 MILL VALLEY 261 225 NOVATO 1,459 2,582 ROSS 25 21 SAN ANSELMO 137 149 SAN RAFAEL 1,571 2,090 SAUSALlTO 181 207 TIBURON 124 164 UNINCORPORATED 1,001 521 MARIN COUNTY 5,869 6,515 e~ rt-- 2C1 OCJ ~--, . "? t Draft Regional Housing Needs Allocation: Example Calculation l/ Committee Previous Proposal RHNA 11/6/06 12:21' PM Regional Need 230,74:3 I 230,743 I AMERICAN CANYON 685 1,323 CALlSTOGA 89 173 NAPA 1,901 3,369 ST HELENA 115 142 YOUNTVILLE 83 87 UNINCORPORATED 621 1,969 NAPA COUNTY 3,494 7,063 SAN FRANCISCO 43,434 20,372 SAN MATEO COUNTY 18,177 16,305 CAMPBELL 735 777 CUPERTINO 1,104 2,720 GILROY 1,634 3,746 LOS ALTOS 300 261 LOS ALTOS HILLS 77 83 LOS GATOS 530 402 MILPITAS 2,804 4,348 MONTE SERENO 39 76 MORGAN HILL 1,366 2,484 MOUNTAIN VIEW 2,967 3,423 PALO ALTO 3,836 1,397 SAN JOSE 33,748 26,114 SANTA CLARA 6,484 6,339 SARATOGA 275 539 SUNNYVALE 4,696 3,836 UNINCORPORATED 179 1,446 SANTA CLARA COUNTY 60,775 57,991 BENICIA 581 413 DIXON 686 1,464 FAIRFIELD 3,660 3,812 RIO VISTA 1,149 1,391 SUISUN CITY 657 1,004 VACAVILLE 2,734 4,636 VALLEJO 3,236 3,242 UNINCORPORATED 94 2,719 SOLANO COUNTY 12,796 18,681 CLOVERDALE 528 423 COTATI 438 567 HEALDSBURG 433 573 PETALUMA 2,085 1,144 ROHNERT PARK 1,835 2,124 SANTA ROSA 6,715 7,654 SEBASTOPOL 167 274 SONOMA 334 684 WINDSOR 721 2,071 UNINCORPORATED 1,314 6,799 SONOMA COUNTY 14,569 22,313 REGION 230,743 230,743 P tl~lll q: u 3D Db 4-Lo ~-. ,..., _..1\ __ I v ASSOCIATION OF BAY AREA GOVERNMENTS EXECUTIVE BOARD RESOLUTION NO. 13-06 RESOLUTION AUTHORIZING RELEASE OF A PROPOSED RHNA METHODOLOGY FOR PUBLIC REVIEW AND COMMENT WHEREAS, the Association of Bay Area Governments (ABAG) is a joint powers agency formed pursuant to the agreement of its members and California Government Code 99 6500, et seq., and is the council of governments (COG) for the San Francisco Bay Area; and WHEREAS, pursuant to the Housing Element Law ("Act") at California Government Code 99 65580, et seq., each COG and the California Department of Housing and Community Development (HCD) are required to determine the existing and projected housing needs in the COG's region; and WHEREAS, under the Act, ABAG determines each city's and county's share of the regional housing needs through the regional housing need allocation process (RHN.A); and WHEREAS, the Executive Board authorized formation of the Housing Methodology Committee (HMC) and charged it, in part, with the responsibility of advising staff on the methodology for allocating the regional housing need among local jurisdictions (RHNA Methodology) ; and WHEREAS, the HMC advised staff to prepare the Draft RHNA Methodology described in the staff memorandum dated October 26, 2006 for consideration by the Executive Board; and WHEREAS, the Act requires that ABAG release the Draft RHNA Methodology for at least a sixty (60) day public review and comment period and conduct a public hearing to receive written and oral comments; and WHEREAS, staff recommends release of the Draft RHNA Methodology for public review and comment. NOW, THEREFORE, BE IT RESOLVED: the Executive Board of the Association of Bay Area Governments hereby: 1. Authorizes staff to release the Draft RHNA Methodology for public review and comment and to provide notification of such release to the general public and to all cities, counties and any city and county in the region; and -1- 3lOO4LP fJ ,- ASSOCIATION OF BAY AREA GOVERNMENTS RESOLUTION NO. 13-06 2. Authorizes staff to conduct a public hearing on the Draft RHNA Methodology at the January 18,2007 Executive Board meeting; and 3. Directs staff to coordinate receipt and review of all comments for presentation to the Executive Board at its January 18, 2007 meeting. The foregoing adopted by the Executive Board this 16th day of November, 2006. David Cortese President Certification of Executive Board Approval I, the undersigned, the appointed and qualified Secretary-Treasurer of the Association of Bay Area Governments (Association), do hereby certify that the foregoing resolution was adopted by the Executive Board of the Association at a duly called meeting held on the 16th day of November, 2006. Henry L. Gardner Secretary-Treasurer Approval as To Legal Form Kenneth K. Moy Legal Counsel -2- 32 oc>'-\lP ASSOCIATION OF BAY AREA GOVERNMENTS o " Representing City and County Governments of the San Francisco Bay Area A~AG MEMO To: From: Date: Subject: Housing Methodology Committee (HMC) ABAG Staff October 11, 2006 Scenarios for Allocating Units by Income Background There are two primary goals at the heart of the Regional Housing Need Allocation (RHNA}Proce1Ss..Tbe first is to increase the supply of housing in California by allocating a share of the sta~-wide Musif\g need to each city and county. The second is to ensure that local governments consider the bou$iUg rtee4Sof persons at all income levels as they prepare their Housing Elements. To achieve these two goals, the allocation of the regional housing need to local governments occurs in two stages. The first is to allocate housing units to each city and county in the region. Tbe second is to split each jurisdiction's total allocation into the four income categories established by the State. Tbe four income categories defined by the State are: . Very Low: households with income up to 50 percent of the county's area median income (AMI) Low: households with income between 50 and 80 percent of the county's AMI Moderate: households with income between 80 and 120 percent of the county's. AMI Above-Moderate: households with income above 120 percent of the county's AMI . '- . . The goals and requirements of the allocation of units by income are specifically addressed in the RHNA objectives. The first is that all cities and counties are responsible for doing their "fair share'; and planning for at least some of the region's need for very-Iow- and low-income units. I The second is that the allocation methodology must avoid or mitigate the over-concentration of income groups inajurisdiction.2 The RHNA allocation methodology must assign the regional need to each jurisdiction Ina way that fully allocates the units in each income category and complies with the two objectives listed above, The HMC requested that ABAG staff generate several possible scenarios for allocating units by income. This memo shows the effects of different strategies for allocating units in each income category.:; Allocation Scenarios When allocatinl! units bv income. oarticularlv affordable units. there is an underlvins:rtension ~tween trying to ensure~that all ~ommuni'ties do thei; ;'fair share" and ~esponding to existing-needs for housing. For example, allocating more low-income units to a jurisdiction that has a higher proportion of low- income residents would help to meet the community's existing needs. However, this strategy would I Government Code Section 65584(d)(l). Government Code Section 65584(d)(4). The allocation of units by income occurs after jurisdictions receive their share of the regional housing need. Since the methodology for this base allocation has not yet been determined, the scenarios show the percent of units in each income category that a jurisdiction would rec~ive, rather than a number of housing units. Mailing Address: P.O. Box 2050 Oakland, California 94604-2050 (510) 464-7900 Fax: [510J 464-7970 info@abag.ca.gov Joseph P. Bort MetroCenter 101 Eighth Street Oakland, California 94607-4756 Attachment 2 3~ D.b y.\.D Scenarios for Allocating Units by Income 10/11/06 Page 2 u promote the further concentration of low-income households in that community and would not move the region toward a more equitable distribution of income. The examples developed by ABAG staff are based on the following possible scenarios (Attached): . Scenario I: Moving every jurisdiction 50 percent toward the county average income distribution Scenario 2: Moving every jurisdiction 50 percent toward the regional average income distribution Scenario 3: Allocating units to each jurisdiction based on the county's average income distribution Scenario 4: Including a factor to address high housing cost burdens . . . Moving Toward a County or Regionallncome Distribution Scenarios 1 and 2 both attempt to balance the existing need for housing with the goal of creating a more equitable income distribution. Both start with a jurisdiction's existing income distribution. In Scenario I, this existing distribution is moved 50 percent toward the county average income distribution. In Scenario 2, the existing distribution is moved 50 percent toward the regional average. Comparing a jurisdiction to the county takes local differences in income into account. In contrast, using the regional income distribution attempts to overcome county-level differences in income to create a more equitable distribution region-wide. These scenarios start with ajurisdiction's existing income distribution and then move part ofthe way to either the county or regional household income average. As a result, these methodologies try to assign units to where they are currently needed while also creating a more fair income distribution. However, the fact that the method starts with the existing conditions means that jurisdictions with more households in affordable categories (relative to the regional average) must still plan for disproportionately more affordable housing, and those with less than the regional average must plan for less. It can be argued that this approach balances meeting the existing need in a specific jurisdiction with the goal of having all jurisdictions do their "fair share" to meet the region's housing needs. At the same time, these approaches can be described as perpetuating the over-concentration of the region's lower income populations in certain communities. Using the County lncome Distribution In contrast to the first two scenarios, Scenario 3 does not take a jurisdiction's existing income distribution into account. In this case, each jurisdiction is assigned the same distribution as the county-wide distribution. In effect, this "equal share" approach applies the county-wide income distribution to each jurisdiction within the county. A primary benefit of this approach is that it is consistent with the idea that every jurisdiction should do its "fair share" to provide affordable housing. It also promotes a more equitable income distribution by moving every jurisdiction in a county to the same standardized income distribution. This method also avoids over-concentrating an income group in a jurisdiftion. However, one potential drawback of this strategy is that by excluding existing conditions, it doe~ not do enough to address the existing needs for affordable housing. 34 Db4LQ ~. ~ Scenarios for Allocating Units by Income 10/11/06 Page 3 v High Housing Cost Burdens As part of its discussions, the HMC felt that high housing cost burdens would be mostappropriately considered as part of the discussion of housing affordability categories. We typically look at hol.ls~hQld income to assess affordability. ., Summary This memo outlines several possible methods for accomplishing the allocation of units ~yinc9m~ fot RHNA. It also describes some of the advantages and drawbacks of the different strategies. In selecting an allocation methodology, the HMC must consider the extent to which it distribl!ltes housing units in a way that: · Provides for the housing needs of persons at all income levels . · Ensures that every jurisdiction does its "fair share" to provide affordable housing · Encourages an equitable distribution of incomes throughout the region · A voids over-concentrating an income group in a jurisdiction. Existing Income Allocation 50% Toward Region Average bounty Aver~ge Housing Very Very Very Cost Low Low Mod Above Low Low Mod Above LQW Low Mod Above Burden <50% <80% <120% Mod <50% <80% <120% Mod <500;0 <80% <120% MOd >30% ALAMEDA 22% 17% 20% 42% 23% 17% 19% 42% 24% 16% 18%. 42% 31% ALBANY 22% 18% 20% 40% 23% 17% 19% 41% 24% 16%. 18% 42% 33% BERKELEY 35% 15% 15% 35% 26% 16% 18% 40% 24% 16% 18% 42% 38% DUBLIN 9% 12% 19% 60% 20% 15% 19% 46% 24% 160/.; 18% 42% 32% EMERYVILLE 31% 18% 19% 31% 25% 17% 19% 39% 24% 16% 18% 42% 42% FREMONT 12% 11% 18% 58% 20% 15% 19% 46% 24% 16% 18% 42% 31% HAYWARD 23% 19% 23% 35% 23% 17% 20% 40% 24% 16% 18% 42% 35% LIVERMORE 12% 12% 18% 57% 20% 15% 19% 46% 24%. 16% 18% 42% 31% NEWAFIK 13% 14% 21% 52% "4 21% 16% 19% 44% 24"!" 10% 18% 42% 31% OAKLAND 36% 19% 16% 29% a$%' 26% 17% 18% 38% 24% 16% 18% 42% 37% PIEDMONT 9% 5% 9% 78% ..6()~' 19% 13% 16% 51% 24% 16% 18% 42% 28% .... ". < : 0') PLEAStiNTON 9% 9% 16% 66% 54%, 20% 14% 18% 48% 24% 16% 18% 42% 29% SAN LEANDRO 23% 20% 22% 35% 18%' 38% 23% 17% 20% 40% 24% 16% 18% 42% 30% UNION CITY 15% 12% 19% 55% 1"\0/0", 4S"!il 21% 15% 19% 45% 24% 16% 18% 42% 32% UNINCORPORA TED 20% 17% 20% 42% 11% 42% 22% 17% 19% 42% 24% 16% 18% 42% 32% Alameda County 24% 16% 18% 42%. 4~% 23% 16% 19% 42% 24% 16% 18% 42% 34% ',. ;:.... :g~~~ 18$,;; 22% .,:J~$%~ ANTIOCH 23% 19% 23% 36% 22% 17% 20% 40% 22% 17% 20% 41% 34% BRENTWOOD 18% 17% 21% 44% :mo/c;, Zr~:i:.;,',(~~: 21% 17% 20% 42% 22% 17% 20% 41% 30% CLAYTON 10% 8% 16% 67% 116%: 19% 15% 19% 48% 22% 17% 20% 41% 25% "';> CONCORD 25% 20% 23% 32% ....... 36%, 23% 17% 20% 39% 22% 17% 20% 41% 33% DANVILLE 8% 9% 12% 72% ,.. 56% 19% 15% 18% 49% 22% 17% 20% 41% 32% EL CERRITO 24% 20% 20% 35% 230/.;' 2~';; "'a~?~ 23% 18% 20% 40% 22% 17% 20% 41% 26% HERCULES 11% 17% 24% 49% 1(Wo 22~'. 45~" 19% 17% 21% 43% 22% 17% 20% 41% 32% LAFAYETTE 11% 10% 16% 63% t7~i$ ',1~~o 526k, 20% 15% 19% 47% 22% 17% 20% 41% 26% MARTII'IEZ 20% 17% 23% 40% 21% 21o/~:.. 40o/c)" 22% 17% 20% 41% 22% 17% 20% 41% 29% MORAGA 11% 11% 16% 62% ,1:7"4 l"'~~%' 20% 15% 19% 46% 22% 17% 20% 41% 26% OAKLEY 15% 18% 30% 37% 1:9% 21% 17% 22% 40% 22% 17% 20% 41% 36% ORINDA 10% 9% 12% 69% . l' 19% 15% 18% 48% 22% 17% 20% 41% 26% PlNOLE 19% 18% 25% 38% .~ 21% 17% 21% 40% 22()/ci 17% 20% 41% 27% PITTSBURG 29% 22% 23% 27% 24% 18% 20% 38% 22% 17% 20% 41% 34% ().) PLEASI\NT HILL 19% 16% 23% 42% 22% 17% 20% 42% 22% 17% 20% 41% 31 % \.7{ RICHMOND 35% 22% 20% 23% 25% 18% 20% 37% 22% 17% 20% 41% 36% SAN PABLO 43% 21% 18% 17% 28% 18% 19% 35% 22% 17% 20% 41% 40o/~ SAN RAMON 8% 11% 17% 65% 19% 15% 19% 47% 22% 17% 20% 41% 29% WALNUT CREEK 22% 18% 20% 41% 22% 17% 20% 41% 22% 17% 20% 41% 29% -t: UNINCORPORATED 22% 16% 19% 43% 22% 16% 19% 42% 22% 17% 20% 41% 32% S Contru Costa County 22% 17% 20% 41% 22% 17% 20% 41% 22% 11% 20% 41% 32% C Existing Income Allocation Very Low Low Mod <50% <80% <120% BELVEDERE 15% 8% 12% CORTE MADERA 16% 17% 20% FAIRFAX 24% 23% 22% LARKSPUR 22% 19% 19% MILL VALLEY 19% 14% 14% NOVATO 23% 20% 21% ROSS 14% 9% 18% SAN ANSELMO 23% 16% 20% SAN RAFAEL 28% 19% 18% SA USA LITO 17% 14% 18% TIBURON 12% 14% 15% UNINCORPORATED 21% 15% 16% Marin County 22% 17% 18% AMERICAN CANYON 22% 17% 19% CALlSTOGA 29% 23% 19% NAPA 22% 19% 20% ST HELENA 20% 15% 17% YOUNTVILLE 28% 15% 21% UNINCORPORATED 16% 15% 18% Napa County 21% 18% 19% San Francisco 25% 15% 16% ATHERTON 4% 6% 9% BELMONT 17% 17% 18% BRISBANE 23% 21% 17% BURLINGAME 22% 19% 19% COlMA 27% 20% 28% DALY CITY 25% 19% 24% EAST PALO ALTO 40% 21% 19% FOSTER CITY 11% 14% 18% HALF MOON SAY 21% 13% 20% HILLSBOROUGH 8% 6% 9% MENLO PARK 20% 14% 17% MILLBRAE 24% 17% 20% PACIFICA 17% 18% 25% ~. ;'" . . ','.: ',. ....:t.... I;. -:,',:" '<;:; 64% :":r.~~i 53 Yo. 21 ~, . ,t$Xo. . . 1-$% .',: 48~, 3 01 .. ":;'3'01 .' .'1'9" ill.' :..; '2"';';;';": '3"g'bi. 5/0 ..'.... '" lO..... : :/0:' ..... ,voYo":"''-: /9' ~~~:i';~';'l~'e'!::~Jf~t~, 35Yo,. '..25%;' .:.18%..: ,18.~' :,,39~. ~~ }iil;;Jllt,!!ltfl 42%..:::,~%'.' ;.'r%,.:,:,., ~'~%':/':~~lW . E~:':'irII:~I~1 42 Yoc ; 2H/o '.::1 a ?{;;, ..::/1~Al;.,-;t':"A.2% :,: ~)~;:: ~~;~~~::':",<.,; :~~;~ \\~~'::";1.;:~'::.'. ~ ~ t. f:~'::;;:.~'2~~:: ~'l:\ l~;~./'~ ~'~".~"':; 44% : ,<2Sil;{, ':.15% ~.;~; 1'6o/ii.....:~"~% :~ f~;~:ji;~~;~i;~;}~{;~~~i~ 40%'" 25% 32% 20% 57% ,\",.c'''''.f.i>~ E~ilgf~~(i~R~l~;*~::fg~~,~ 50% Toward Region Average ", County Average .', Housing Very . Very Cost Low Low Mod Above LOw ,Low, Mod Above Burden <50% <80% <120% Mod <50% ~80%.. <:i 20% Mod >30% 21% 15% 17% 47% 22% 17%, '18%, ,42% 35% 21% 17% 19% 43% 22%. ,.17% 18%' 42% 31% 23% 18% 20% 39% 22% 17% 18%. 42% 41% 22% 17% 19% 42% 22% 11% 18% 42% 34% 22% 16% 18% 45% 22%. .17% ' 18% 420/0 33% 23% 18% 19% 40% 22% 11% ' 18% 42% 38% 21% 15% 19% 46% ,220/0,' 17o/~ 18% 42% 43% 23% 16% 19% 42% 22%. 170/0 18% 42% 37% 24% 17% 19% 40% 22% 17% 18% 42% 37% 21% 16% 19% 44% 22%. .17% 18% 42% 35% 20% 16% 18% 46% ,22%, " 17~/o " 18% 42% 31% 22% 16% 18% 43% 22%,. 17% , , 18% 42% 33% 23% 17% 19% 42% 22% 17% 18% 42% 35% . -' .' . 22% 17% 19% 42% .21% '. :18% :19%', ,'42% 31% 24% 19% 19% 38% '2~%,'> 18% 19% 42% 30% 22% 17% 19% 41% 210/0 180/0' 19% ,42% 32% 22% 16% 19% 43% 21%. ' 180ici 19% ,'42% 32% 24% 16% 20% 40% ' 21o/~ '18% '.19% 42% 35% 21% 16% 19% 44% 21ro "18% 19% 42% 26% 22% 17% 19% 42% 21%. ' 18o/c " , ,19%' 42% 31% " : ..,'0, .. " ..'2~% -- 15o/~ 33% 24% 16% 18% 43% 1e% 44% OJ n J1 t '~ .' . \: Existing Income Allocation 50% Toward Region Average C6urityAv~rl:1g~ Housing Very Very VfjJr'j Cost Low Low Mod Above Low Low Mod Above Low Low Mod Above Burden <50% <80% <120% Mod <50% <80% <120% Mod <50% . .:zBOOZ(J, . <1200/0 Mod >30% PORTOlA VALLEY 10% 6% 9% 75% REDWOOD CITY 24% 18% 20% 38% SAN BRUNO 24% 20% 24% 32% SAN CARLOS 17% 15% 17% 52% SAN MA TEO 24% 19% 20% 37% SOUTH SAN FRANCISCO 25% 20% 24% 31% . WOODSIDE 9% 9% 11% 71% UNINCORPORATED 18% 13% 19% 51% San Mateo County 21% 17% 20% 41% ",;~1% 21% 1'7% 20% 41% 33% ,'";' CAMPBELL 23% 20% 21% 35% 21% ,"~~" 23% 18% 20% 40% 22% 17% 20% 41% 33% CUPERTINO 14% 12% 17% 56% 1;ij,p 19%' 20% 16% 19% 45% 22% 17% 20% 41% 28% GILROY 27% 20% 23% 30%, 19% 2f'~~ 3po/c;' 23% 18% 20% 39% 22% 17% 20% 41% 34% LOS ALTOS 12% 10% 12% 66% t4~, ",,1~0& Q3~!~' 20% 15% 18% 48% 22% 17% 20% 41% 26% LOS ALTOS HILLS 9% 6% 9% 76% 12% '" 14~?" 5~~, 19% 14% 17% 50% 22% 17% 20% 41% 33% 17% 15% 16% 53% 16% " , , 47%, LOS GATOS 21% 16% 19% 44% 22% 17% 20% 41% 32% MILPITAS 16% 16% 21% 47% '1~~~, 44% 21% 16% 20% 43% 22% 17% 20% 41% 29% MONTE SERENO 11% 8% 10% 70%,'" 1304';,: 20% 15% 17% 49% 22% 11% :2.0% 41% 34% MORGAN HILL 21% 13% 20% 46% 22% 16% 20% 43% 22% 17% 20% 41% 32% MOUNTAIN VIEW 24% 18% 20% 38% 23% 17% 20% 41% 22% 17% 20% 41% 31% PALO ALTO 21% 13% 15% 51% 22% 16% 18% 44% 22% 11% 20% 41% 28% SAN JOSE 23% 18% 21% 38% 23% 17% 20% 40% 22% 17% 20% 41% 33% SANTA CLARA 24% 18% 22% 36% 23% 17% 20% 40% 22% 17% 20% 41% 29% SARATOGA 12% 7% 10% 71% 120/0 ",~~,o/O" 20% 14% 17% 49% 22% 17% 20% 41% 27% SUNNYVALE 21% 17% 22% 41% 1'7.% 41 ii/l) 22% 17% 20% 41% 22% 17% 20% 41% 27% UNINCORPORATED 25% 17% 17% 41% 1'7% 4.1% 23% 17% 19% 41% 22% 17% 20% 41% 31% Santa Clara County 22% 17% 20% 41% 17% 'L,:~1~o 22% 17% 20% 41% 22% 17% 20% 41% 31% BENICIA 16% 14% 18% 52% 1$%,;, 21% 16% 19% 44% 21% 17% 21% 40% 31% DIXON 17% 20% 23% 40% ?T~~~:, 21% 18% 21% 41% 21% 17% 21% 40% 30% FAIRFIELD 22% 19% 21% 38% 22% 17% 20% 40% 21% 17% 21% 40% 30% \..).) RIO VISTA 30% 19% 22% 29% ;i~5.~' 24% 17% 20% 38% 21% 17% 21% 40% 32% :.J SUI SUN CITY 15% 15% 25% 46%. :;,jQ% 20% 16% 21% 42% 21% 17% 21% 40% 31 "Ik)J VACAVILLE 18% 17% 21% 43% ""~Q$; 21% 17% 20% 42% 21% 17% 21% 40% 300;' VALLEJO 25% 18% 21% 36% 23% 17% 20% 40% 21% 17% 21% 40% 33% ...(:. UNINCORPORATED 19% 16% 20% 45%;. ' 21% 17% 20% 42% 21% 17% 21% 40% 30% b \< ":i,,,,. '.,:' Solano County 21% 17% 21% 40%' >t'!1'~Ai', 22% 17% 20% 41% 21% 17% 21% 40% 31% . ",'j",lt" . ;: C CLOVERDALE COT A TI HEALDSBURG PETALUMA ROHNEFH PARK SANTA ROSA SEBASTOPOL SONOMA WINDSOR UNINCORPORATED Sonoma County Bay Area 2.000 Ct.-OSI),.> 30% 18% 24% 17% 21% 22% 29% 26% 16% 22% 21% 23% Low Mod <80% <120% 19% 20% 19% 14% 19% 18% 17% 17% 14% 17% 17% 17% 19% 22% 23%' 20% 22% 22% 23% 19% 20% 19% 21% 19% 41 Yo".<20,Yo,{~8~ '.,~j%.;,.,.~,41%; 3401 1~~..::L2'-:'3.'''o;';'';, "1' 8"a;',";~'~~dP;":X~:7"'~h:- 10,,'."'1," . '/0' '," r70' ,:,j~ ~lO'\"'V '\7 .~::-:; i;r~~?l~j~I~~~ 32 Yo .,,-j~5*,.. .17*',:",22%:, ":.~6}{j:, 38:0 ::;;:1A1~';,..\::1t:~::>'{\~Q.~n;;j~~:: 50 Yo ,-:-.:1-9?k,;,. ..' .16'%, ",,20 J{,.\,.,.,~.~ 50% Toward Region Average ... .. '~Glmty Av~rage . ,. ',.. '.' ... . Housing Very ',Very Cost Low Low Mod Above ..Low, Low, Mod Above Burden <50% <80% <120% Mod ,', .<150%' . .<::80% .:':120%' MQd >30% .. '. 24% 17% 20% 39% ..~1% :', '17%:' ,21%. 41% 36% 21% 17% 20% 41% ~1~'. ,17%. ~1% "41% 35% 23% 17% 21% 39% ....21%:; 17% 21% .41% 30% 21% 16% 20% 43% ?1% .. 170/0 ': 21% 41CYo 31% 22% 17% 20% 41% 21% 11%'.'. 21%' . 41 0/0: 38% 22% 17% 20% 40% '.~1% : 17% '21% 41% 33% : 24% 17% 21% 39% 21<>(0- 17% . 21% . 41% 35% 23% 17% 19% 41% 21% 17% 21% : 41% 36% 21% 16% 20% 43% 21% 17%. .21% 41% 34% 22% 17% 20% 41% ,21% 17'Yc' 21% 41% 32% " .' ..0, 22% 17% 20% 41% '21%. .17% 21% 41% 33% , . " ,,' , . U) ~ dJ~ ~ J c ASSOCIATION OF BAY AREA GOVERNMENTS :3q Ob4LD o Representing Ci!y and County Governments of the San Francisco Bay Area ABAG MEMO To: From: Date: Subject: Housing Methodology Committee (HMe) ABAG Staff January 4, 2007 Alternative Income Allocation Method Background On November 16, 2006, ABAG's Executive Board authorized the release of the Housing Methodology Committee's draft methodology for the Regional Housing Needs Allocation (RHNA) for 2007-2014. The release of the methodology opened a 60-day public comment period. The comment period will close on January 18, 2007. On that date, staff will bring to the Executive Board recommendations for the fi~al RHNA methodology. Several comments received on the draft RHNA method pertain to the income allocation component of the methodology. Some local jurisdictions believe the proposed income allocation methodology does not do enough to alleviate existing concentrations of poverty. There is concern that, because the draft recommendation assigns an "equal share" to each jurisdiction and does not take a jurisdiction's existing income distribution into account, it unfairly burdens jurisdictions with existing high concentrations of poverty. As a result, the draft method is perceived to perpetuate regional social and economic inequities. Staff has developed three alternative income allocation scenarios for consideration by the HMC and the ABAG Executive Board at its meeting on January 18th. In contrast to the draft methodology, these alternative scenarios take into account existing income distributions within individual communities and attempt to address existing concentrations of poverty. This staff report describes these alternative income allocations. HMC Recommended Income Allocation In the recommendation to the ABAG Executive Board, the HMC and ABAG staff proposed that each local jurisdiction plan for income-based housing units in the same ratio as the regional average income distribution. This is deemed an "equal share" approach because each jurisdiction would receive the same proportion of housing units in each affordability category (very-low, low, moderate, and above moderate). Although cOlisidered an equitable approach, this income allocation method does not consider existing concentrations of poverty in a community. Based on 2000 Census figures, the regional income distribution is: . Very Low, 23 Percent Households with income up to 50 percent of the county's area median income (AMI) Low, 16 Percent Households with income between 50 and 80 percent ofthe county's AMI Moderate, 19 Percent Households with income between 80 and 120 percent of the county's AMI Above-Moderate, 42 Percent Households with income above 120 percent of the county's AMI . . . Mailing Address: P.O. Box 2050 Oakland, California 94604-2050 (510) 464-7900 Fax: (510) 464-7970 info@abag.ca.gov Joseph P. Bort MetroCenter 101 Eighth Street Oakland, California 94607-4756 Attachment 2 l-\O O"b 4\J2 RHNA Income Allocation 1/04/'07 Page 2 Percent Adjustment Toward Regional Average By allocating each jurisdiction an equal share based on the regional income distribution, the draft allocation scenario moves each jurisdiction 100 percent toward the regional income distribution. It is focused on promoting an equitable regional distribution for future housing production, but does not consider existing concentrations of poverty in a community or take steps to reduce them. In contrast, the first two alternative income allocation scenarios give each jurisdiction either 150 or 175 percent of the difference between their 2000 household income distribution and the 2000 regional household income distribution. The first step in this process is to determine the difference between the regional proportion of households in an income category and the jurisdiction's proportion for that category. This difference is then multiplied by either 150 or 175 percent to determine an "adjustment factor." Finally, this adjustment factor is added to the jurisdiction's initial proportion of households in the income category, which results in the total share of the jurisdiction's housing unit allocation that will be in that income category. Using the 175 percent factor and the City of Oakland's very low income category as an example, 36 percent of households in Oakland were in this category, while the regional total was 23 percent. Oakland -23 Total Share 13 -13 Multiplier 175% Adjustment Factor City Jurisdiction Proportion 36 Regional Proportion 23 Difference The difference between 23 and 36 is -13. This is multiplied by 175 percent for a result of -22.75 (rounded to 23). This is then added to the city's original distribution of36 percent, for a total share of 13 percent. A similar calculation for Piedmont, which has a relatively low proportion of households in the "very low" income category yields the following results: Piedmont 24 Total Share 33 City Jurisdiction Proportion 9 Regional Proportion 23 Difference 14 Multiplier 175% Adjustment Factor As shown above, those jurisdictions that have a larger proportion of households in an income category will receive a smaller allocation of housing units in that category. Conversely, those jurisdictions that have a relatively low proportion of households in a category would receive a higher allocation of housing units in that category. The effect of these allocation scenarios is to change the income distribution in each jurisdiction to more closely match the regional distribution by taking both a jurisdiction's existing conditions and future development into account. By addressing existing concentrations of poverty, these scenarios more aggressively promote an equitable regional income distribution. The multiplier determines how aggressively the scenario functions; the higher the multiplier, the more aggressive. Tiered Adjustment Based on Concentration of Poverty The third alternative scenario is similar to the first two alternatives in that it uses existing conditions to move each jurisdiction closer to the regional income distribution. The key difference in this scenario is that jurisdictions are first separated into three groups based on the jurisdiction's proportion of low- and very low-income households compared to the proportion for the region. The three groups correspond to L.\ \ Db~ RHNA Income Allocation 1/04/07 Page 3 three different multipliers (like the 175 percent example used above) that determine how far a jurisdiction must move toward the regional income distribution. The fIrst step in this process is to add together the percentages of very low and low income households in a jurisdiction. Each jurisdiction's result is then compared to the regional proportion. Based on this comparison, jurisdictions are put into one of three categories: . Low concentration: where less than 25 percent of total households have very low or low incomes. Moderate concentration: where less than 45 percent of total households have very low or low Incomes. . . High concentration: where more than 45 percent of total households have very low or low incomes (San Pablo is the highest in the region at 65 percent). Jurisdictions in the low concentration category, such as Livermore, Pleas anton, Clayton, Danville, and Los Altos Hills move the furthest (185 percent) toward the regional average. Those in the moderate concentration category, such as Albany, Walnut Creek, Napa, San Francisco, and San Jose, move 180 percent and those in the high concentration category, which includes Berkeley, Oakland, Richmond, San Rafael, Gilroy, and Sebastopol, move 175 percent. Once the multiplier for the jurisdiction has been determined, the steps for determining the jurisdiction's share of housing units in each income category is the same as the one for the fIrst alternative methodology described above. Taking the City of Piedmont example used above, this scenario would result in a higher share of very low-income units for the city because the city falls into the low concentration category and has a multiplier of 185 percent. Here, the share is 35 percent compared to 33 percent in the example above. 14 Multiplier 185% Adjustment Factor Total Share City Piedmont Jurisdiction Proportion 9 Regional Proportion 23 Difference 26 35 The result of this allocation scenario is that jurisdictions with a low concentration of low and very low income households get higher allocations of very low- and low-income housing units. Those jurisdictions that already have a high concentration of very low- and low-income households are allocated fewer units in these categories. As in the fIrst alternative scenario, the effect of this allocation scenario is to change the income distribution in each jurisdiction to more closely match the regional distribution by taking both a jurisdiction's existing conditions and future development into account. This third alternative scenario specifIcally looks at the proportion of very low- and low-income households in a jurisdiction as the factor for determining how far the jurisdiction must move toward the regional average income distribution. Summary The alternative allocation scenarios described above have been designed to promote a more equitable regional income distribution by addressing existing concentrations of poverty in individual jurisdictions. The scenarios demonstrate different possible approaches and outcomes for moving jurisdictions toward the region's income distribution. Staff recommends that the HMC consider these alternative income allocations and come to a consensus on a recommendation to the ABAG Executive Board. Income Catego. .Iternatives Existing % into 3 Groups Existing Percentages Plus Existing Percentages Plus Higher Existing Concentration Gets Average Regional Percentage 150% Regional Average Minus Exist 175% Regional Average Minus Exist Lower Allocation of Affordable Draft Allocation Proposal II 150% Toward Regional Average U 175% Toward Regional Average I Tiered Adjustment Very Very Very Very T~tli!' . Low Low Mod Above Low Low Mod Above Low Low Mod Above Low Low Mod Above Ne~!l. <50% <80% <120% Mod <50% <80% <120% Mod <50% <80% <120% Mod <50% <80% <120% Mod ALAMEDA 2.,O7~. 469 343 399 864 483 339 395 858 485 338 394 858 488 337 396 862 ALBANY 59 43 50 109 61 42 49 111 61 41 49 112 61 41 49 112 BERKELEY 614 449 521 1,130 448 468 579 1,218 361 479 608 1,266 362 479 612 1,272 DUBLIN 778 569 661 1,432 1,013 648 666 1,115 1,121 690 669 960 1,171 706 674 901 EMERYVILLE 348 254 295 640 283 243 293 716 249 239 293 757- 250 239 295 761 FREMONT 1,092 799 927 2,009 1,357 923 947 1,604 1,476 988 957 1,406 1,533 1,012 968 1,332 HAYWARD 757 554 643 1,394 758 506 585 1,499 751 484 556 1,557 754 479 554 1,576 LIVERMORE 774 567 657 1,425 958 636 674 1,157 1,040 673 682 1,028 1,080 686 690 979 NEWARK 203 149 172 374 246 161 164 327 265 168 160 304 270 169 160 301 OAKLAND 3,867 2,831 3,284 7,117 2,766 2,595 3,521 8,208 2,189 2,487 3,641 8,782 2,197 2,486 3,666 8,825 PIEDMONT 8 6 7 16 11 8 9 9 12 10 10 5 13 10 11 4 PLEASANTON 834 610 708 1,535 1,087 753 772 1,078 1,204 827 804 853 1,258 855 822 766 SAN LEANDRO 424 310 360 780 423 280 330 841 419 267 315 874 420 263 314 885 UNION CITY 455 333 386 837 539 382 389 702 576 408 390 637 587 413 393 626 UNINCORPORATED 507 371 430 932 539 360 416 925 549 356 409 925 554 355 411 929 ALAMEDA COUNTY 11,189 8,190 9,502 20,593 10,972 8,344 9,788 20,368 10,711 8,361 9,831 20,571 11,000 8,531 10,013 20,133 ANTIOCH 521 381 442 958 521 357 400 1,023 516 347 380 1,059 518 344 378 1,071 BRENTWOOD 635 465 539 1,168 708 458 509 1,132 738 457 493 1,118 748 456 494 1,120 CLAYTON 33 24 28 60 42 30 30 42 47 33 31 33 49 35 32 30 CONCORD 706 517 599 1,299 672 466 536 1,445 649 443 505 1,524 648 438 502 1,546 DANVILLE 125 92 106 230 166 113 127 147 185 124 138 106 194 129 143 90 EL CERRITO 118 86 100 217 114 77 97 233 112 73 96 242 112 72 96 245 HERCULES 97 71 83 179 124 71 73 163 136 71 69 156 139 71 68 155 LAFAYETTE 81 59 69 149 102 71 75 110 112 77 78 91 116 80 80 83 MARTINEZ 236 173 201 435 251 168 183 444 255 166 174 449 258 166 174 452 MORAGA 50 37 43 93 63 42 47 70 69 45 49 59 72 46 50 55 OAKLEY 169 124 144 312 198 119 104 328 210 118 83 338 214 117 80 341 ORINOA 50 37 42 92 64 45 51 61 70 49 55 46 73 51 57 40 PINOLE 69 51 59 128 76 48 49 133 78 47 45 136 79 47 44 137 PITTS BURG 457 335 388 842 397 283 352 989 363 259 334 1,066 365 258 336 1,072 PLEASANT HILL 134 98 114 247 145 100 104 244 150 101 99 243 151 101 98 244 RICHMOND 624 457 530 1,149 462 376 525 1,396 376 337 523 1,524 378 337 526 1,532 SAN PABLO 64 47 54 118 35 40 56 152 20 37 57 169 20 37 57 170 SAN RAMON 744 545 632 1,370 994 637 676 987 1,110 686 698 798 1,163 704 711 726 WALNUT CREEK 499 365 424 919 510 351 420 927 510 346 417 935 513 344 420 940 UNINCORPORATED 828 606 703 1,524 844 622 708 1,489 844 632 711 1,476 848 633 716 1,480 ..r: CONTRA COSTA COUNTY 6,242 4,569 5,301 11,489 6,489 4,476 5,122 11,516 6,391 4,455 5,091 11,665 6,656 4,466 5,063 11,530 rJ a ~ f; Income Catego. .Iternatives Existing % into 3 Groups Existing Percentages Plus Existing Percentages Plus Higher Existing Concentration Gets Average Regional Percentage 150% Regional Average Minus Exist 175% Regional Average Minus Exist Lower Allocation of Affordable .0""'.'.,1 Draft Allocation Proposal II 150% Toward Regional Average II 175% Toward Regional Average U Tiered Adjustment Very Very Very Very Low Low Mod Above Low Low Mod Above Low Low Mod Above Low Low Mod Above <50% <80% <120% Mod <50% <80% <120% Mod <50% <80% <120% Mod <50% <80% <120% Mod BELVEDERE 6 4 5 10 7 5 6 7 7 6 6 6 7 6 6 6 CORTE MADERA 52 38 44 96 61 37 44 90 64 37 43 88 65 37 43 88 FAIRFAX 16 12 14 30 16 10 13 34 15 8 12 36 15 8 12 36 LARKSPUR 138 101 118 255 142 93 119 258 143 90 119 260 144 89 120 262 MILL VALLEY 63 46 53 116 68 50 60 100 70 52 64 92 70 52 65 91 NOVATO 324 237 275 596 320 212 259 640 315 200 252 664 315 198 252 672 ROSS 6 4 5 11 7 5 5 8 7 6 5 7 8 6 5 7 SAN ANSELMO 24 18 21 45 24 18 20 45 24 18 20 45 24 18 20 45 SAN RAFAEL 353 258 299 649 312 241 311 695 288 233 317 721 289 233 319 724 SAUSALlTO 40 29 34 74 46 32 35 65 48 33 36 61 49 33 36 60 TIBURON 28 20 24 51 34 22 26 41 37 23 28 35 38 23 28 34 UNINCORPORATED 155 113 131 284 160 119 142 263 161 122 148 253 162 123 150 252 MARIN COUNTY 1,204 882 1,023 2,217 1,196 843 1,041 2,246 1,210 861 1,072 2,182 1,187 825 1,058 2,277 AMERICAN CANYON 157 115 133 288 160 112 134 287 159 112 135 287 160 111 136 288 CALISTOGA 20 15 17 37 17 12 17 43 16 10 17 46 16 10 18 46 NAPA 433 317 368 798 439 294 361 823 438 283 357 839 440 280 359 846 ST HELENA 26 19 22 48 28 20 23 45 28 20 24 43 29 21 24 43 YOUNlVlLLE 19 14 16 35 17 14 15 37 15 15 15 38 15 15 15 39 UNINCORPORATED 141 104 120 260 163 109 123 231 173 112 124 217 175 113 125 215 NAPA COUNTY 797 583 677 1,467 824 561 673 1,465 833 550 672 1,469 835 550 676 1,476 SAN FRANCISCO COUNTY 9,158 6,703 7,778 16,855 8,759 7,061 8,387 16,285 8,477 7,268 8,695 16,055 8,464 7,301 8,816 16,080 SAN MATEO COUNTY 4,132 3,024 3,509 7,605 4,132 3,024 3,509 7,605 4,292 2,930 3,382 7,667 4,302 2,923 3,374 7,671 CAMPBELL 167 122 142 308 166 109 134 331 163 102 130 344 164 101 130 . 348 CUPERTINO 252 184 214 463 300 208 224 381 322 220 229 342 328 222 231 335 GILROY 358 262 304 660 328 231 277 749 310 216 263 796 311 216 265 800 LOS ALTOS 68 50 58 126 85 59 69 89 92 64 74 71 96 66 77 64 LOS ALTOS HILLS 17 13 15 32 23 17 19 19 25 19 21 12 26 19 22 10 LOS GA TOS 121 88 102 222 138 93 111 192 145 96 115 177 147 96 117 175 MILPITAS 593 434 503 1,091 683 442 474 1,022 721 449 460 991 733 449 460 989 MONTE SERENO 9 7 8 16 11 8 9 11 12 9 10 8 13 9 11 7 MORGAN HILL 300 220 255 553 315 242 249 522 319 255 247 509 321 257 248 508 MOUNTAIN VIEW 623 456 529 1,146 611 429 518 1,195 600 417 513 1,224 601 414 515 1,235 PALO ALTO 840 615 714 1,547 879 679 789 1,370 889 714 827 1,286 896 720 840 1,275 ~ SAN JOSE 7,522 5,506 6,388 13,844 7,462 5,265 6,046 14,485 7,361 5,166 5,877 14,855 7,378 5,140 5,883 14,995 SANTA CLARA 1,351 989 1,147 2,487 1,328 955 1,055 2,636 1,304 942 1,009 2,719 1,306 938 1,006 2,748 l}l SARATOGA 63 46 53 115 78 58 66 75 85 65 73 55 88 67 76 47 SUNNYVALE 1,037 759 881 1,908 1,087 746 824 1,927 1,102 743 795 1,943 1,111 742 795 1,955 J1 UNINCORPORATED 36 26 31 67 35 26 32 67 34 26 33 67 34 26 33 68 SANTA CLARA COUNTY 13,357 9,777 11,344 24,584 .13,528 9,569 10,895 25,071 13,668 9,642 10,940 24,813 13,553 9,484 10,709 25,560 .L b Income Catego. .Iternatives Existing % into 3 Groups Existing Percentages Plus Existing Percentages Plus Higher Existing Concentration Gets Average Regional Percentage 150% Regional Average Minus Exist 175% Regional Average Minus Exist Lower Allocation of Affordable Draft Allocation Proposal II 150% Toward Regional Average II 175% Toward Regional Average n Tiered Adjustment Very Very Very Very Low Low Mod Above Low Low Mod Above Low Low Mod Above Low Low Mod Above <50% <80% <120% Mod <50% <80% <120% Mod <50% <80% <120% Mod <50% <80% <120% Mod BENICIA 114 84 97 210 132 91 100 183 139 95 102 170 141 96 103 168 DIXON 157 115 133 288 177 101 121 293 186 95 116 296 188 93 115 298 FAIRFIELD 829 607 704 1,526 839 568 665 1,594 836 550 645 1,634 840 546 646 1,649 RIO VISTA 262 192 223 482 222 177 204 556 200 170 194 594 201 170 196 597 SUISUN CITY 135 99 115 248 158 104 99 235 168 108 91 230 171 108 90 230 VAGAVILLE 624 456 530 1,148 686 451 499 1,121 711 451 484 1,111 720 450 485 1,114 VALLEJO 700 512 594 1,288 669 485 572 1,367 648 474 561 1,411 647 471 563 1,426 UNlNGORPORA TED 21 16 18 39 23 16 17 37 24 16 17 37 24 16 17 37 SOLANO COUNTY 2,841 2,080 2,413 5,229 2,907 1,993 2,277 5,386 2,990 1,998 2,236 5,338 2,932 1,950 2,214 5,519 CLOVERDALE 114 84 97 210 95 78 97 235 85 75 97 248 85 75 97 250 COTATI 85 63 73 157 94 57 68 159 98 54 66 160 99 53 65 161 HEALDSBURG 90 66 76 165 87 61 69 181 84 58 65 189 84 58 65 192 PETALUMA 466 341 395 857 524 364 390 781 549 376 388 745 556 379 390 742 ROHNERT PARK 429 314 364 790 445 294 341 816 449 286 329 832 453 284 329 839 SANTA ROSA 1,509 1,105 1,282 2,778 1,539 1,053 1,183 2,899 1,540 1,031 1,134 2,969 1,548 1,025 1,131 2,996 SEBASTOPOL 38 28 32 70 33 27 29 78 31 27 28 83 31 27 28 83 SONOMA 76 56 64 140 71 54 65 145 68 53 65 148 68 53 66 150 WINDSOR 158 116 134 291 181 123 133 262 191 128 132 248 194 128 133 247 UNINGORPORA TED 299 219 254 549 306 214 253 547 306 213 253 548 308 212 254 551 SONOMA COUNTY 3,263 2,389 2,772 6,006 3,377 2,324 2,627 6,103 3,395 2,319 2,612 6,104 3,242 2,166 2,396 5,799 REGION 52,183 38,197 44,319 96,044 52,183 38,197 44,319 96,044 52,183 38,197 44,319 96,044 52,166 38,151 44,327 96,098 J: j:.. { b L.\ 5 D[) L\\.o CITY OF DUBLIN 100 Civic Plaza, Dublin, California 94568 Website: http://www.ci.dublin.ca.us January 17, 2007 VIA FACSIMILE AND MAIL (510) 464-7970 Association of Bay Area Governments Attn: Paul Fassinger, Research Director P.O. Box 2050 Oakland, CA 94604-2050 Subject: Alternative RHNA Allocation Methodology, Income Allocation Dear Mr. Fassinger: Thank you for providing us with an opportunity to review and comment on the draft Regional Housing Needs Allocation methodology which was authorized for release by the ABAG Executive Board on November 16, 2006. The City of Dublin supports the proposed methodology for the allocation of the region's housing need which is based on 40% household growth, 20% existing employment, 20% employment growth, 10% household growth near transit and 10% employment growth near transit. Dublin also supports the methodology for the allocation of housing units by income level which is based on an "equal share" approach where every jurisdiction would provide 23% very low income units, 16% low income units, 19% moderate income units and 42% above moderate income units. At the January 4, 2007 Housing Methodology Committee (HMC) meting, ABAG presented 3 alternative methodologies for the allocation of housing units by income level in response to comments received by some local jurisdictions. The alternative methodology recommended by the HMC uses a 175% multiplier to calculate the allocation of housing units by income level in an effort to address existing concentrations of lower income housing within the region. Dublin supports both ABAG and the HMC in their efforts to reduce existing concentrations of lower income housing by considering alternative methodologies for the allocation of housing units based on income level however, we feel that the 175% multiplier is too aggressive for the 7-year planning period. The City respectfully requests that ABAG staff and the Executive Board consider a less aggressive multiplier of 100% or 125%. It is our belief that a less aggressive multiplier still works towards the goal of reducing existing concentrations of lower income Area Code (925) . City Manager 833-6650 . City Council 833-6650 . Personnel 833-6605 . Economic Development 833-6650 Finance 833-6640 . Public Works/Engineering 833-6630 . Parks & Community Services 833-6645 . Police 833-6670 Planning/Code Enforcement 833-6610 . Building Inspection 833-6620' Fire Prevention Bureau 833-6606 Attachment 3 4 ta OC> ~\.C> housing while producing income allocations that are more realistic and achievable for local jurisdictions. In addition to concerns over the aggressiveness of the multiplier, the City is also concerned about the lack of services available to serve lower income households in the Tri-Valley area. Again, while Dublin supports the efforts to reduce existing concentrations of lower income housing, we feel that approaching the issue incrementally will not only set more realistic goals for our community and the entire Bay Area, but will also give the support service providers, needed by lower income households, the opportunity to redirect resources to outlying areas as the service population grows. The City of Dublin has made great strides during the last RHNA cycle to remove constraints and zone for lower income housing. Over the last RNHA cycle, the City of Dublin has constructed 3,585 housing units offering a range of housing opportunities for all income levels and will continue to work towards providing housing that is affordable to all income levels. We recognize the need to address existing concentrations of lower income housing and believe that taking smaller steps towards achieving this goal will yield better results than setting unrealistic goals that will not be achievable. Best Regards, Janet Lockhart Mayor CC: Richard Ambrose, Dublin City Manager Henry Gardner, ABAG Executive Director 20f2