Last month, Pew Charitable Trusts published Defaulting on the Dream: States Respond to America’s Foreclosure Crisis, the first comprehensive report on each state’s efforts to respond to the crisis.  Based on statistics obtained from the Center for Responsible Lending, the report states that one in 33 current U.S. homeowners will end up on foreclosure.   For California, the number is 1 in 20.  Uniquely, the report offers sobering statistics with respect to the ripple effect of the crisis, such as the number of neighboring homes in each state projected to experience devaluation in 2008 and 2009 - over 7.5 million in California.  In terms of fixes or responses, the states are all over the map, so to speak.  For instance, while some states, like California and Pennsylvania, have foreclosure intervention laws and regulations, others, such as Illinois and Ohio, also have statewide counseling services and hotlines.  Some states, including Washington, Oregon and Texas, have none of the above.  As the report predicts that there will be 1 million foreclosures in 2009 if homes values continue to fall at the current pace, it urges states to act now with aggressive laws that protect homeowners at risk against scams, and laws that reform underwriting and income verification standards.   Pew also has posted on its webpage related facts sheets for each state.

Joining Florence Wagman Roisman’s clarion call in End Racial Segregation: Build Communities that Look Like America, recently posted on this page, two other fair housing/civil rights heavyweights urge the social justice community to fully engage in strategic race-conscious fair housing and community development advocacy as the best way to fulfill the promise of the federal Fair Housing Act, now in its 40th year.

In An Unfinished Agenda: Fair Housing and Community Development To Fight the Vestiges of Segregation, recently published in the Black Agenda Report and ShelterForce Online, renown civil rights attorney Betsy Julian calls on social justice advocates to coalesce around and move forward with an agenda that demands implementation of a true anti-segregation approach in housing and community development policy at the local, state and national levels. Like Roisman, Julian reminds us of the direct connection between government-created and sanctioned housing segregation and discrimination and the ongoing “[r]acial disparities [that] exist in almost every indicator of health and well-being.” She rightly asks whether we in the justice community are complicit in maintaining structurally racist systems when we insist on “colorblindness” and “class over race” as paradigms in approaching our work when, in fact, the demographics reveal stark differences in access to opportunity and decent living conditions between poor whites and poor people of color. Citing successful examples, she urges advocates to pursue impact litigation to address disparities in housing and municipal services and to push Congress and other law-making bodies to remove from the Low Income Housing Tax Credit, HOPE IV Public Housing Program and other programs the components that perpetuate racial segregation.

In Is local housing really fair? (April 26, Press Democrat), civil rights and land use attorney David Grabill also links racially discriminatory zoning practices to school segregation in the context of a critique of Santa Rosa, California’s “inclusionary” zoning ordinance. The ordinance, states Grabill, fails to live up to its title because it allows developers to pay fees in lieu of building affordable units in affluent high opportunity areas, thus excluding low income people who are disproportionately people of color from such neighborhoods and exporting the inclusionary obligation to poorer, mostly of color areas. Grabill offers workable local solutions such as requiring that inclusionary zoning laws apply in single-family home areas and requiring jurisdictions to match their hunger for economic development with a commitment to fairly house the workers that make such development possible.

The Harvard Law & Policy Review Online, published a note, entitled End Residential Racial Segregation: Build Communities that Look Like America, by long time housing advocate and Indiana University law professor Florence Wagman Roisman. After detailing the history of federal policies that have resegregated American cities along racial lines, the author suggests seven common sense initiatives to address the problem. We join Florence in her hope that we soon find leaders with the power, vision and courage to implement these needed changes.

The City of Baltimore filed a federal lawsuit under the Federal Fair Housing Act on January 8 alleging that defendant Wells Fargo Bank intentionally targeted Baltimore’s African-American communities for predatory loans. The complaint further alleges that Wells Fargo’s “reverse redlining” practices have led to very high rates of foreclosure in the city’s African-American and other communities of color costing the city millions in lost revenues and resulting in further distressed and destabilized neighborhoods. The complaint sets forth startling statistics, e.g. a Wells Fargo loan in a predominantly African-American community in Baltimore is four times as likely to be in foreclosure as a Wells Fargo loan in a predominantly white community, and contains several maps to illustrate such disparities, among other thing. Civil rights firm Relman & Dane is representing the city. For recent press on the lawsuit, see Baltimore Is Suing Bank Over Foreclosure Crisis (NY Times, 1/8/08) and Suspect Foreclosures (Baltimore Sun, 1/10/08) or listen to/read National Public Radio’s Morning Edition report (1/11/08) (with links to more maps) Baltimore Blames Bank for Wave of Foreclosures.

LSNC and other Legal Services corporations have been inundated with foreclosure related issues in recent months. As most poverty attorneys who have handled a foreclosure case will attest, prevention and early intervention are key to preventing foreclosure. Of course, before you can deliver education and community outreach to LSC eligible homeowners you need to know were they live. You also need to identify where populations of LSC eligible homeowners of color live. In many areas, due to the greater frequency of asset accumulation of Whites, if you do not include a separate analysis of race and ethnicity you will end up serving mostly White LSC eligible homeowners and excluding homeowners of color.

Lets conduct this analysis for Los Angeles County, California, using free online mapping software and free census data extraction tools so that any Legal Services program can replicate this process for their service area if it has a computer, Microsoft Office, and an internet connection. The online mapping software we will use is DataPlace and the free census extraction tool is GIStools. For purposes of space, this tutorial assumes that you have created an account with DataPlace and have downloaded the software and relevant datasets for GIStools.

First, we need to identify what Census data to use. Since we want to identify areas where foreclosure services outreach will have the greatest impact, we need to find the areas in Los Angeles county where there is a high percentage of homeownership and where there is a high percentage of LSC eligible clients. Since we also want to make sure that our outreach effectively reaches all LSC eligible homeowners we also want to find areas where there is a high percentage of homeowners of color and a high percentage of LSC eligible persons.

My suggestion is to use three datasets from the 2000 Census, SF3, to identify areas for possible outreach - P088 (Population by ratio of income to poverty), H007 (Tenure), and H013 (Tenure, White alone not Hispanic). Since we will be using DataPlace to map the data, we need to obtain the data at the Census Tract summary level (the smallest unit of Census geography that DataPlace can map). If I was going to map the data using ArcGIS, I would probably want to obtain the data at the Block Group summary level (the smallest unit of Census geography SF3 data is available at). Using GIStools extract the P088 and H013 data for California at the Census Tract summary level. Open the dbf. files (one for P088, one for H007, and one for H013) using Excel and copy and paste the all the data sets into one Excel spreadsheet (view example). Delete all rows for Census tracts not in Los Angeles county. You can tell which rows are for tracts in Los Angeles County by looking at the FIPSCO column. The first two numbers in the entry (”06″) represent the state code for California. The next three numbers are the FIPS codes for the various coutys in California. Los Angeles county’s FIPS code is “037.” Simply delete all rows where the value of the FIPSCO entry is not “06037″ (view example).

Second, we need to combine some of the data fields to simplify our spread sheet. Columns P088001 - 10 represent the various data fields of P088. Take a look at the Cenus Bureau’s technical documentation of the 2000 Census SF3 file to see what each of these columns represent. Since we want to know the count of person’s below 200% of the poverty level (our approximation of LSC client eligibility), we will create a new column (LSCPOP) that is the sum of P088002 - 09. The values of LSCPOP give us the count of potentially LSC services eligible persons for every Census tract in Los Angeles county (view example). Since it would also be helpful to know what percentage of the population is LSC eligible, lets create a new column (PERLSC) and use Excel to divide LSCPOP by P008001 giving use the percentage of the population that is LSC eligible for every Census tract in Los Angeles county (view example).

Columns H007001 -03 and H013001-03 represent the various data fields of H007 and H013 respectively. Take a look at the Cenus Bureau’s technical documentation of the 2000 Census SF3 file to see what each of these columns represent. We are going to use these columns to calculate the count of homeowners, the count of homeowners of color, and various percentages related to these categories.

The count of homeowners in a Census tract is simply H007002. We need to create a new column (PEROWN) to calculate the percentage of the population in each Census tract that is a homeowner. The values for this column are obtained by dividing H007002 by H007001 (view example).

The count of White homeowners is simply H013002. We need to calculate a new column (PERWHITE) to calculate the percentage of homeowners who are White in a Census tract. The values for this column are obtained by dividing H013002 by H007002 (view example).

We need to create a new column (HOCOLOR) to calculate the count of homeowners of color in a given Census tract. The values for this column are obtained by subtracting H013002 from H007002 (view example). We also need a new column (PERHOCO) to calculate the percentage of homeowners who are homeowners of color in a Census tract. The values for this column are obtained by dividing HOCOLOR by H007002 (view example).

Before we move on to step three, lets “clean up” our spread sheet by deleting columns that we no longer need. Before we do this, copy the whole spreadsheet and “Paste Spacial” it into a new spreadsheet. Paste “Values” only. Take a look at our the “cleaned up” spreadsheet showing the columns that we need to keep (view example). You should also replace all “#DIV/0!” with a null value and delete any extra sheets.

Third, we are going to identify the census tracts in Los Angeles county that will likely be the best areas to provide foreclosure related services to. We need to set the a criteria for identifying the tracts. What criteria you set is, of course, fairly subjective. When I create criteria like this I tend to select criteria that are restrictive enough to eliminate the majority of tracts but not so restrictive that I the pool of identified tracts is too small to be useful. For the purpose of this tutorial, our criteria will that tracts must have (1) 200 or more units that are owner occupied and (2) have a population that is 70% or more LSC eligible.

Create a new column (IMPACT). Using the Excel “If function” calculate whether each tract meets the criteria discussed above. Our “If Function” will read “=IF(PERLSC<.7,"",IF(H007002<200,"",1))"(view example). This formula will return a one in the IMPACT field if the tract meets our criteria and a null value if it does not.

Create a new column (RIMPACT). Using the Excel “If function” calculate whether each tract meets the criteria discussed above. Our “If Function” will read “=IF(PERLSC<.7,"",IF(H0COLOR<200,"",1))"(view example). This formula will return a one in the RIMPACT field if the tract meets our criteria and a null value if it does not.

Fourth, lets map! Save the Excel file as “Foreclosure Data.” Logon to Dataplace. Select “My Dataplace.” Select “Create New Project.” Title your project and select “Save.” Select “Upload the file from your computer.” Browse to the “Foreclosure Data” and upload it. Select “Extract Tables.” Select “Create Dataset.” Enter the required information. You may leave the default dates or enter todays date. The source of the data is “SF3 2000 Census.”Select “OK.” Select the entry “SFID.” Unselect “Indicator” and select “Part of Region.” Select “Update.” Select “Generate Indicators.” (It will take a few minutes for DataPlace to generate the indicators…be patient.) Lastly, map the indicator of your choice (IMPACT or RIMPACT) and zoom in to the appropriate level so that you can see those Census Tracts were large populations of low-income homeowners live.

• Filed under: Data, Mapping, Housing
• Posted by ElektroMoose | 11:43 am | No Comments »