Loading...
The URL can be used to link to this page
Your browser does not support the video tag.
Report on Rental Housing and Arrest Activity in Dubuque
THE CITY OF Dubuque DT~ T~ ~ All-AmericaCity ~,,,J 1 Masterpiece on the Mississippi 2007 TO: The Honorable Mayor and City Council Members FROM: Michael C. Van Milligen, City Manager SUBJECT: Neighborhood Reinvestment DATE: December 7, 2009 Housing and Community Development Department Director David Harris has provided two memorandums dated December 7, 2009: 1. Washington Neighborhood Revitalization Strategy 2. Status Report on Rental Policies and Enforcement Acting Chief of Police Terry Tobin has provided afive-year review of Part I and Part II Crimes, including a projection for the current fiscal year which ends June 30, 2010. I provide these as you look at the results of the Report on Rental Housing and Arrest Activity in Dubuque. Michael C. Van Milligen MCVM:jh Attachments cc: Barry Lindahl, City Attorney Cindy Steinhauser, Assistant City Manager David Harris, Housing and Community Development Department Director Terry Tobin, Acting Chief of Police Jerelyn O'Connor, Neighborhood Development Specialist THE CTTY OF DUB E Masterpiece on the Mississippi 7 December 09 MEMORANDUM To: Michael Van Milligen, City Manager From: David Harris, Housing and Community Development Department Report to City Council: Washington Neighborhood Revitalization Strategy The `Washington Initiative,' a partnership including the Washington Neighborhood Association, city departments, private lenders and neighborhood businesses, was introduced in 2005. Key objectives included increasing homeowner occupancies, refurbishing older buildings, improving the appearance of the area and greater resident involvement. Soon after, the Washington Neighborhood Association (WNA) was organized and incorporated. Internal conflicts within the WNA, beginning in 2007, began to curtail participation. In September of this year, the board of the Association voted to dissolve the non-profit corporation. We hope to work with residents to reconstitute 'the neighborhood association, under new leadership, as soon as practicable. The Dubuque Community School Board made a significant commitment to the neighborhood by constructing the new charter Prescott Elementary School. This was an essential part of a strategy to attract new home owners, by replacing an aging facility with afirst-class school in the downtown. The City Council approved funds to construct a Neighborhood Resource Center in the new school building, allowing community groups to have a place for evening and weekend meetings and activities. Homes have now been purchased and rehabbed by 29 first-time owner families throughout the neighborhood. Previous rental dwellings and vacant structures have been historically restored for owner occupancy. Since late 2005, the Housing Department has loaned $3.8 million and a total of $5.6 million has been reinvested in housing in the Washington Neighborhood. This has included construction of historic front porches, bringing back the turn-of-the-century look of these homes, and bringing people out of the house -onto the porch -and into new relationships with their neighbors. The City offers a variety of financial assistance programs to encourage purchase and rehabilitation, for households at all income levels. Washington Neighborhood residents qualify for up to $40 000 in grants and deferred-payment loans, making homeownership affordable to many more families. In October, downpayment assistance was increased to 20% - up to $15 000 - to further encourage buyers facing tightened lending requirements. A tax abatement program eliminates increases in property taxes on improvements to the home for 10 years. This abatement program also applies to commercial properties, for athree-year term. Helping to fund this level of homeowner assistance has been Dubuque's Housing Trust Fund, which successfully applied again this year to the Iowa Finance Authority, for a $157 000 grant. This was the fourth Trust Fund award received, totaling $702 000 in support of Washington Neighborhood reinvestment. Trust Funds were used to assist Maria House with a $68 300 renovation project including a new roof, completely remodeled kitchen and replacement of flooring in the bathrooms. With the recently-approved Neighborhood Stabilization Program grant of $444 000 from the Iowa Department of Economic Development, the Housing Department purchased two foreclosed homes on Washington Street. We will use these funds to accomplish needed repairs, then market them to income-qualifying families and provide necessary secondary financing. In this way, we can respond to foreclosed properties as they come on the market and accomplish re-occupancy as quickly as possible. The Housing Department also signed a contract with Project Concern, utilizing a $502 000 HUD Homelessness Prevention grant. Project Concern outreach staff will use these funds to assist families at risk of losing their housing to stabilize their finances; and to place homeless persons and families in permanent rental housing. A partnership between the City and Dubuque Bank and Trust has resulted in purchase, rehab and resale of four beautifully restored homes to new families. DB&T purchases and holds properties identified by the City as vacant and derelict, until homebuyer families can be recruited and complete financial counseling courses offered through the Housing Department. Then financing is arranged, restorations completed and the homes are purchased. In this way, the goal of increasing home owners in the neighborhood is achieved while the number of vacant houses is reduced. In September 2009, DB&T passed the $1 million level for mortgage lending in the neighborhood. The bank was recognized for its leadership at a City Council meeting held in October. In recognition of our historic restoration activities, the Iowa Historic Preservation Alliance presented the Washington Initiative with a "Preservation at its Best" award. The Washington Initiative and the Neighborhood Association were jointly recognized by the Historic Preservation Commission with a Ken Kringle award this year; this award was also accorded to an Elm Street homeowner, Nancy Leslein. And the HEART Program received a 1000 Friends of Iowa award for the Washington Street home restoration project. City resources have also been committed through two new staff positions at the Housing Department. A housing inspector was assigned to work full-time in the Washington Neighborhood, beginning in April last year, concentrating efforts in rental unit inspections and daily driving of the alleys. The inspector develops relationships with residents and landlords, responds quickly to all complaints and follows through on all enforcement issues. More than 630 housing inspections of Washington properties have been completed to-date. Another new staff person at the Housing Department is a corporal from the Community Policing Unit, assigned to the Section 8 rental assistance program. This officer responds to all complaints of unauthorized tenants or disturbances, conducts investigations and initiates termination proceedings for households found in violation of program regulations. In this way, the City holds program tenants accountable and assures that unauthorized activities are quickly identified and eliminated. More than 560 investigations have been initiated to-date, resulting in termination of benefits for over 170 families. The Washington Court apartments were developed in the long-vacant former Dubuque Casket Company building, in a $7 million public-private private venture that has earned historic preservation awards. This project is also the home of the Crescent Community Health Center, providing affordable health services to uninsured households in the Tri States area. In the last year the dental clinic has expanded and the first full-time physician has been hired. Competitive federal funds have been awarded to secure future operations and expand staff capacity. Orange Park was developed by the City in response to citizen requests for additional green space in the neighborhood. A play structure and passive play area now provide parents with a place to meet and bring their young children. The Leisure Services Department conducts summer programs there in the evenings. An ambitious planning process began in 2007, starting with a `visioning' effort that defined a future neighborhood -one that promotes pride, diversity, homeownership, civic responsibility and opportunity. This was followed by a strategic planning effort involving ayear-long series of meetings of stakeholder groups. The Neighborhood Plan adopted by the City Council in April of this year makes 68 separate recommendations for citizen and public initiatives. These include actions in business and economic development, youth and family development, and housing and community development. A board of directors for a new Washington Neighborhood Development Corporation (WNDC) has been formed to implement this ambitious agenda. The Council authorized first-year funds in the amount of $100 000 to hire an executive director. Angela Petsche, formerly a management analyst at DHS, was selected and began her new position in November. An AmeriCorps member has also been assigned to the WNDC. Additional City-sponsored initiatives include a `green alley' project, to test various pervious pavement alternatives for absorbing street stormwater run-off. A two- blockalley project was completed in August, financed with a CDBG stimulus grant of $200 000, between White and Jackson Streets. Last summer the Public Works Department rolled out 500 refuse collection carts throughout the area, in an effort to combat litter and garbage complaints. These carts have increased capacity and have quickly become effective in encouraging more responsible trash management. New street lights at alley-street intersections from 12t" to 20t" Streets are being installed as requested by residents. To-date, all 38 possible installations have been approved, with 36 new lights installed. Washington Street was resurfaced by City crews from 17t" to 24t" Streets and additional accessible curbs were installed on Washington and Jackson Streets. In an innovative partnership with the School District, the City purchased along-derelict District-owned apartment building on White Street near Prescott School and sold it to a private developer for conversion to condominiums. City assistance included a $250 000 OurHome program construction loan from the Iowa Finance Authority and purchase and removal of a derelict adjacent house for additional parking. This project has been completed, offering two-bedroom, two-bath units with private garages in a beautifully refurbished `Second Empire'-style historic building. With the financial incentives package available to Washington Neighborhood residents, buyers are able to finance these condo units with bank mortgages under $100 000. The intent of this project is to demonstrate the market for conversion of older, obsolete rentals into condominium occupancies, while maintaining and restoring architectural features of historically significant buildings. Downtown working professionals seeking abike-walk commute to work is the intended market for this type of housing. The first four units were sold by November, at prices ranging from $120 000 to $140 000. Commercial activity in the Washington Neighborhood has also kept pace. The new Walgreen Drug opened in the Five Points this summer. A KFC on Central Avenue, touted as one of three nationally to be built according to a new corporate model, was completed in November. Previous improvements to City Hall and to DB&T's Heartland Financial offices in the former Walsh Store have anchored development in the lower Central Avenue area. Coordinating with recommendations from the Neighborhood Plan, efforts to develop "human capital" are part of this revitalization effort. Project HOPE has organized a collaboration of city, county, school district and business interests to offer training opportunities to unemployed and under-employed residents. The Community Foundation of Greater Dubuque is assisting with this initiative. The former Kephart Music store has been converted into the Multicultural Family Center, opened in September as a beautiful new facility offering a computer lab, social service offices, meeting rooms and after-school programming. School District personnel are providing language classes to newcomer parents and their children. Tara Velez, the executive director, has been employed through the Leisure Services Department, and is guided by anewly-incorporated board of directors for the center. The "Getting Ahead in a Just Gettin'-by World" training program was expanded, offering a 20-week course to more than 100 persons in poverty. 72 participants have now graduated from the program. This expansion was assisted with funds authorized by the Council to send several Dubuque staff and program graduates to a national trainer certification program in Dallas, expanding .our capacity to bring this message of empowerment to more Section 8 and Family Self-Sufficiency Program participants. Five of the graduates have been hired as AmeriCorps members, working at the Multicultural Family Center, Prescott School and the Housing Department. The Housing Department's relationship with the HEART Program continued to expand. HEART students were involved in reconstruction of the White Street condominium project and have worked on several City/DB&T-owned houses in the neighborhood. HEART/YouthBuild crews will be working on units in the Washington Street row house development, scheduled to commence construction by next spring. The Lead Hazard Reduction Program completed 40 units in the neighborhood, making this housing `lead-safe' for young children. Another 23 applications are currently pending. Forgivable loan amounts were doubled, to $12 000/unit, in recognition of the increasing costs of renovation in older housing. Recognizing the importance of our partnership with area landlords, the City Manager, Housing and other City staff met throughout the past year with representatives of the Dubuque Landlords Association. Discussions centered on mutual responsibilities for management of tenant behaviors. Currently, the Legal Department is developing a model fora `tenant data base' system, which would be offered by the City to landlords for background checks on applicant tenants. Owners could also provide information on histories with problem tenants -such as evictions or damages - to this data base, enabling prospective landlords to better-evaluate applicants. It is the City's intent to implement and operate this system in the coming year, and eventually to compel all rental property owners to use it to screen all tenants for occupancy. A problem property task force organized through the Housing Department, consisting of staff from a number of other departments, made additional recommendations to address chronic complaints in vacant and poorly-managed properties. These will be presented to the City Council in the coming months. Principal among these are implementation of fees for unscheduled refuse pick-ups by the Public Works Department, reduced response times for garbage/refuse complaints, reduced extensions of time to owners for compliance with housing code enforcement, increased fees for renewals of building permits and licensing of vacant properties, and designating neighborhood association representatives to the Housing Code Appeals Board. Scott Potter completed construction of Davis Place IV, a single room occupancy (SRO) facility for men, using a $700 000 HOME Program award from the Iowa Department of Economic Development. This is the fourth new building on his campus, offering affordable rooming units to a total of 60 men. Michelle Mihalakis broke ground in September for Salvia House, which will be her second SRO facility for single women. It is also a recipient of a $800 000 HOME Program award. The City assisted on both of these projects by designating the sites as Urban Revitalization Program areas. The Community Policing (COP) Program continued as a valued .partner in Washington revitalization efforts. Examples of that support include special traffic enforcement projects, walking beats by patrol, surveillance operations and placement of mobile cameras at selected sites throughout the neighborhood. COP officers attend all neighborhood meetings and are now providing support to the new neighborhood development corporation (WNDC.) THE CITY ©F Dubuque ~~ DT T~ ~ All-AmericaCity ~J ' I Masterpiece on the M#ssissippi 2007 TO: Michael Van Milligen, City Manager FROM: David Harris, Housing and Community Development Department SUBJECT: Status Report on Rental Policies and Enforcement DATE: 7 December 09 The purpose of this memorandum is to provide an up-date on changes in policies and enforcement procedures, both in the General Housing and Section 8 Program activities at the Housing Department. Section 8 The Section 8 Program Administrative Plan is continuously amended by the Housing Commission to respond to issues as they are identified. The following is a chronology of recently-adopted administrative changes to the program. 1. Preference points were established for Dubuque residence, .beginning in January 07. This had the effect of relegating non-resident applicants to a longer wait for housing assistance. 2. Program participants can be terminated for actions of any family member or guest constituting a `clear and present danger' to other persons. 3. Participants must report any absence from the unit exceeding two weeks, or face termination of benefits. 4. Participants may be terminated for failure to correct damages to unit caused by any family member or guest. 5. Appeals process stream-lined: additional appeals to Housing Commissioners or to the full Housing Commission have been eliminated. Appeals now heard only by department manager. Only one re-schedule of a hearing is now allowed. 6. Additional unlawful behaviors have been included to disqualify participants, including charges for disturbing the peace, disorderly conduct or interference with official acts. 7. Behaviors by juvenile members of the household have been added, to disqualify the family, including engaging in public disturbances or interference with official acts. 8. In November 09, waiting list closed to all applicants other than Dubuque residents and the elderly or disabled. 9. Deferred judgments now considered same as a conviction, for purposes of establishing basis for termination of participation or denial of application. 10. Corporal from Community Policing unit assigned to the program, as a full-time investigator. All complaints of fraud, disturbances and illegal occupancies are assigned to the police officer. More than 560 investigations have been initiated to-date, resulting in over 170 terminations of participant benefits. In addition, we are researching strategies to `deconcentrate' the number of Section 8 units in downtown neighborhoods. One possible option is to request HUD to allow "exception rents" for west-side occupancies -currently limited in availability due to market rents in excess of HUD requirements. General Housing Code Enforcement 1. Permits Plus system capability expanded during FY09; inspectors now carry laptops (TuffBooks) and make all inspection entries electronically, in the field. Back at the office, the inspectors dock their laptops and the inspection reports are automatically generated, eliminating the need for clerical staff to type them. This speeds up the notification process, allowing more time to landlords to make required repairs. 2. Additional inspector hired and assigned to the Washington Neighborhood. More than 630 inspections have been completed to-date, with 100% of all rental properties in the neighborhood inspected at least once. 3. As a result of these improvements, the inspection cycle of all the city's 7800 rental units has been reduced, from 7.8 to 5.5 years. We expect to further reduce the length of the inspection cycle in the coming fiscal year. 4. A `problem property task force' has developed recommendations for response to chronic inspection issues. These include reduced time for compliance -granted by both the housing inspector and the Housing Code Appeals Board - in order to get code repairs corrected more quickly. The combined, current, maximum time allowed - as much as two years in some cases -will be reduced to nine months. The Housing and Health Departments have adopted similar notice-and-order policies for response to garbage complaints. Owners receive a 3-day notice to comply; city contractors are otherwise dispatched to clean up the area and costs are assessed to the property. Owners receive one such notice, per address, per year; repeated complaints at the address are handled by sending the contractor to clean it up. The task force has recommended that the Public Works Department adopt similar policies. In addition, DPW would perform unscheduled pick-ups at chronic garbage properties and add the costs to the owner's utility bill. Extensions of building permits for rehab of residential properties would be accompanied with escalating fees, in an attempt to speed up completion of long- term projects presenting an unsightly appearance to neighboring properties. Neighborhood associations would be able to recommend appointment of two members to the Housing Code Appeals Board, to gain aneighborhood-based review of owner requests for extensions of time to complete repairs. 5. Increased enforcement of vacant-and-abandoned (VAB) properties has resulted in removal of 21 chronic problem properties from the list, since 2007. Seven were demolished; the others were rehabbed and/or re-occupied. 6. An interdepartmental group of City staff have met. with landlords throughout the past year, in discussion of problem property and problem tenant management issues. In response to landlord concerns, Chief Tobin is researching a way to provide automated notification of disturbances and calls for service at rental properties. Legal staff is researching establishment of a `tenant data base' service, which would offer landlords background checks on prospective tenants. If funded, the City would provide this service, likely through the Police Department. The plan is to offer the service at no cost, on a voluntary basis for a year, in the hope that landlords would take advantage of it. In following years, an ordinance requirement to mandate criminal background checks on all tenants could be proposed to the City Council. 7. Legal staff is also researching establishment of an `administrative court' which would hear all cases regarding enforcement of housing code orders. This could be held as often as weekly, with use of administrative judges recruited from a pool of local attorneys. The advantages of this approach would be quicker adjudication of requests from landlords for extensions of time to complete repairs, and a `professional' hearing process to resolve disputes of enforcement orders. It is possible that other departments could eventually utilize this process, including the hearing of Section 8 Program appeals. Dubuque Police Department: Part I & Part II Crimes FY05 - FY10* Five Year Part I Crimes Homicide Sex Assault Robbery A~~ Assault Five Year Part II Crimes Burglary MV Burglary Theft MV Theft .,, 1220 1215 1148 1131 1094 1120 40 ~ 25 40 37 '' 41 39 34 33 0_ 1 _ 0 1 ~~---~-' 2 FY05 FY06 FY07 FY08 FY09 *FY10 ~ 606 582 539 ..... 449 481 .._... _ _ 511 446 51 328 343 370 317 62 41 74 h~ 55 - - 70 FY05 FY06 FY07 FY08 FY09 *FY10 *FY10 figures are projections based on actual activity 7/1/09 -11/30/09 PART I CRIMES PERFORMANCE MEASURES FY05 FY06 FY07 FY08 FY09 FY10* FY 10 Projected* Number of crimes against persons 108 120 119 148 119 51 118 Murder 0 1 0 1 0 2 2 Sexual Assault 36 52 54 68 49 17 41 Robbery 18 16 25 39 33 17 41 Aggravated Assault 54 51 40 40 37 14 34 of Crimes Against Persons Cleared by Arrest National avera a in 2008 = 45% 59% 68% 66% 64% 71 % 51 Number of crimes against property 2059 1996 2265 2238 2228 830 1992 Burglary 449 481 606 582 539 213 511 Burgla to MV 328 343 370 446 514 132 317 Theft 1220 1131 1215 1148 1120 456 1094 Theft of MV 62 41 74 62 55 29 70 of Crimes Against Property Cleared by Arrest National avera a in 2008 = 17.4% 22% 20% 23% 23% 25% . 23% of Stolen Motor Vehicles Recovered 60% 73% 64% 72% 84% 79% *FY10 numbers reflects 5 monfhs of fhe fiscal year (July 1, 2009 through December 1, 2009) *FY10 Projected uses the first 5 months of FY10 dafa to project through the year based on monthly average for the first five monfhs of FY10. THE CITY OF Dubuque DT T~ ~ All•AmericaCity ~..J i Masterpiece on the Mississippi 2007 ~TO: The Honorable Mayor and City Council Members FROM: Michael C. Van Milligen, City Manager SUBJECT: Report on Rental Housing and Arrest Activity in Dubuque DATE: December 2, 2009 Housing and Community Development Department Director David Harris is transmitting a study of crime in Dubuque for the months of June and July 2009 conducted by Alta Vista Research. The study was commissioned by the Housing Commission and the objectives of the Research Project were identified as: "The overall goal of this research was to conduct an analysis of secondary data sources to investigate variations in arrest activity associated with two types of rental properties in the City of Dubuque: Section 8 and non- Section 8 rental units. More specifically, the purpose of the study was to determine if there was a high concentration of individuals arrested for crimes who resided in publicly subsidized (Section 8) housing in the City of Dubuque." In this two-month period there were 695 people arrested, some on multiple charges. Eliminating those with non-Dubuque addresses or no permanent addresses, a key point identified in the report is that: "While Section 8 estimated population is about 2,326 (about 3.9%) of the Dubuque population, they accounted for over a fifth (21.9%) of all arrestee addresses during the study period." Note: The above calculation is based on a population of 60,000. It should be no surprise that Section 8 tenants represent a disproportionate percentage of crime. These are people of income levels at 50% of area median income or below, averaging $8,500 in annual earnings. As stated in a 2007 report from the United States Government Accountability Office, "Economic Research shows an association between poverty and crime." Housing and Community Development Department Director David Harris recommends that the report from Alta Vista Research be used as the beginning point for an expanded, longer-term study that could provide information for policy decisions to address public concerns about the City's Section 8 Program. In particular, a study of more length would produce an in-depth analysis of behaviors, barriers and potential solutions. David Harris further recommends that the City develop a request for proposals and solicit interest from research firms to help with this analysis and policy recommendation. A preliminary estimate from Alta Vista Research suggests a 12- month study, at an approximate cost of $14,000. concur with the recommendation and respectfully request Mayor and City Council approval. Michael C. Van Milligen MCVM:jh Attachment cc: Barry Lindahl, City Attorney Cindy Steinhauser, Assistant City Manager David Harris, Housing and Community Development Department Director THE CITY OF Dubuque DT TB ~ All•AmericaCily ~J 1 I Masterpiece on the Mississippi 2007 TO: Michael Va~n~~ illigen, City Manager FROM: Davic'N'~arris Housin and Communit Develo ment De artment g Y p p SUBJECT: Report on Rental Housing and Arrest Activity in Dubuque DATE: 2 December 09 The "Report on Rental Housing and Arrest Activity in the City of Dubuque" has been released. The Housing Commission contracted for this study with Alta Vista Research Inc, to document the number of persons arrested in Section 8 Program units, relative to the total number of all Dubuque rental units. The report, while informative, points to the need for additional research and analysis. The study was designed as a `snap-shot,' covering only two months -June and July - during 2009. The sample size (121 Section 8 participants) was quite small. It calculated number of persons arrested during this -time period, and matched them to their place of residence. Alta Vista Research determined that the 1085 persons arrested represented 695 unique individuals, of which only 553 had Dubuque addresses. From this total of arrestees, the number of renters and non-renters was calculated. Alta Vista determined that there were actually fewer renters arrested than non-renters. Of the 257 renters arrested, less than half (121 persons or 47%) resided in Section 8 rental units, and just over half (136 or 53%) lived in non-Section 8 rental housing. However, as Section 8 units comprise only about 14% of the total number of rental units in the City, and 47% of arrests during the study period were matched to Section 8 addresses, Alta Vista concluded that Section 8 residents represented a disproportionate number of those arrested among the rental population. As a general conclusion, the report seems to debunk the consensus opinion that renters make up the majority of persons arrested, in addition to the idea that Section 8 renters comprise a majority of those arrested. However, the report does confirm that Section 8 renters are disproportionately represented among all renters arrested for criminal activities. From a public policy viewpoint, however, what has been learned about ways to better- administer the program? For instance, how can more lawful behaviors and good citizenship be promoted? Can participants be `incented' to go back to school, re-unite their families or break the cycle of inter-generational poverty? Is there an opportunity to make Dubuque's Section 8 program a model of self-help efforts -like the "Getting Ahead in a Just Gettin'-by World" program -promoting personal achievement and responsibility? Section 8 households are poor: Federal regulations require incomes below 50% of area median. Dubuque's participants average $8500 in earnings annually. Many studies have drawn relationships between poverty and crime, poor health and lack of education. Some have even linked poverty with a negative effect on a community's economic growth. The development of `human capital' is considered a driver of local economy; persons in poverty, however, are limited in their ability to remain healthy and develop marketable job skills. And when poverty affects a significant part of the population, this can extend to the larger community and slow rates of economic growth. (US General Accountability Office; January 200 An Ohio State University study published in June 2009 defined "concentrated poverty" as occurring when more than 40% of a community earns less than the Federal poverty standard. "When a neighborhood reaches a certain level of poverty, it invites crime to it." It concluded that it is essential to disperse low-income housing throughout affordable neighborhoods in a community, rather than concentrating it in only a few. Calling this "opportunity-based housing," this approach seeks to reverse poverty effects by locating lower-income households close to jobs, schools and public transportation. Recommendation My recommendation is that the report from Alta Vista Research be used as the beginning point for an expanded, longer-term study which could provide policy recommendations to address public concerns about our Section 8 Program. In particular, a study of more length would produce an in-depth analysis of behaviors, barriers and potential solutions. I recommend we develop a request for proposals and solicit interest from research firms to help us with this analysis and policy recommendation. A preliminary estimate from Alta Vista Research suggests a 12- month study, at an approximate cost of $14 000. The Budget Director has identified savings from the City Clerk's general election budget that could be made available for this purpose. December 2, 2009 Mr. David Harris, Director City of Dubuque Housing and Community Development 350 W. 6th St.; Suite 312 Dubuque, IA 52001. David: ~ 1 ~ RESEARCH Please find enclosed the final report for the Section 8 Arrest Analysis study of City data .completed this fall and previously shared and discussed: As a result of some questions and requests for additional analysis, we have augmented it with some additional tables, graphs and conclusions. While the study was commissioned long before the current Crime Task Force was created, vve have gleaned about as much from this data set as is possible given the time and budget constraints. Key takeaways from -this study inc-ude: • Non-Dubuque and No Permanent Address arrestees made up over a fifth (20%) of all arrestees • Non-renters (those riot identifiable as Giving in either Section 8 ornon-Section 8 addresses) accounted for more (42;7%) of al arrestees than Renters {37%) + Similarly, non-renters (those not identifiable as living in either Section 8 ornon-Section 8 addresses) accounted for more (53%) of Dubuquer arrestees than renters (47%) • Non-.Section 8 renters made up more arrestees during the study period (19:6°/v) than .Section 8 renters (17.4%) • While Section 8 addresses (averaging 1,092) make up about 14% of all rental addresses, they accounted for just under half (47.1%- of all rental arrestee addresses during the study period. Recommendations for future data collection and research include: • Processing the data would be enhanced if the addresses were broken into separate components/fields e.g. rather than 1 column foraddress • It would be preferable to look at the data over a longer period of time, say a full year • It would likely be beneficial to delve deeper into all arrests (vs. arrestees) to determine recidivism in the sub-samples (Section 8 and others) • It could be illuminating to look at Section 8 participant turnover over a period of time (1 year or longer) If possible, it could be helpful to analyze the type of crimes being committed compared to those that are used to disqualify renters from Section 8 participation. In accordance with these recommendations, and at the request of the City Manager, we are providing a proposal fora more involved, in-depth study. This incorporates a longer time frame with more data, as well as $ome deeper, and different, analysis. Details of these are included within the proposal. Thank you for the opportunity to work with you on this project. We will be meeting with the Crime Task Force research sub-committee next week. We look forward to working with the City again soon. Sincerely yours, ~~/L---- ;, -- Bob Woodward President/ CEO 1450 Alta Vista Street 563-588-7090 Dubuque, Iowa 52003 www.AltaVistaResearch.com RESEARCH A Report on Rental Housing and Arrest Activity in the City of Dubuque Presented to: City of Dubuque, Iowa November 2009 Final © 2009, Alta Vista Research, Inc. Objectives of the Research Project The overall goal of this research was to conduct an analysis of secondary data sources to investigate variations in arrest activity associated with two types of rental properties in the City of Dubuque: Section 8 and non-Section 8 rental units. More specifically, the purpose of the study was to determine if there was a high concentration of individuals arrested for crimes who resided in publicly subsidized (Section 8) housing in the City of Dubuque. Methodology Secondary data was analyzed from a number of databases to address the research question. Information on all rental property addresses as ofJuly 2009 and all renters living in Section 8 housing for the months of June & July 2009 was provided by the Dubuque Housing and Community Development Department. Data on arrests made from June 1 to July 31, 2009 were provided by the City of Dubuque information Services. Arrest data forthese 2 summer months were chosen because the incidence of crime is generally at its highest during the summer months of any particular year. All data was analyzed using Microsoft Excel software. To facilitate the analyses, all name data was broken down into separate fields (e.g., last name, first name, middle initial) and all address data was broken down into fields for street number, street name, city, state, zip code, etc. This allowed the arrest data to be more easily "matched" with the housing data. The results for this report are based upon three separate "matching" analyses conducted with data contained in the various databases: 1) Comparison of arrested persons' names with names of Section 8 June & July 2009 renters; 2) Comparison of home addresses listed for~each arrest record with address of Section 8 rental properties; 3) Comparison of home addresses listed for each arrest record with addresses of all rental properties; The matching of names and addresses of those arrested with names (when possible) and addresses in rental housing databases provides information concerning the relationship between arrest activity and the type of rental housing occupied by those arrested. Page 1 ©2009 Alta Vista Research, Inc. RE6EAR CH The Data The following are Excel sheet tabs created during the analyses of the housing and arrest databases. 1. Arrests_2009_07 -contains 1,085 (6/1/2009 - 7/31/2009) arrest records including the person's name, home address, and location of arrest. Of the 1,085 arrest records, 695(64%) were for unique individuals, 390 (36%) were records for multiple arrest citations, for an average of 1.6 arrest citations per person during the June-July 2009 time period. Without adjusting forthe number of individual persons, the average age at time of arrest was 27.7 years, and the number of records from the list for various age brackets is as follows: AGE Records % of total Records 0-<10 6 1% 10-<20 288 27 20-<30 440 41% 30-<40 152 14% 40-<50 136 13 50-<60 53 5% 60-<70 8 1% 70+ 2 > 1% NOTE: refer to Age Analysis sheet in Tables for Study.xlsx file for details. Percentages may not add up to 100% due to rounding. 2. Individuals -removes multiple arrest records so we can identify individuals. After removing these records, there are 695 records remaining. 3. Remove NPA - Contains a list of all individuals AFTER those with NPA - No permanent Address - were removed from the list (leaving 672 of the original 695 individuals, 96.7%) 4. Remove Non DBQ- Contains a list of all individuals AFTER those with NPA- No Permanent Address -were removed, as well as those whose City of residence is not Dubuque. This would leave all persons listing Dubuque as their City of residence (553 of the original 695 individuals, 79.6%) 5. Remove Non rental - Contains a list of all individuals AFTER those with NPA, not Dubuque, and not matching the addresses in either the Section 8 July list or the all Rental list. This would leave all those people arrested that live in rental units in Dubuque. (257 of the original 695 individuals, 37.0%) Page 2 ©2009 Alta Vista Research, Inc. RE6EAR CFI 6. Section 8_2009_07 -Contains 1,261 records of Section 8 housing as of July 2009. When cross- referenced with the All Rental Property list (Rentals formatted) 76% of the addresses matched.l 7. Section 8_2009_06 -Contains 1,248 records of Sec 8 housing as of June 2009. the same issue arises in that not all the Section 8 addresses are found in the Rental list.l 8. Rentals formatted - Contains a list of all rental records (2,554 records representing 7,900+ units) formatted so the street addresses can be "matched" to the arrest records. 9. NPA - Contains a list of all individuals with NPA- No Permanent Address - (23 of the original 695 individuals, 3.3%) 10. Non DBQ- Contains a list of all individuals not having a City of Residence listed as Dubuque, e.g. Asbury, East Dubuque, etc. (119 of the original 695 individuals, 17.1%) 11. Non rental - Contains a list of all individuals with a City of Residence listed as Dubuque but the address did NOT match either the Section 8 or all Rental addresses (296 of the original 695 individuals, 42.6%) 1 Note: some of the discrepancy may be due to coding errors of the data, but some clarification may be needed in further studies. It may be that all Section 8 housing is not necessarily part of the Rental formatted list. Page 3 ©2009 Alta Vista Research, Inc. The Analyses 1. Arrested Persons' Names With Section 8 Names The first analysis involved a match of the arrested person's name with those names contained in the Section 8 lists. Based simply upon name, 53/1085 (4.9%) of the records matched. This represented 37 unique individuals whose names were listed in the July 2009 Section 8 list. Note: checking the July Section 8 list, some anomies did occur. Seven individuals' names "matched" the Section 8 list, but issues arose, e.g., one person appeared to be the son of a person on the Section 8 list, another had a different home address on the Arrest list, yet the name and DOB (date of birth) matched. These seven only represent 0.6% of the entire number of records, but they should be noted. Checking the names of those arrested against the June 2009 Section 8 records provided similar results -approximately 5% of the records (54/1085) matched those names listed in the Section 8 I ist. 2. Dubuque Arrestees' Home Addresses with Section 8 Addresses The second analysis involved a match of the home address listed on each arrest record with the address on the Section 8 lists. A "match" was determined if the person's address matched the street address provided in the Section 8 list. A total of 121 records were matched (21.9% of the 553 Dubuque individuals arrested). 3. Dubuque Arrestees' Home Addresses with All Rental Properties A third analysis involved a match of the home address listed on each arrest record with addresses of the total rental property list, (Rentals formatted). This resulted in 136 records matching (24.6% of the 553 Dubuque individuals arrested). Page 4 ©2009 Alta Vista Research, Inc. RE GEAR CH Consolidated Overview The following table shows the number of arrests, number of arrestees, address by resident/non- residentand breakdown by category of homeowner, renter and further into Section 8 and non-Section 8 renters. The graphs on the following pages help illustrate key relationships and percentages. Dubuque Section 8 Arrest Analysis Overview I Total arrests ; ; 1085 Less Duplicates i -390] 35.9% I Total arrestees ~ ~ 6951 I ~ j _ .. less No Permanent Address ~ -23j ! 3.3% Iof all arrestees (695) ~ less non-Dubuque addresses -119; 17.1%~ of all arrestees (695) ! Arrestees with addresses _. .. i _ 672 ~ F, Dubuque address Arrestees ~ ~ 553 79.6% of all arrestees (695) _ not identifiable as renters ~ 296; 53.5% of all Dubuquers arre sted renters (per DBQ Housing list match) ~ 257E ~ 46.5% __ _ of all Dubuquers arre _... sted ', ..,_ * Section 8 renters j ~ 121; 47.1% of all renters __ _ _ _ - 17.4% of all arre stees (695) *Non-Section 8 renters ! ~ 136 52.9% f of all renters j I 19.6% of all arrestees (695)( j Total l ~ ~, ~ #j Arrests] % ~ ! ~~ Sectlon 8 name match -arrests ; 53 1085; 4.9% Sectlon 8 name match - arrestee (unique individual) _ __ _ .. j 37~ i i 1 j 695; 5.3% ~ )) Ij 1 '~ t i I ! l Total ~ ( ( }} I. I AI I ~ ~ ', Dubuquers ( Total ~ ', #~ Arrests % Arrestees % ~ ~i Section 8address match 121 I ~ _'_ 553 ~ 9% 21. 17.4% 695 4 - - Renter addresses match (non-Sect. 8) j 136] I 553 i 24.6% ( _ _ 695 19.6% _ ! __ ! i i ~ Ttl DBQ ~ ~ ~ f _ t I ~Sec8Address; Renters; % ~ ~ ~ ', Section 8 Addresses (avg of 1,087 & 1,097) ~ 1,092 ~ I 7,900 ! 13.8% II of all rende!rs ~'~ f #~ ! Tot. DBQ Pop.; I % ( I _ Section 8 Population (2.13 per address) ; 2,326 ~ 60,000 i 3.9% ~ of population ; ', Page 5 ©2009 Alta Vista Research, Inc. RE6EARCH Interpretation The key statistics to focus on in this report are both the numbers and percentages of addresses that match. As indicated in the Documentation tab of the complete arrest analysis Spreadsheet file, of the 1,085 arrest records, 695 involved unique individuals arrested for crimes. Of the 695 individuals arrested in June/July 2009,121(17.4%) had a home address that matched that of a Section 8 housing unit. Another 136 individuals (19.6%) indicated their home address was one that matched with the non-Section 8 rental units. Upon further analysis of the 695 arrestees, 553 (79.6%) were Dubuque residents. The remaining 142 (20.4%)arrestees were non-Dubuque residents or had no permanent address listed. Of the 553 arrestees, 257 (46.5%) lived in rental units and 296 (53.5%) lived in non-rental units. Of the 257 Dubuque arrestees living in rental units, 121(47.1%) lived in Section 8 housing and 136 (52.9%) lived in non-Section 8 rental units. It should be noted that there were some problems matching the arrest records with the rental records. Some inconsistencies occurred when individuals would move during the June/July period, or address information was missing/incomplete. A list of some of these individuals is included in the final tab of the spreadsheet file (e.g., 24 of the 695 individuals, 3.5%) Conclusions Keeping in mind the limitations and inconsistencies ofthe databases, several conclusions appearto be warranted from the data: 1. The pattern of large numbers of arrests in the 10 < 20 and 20 < 30 age categories is consistent with other data concerning the relationship between age and crime. 2. It is reasonable to conclude that approximately 17% of those arrested in the City of Dubuque during the months of June and July 2009 live in Section 8 housing. 3. It is reasonable to conclude that approximately 20% of those arrested in the City of Dubuque during the months of June and July 2009 live in non-Section 8 housing. 4. The remaining 63% of those arrested in the City of Dubuque during the months of June and July 2009 either live in non-rental housing, outside of Dubuque, or had no permanent address. 5. It is reasonable to conclude that a significant amount of arrestees (about 20%) came from individuals not identifiable as living in Dubuque (No Permanent address and non-Dubuque address). 6. It is reasonable to conclude that more Dubuquer arrestees came from non-rental housing 53.5% (as identified from Dubuque Housing Department rental lists) than renters (46.5%). 7. It is reasonable to conclude that a disproportionately larger percentage of arrests came from Section 8 housing addresses (121 is 47.1% of all 257 renter arrestees) than the number of addresses in the Section 8 program (averaged at 1,092 over two months, or 13.8%) compared to the total number of rental addresses (about 7,900). Page 10 ©2009 Alta Vista Research, Inc. Recommendations Concerning Future Data Collection and Analysis This report is a first cut at analyzing some complex data. A few suggestions are being offered for future study: • The Data 1. Processing the data would be enhanced if the addresses were broken into separate components/fields e.g. rather than 1 column for address, break this apart by Example: Street Number 2218 Fraction 1/2 Direction W Street Third Type Ave SFX NE City Dyersville State Zip by: The same goes for the names. Rather than 1 column for name, break this apart First Anthony Middle Lawrence Middle 2 Steven Last Smith SFX Jr Since the data comes from different sources, some coordination may be needed to ensure its integrity. 2. Follow up on the contents of the total rental property database compared to the Section 8 database to ensure that these lists match address information more closely. Page 11 ©2009 Alta Vista Research, Inc. RESEARCH, The Analysis Consider using some comparison data to put the numbers into better context, for example, if 17% of the arrest records match Section 8 housing does Section 8 housing account for 17% of all rental housing options? If so, these numbers are in line. If not, further study may be needed. A similar comparison could be done for other housing types. There is a considerable amount of data in the arrest list that could be analyzed, for example, types of arrests, etc. Computing the age counts was a fairly easy process and may provide some additional insight if this is not already being done elsewhere. If one of the goals is to provide better information to the public, consider the use of software to help "map" this data. There are several commercial sites that provide such services and may be worth researching to gauge their effectiveness. Page 12 ©2009 Alta Vista Research, Inc. RESEARCH RESEARCH Proposal In-depth Arrest Activity Analysis for Various Address Statuses in the City of Dubuque, Iowa Presented to: The City of Dubuque, Iowa December 2009 Overview and Research Goals The overall goal of this research is to conduct afollow-up study to the recently completed arrest analysis conducted for the City of Dubuque during the summer and early fall of 2009. This more in-depth analysis of secondary data sources will help further aid in the understanding of the comparative arrest frequency and type between Section 8 housing locations and non-Section 8 housing. In addition, it will delve further into both Section 8 and non-Section 8 arrests and help to further identify additional factors relating to street crime and arrests during the broader period of time. Alta Vista Research will conduct analyses utilizing secondary data sources from the Dubuque Housing Department and the City of Dubuque Police Department to compare arrest frequency for both Section 8 (assisted) and non-Section 8 housing. Specifically: I~ Arrest data will be provided in 2 database formats: a) arrest data according to offender address information (as in the database format provided by Stacey Moore on June 8, 2009) and b) arrest data according to crime location (as in the database format provided by Stacey Moore on May 27, 2009) for the months of June & July 2009. An additional database of non-Dubuque residents will also be included and AVR staff will add non-DBQ residents to these arrest databases. +~ ® Section 8 rental housing data will be provided in the most recent database format for the months of June & July 2009. ® Pre-billing rental housing data will be provided for the months of June & July 2009 and the Section 8 addresses will be deleted from this database. We understand from Tammy that we are not able to secure the Pre-billing list data for the previously considered analysis time frame of June & July 2008. Section 8 data will be matched directly with both name and address information from the arrest database (direct matches) and probable matches will be determined on the basis of names matching from the 2 databases but the addresses are slightly different OR the addresses match from the two databases but the name of the tenant doesn't Page 1 ©Copyright 2009 match the name ofthe arrestee (who could be living in the rental unit but not have his/her name listed as the renter). ® Non-section 8 address data will be matched directly using only address information from the arrest database (direct matches) since there are no names of renters contained in the non-section 8 database. Probable matches will also be determined as accurately as possible using the available address information in the 2 databases. ® Lists of frequencies and percentages for various arrest categories will be tabulated for both section 8 and non- section 8 rental properties. The number of arrest categories may be collapsed for greater meaningfulness if desired. ® All analyses and calculations will be performed on a "best effort" basis given the idiosyncrasies of the respective databases being worked with. . ® Atwelve-month period (as recent and complete as possible) with all rental addresses, section 8 addresses and arrest databases will be provided to Alta Vista Research by the City of Dubuque Housing Department and the City of Dubuque Police Department. Page 2 ©Copyright 2009 Additional Analysis Alta Vista Research will conduct not only a wider analysis of the date (using a longer time frame than done previously), we will also dive deeper into the data, looking for significant trends and patterns that pertain to crime in general, both Section 8 and non-Section 8 in nature. Additional in-depth analysis from that done previously (to the extent possible, given limitations of the data and practicality) will include, but not be limited to: ® Longer period of time (12 months) will be analyzed than the previous study (2 months) ® Section 8 turnover will be examined during the period (and perhaps over a longer period if possible) ~] Section 8 will be further analyzed as asub-sample in an attempt to determine the level of recidivism among that group (and compared to others) as well as whether a further sub-group is primarily responsible for a disproportionate amount of crimes ® The types of crimes being committed will be analyzed to the extent possible and compared to the types of crimes for which the Dubuque Housing Department is removing participants from the Section 8 program. Page 3 ©Copyright 2009 RESEaACH~ Proposed Study Design We propose a study of secondary research data, providing important insights into arrests at both Section Eight and non- Section Eight locations in the city. We will work with City of Dubuque Housing and Police Department staff to identify and obtain secondary data for analysis, analysis comparisons and reporting. Deliverables and Reporting During the project definition meeting we will work with the City to confirm the preferred method(s) of reporting the final results. We are able to provide in a variety of formats, including: ® PowerPoint ® MS Word If desired, raw data files and other research data can be provide in electronic format for further internal analysis and presentation. We will provide the report to the team at the City of Dubuque. All deliverables will be provided in electronic format for ease of sharing with interested stakeholders and printing on a full or partial basis. This will also facilitate information sharing with internal or external stakeholders and partners. One hard copy of the study results will also be provided, if desired. Page 4 ©Copyright 2009 RE SEnR CH• Program Timeline We propose the following timeline as part of the research agreement: December 2009 Secondary data identification and /January 2010 provision to Alta Vista Research January /February Secondary data analysis 2010 March • Report provided to City of Dubuque With the assistance and cooperation of the City, we will devote sufficient resources to the project to meet this timeline in order to provide complete,~accurate, and timely results. Page 5 ©Copyright 2009 "ESEAA~"~ Study Contacts Due to their experience in market research and the social research field, the following Alta Vista Research contacts will be assigned to your study: Primary contact: Len Decker, Ph.D. Secondary contacts: Bob Woodward Confidentiality We treat all client information as confidential. This includes information provided by the client as well as the data, findings, conclusions and recommendations created through the research process. We are able to sign anon-disclosure agreement if required as part of the study. Terms 1. INSURANCE. Consultant shall at all times during the performance of this Agreement provide insurance as required by the attached Insurance Schedule with the exception of auto coverage (AVR does not own a car), excess liability, and professional liability (neither AVR staff have customarily carried nor has the College). 2. INDEMNIFICATION. To the fullest extent permitted by law, Consultant shall indemnify and hold harmless the City its officers, agents, and employees from and against all claims, damages, losses and expenses, including but not limited to attorneys' fees, arising out of or resulting .from performance of the Contract, provided that such claim, damages, loss or expense is attributable to bodily injury, sickness, disease or death, or injury to or destruction of property (other than the Project itself) including loss of use resulting therefrom, but only to the extent caused in whole or in part by negligent acts or omissions of the Consultant, Consultant's subcontractor, or anyone directly or indirectly employed by Consultant or Consultant subcontractor or anyone for whose acts Consultant or Consultant's subcontractor may be liable, regardless of whether or not such claim, damage, loss or expense is caused in part by a party indemnified hereunder. 3. TERMINATION. City may terminate this agreement, with or without cause, upon providing 14 days written notice to the Consultant. Page 6 ©Copyright 2009 Research Investment Options Because of the format of the data available from the City of Dubuque Police and Housing Departments, a considerable portion of this process is manual. Since a much larger sample is being analyzed, and as there are more variables (including additions and removal from the Section 8 program over that time period), the investment level is significantly more than that required for the previous study City of Dubuque Section 8 Arrest Analysis: Section 8 Arrest Data research, analysis and $14,000 reporting Includes the following components: ~ Study design and management ® Secondary research data procurement ® Data analysis ® One hard copy of report if desired ~ Client consultation during and after the study We will invoice one half (50%) at the time of the project definition meeting and the balance after the initial report is provided. These prices are good for 180 days. Page 7 ©Copyright 2009 RESEARCH. United States Government Accountability Office GAO Report to Congressional Requesters January 2007 pOVE RTY IN AMERICA Economic Research Shows Adverse Impacts on Health Status and Other Social Conditions as well as the Economic Growth Rate R* rt*~ k** *** **** **** Accountability * Integrity * Reliability GAO-07-344 - ~~ =~, GAO - = - POVERTY IN AMERICA - - --- ~-Accountability Integnry Reliability Hl ~11T 1`ltS = Economic Research Shows Adverse h~9hts of GAO.07 344 a report tothe = H, I mpacts on Health Status and Other g l ~ nt U d ~+ Social Conditions As Well As the Mea == - ns House of Represe a Ves - Economic Growth Rate Why,GAO=Did This Study What GAO Found In :2005, 37 milhonpeople, Economic research suggests that individuals living in poverty face an approximately-l3 percent of-the increased risk of adverse outcomes, such as poor health and criminal =total population; lived below-the activity, both of which may lead to reduced participation in the labor market. '-poverty line, as defut_ed by the -_ While the mechanisms by which poverty affects health are complex, some Census Bureau Poverty unposes -costs on the nation ui terms of both research suggests that adverse health outcomes can be due, in part, to programmatic outlays and °= limited access to health care as well as greater exposure to environmental = productivity losses-that can affect hazards and engaging in risky behaviors. For example, some research has =the economy as a whole To better ___ _ shown that increased availability of health insurance such as Medicaid for understand the potential range of =- low-income mothers led to a decrease in infant mortality. Additionally, 'effects=of poverty, GAO was =asked _' exposure to higher levels of alr pollution from living in urban areas close to to examine (1) what the econonuc highways can lead to acute health conditions. Data suggest that engaging in research=tells us about the risky behaviors, such as tobacco and alcohol use, a sedentary life-style, and a relationship between poverty and low consumption of nutritional foods, can account for some health adverse social=conditions, such as= disparities between lower and upper income groups. The economic research poor_health outcomes, crime, and we reviewed also points to links between poverty and crime. For example, labor force attachment, and (2) what links economic research has one study indicated that higher levels of unemployment are associated with found between poverty and higher levels of property crime. The relationship between poverty and -- economic growth. To answer these - adverse outcomes for individuals is complex, in part because most variables, =question_s, GAO reviewed the _ like health status, can be both a cause and a result of poverty. These adverse economic literature by acader ruc outcomes affect individuals in many ways, including limiting their _ ==experts,-think tanks,=and development of the skills, abilities, knowledge, and habits necessary to fully government agencies;==and reviewed.= participate in the labor force. additional literature by searching vanous databases for peer _ Research shows that poverty can negatively affect economic growth by reviewed economic journals, _= affecting the accumulation of human capital and rates of crime and social specialty journals, and books:-We - unrest. Economic theory has long suggested that human capital-that is, the =also provided our draft report =for - review by experts on flits topic education work e ~ xperience, training, and health of the workforce-is considered one of the fundamental drivers of economic growth. The conditions associated with poverty can work against this human capital _- _- = development by limiting individuals' ability to remain healthy and develop - skills, in turn decreasing the potential to contribute talents, ideas, and even labor to the economy. An educated labor force, for example, is better at learning, creating and implementing new technologies. Economic theory -_ suggests that when poverty affects a significant portion of the population, these effects can extend to the society at large and produce slower rates of = growth. Although historically research has focused mainly on the extent to which economic growth alleviates poverty, some recent empirical studies - = = have begun to demonstrate that higher rates of poverty are associated with _ = = lower rates of growth in the economy as a whole. For example, areas with _ _ - _ = higher poverty rates experience, on average, slower per capita income _ _ =- - = growth rates than low-poverty areas. www_gao gov/cgi-bm/ge[rp#?GAO-07-344. To view the full product, including the scope =and methodology, click on-the_link=above - - For more informaiion,=contact Sigurd _R Nilsen=at{202):512-_7.215 or at =_ __ nilsens®gao.gov -- _ - United States Government Accountability Office Contents Letter 1 Results in Brief 2 Background 3 Econonuc Research Links Poverty with Adverse Outcomes for Individuals Such as Poor Health and Crime 9 Economic Research Suggests a Negative Association between Poverty and Economic Growth 19 Concluding Observations 21 Reviewer Comments 22 Appendix I Bibliography 24 Appendix II Contacts and Acknowledgments 30 Table Table 1: Selected Examples of Federal Cash and Noncash Assistance to Low-Income Families and Individuals, Fiscal Year 2004 7 Figures Figure 1: Selected Health Indicators by Poverty Status 10 Figure 2: Percentage of Population with No Health Insurance (Private or Medicaid) by Poverty Status 11 Figure 3: No Visits to Any Health Provider in the Past 12 Months (Children under 18 Years of Age) by Level of Insurance 12 Figure 4: Percentage of Population Who Have a Sedentary Lifestyle, Are Overweight, or Are Obese, by Poverty Status 15 Page i GAO-07-344 Poverty in America Abbreviations CCDBG Child Care and Development Block Grant CRS Congressional Research Service EITC Earned Income Tax Credit GDP gross domestic product HHS Health and Human Services LIHEAP Low-Income Home Energy Assistance Program NAS National Academy of Sciences NBER National Bureau of Economic Research SCHIP State Children's Health Insurance Program SSBG Social Services Block Grant TANF Temporary Assistance for Needy Families WIC Special Supplemental Nutrition Program for Women, Infants and Children This is a work of the U.S. government and is not subject to copyright protection in the United States.. It may be reproduced and distributed in its entirety without further permission from GAO. However, because this work may contain copyrighted images or other material, permission from the copyright holder may be necessary if you wish to reproduce this material separately. Page ii GAO-07-344 Poverty in America . GAO Accountablliiy * Integrity * Reliability United States Government Accountability Office Washington, DC 20548 January 24, 2007 The Honorable Charles B. Rangel Chairman Committee on Ways and Means House of Representatives Dear Mr. Chairman: According to the Census Bureau, approximately 37 million people in the United States-nearly 13 percent of the total population-lived below the poverty line in 2005.' This percentage was significantly larger for particular population groups, specifically children, minorities, and those living in certain geographic areas such as inner cities. The federal government spends billions of dollars on programs to assist low-income individuals and families.2 These programs included Medicaid, food stamps, Temporary Assistance for Needy Families (TANF), and the Earned Income Tax Credit (EITC), to name some of the largest. While some have taken issue with Census' official poverty measure and proposed alternative measures, it is generally recognized that poverty imposes costs on the nation as a whole, not merely in terms of programmatic outlays but also through lost productivity that can affect the overall economy. A substantial body of economic research has looked at the effects of . poverty and you asked us to discuss (1) what the economic research tells us about the relationship between poverty and adverse social conditions, such as poor health outcomes, crime, and labor force attachment; and (2) what links economic research has found between poverty and economic growth. To answer these questions, we reviewed the economic literature by academic experts, think tanks, and government agencies, which we collected from searches of various databases, peer-reviewed economic journals, specialty journals, and books. We also provided our draft report ' In 2005 the poverty threshold for a family of four was $19,971. z Congressional Research Service, Cash and Noncash Benefits for Persons with Limited Income: Eligibility Rules, Recipient and Expenditure Data, FY2002-FY200~4 (Washington, D.C.: Mar. 27, 2006). Page 1 GAO-0?-344 Poverty in America to four external reviewers. They are recognized experts who have conducted research and published on the topic of poverty and economic growth and whose work has recommended a variety of approaches and strategies to policymakers. We limited the scope of our work by looking at recent studies published since 1996, excluding anything older, with exceptions made for work that was considered seminal. Thus, our results are not an exhaustive or historical treatment of the topic. Our review was primarily driven by the economic literature focused on the United States either exclusively or including other developed nations; studies from other disciplines were excluded unless they were captured in either the economic study under review or its bibliography. When we refer to poverty in the report, we are using an absolute measure, not a relative one. This means that, for the most part, the studies we reviewed typically used the official poverty line published by the Census Bureau as its benchmark. A few of the studies we reviewed used relative measures such as the poorest 10 percent of the population. Our work was conducted between October 2006 and January 2007 according to generally accepted government auditing standards. Because we did not evaluate the policies, operations, or programs of any federal agency to develop the information presented in this report, and because we are not making any recommendations, we did not seek agency comments. However, we met with agency officials from the Departments of Commerce, Health and Human Services, Justice, and Labor to obtain information on research they or others had conducted related to our work objectives. Results in Brief Economic research suggests that individuals living in poverty face an increased risk of adverse outcomes, such as poor health and criminal activity, both of which may lead to reduced participation in the labor market. While the mechanisms by which poverty affects health are complex, some research suggests that adverse health outcomes are due, in part, to limited access to health care as well as exposure to environmental hazards and engaging in risky behaviors. For example, some research has shown that increased availability of health insurance such as Medicaid for low-income mothers led to a decrease in infant mortality. Likewise, exposure to high levels of air pollution from living in urban areas close to highways can lead to acute health conditions. Data suggest that engaging in risky behaviors, such as tobacco and alcohol use, a comparatively sedentary life-style, and a low consumption of nutritional foods can account for some portion of the health disparities between lower and upper income groups. The economic research we reviewed also points to Page 2 GAO-07-344 Poverty in America links between poverty and crime. For example, one study indicated that higher levels of unemployment are associated with higher levels of property crime. The relationship between poverty and adverse outcomes for individuals is complex, in part because most variables, like health status, can be both a cause and a result of poverty. Regardless of whether poverty is a cause or an effect, the conditions associated with poverty can limit the ability of individuals to develop the skills, abilities, knowledge, and habits necessary to fully participate in the labor force. Research shows that poverty can negatively impact economic growth by affecting the accumulation of human capital and rates of crime and social unrest. Economic theory has long suggested that human capital-that is, 'the education, work experience, training, and health of the workforce-is considered one of the fundamental drivers of economic growth. The conditions associated with poverty can work against this human capital development by limiting individuals' ability to remain healthy and develop skills, in turn decreasing the potential to contribute talents, ideas, and even labor to the economy. An educated labor force, for example, is better at learning, creating, and implementing new technologies. Economic theory suggests that when poverty affects a significant portion of the population, these effects can extend to the society at large and produce slower rates of growth. Although historically research has focused mainly on the extent to which economic growth alleviates poverty, some recent empirical studies have begun to demonstrate that higher rates of poverty are associated with lower rates of growth in the economy as a whole. For example, areas with higher poverty rates experience, on average, slower per capita income growth rates than low-poverty areas. Background Economic growth is one of the indicators by which the well-being of the nation is typically measured, although recent discussions have focused on a broader set of indicators, such as poverty. Poverty in the United States is officially measured by the Census Bureau, which calculates the number of persons or households living below an established level of income deemed minimally adequate to support them. The federal government has a long- standing history of assisting individuals and families living in poverty by providing services and income transfers through numerous and various types of programs. Page 3 GAO-07-344 Poverty in America Measuring the Nation's Economic growth is typically defined as the increase in the value of goods Well-Being: ECOnOm1C and services produced by an economy; traditionally this growth has been Growth and Other measured by the percentage rate of increase in a country's gross domestic Indicators product, or GDP. The growth in GDP is a key measure by which policy- makers estimate how well the economy is doing. However, it provides little information about how well individuals and households are faring. Recently there has been a substantial amount of activity in the United States and elsewhere to develop a comprehensive set of key indicators for communities, states, and the nation that go beyond traditional economic measures.3 Many believe that such a system would better inform individuals, groups, and institutions on the nation as a whole.4 Poverty is one of these key indicators. Poverty, both narrowly and more broadly defined, is a characteristic of society that is frequently monitored and defined and measured in a number of ways.6 How Is Poverty Defined in The Census Bureau is responsible for establishing a poverty threshold the United States.`? amount each year; persons or families having income below this amount are, for statistical purposes, considered to be living in poverty.s The threshold reflects estimates of the amount of money individuals and families of various sizes need to purchase goods and services deemed minimally adequate based on 1960s living standards, and is adjusted each year using the consumer price index. The poverty rate is the percentage of individuals in total or as part of various subgroups in the United States who are living on income below the threshold amounts. Over the years, experts have debated whether or not the way in which the poverty threshold is calculated should be changed. Currently the calculation only accounts for pretax income and does not include noncash benefits and tax transfers, which, especially in recent years, have comprised larger portions of the assistance package to those who are low- a GAO, Informing Our Nation: Improving How to Understand and Assess the USA's Position and Progress, GAO-05-1 (Washington, D.C., November 2004), p.4. a GAO-05-01. e GAO-06-O1, p.34. s The U.S. Department of Health and Human Services (HHS) establishes poverty guidelines that are similar to the poverty thresholds but are used by HHS and other agencies for administering programs, such as determining program eligibility. Page 4 GAO-07-344 Poverty in America income.' For example, food stamps and the Earned Income Tax Credit could provide a combined amount of assistance worth an estimated $5,000 for working adults with children who earn approximately $12,000 a year.8 If noncash benefits were included in a calculation of the poverty threshold, the number and percentage of individuals at or below the poverty line could change. In 1995, a National Academy of Sciences (NAS) panel recommended that changes be made to the threshold to count noncash benefits, tax credits, and taxes; deduct certain expenses from income such as child care and transportation; and adjust income levels according to an area's cost of living.9 In response, the Census Bureau published an experimental poverty measure in 1999 using the NAS recommendations in addition to its traditional measure but, to date, Census has not changed the official measure.10 U.S. Poverty Rates In 2005, close to 13 percent of the total U.S. population-about 37 million people-were counted as living below the poverty line, a number that essentially remained unchanged from 2004. Poverty rates differ, however, by age, gender, race, and ethnicity and other factors. For example, • Children: In 2005, 12.3 million children, or 17.1 percent of children under the age of 18, were counted as living in poverty. Children of color were at least three times more likely to be in poverty than those who were white: 3.7 million, or 34.2 percent of, children who were African- American and 4 million, or 27.7 percent of, children who were Hispanic Congressional Research Service, Poverty in the United States: 2005 (Washington, D.C.: Aug. 31, 2006). s Danzinger, Sheldon, "Fighting Poverty Revisited: What Did Researchers Know 40 Years Ago? What Do We know Today?" Dec. 4, 2006. s For a summary of the NAS panel recommendations see Congressional Research Service Report 95-539, Redefining Poverty in the United States: National Academy of Science Panel Recommendations, by Thomas R. Gabe (archived) (Washington, D.C.: 1995). 10 U.S. Census Bureau, Poverty among Working Families: Findings from Experimental Poverty Measures (Washington, D.C.: Sept. 2000). Page 6 GAO-07-344 Poverty in America lived below the poverty line compared to 4 million, or 9.5 percent of, children who were white.ll • Racial and ethnic minorities: African-Americans and Hispanics have significantly higher rates of poverty than whites. In 2005, 24.9 percent of African-Americans (9.2 million) and 22 percent of Hispanics (9.4 million) lived in poverty, compared to 8.3 percent for whites (16.2 million). • Elderly: The elderly have lower rates of poverty than other groups. For example, 10.1 percent of adults (3.6 million) aged 65 or older lived in poverty. Poverty rates also differ depending on geographical location and for urban and nonurban areas. Poverty rates for urban areas were double those in suburbs, 17 percent compared to 9.3 percent.12 Poverty rates in the South were the highest at 14 percent; the West had a rate of 12.6 percent, followed by the Midwest with 11.4 percent and the Northeast at 11.3 percent.13 The Role of the Federal The U.S. government has a long history of efforts to improve the Government conditions of those living with severely limited resources and income. Presidents, Congress, and other policymakers have actively sought to help citizens who were poor, beginning as early as the 1850s through the more recent efforts established through welfare reform initiatives enacted in 1996. Over the years, the policy approaches used to help low-income individuals and families have varied. For example, in the1960s federal programs u Beginning in March 2003, the Census Bureau allowed survey respondents to identify themselves as belonging to one or more racial groups. In prior years, respondents could select only one racial category. Consequently, poverty statistics for different racial groups for 2002 and after are not directly comparable to earlier years' data. The term "blacks and white" refers to persons who identified with only one single racial group. The term "Hispanic" refers to individuals' ethnic, as opposed to racial, identification. Hispanics may be of any race. iz Congressional Research Service, Poverty in the United States: 2005 (Washington, D.C.: Aug. 31, 2006). is Congressional Research Service, Poverty in the United States: 2005 (Washington, D.C.: Aug. 31, 2006). Page 6 GAO-07-344 Poverty in America focused on increasing the education and training of those living in poverty. In the 1970s, policy reflected a more income-oriented approach with the introduction of several comprehensive federal assistance plans. More recently, welfare reform efforts have emphasized the role of individual responsibility and behaviors in areas such as family formation and work to assist people in becoming self-sufficient. Although alleviating poverty and the conditions associated with it has long been a federal priority, approaches to developing effective interventions have sometimes been controversial, as evidenced by the diversity of federal programs in existence and the ways in which they have evolved over time. Currently, the federal government, often in partnership with the states, has created an array of programs to assist low-income individuals and families. According to a recent study by the Congressional Research Service (CRS), the federal government spent over $400 billion on 84 programs in 2004 that provided cash and noncash benefits to individuals and families with limited income. These programs cover a broad array of services: Examples include income supports or transfers such as the Earned Income Tax Credit and TANF; work supports such as subsidized child care and job training; health supports and insurance through programs like the State Children's Health Insurance Program (SCHIP) and Medicaid; and other social services such as food, housing, and utility assistance. Table 1 provides a list of examples of selected programs. Table 1: Selected Examples of Federal Cash and Noncash Assistance to Low-Income Families and Individuals, Fiscal Year 2004 Federal Purpose Program cash outlay Program description Cash aid Temporary Assistance for Needy $10.4 billions Permits a state to give ongoing basic cash aid to Families (TANF) families that include a minors or a pregnant woman. Work and other requirements must be met. Earned Income Tax Credit (EITC) $37.9 billion° Provides a refundable credit to workers with and without children. Food and nutrition Food Stamp Program $27.2 billion` Provides certain allotments to individuals for purchasing of food items, based upon the individual's level of eligibility/need. Special Supplemental Nutrition $4.5 million Provides benefits for low-income mothers, infants, and Program for Women, Infants and children considered to be at "nutritional risk." Children (WIC) Medical Medicaid $176 billion Provides payments to health care providers in full or via co-pay for eligible low-income families and individuals and for long-term care to eligible individuals who are aged or disabled. Page 7 GAO-07-344 Poverty in America Federal Purpose Program cash outlay Program description State Children's Health Insurance $4.ti billion" Provides federal matching funds for states and Program (SCRIP) territories to provide health insurance to targeted low-. income children. Educational Federal Pell Grant Program $12 billion Provides assistance to undergraduate students who meet a certain needs test and are enrolled in an eligible institution of postsecondary education. Head Start $6.8 billions Provides comprehensive services to targeted low- income children. Services include educational, medical, dental, nutritional, and social services. Housing Section 8Low-Income Housing $22.4 billion Provides rental assistance through vouchers or rental Assistance subsidies to eligible low-income families or single persons. Services Child Care and Development Block $6.9 billion Provides funding to low-income parents for child care. Grant (CCDBG) Social Services Block Grant (SSBG) $1.7 billion Provides funding to assist states in providing social (Title XX) services to eligible low-income individuals or families. Jobs Job Corps $1.5 billion Provides no-cost training and education to low-income individuals ages 16-24 while providing a monthly allowance payment. Energy Low-Income Home Energy $1.9 billion Provides assistance to low-income home owners and Assistance Program (LIHEAP) renters to help meet energy needs such as heating and cooling. Source: For a full list offederal programs, see Cash and Noncash Benefits for Persons with Limited Income: Eligibility Rules, Recipient and Expenditure Data, FY2002-FY2004; Washington D.C. 2006. FFederal outlay figures in table 1 are from fiscal year 2004, as reflected in the CRS report from which they are taken, sourced above. Some exceptions apply and are noted. The TANF figure, $10.4 billion, is the estimated total of federal and state expenditures combined for on1yTANF cash aid in fiscal year 2004. This figure does not include other combined federal and state funding for the following: TANF child care, estimated at $2.5 billion in fiscal year 2004; TANF work programs and activities, estimated at $2.2 billion in fiscal year 2004; and TANF services estimated at $6.3 billion in fiscal year 2004. "EITC federal outlay total of $37.9 billion is for fiscal year 2003 as reported in GAO, Means Tested Programs: Information on Program Access Can Be an Important Management Tool, GAO-05-221 (Washington, D.C. March 2005). `For more on the Food Stamp Program, see GAO-05-839R, (Washington, D.C.: June 30, 2005). "For more on SCRIP federal outlay figure of $4.6 billion, see GAO-05-839R. `Head Start federal outlay total of $6.8 billion is for fiscal year 2005. Page 8 GAO-07-344 Poverty in America Economic Research Economic research suggests that individuals living in poverty face an increased risk for adverse outcomes, such as poor health, criminal activity, Links Poverty with and low participation in the workforce. The adverse outcomes that are Adverse Outcomes for associated with poverty tend to limit the development of stalls and abilities individuals need to contribute productively to the economy Individuals Such as through work, and this in turn, results in low incomes. The relationship Poor Health and between poverty and outcomes for individuals is complex, in part because most variables, like health status, can be both a cause and a result of Crime poverty. The direction of the causality can have important policy implications. To the extent that poor health causes poverty, and not the other way around, then alleviating poverty may not improve health. Individuals Living in Health outcomes are worse for individuals with low incomes than for their Poverty Experience Higher more affluent counterparts. Lower-income individuals experience higher Rates of Adverse Health rates of chronic illness, disease, and disabilities, and also die younger than Outcomes in Part because those who have higher incomes.' As reported by the National Center on , of Limited Access to Health Statistics, individuals living in poverty are more likely than their affluent counterparts to experience fair or poor health, or suffer from Health Care, conditions that limit their everyday activities (fig.l). They also report Environmental Hazards, higher rates of chronic conditions such as hypertension, high blood and Risky Behaviors pressure, and elevated serum cholesterol, which can be predictors of more acute conditions in the future. Life expectancies for individuals in poor families as compared to nonpoor families also differ significantly. One study showed that individuals with low incomes had life expectancies 25 percent lower than those with higher incomes.15 Other research suggests that an individual's household wealth predicts the amount of functionality of that individual in retirement.ls i9 Centers for Disease Control and Prevention, Health, United States, 2006; 1998 (Hyattsville, Maryland). ie Deaton, Angus, "Policy Implications of The Gradient of Health and Wealth," Health Affairs, Vol. 21., No.2, March 2002. is Smith, James, and Raynard Kington, "Demographic and Economic Correlates of Health in Old Age." Demography, Vol. 34, No. 1, 1997. Page 9 GAO-07-344 Poverty in America Figure 1: Selected Health Indicators by Poverty Status Percent 25 23 20 15 10 Below 100 percentof the poverty line 100percent -Less than 200 percent of the poverty line 200percent or more above the Poverty line Sourcei National Center for Health Stalislics, Health. United States, 2006 with Charlhook do Trends in the Health olAmericans (Hyattsvlle,Maryland:2006)-. Research suggests that part of the reason that those in poverty have poor health outcomes is that they have less access to health insurance and thus less access to health care, particularly preventive care, than others who are nonpoor. Very low-income individuals were three times as likely not to have health insurance than those with higher incomes, which may lead to reduced access to and utilization of health care (fig. 2). Page 10 GAO-07-344 Poverty in America Self-reported Percentof persons ~ifficulfy seeing Serious fair or poor with any activity (even with psychological hesith limitation correction) distress Figure 2: Percentage of Population with No Health Insurance (Private or Medicaid) by Poverty Status Percent 35 30 25 20 15 10 Below 100 percent of the poverty line 100percent-i49 percent of the poverty line 150 percent-199 percent of thepoverty line ® 200 percent or more above the poverty line Source; Natohal Center for Health Statistics, Health, l/nited Slefes, 2006 with Chart6ook on Trends in the Health of Americans (Hyattsdill®, Maryland: 2006). Data show that those who are poor with no health insurance access the health system less often than those who are either insured or wealthier when measured by one indicator of health care access: visits to the doctor. For example, data from the National Center on Health Statistics show that children in families with income below the poverty line who were continuously without health insurance were three to four times more likely to have not visited a doctor in the last 12 months than children in similar economic circumstances who were insured (fig. 3). Research also suggests that a link between income and health exists independent of health insurance coverage. Figure 3 also shows that while children who are uninsured but in wealthier families visit the doctor fewer times than those who are insured, they still go more often than children who are uninsured but living in poverty. Page 11 GAO-07-344 Poverty in America All persons .Children under 65 (under 18) Figure 3: No Visits to Any Health Provider in the Past 12 Months (Children under 18 Years of Age) by Level of Insurance Percent 50 47.4 Below 100 percent of poveriy level 100 percent-less 200 percent or than 200 percent more All children Irisuied continuously all 12 months lJriinsured for any period up to 12 moritFis S Uriinsured more than 12 months Source: National Center for Health Statistics, Health, United States, 2006 with Chartbook on Trends in the Health olAmericans (Hyatt$yille, MarylanB:2006), Some research examining government health insurance suggests that increased health insurance availability improves health outcomes. Economists have studied the expansion of Medicaid, which provides health insurance to those with low income. They found that Medicaid's expansion of coverage, which occurred between 1979 and 1992, increased the availability of insurance and improved children's health outcomes. For example, one study found that a 30 percentage point increase in eligibility for mothers aged 15-44 translated into a decrease in infant mortality of 8.5 percent.l' Another study looked at the impact of health insurance coverage through Medicare and its effects on the health of the elderly and also 1' Culxie, Janet, and Jonathan Gruber, "Saving Babies: The Efficacy and Cost of Recent Changes in the Medicaid Eligibility of Pregnant Women," The Journal of Political Economy, Vol. 104, No. 6, December 1996. Page 12 GAO-07-344 Poverty in America found a statistically significant though modest impact.18 There is some evidence that variations in health insurance coverage do not explain all the differences in health outcomes. A study done in Canada found improvements in children's health with increases in income, even though Canada offers universal health insurance coverage for hospital services, indicating that health insurance is only part of the story.19 Although there is a connection among poverty, having health insurance, and health outcomes, having health insurance is often associated with other attributes of an individual, thus making it difficult to isolate the direct effect of health insurance alone. Most individuals in the United States are either self-insured or insured through their employer. If those who are uninsured have lower levels of education, as do individuals with low income, differences in health between the insured and uninsured might be due to level or quality of education, and' not necessarily insurance.20 Another reason that individuals living in poverty may have more negative health outcomes is because they live and work in areas that expose them to environmental hazards such as pollution or substandard housing. Some researchers have found that because poorer neighborhoods maybe located closer to industrial areas or highways than more affluent neighborhoods, there tend to be higher levels of pollution in lower-income 18 Card, David, et. al., "The Impact of Nearly Universal Insurance Coverage on Health Care Utilization and Health: Evidence from Medicare" National Bureau of Economic Research, Working Paper 10365. NBER, March 2004. 19 Currie, Janet, and Mark Stabile, "Socioeconomic Status and Child Health: Why Is the Relationship Stronger for Older Children." Ame1^ican Economic Review, Vol. 93, No. 5, December 2003. 20Additionally, differences in individual health outcomes can sometimes be explained by other factors that maybe associated with poverty, but are difficult to detect, such as risk aversion. Page 13 GAO-07-344 Poverty in America neighborhoods.21 The Institute of Medicine concluded that minority and low-income communities had disproportionately higher exposure to environmental hazards than the general population, and because of their impoverished conditions were less able to effectively change these conditions.82 The link between poverty and health outcomes may also be explained by lifestyle issues associated with poverty. Sedentary life-style: the use of alcohol and drugs; as well as lower consumption of fiber, fresh fruits, and vegetables are some of the behaviors that have been associated with lower socioeconomic status. Cigarette smoking is also more common among adults who live below the poverty line than among those above it, about 30 percent compared to 21 percent.'' Similarly, problems with being overweight and obese are common among those with low family incomes, although most prevalent in women: Women with incomes below 130 percent of the poverty line were 50 percent more likely to be obese than those with incomes above this amount.26 Figure 4 shows that people living zi While much of the specific biological mechanism by which air pollution might affect health is still unknown, some recent research by economists has noted a link between pollution and health, especially for infants. Currie and Neidell (2005) find that the decrease in the level of carbon monoxide in California in the 1990s had a significant effect on reducing infant mortality. See Currie, Janet, and Matthew Neidell, "Air Pollution and Infant Health: What Can We Learn From California's Recent Experience?" Quarterly Journal of Economics, 120 (3), 2005. Similarly, Chay and Greenstone (2003) find that the reduction in total suspended particulates due to the 1970 Clean Air Act had a significant impact on infant mortality. See Chay, Kenneth, and Michael Greenstone, "Air Quality, Infant Mortality, and the Clean Air Act of 1970." National Bureau of Economic Research, Working Paper No. 10053. NBER, 2003. zz Institute of Medicine, Committee on Environmental Justice, "Toward Environmental Justice: Research, Education, and Health Policy Needs", (Washington, D.C.: 1999), p.6. Adler, Nancy E., and Katherine Newman, "Socioeconomic Disparities in Health: Pathways and Policies." Health Affairs, Vol. 21 No. 2, 2002. See also Deaton, Angus. "Policy Implications of the Gradient of Health and Wealth." Health Affairs, Vol. 21, No.2: 2002. ~ Centers for Disease Control and Prevention, Tobacco Use among Adults-United States, 2005. Morbidity and Mortality Weekly Report , 2006; 55(42): 1145-1148. Some research suggests that part of the reason why smoking rates are higher may be peer effects, especially among youth smokers. See DeCicca, Phillip, Donald Kenkel, and Alan Mathios, "Racial Difference in the Determinants of Smoking Onset." Journal of Risk and Uncertainty. Boston: 2000. Vol. 21, Iss. 2/3; p311.Other studies have shown that educational attainment can affect smoking use as well. See DeCicca, Philip, Donald Kenkel, and Alan Mathios,"Putting Out the Fires: Will Higher Taxes Reduce the Onset of Youth Smoking?" Journal of Political Economy. Chicago 2002.Vo1.110, Iss.l; p. 144. as U.S. Public Health Service, Surgeon General's Call To Action to Prevent and Decrease Overweight and Obesity 2001, Washington, DC, pp. 13-14. Page 14 GAO-07-344 Poverty in America in poverty are less likely to engage in regular, leisure-time physical activity than others and are somewhat more likely to be obese, and children in poverty are somewhat more likely to be overweight than children living above the poverty line. In addition, there is also evidence to suggest a link among poverty, stress, and adverse health outcomes, such as compromised immune systems.zs Figure 4: Percentage of Population Who Have a Sedentary Lifestyle, Are Overweight, or Are Obese, by Poverty Status Percent 70 60 50 40 30 20 10 Below 100 percent of the poverty line 100 percent-less than 200 percent of The poverty line 200 percerit or more atiove the poverty line Source: National CenteFloT Neellh Statistics,. Healfh, Uriifed States, 2006 with Chetlbook on Trends !n the Health o! Amerlcaris (Hyallsvifle, Maryland; 20D6). zs While access to care, behavior, and environmental factors are some of the most commonly offered reasons for the relationship between poverty and health, recent literature.has suggested other alternative theories, of which there is less of a research tradition. These include the effect of short exposures to health shocks as a result of poverty, such as poor nutrition or increased adrenalin due to higher levels of stress, and psycho-social stress that leads to problems with the immune system. See Smith, James P., "Healthy Bodies and Thick Wallets: The Dual Relation between Health and Economic Status." The Journal of Economic Perspectives, Vol. 13, No. 2, 1999. Page 16 GAO-07-344 Poverty in America Overweight No leisure time Obesity among Overweight among among aduks physical activity, adults chltdreh ages 6-11 aauics While evidence shows how poverty could result in poor health, the opposite could also be true. For example, a health condition could result, over time, in restricting an individual's employment, resulting in lower income. Additionally, the relationship between poverty and health outcomes could also vary by demographic group. ~' Failing health, for example, can be more directly associated with household income for middle-aged and older individuals than with children, since adults are typically the ones who work. Economic Research Shows Just as research has established a link between poverty and adverse health an Association Between outcomes, evidence suggests a link between poverty and crime. Economic Poverty and Crime theory predicts that low wages or unemployment makes crime more attractive, even with the risks of arrest and incarceration, because of lower returns to an individual through legal activities.' While more mixed, empirical research provides support for this. For example, one study shows that higher levels of unemployment are associated with higher levels of property crime, but is less conclusive in predicting violent crime.29 Another study has shown that both wages and unemployment affect crime, but that wages play a larger role,so Research has found that peer influence and neighborhood effects may also lead to increased criminal behavior by residents. Having many peers that engage in negative behavior may reduce social stigma surrounding that behavior.31 In addition, increased crime in an area may decrease the Z'It is not clear whether these adverse outcomes occur with greater frequency among all individuals living in households below the poverty line or only among those experiencing extreme poverty; those who experience poverty during critical development stages, such as infancy or early childhood; or those who experience long bouts of poverty. ~ Criminal behavior has been measured by reports to the police in an area, self-reported crime by individuals in surveys or arrests, as well as other measures. See also Freeman, Richard, "Why Do So Many Young American Men Commit Crimes and What Might We Do About It?"Journal of Economic Perspectives, Vol. 10, No. 1: Winter 2006. zs Raphael, Steven, and Rudolf Winter-Ebner, "Identifying the Effect of Unemployment on Crime." Journal of Law and Economics, Vol. XLIV. 2001. ao Gould, Eric D., Bruce A. Weinberg, and David B. Mustard, "Crime Rates and Local Labor Market Opportunities in the United States: 1979-1997. Reaiew of Economics and Statistics, 84 (1): 2002. ai Katz, Lawrence F., Jeffrey R. HIing, and Jeffrey B. Liebman, "Moving to Opportunity in Boston: Early Results of a Randomized Mobility Experiment." Quarterly Journal of Economics, May 2001. Page 16 GAO-07-344 Poverty in America chances that any particular criminal activity will result in an arrest. Other research suggests that the neighborhood itself, independent of the characteristics of the individuals who live in it, affects criminal behavior. 3Z One study found that arrest rates were lower among young people from low-income families who were given a voucher to live in aloes-poverty neighborhood, as opposed to their peers who stayed in high-poverty neighborhoods. The most notable decrease was in arrests for violent crimes; the results for property crimes, however, were mixed, with arrest rates increasing for males and decreasing for females. Adverse Outcomes, SUCK Regardless of whether poverty is a cause or an effect, the conditions as Poor Health and Low associated with poverty limit the ability of low-income individuals to Educational Attainment, develop the skills, abilities, knowledge, and habits necessary to fully Lead to Reduced participate in the labor force, in turn, leads to lower incomes. According to 2000 Census data, people aged 20-64 with income above the poverty line in Participation in the Labor 1999 were almost twice as likely to be employed as compared to those Market with incomes below it.3`' Some of the reasons for these outcomes include educational attainment and health status. az However, a challenge that researchers face is that, almost by definition, many individuals share the same characteristics in aneighborhood. Therefore, it is difficult to determine whether it is the characteristic of the individual or the neighborhood that is the source of the behavior. ~ Http://www.huduser.org/publications/fairhsg/MTODemData.html and http://www.hud.gov/prodesc/mto.cfm .Some economists have used data from the Moving- to-Opportunity experiment as a way to attribute causality. Moving-to-Opportunity is a research demonstration in which a number of families, chosen randomly, within five public housing authorities were given housing vouchers to be used in low-poverty neighborhoods. Another group of families acted as the control, and were not given the vouchers. Using these data, some economists have compared the outcomes for children whose families received the vouchers and those that did not. To some extent, the results have confirmed that neighborhood, independent of individual characteristics, affects criminal behavior, but the results have also been mixed. Using data from the randomized housing experiment, Ludwig, Duncan, and Hirschfeld (2001) found that the housing vouchers reduced violent arrests by teens, but may have increased the number of property arrests. Kling, Ludwig, and Katz (2005) also used the Moving-to-Opportunity data, but looked for differential effects by gender. The authors found that for females, there were large reductions in the amount of arrests for both property and violent crime, when compared to those for the control group. For males, there were reductions in violent arrests, but proportionally smaller than the drops for females. In addition, there were significant increases in the rate of property arrests. ~' U.S. Census Bureau, Employment Status: 2000, Census 2000 Brief (Washington, D.C., August 2003), p.4 Page 17 GAO-07-344 Poverty in America Poverty is associated with lower educational quality and attainment, both of which can affect labor market outcomes. Research has consistently demonstrated that the quality and level of education attained bylower- income children is substantially below those for children from middle- or upper-income families. Moreover, high school dropout rates in 2004 were four times higher for students from low-income families than those in high-income families.35 Those with less than a high school degree have unemployment rates almost three times greater than those with a college degree, 7.6 percent compared to 2.6 percent in 2005. And the percentage of low-income students who attend college immediately after high school is significantly lower than for their wealthier counterparts: 49 percent compared to 78 percent.36 A significant body of economic research directly links adverse health outcomes, which are also associated with low incomes, with the quality and quantity of labor that the individual is able to offer to the workforce. Many studies that have examined the relationship among individual adult health and wages, labor force participation, and job choice have documented positive empirical relationships among health and wages, earnings, and hours of work.37 Although there is no consensus about the exact magnitude of the effects, the empirical literature suggests that poor health reduces the capacity to work and has substantive effects on wages, labor force participation, and job choice, meaning that poor health is associated with low income. ss National Center for Education Statistics, U.S. Department of Education, Dropout Rates in the United States: 2004, (Washington, D.C. November 2006), p. 4. 3~Choy, Susan, "College Access and Affordability," Education Statistics Quarterly, Vol. 1, Issue 2, Topic: Postsecondary Education. a7 Several methodological challenges exist in this literature: For example, many of these findings could reflect the effect of income on health rather than vice versa. In addition, results are highly sensitive to the measures of health that are used, with self-reported health status subject to several forms of bias, some of which could overstate the relationship between income and health, and others of which could understate the relationship. For example, individuals who have reduced their hours of work or left the labor force may be more likely to report poor health, in order to justify their reduced labor supply or because govemment programs provide incentives to report disability; this would lead to an upward bias in the estimated relationship between income and health. On the other hand, it is possible that higher-income individuals, who on average have greater health care utilization, may be more likely to be diagnosed with certain conditions simply because of their greater access to health care. This would lead to a downward bias in the estimated relationship between income and health. Page 18 GAO-07-344 Poverty in America Research also demonstrates that poor childhood health has substantial effects on children's future outcomes as adults. Some research, for example, shows that low birth weight is correlated with a low health status later in life. Research also suggests that poor childhood health is associated with reduced educational attainment and reduced cognitive development. Reduced educational attainment may in turn have a causal effect not only on future wages as discussed above but also on adult health if the more educated are better able to process health information or make more informed choices about their health care or if education makes people more "future oriented" by helping them think about the consequences of their choices. In addition, some research shows that poor childhood health is predictive of poor adult health and poor adult economic status in middle age, even after controlling for educational attainment. Economic Research The economic literature suggests that poverty not only affects individuals but can also create larger challenges for economic growth. Traditionally, Suggests a Negative research has focused on the importance of economic growth for Association between generating rising living standards and alleviating poverty, but more recently it has examined the reverse, the impact of poverty on economic Poverty and growth. In the United States, poverty can impact economic growth by Economic Growth affecting the accumulation of human capital and rates of crime and social unrest. While the empirical research is limited, it points to the negative association between poverty and economic growth consistent with the theoretical literature's conclusion that higher rates of poverty can result in lower rates of growth. Research has shown that accumulation of human capital is one of the fundamental drivers of economic growth. ~ Human capital consists of the 38Economic models that consider human capital to be a fundamental driver of economic growth are commonly referred to as endogenous growth models, although the more traditional neoclassical model has also been augmented to include the role of human capital. Endogenous growth theory posits technological growth as occurring through dynamics inside the model. Although there are several competing models, crucial importance in each is given to the production of new technologies and human capital. While the major point these models emphasize is that human capital is the driving force behind growth, the actual modeling of the relationship is still a controversial issue in the economic literature. Some growth models assert that the driving force behind economic growth is the rate of accumulation of human capital, in which the rate of economic growth is proportional to the rate of accumulation of human capital. Another approach considers that high levels of human capital, as embodied in the level of the educational attainment of the world'orce, increases the capacity of individuals to innovate (discover new technology) or to adopt new technology. Page 19 GAO-07-344 Poverty in America skills, abilities, talents, and knowledge of individuals as used in employment. The accumulation of human capital is generally held to be a function of the education level, work experience, training, and healthiness of the workforce.39 Therefore, schooling at the secondary and higher levels is a key component for building an educated labor force that is better at learning, creating, and implementing new technologies. Health is also an important component of human capital, as it can enhance workers' productivity by increasing their physical capacities, such as strength and endurance, as well as mental capacities, such as cognitive functioning and reasoning ability. Improved health increases workforce productivity by reducing incapacity, disability, and the number of days lost to sick leave, and increasing the opportunities to accumulate work experience. Further, good health helps improve education by increasing levels of schooling and scholastic performance. The accumulation of human capital can be diminished when significant portions of the population have experienced long periods of poverty, or were living in poverty at a critical developmental juncture. For example, recent research has found that the distinct slowdown in some measures of human capital development ~is most heavily concentrated among youth from impoverished backgrounds. When individuals who have experienced poverty enter the workforce, their contributions may be restricted or minimal, while others may not enter the workforce in a significant way. Not only is the productive capability of some citizens lost, but their purchasing power and savings, which could be channeled into productive investments, is forgone as well. In addition to the effects of poverty on human capital, some economic literature suggests that poverty can affect economic growth to the extent that it is associated with crime, violence, and social unrest. According to some theories, when citizens engage in unproductive criminal activities they deter others from making productive investments or their actions force others to divert resources toward defensive activities and expenditures. The increased risk due to insecurity can unfavorably affect 39In general, economists regard expenditures on education, training, medical care, and so on as investments inhuman capital. Collectively, theoretical growth models suggest economic growth results from improvements in human capital as embodied in the skills and experience of the labor force; from expansion of physical capital in the form of plant and equipment; and from progress in science, engineering, and management that generates technological advance. While many variables have been empirically tested, only a few have been accepted as being statistically significant in explaining growth. The role of human capital is now almost universally regarded as being indispensable in this respect. Page 20 GAO-07-344 Poverty in America investment decisions-and hence economic growth-in areas afflicted by concentrated poverty. Although such theories link poverty to human capital deficiencies and criminal activity, the magnitude of their impact on economic growth for an economy such as the United States is unclear at this time.40 In addition, people living in impoverished conditions generate budgetary costs for the federal government, which spends billions of dollars on programs to assist low-income individuals and families. Alleviating these conditions would allow the federal government to redirect these resources toward other purposes. While economic theory provides a guide to understanding how poverty might compromise economic growth, empirical researchers have not as extensively studied poverty as a determinant of growth in the United States. Empirical evidence on the United States and other rich nations is quite limited, but some recent studies support a negative association between poverty and economic growth. For example, some research finds that economic growth is slower in U.S. metropolitan areas characterized by higher rates of poverty than those with lower rates of poverty.41 Another study, using data from 21 wealthy countries, has found a similar negative relationship between poverty and economic growth.42 Concluding Maintaining and enhancing economic growth is a national priority that touches on all aspects of federal decision making. As the nation moves Observations forward in thinking about how to address the major challenges it will face 40 Human capital deficits experienced by some impoverished individuals cannot always be attributed to experience of poverty. In some cases, low education attainment and poor health, although associated with poverty, may actually be caused by some other factor that is also responsible for poverty. In this case, poverty would be a symptom rather than a cause (i.e., poor health, poor choices, or addiction may erode human capital potential and cause poverty). Similarly, most poor people do not commit crimes, and those that do may be motivated by forces unrelated to their incomes. ai The relationship is not always statistically significant in all regions. Statistical insignificance in some cases might be more attributable to data issues such as sample size or multicollinearityyather than an indication of nonrelationshipbetveen poverty and income growth in various regions. See S. Dev Bhatta, "Are Inequality and Poverty Harmful for Economic Growth," Journal of Urban Affair s, 22 (3-4): 2001. This study provides, arguably, a better comparison group than cross-country studies, since metropolitan statistical areas in the United States are at relatively similar stages of development. ~'ZVoitchovslzy, S., "Does the Profile of Income Inequality Matter for Economic Growth? Distinguishing between the Effects of Inequality in Different Parts of the Income Distribution." Journal of Economic growth, Vo1.10.: 2005. Page 21 GAO-07-344 Poverty in America in the twenty-first century, the impact of specific policies on economic growth will factor into decisions on topics as far ranging as taxes, support for scientific and technical innovation, retirement and disability, health care, education and employment. To the extent that empirical research can shed light on the factors that affect economic growth, this information can guide policymakers in allocating resources, setting priorities, and planning strategically for our nation's future. Economists have long recognized the strong association between poverty and a range of adverse outcomes for individuals, and empirical research, while limited, has also begun to help us better understand the impact of poverty on a nation's economic growth. The interrelationships between poverty and various adverse social outcomes are complex, and our understanding of these relationships can lead to vastly different conclusions regarding appropriate interventions to address each specific outcome. Ftiirthermore, any such interventions could take years, or even a generation, to yield significant and lasting results, as the greatest impacts are likely to be seen among children. Nevertheless, whatever the underlying causes of poverty maybe, economic research suggests that improvements in the health, neighborhoods, education, and skills of those living in poverty could have impacts far beyond individuals and families, potentially improving the economic well-being of the nation as a whole. Reviewer Comments We provided the draft report to four outside reviewers with expertise in the areas of poverty and economic growth. The reviewers generally acknowledged that our report covers a substantial body of recent economic research on the topic and did not dispute the validity of the specific studies included in our review. However, they expressed some disagreement over our presentation of this research. Some reviewers felt that the evidence directly linking poverty to adverse outcomes is more robust than implied by our summary and directed us to additional research that bolsters the link between poverty and poor health and crime. We did not incorporate this additional research into our findings, but we reviewed it and found it consistent with the evidence already incorporated in our summary. Other reviewers felt that our report implied a stronger relationship between poverty and adverse outcomes than is supported by the research. They felt that the report did not provide adequate information on the causes of poverty and external factors that could be responsible for both poverty and adverse outcomes. In response to these comments, we made several revisions to the text to ensure that Page 22 GAO-07-344 Poverty in America the information we presented was balanced. The reviewers also provided technical comments that we incorporated as appropriate. Copies of this report are being sent to the Departments of Commerce, Health and Human Services, Justice, and Labor; appropriate congressional committees; and other interested parties. Copies will be made available to others upon request. The report is also available at no charge on the GAO Web site at http://www.gao.gov. If you or your staff have any questions about matters discussed in this report, please contact me at (202) 512-7215 or at nilsens@gao.gov. Other contact and staff aclrnowledgments are listed in appendix II. Sincerely, Sigurd R. Nilsen Director, Education, Worl~orce, and Income Security Issues Page 23 GAO-07-344 Poverty in America Appendix I: Bibliography Adler, Nancy E., and Katherine Newman. "Socioeconomic Disparities in Health: Pathways and Policies." Health Affairs, Vol. 21 No. 2, 2002. Aghion, Phillipe, et al. "Inequality and Economic Growth: The Perspective of the New Growth Theories." Journal of Economic Literature, Vol. XXXVII: 1999. Barro, Robert. "Inequality and growth in a panel of countries." Journal of Economic Growth, 5 (1): 2000. Barsky, Robert B., et al. "Preference Parameters and Behavioral Heterogenity: An Experimental Approach in the Health and Retirement Study." Review of Economic Statistics, 1997. Burtless, G., and C. Jenks. "American Inequality and Its Consequences." In (eds), H. Aaron et al, Agenda for the Nation. Washington, DC: Brookings Institution Press, 2003. Card, David, and Carlos Dobkin, Nicole Maestas. "The Impact of Nearly Universal Insurance Coverage on Health Care Utilization and Health: Evidence from Medicare." National Bureau of Economic Research, Working Paper No. 10365. Cambridge, Massachusetts: National Bureau of Economic Research: 2004. Case, Anne C., and Angus Deaton. "Broken Down by Work and Sex: How our Health Declines." National Bureau of Economic Research, Working Paper No. 9821. Cambridge, Massachusetts: National Bureau of Economic Research: 2003. Case, Anne, Angela Fertig, and Christina Paxson. "The Lasting Impact Of Childhood Health And Circumstance." Journal of Health Economics, 24 (2): 2005. Case, Anne, Darren Lubotsky, and Christina Paxson. "Economic Status and Health in Childhood: The Origins of the Gradient." American Economic Review, Vol. 92, No. 5., Dec. 2002. Chay, Kenneth, and Michael Greenstone. "Air Quality, Infant Mortality, and the Clean Air Act of 1970." National Bureau of Economic Research, Working Paper No. 10053. Cambridge, Massachusetts: National Bureau of Economic Research: 2003. Page 24 GAO-07-344 Poverty in America Appendix I: Bibliography Chui, W. Henry. "Income Inequality, Human Capital Accumulation and Economic Performance." Economic Journal, 108. 1998. Currie, Janet, and Jonathan Gruber. "Saving Babies: The Efficiency and Cost of Recent Changes in the Medicaid Eligibility of Pregnant Women." Journal of Political Economy, Vol. 104, No. 6, 1996. Currie, Janet, and Rosemary Hyson. "Is the Impact of Health Shocks Cushioned by Socioecoomic Status? The Case of Low Birthweight" American Economic Review Papers and Proceedings of the One Hundred Eleventh Annual Meeting of the American Economic Association, 89 (2): 1999. Currie, Janet, and Brigitte Madrian. "Health, Health Insurance and the Labor Market." In (eds), O. Ashenfelter and D. Card, Handbook of Labor Economics, Vol. 3. Elsevier Science. 1999. Currie, Janet and Mark Stabile. "Socioeconomic Status and Child Health: Why is the Relationship Stronger for Older Children?" American Economic Review, Vol. 93, No 5., Dec. 2003. Currie, Janet, and Matthew Neidell. "Air Pollution and Infant Health: What Can We Learn Flom California's Recent Experience?" Quarterly Journal of Economics, 120 (3), 2005. Cutler, David, Angus Deaton, and Adriana Lleras-Muney. "The Determinants of Mortality." Journal of Economic Perspectives, Vol. 20, No. 3, 2006. DeCicca, Phillip, Donald Kenkel, Alan Mathios. "Racial Difference in the Determinants of Smoking Onset." Journal of Risk and Uncertainty. 2000. Vol. 21, Iss. 2/3; p311. . "Putting Out The Fires: Will Higher Taxes Reduce the Onset of Youth Smoking?" Journal of Political Economy. 2002.Vo1.110, Iss.l; p. 144. Deaton, Angus. "Policy Implications of the Gradient of Health and Wealth." Health Affairs, Vol. 21, No.2, 2002. Delong, J. et al. "Sustaining U.S. Economic Growth." In H. Aaron et al. (eds.), Agenda for the Nation. Washington, DC: Brookings Institution Press, 2003. Page 26 GAO-07-344 Poverty in America Appendix I: Bibliography Dev Bhatta, Saurav. "Are Inequality and Poverty Harmful for Economic Growth: Evidence from the Metropolitan Areas of the United States." Journal of Urban Affairs, 23 (3&4): 2001. Fallah, B., and M. Partridge. "The Elusive Inequality-Economic Growth Relationship: Are There Differences between Cities and the Countryside?" University of Saskatchewan Working Paper, February 2006. Federal Reserve Bank of New York, "Unequal Incomes, Unequal Outcomes? Economic Inequality and Measures of Well-Being: Proceedings of a Conference Sponsored by the Federal Reserve Bank of New York," Economic Policy Review, Vol. 5 (3), September 1999. http://www. ny.frb. org/research/epr/1999n3.htm1. Forbes, K. "A Reassessment of the Relationship between Inequality and Growth." The American Economic Review, 90 (4): 2000. Freeman, Richard B. "Why Do So Many Young American Men Commit Crimes and What Might We Do About It?" Journal of Economic Perspectives, Vol. 10, No. 1, 1996. Gould, Eric D., Bruce A. Weinberg, and David B. Mustard. "Crime Rates and Local Labor Market Opportunities in the United States: 1979-1997." The Review of Economics and Statistics, 84 (1): 2002. Grogger, Jeff. "Market Wages and Youth Crime." Journal of Labor Economics, Vol. 16, No. 4. Chicago: 1998. Heckman, J., and A. Krueger. Inequality in America: What Role for Human Capital Policies. Cambridge, Massachusetts: The MIT Press, 2003. Ho, P. "Income Inequality and Economic Growth." Kylos, 53 (3): 2003. Holzer, Harry, et al. "The Economic Costs of Poverty in the United States." Unpublished working paper, 2006. Hsing, Yu. "Economic Growth And Income Inequality: The Case Of The US." International Journal of Social Economics, 32 (7): 2005. Katz, Lawrence F., Jeffrey R. Kling, and Jeffrey B. Liebman. "Moving to Opportunity in Boston: Early Results of a Randomized Mobility Experiment." The Quarterly Journal of Economics, May 2001. Page 26 GAO-07-344 Poverty in America Appendix I: Bibliography Kling, Jeffrey R., Jens Ludwig, and Lawrence F. Katz. "Neighborhood Effects on Crime for Female and Male Youth: Evidence from a Randomized Housing Voucher Experiment." Quarterly Journal of Economics, Feb. 2005. Lochner, Lance, and Enrico Moretti. "The Effect of Education on Crime: Evidence from Prison Inmates, Arrests and Self-Reports." American Economic Review, 2004. Ludwig, Jens, and Greg J. Duncan, Paul Hirschfield. "Urban Poverty and Juvenile Crime: Evidence from a Randomized Housing-Mobility Experiment." Quarterly Journal of Economics, May 2001. McGarry, Kathleen. "Health and Retirement: Do Changes in Health Affect Retirement Expectations?" Journal of Human Resources, Vol. XXXIX, 2004. Mo, P. "Income Inequality and Economic Growth." Kyklos, 53 (3): 2000. Newberger, R., and T. Riggs, "The Impact of Poverty on Location of Financial Establishments: Evidence from Across-Country Data." Profitwise News and Views, Federal Reserve Bank of Chicago, Apri12006. Panizza, Ugo. "Income Inequality and Economic Growth: Evidence from American Data." Journal of Economic Growth, 7 (1): 2002. Partridge, Mark. "Is Inequality Harmful for Growth? Comment." The American Economic Review, 87 (5): 1997. Persson, T., and G. Tabellini. "Is Inequality Harmful for Growth?" The American Economic Review, 84 (3): 1994. Rank, Mark. One Nation Underprivileged: Why American Poverty Affects Us All. Oxford: Oxford University Press, 2004. Raphael, Steven, and Rudolf Winter-Ebner. "Identifying the Effect of Unemployment on Crime." Journal of Law and Economics, Vol. XLIV. 2001. Sallis, J.F., et al. "The Association of School Environments with Youth Physical Activity." Amerlcan Journal of Public Health, Vol. 91, No. 4, 2001. Page 27 GAO-07-344 Poverty in America Appendix I: Bibliography Sandy, Carola. "Essays on the Macroeconomic Impact of Poverty." Columbia University Libraries, http://digitalcommons.libraries. Columbia. edu/dissertations/AAI9970273, 2000. Sherman, Arloc. Wasting America's Future: The Children's Defense Fund Report On The Costs Of Child Poverty. Boston, Massachusetts: Beacon Press Books, 1994. Siegel, Michele J. "Measuring the Effect of Husband's Health on Wife's Labor Supply." Health Economics, 15 (6): 2006. Smith, James P. "Healthy Bodies and-Thick Wallets: The Dual Relation between Health and Economic Status." Journal of Economic Perspectives, Vol. 13, No. 2, 1999. . "The Impact of SES on Health over the Life-Course." Rand Working Paper Series. Rand Labor and Population: 2005. Smith, James, and Raynard Kington. "Demographic and Economic Correlates of Health in Old Age." Demography, Vol. 34, No. 1, 1997. Teles, Vladimir. "The Role of Human Capital in Economic Growth." Applied Economic Letters, 12: 2005. U.S. Census Bureau. Income, Poverty, and Health Insurance Coverage in the United States: 2005. Washington, D.C.: 2006 U.S. Department of Health and Human Services, Centers for Disease Control and Prevention. Health, United States, 2006. Washington, D.C.: 2006. . Health, United States, 1998. Washington, D.C.: 1998. U.S. Department of Housing and Urban Development. Moving to Opportunity Demonstration Data. Washington, D.C.: May, 2004. . Moving to Opportunity for Fair Housing. Washington, D.C.: Dec. 2000. http://www.hud.gov/progdesc/mto.cfm. Page 28 GAO-07-344 Poverty in America Appendix I: Bibliography Voitchovsky, S. "Does the Profile of Income Inequality Matter for Economic Growth? Distinguishing Between the Effects of Inequality in Different Parts of the Income Distribution." Journal of Economic Growth, Vol. 10 (3): 2005. Page 29 GAO-07-344 Poverty in America Appendix II: Contacts and Acknowledgments GAO Contact Sigurd Nilsen, (202) 512-7215 or nilsens@gao.gov Acknowledgments Kathy Larin, Assistant Director, and Janet Marcia, Analyst-in-Charge, managed this assignment. Lawrance Evans, Ben Bolitzer ,Ken Bombara, Amanda Seese, and Rhiannon Patterson made significant contributions throughout the assignment. Charles Willson, Susannah Compton, and Patrick DiBattista helped develop the report's message. In addition, Doug Besharov, Dr. Maria Cancian, Dr. Sheldon Danziger, and Dr. Lawrence Mead reviewed and provided comments on the report. (130619) page 30 ty in America GAO-07-344 Pover GAO's M1SS1On The Government Accountability Office, the audit, evaluation and investigative arm of Congress, exists to support Congress in meeting its constitutional responsibilities and to help improve the performance and accountability of the federal government for the American people. GAO examines the use of public funds; evaluates federal programs and policies; and provides analyses, recommendations, and other assistance to help Congress make informed oversight, policy, and funding decisions. GAO's commitment to good government is reflected in its core values of accountability, integrity, and reliability. Obtaining Copies of GAO Reports and The fastest and easiest way to obtain copies of GAO documents at no cost is through GAO's Web site (www.gao.gov). Each weekday, GAO posts newly released reports, testimony, and correspondence on its Web site. To Testimony have GAO e-mail you a list of newly posted products every afternoon, go to www.gao.gov and select "Subscribe to Updates." Order by Mail or Phone The first copy of each printed report is free. Additional copies are $2 each. A check or money order should be made out to the Superintendent of Documents. GAO also accepts VISA and Mastercard. Orders for 100 or more copies mailed to a single address are discounted 25 percent. Orders should be sent to: U.S. Government Accountability Office 441 G Street NW, Room LM Washington, D.C. 20548 To order by Phone: Voice: (202) 512-6000 TDD: (202) 512-2537 Fax: (202) 512-6061 To Report Fraud, Contact: Waste, and Abuse In . Web site: www.gao.gov/fraudnet/fraudnet.htm E-mail: fraudnet@gao.gov Federal Programs Automated answering system: (800) 424-5454 or (202) 512-7470 Congressional Gloria Jarmon, Managing Director, JarmonG@gao.gov (202) 512-4400 U.S. Government Accountability Office, 441 G Street NW, Room 7125 Relations Washington, D.C. 20548 Public Affairs Paul Anderson, Managing Director, AndersonPl@gao.gov (202) 512-4800 U.S. Government Accountability Office, 441 G Street NW, Room 7149 Washington, D.C. 20548 PRINTED ON ~~ RECYCLED PAPER