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Denver Divided: Sprawl, Race, and Poverty

in Greater Denver

By David Rusk

Introduction (re-draft 9-04-03)

By almost any standard, Denver is one of America’s premier

metropolitan regions. It boasts a spectacular natural setting, an invigorating, four-season climate, a dynamic economy, a wealth of high-quality educational and cultural institutions, and, with five major league sports teams, a wide choice of spectator sports as well as participant sports. With its high quality of life, it is easy to understand why so many Denverites have a strong commitment to the region and why it is so widely admired.

Every region has its unique history and distinctive character, but what makes a region different are typically its positive attributes. The problems regions face, by contrast, are distressingly common – sprawl, racial segregation, and concentrated poverty.

Denver Divided is an examination of sprawl, racial segregation, and concentrated poverty in the Denver region. It has been commissioned by the School of Social Work and the School of Education of the University of Denver as part of “Bridges to the Future,” a joint community service program with Colorado State University.

This is a view of the Denver region as seen through my eyes. My perspectives are derived from my own values and experiences as a civil rights and anti-poverty worker, federal Labor Department official, New Mexico legislator, mayor of Albuquerque, and, for the past twelve years, author, speaker, and consultant on urban policy. In this latter role, I have analyzed five decades of census reports for 331 metropolitan regions, for their 541 central cities, and for over 400 “urbanized” areas. I have spoken and consulted in over 100 cities, and prepared major reports on a half dozen communities, including Baltimore, New Orleans, and now Denver.

Denver Divided is, in effect, my “take” on the Denver region. It does not represent the official views of the University of Denver. However,

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university officials do feel that presenting this information would be a valuable contribution to community debate over the future of the region.

I am not an expert on the Denver region. (Having lived and been an elected official in Albuquerque, New Mexico, though, does give me a certain affinity for physical, social, and political conditions in the Mountain West.) What I do offer as an expert is a comparative context in which to analyze certain challenges the Denver region faces.

Following an executive summary, Denver Divided is organized as eight modules that serve as a study guide for a series of citizen study groups organized by DU for the fall of 2003. DU faculty will serve as study group discussion leaders. Each module will have a summary paragraph, followed by 10-12 pages of analysis and statistical tables, and conclude with annotated suggestions for further readings.

Modules 1 (“Sprawl … You Know It When You See It”) and 2 (“Today’s Winners Become Tomorrow’s Losers”) discuss the region’s uneven development patterns and their consequences for the region’s counties and municipalities. Why are some communities seen as successful and others are not? How does that pattern change over time? These two modules will be the topic of the first study group session.

The next three modules deal with the social consequences of the region’s uneven housing patterns and will be the topic of the second study group session. Module 3 (“Divided by Race”) traces residential segregation of African Americans (declining slowly) and of Hispanics (rising with rapid immigration). Module 4 (“Divided by Income”) traces trends in economic segregation. Finally, module 5 (“Housing Policy Is School Policy”) links housing trends to school enrollment trends … and their implications for academic performance.

The third study group session will focus on potential solutions for these problems. The three modules will present policies which have worked well for other regions confronted with the similar issues of sprawl, racial segregation, and concentrated poverty. Module 6 (“Portland’s Great Wall – It Works!) summarizes a model anti-sprawl policy. Module 7 (“Restoring the Common School”) looks at several school districts that have adopted pupil assignment policies to achieve greater economic integration. Finally, Module 8 (“Mixing Up the Neighborhood”) explores inclusionary zoning

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and what widespread adoption of mixed-income housing policies would mean for greater economic integration in the region’s public schools.

Throughout the modules, shorter, boxed sections will be inserted at appropriate points. Generally, the boxes will convey specific examples of activities and initiatives in the Denver region itself that are relevant to the topic being discussed.

I offer some concluding comments. This section, however, is merely a temporary place holder. After completion of the study groups, a revised concluding chapter will convey the findings and recommendations of the participants themselves.

A brief word about what constitutes “the Denver region” for my study. For Census 2000, the U.S. Bureau of the Census officially defined the Denver-Boulder-Greeley Consolidated Metropolitan Statistical Area (CMSA). This almost 2.6 million-person super-region had three major sub-components (Primary Metropolitan Statistical Areas, or PMSAs): the Denver PMSA (Adams, Arapahoe, Denver, Douglas, and Jefferson counties); the Boulder-Longmont PMSA (Boulder County), which has long been considered part of the Denver area but achieved semi-autonomous status after the 1980 census; and the Greeley PMSA (Weld County), which was only joined to the Denver CMSA after the 1990 census.

In my analysis I have focused solely on the five-county Denver PMSA for four reasons. First, it conforms more closely to the Denver-Aurora urbanized area, which is the focus of Module 1. (Boulder, Longmont, and Greeley each have been designated as their own free-standing urbanized areas.) Second, all racial, ethnic, and economic segregation indices used in Modules 3, 4, and 5 were calculated on a PMSA basis. Third, the Denver PMSA constitutes almost 82 percent of the population of the super-region. And fourth, as outliers, both the Boulder-Longmont and Greeley PMSAs have somewhat different social and economic profiles from the metropolitan core and its immediate suburbs.

All data presented (with the exception of school enrollment data) come from Census 2000. Population and housing counts date from April 1, 2000; all income and poverty data apply to 1999 (the peak year of the 1990s economic boom). Some may argue that the information is already out of date. The latest Census Bureau estimates, for example, are that the Denver PMSA’s population has already increased 3.7 percent to 2,187,464 by July

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1, 2002. (Almost half that increase occurred in Douglas County, whose population was estimated to have grown by 20 percent in just two years.) These are, of course, just estimates. Whereas gross population estimates may be reasonably reliable for larger jurisdictions, any characterization of a population’s racial and ethnic background would be a guess. Efforts to update income levels and poverty statistics would be wild guesses. (Suffice it to say, we can have confidence that by mid-2003, in the midst of a three-year economic slump, the Denver region’s economic profile would have deteriorated from Census 2000’s portrayal.) In my experience, using not-so-old US census data (that provides the world’s most detailed snapshot of a society’s characteristics) is preferable to using “updated” data. Where current data (such as school enrollment) are available from other sources, I have used the most currently available.

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Denver Divided: Sprawl, Race, and Poverty

in Greater Denver

Executive Summary (draft 9/05/03)

The General Argument

Most American regions suffer from three interlocking problems –

sprawl, racial segregation, and concentrated poverty. Sprawl and racial segregation interact with each other. They are linked most clearly through the concentration of poverty.

Concentrated poverty is urban America’s core problem – both socially and geographically. Concentrated poverty creates push-pull factors. Push factors – high crime rates, failing schools, falling property values, often higher tax rates – push middle class families out of poverty-impacted neighborhoods in central cities and many older suburbs. Pull factors – safer neighborhoods, better schools, rising home values, often lower tax rates – pull such families to newer suburban areas.

It is not any “superior virtue” of suburban governments that is responsible for suburban pull factors. Pull factors simply reflect the fact that most suburbs are low-poverty areas. Indeed, they are designed to be that way by a variety of federal, state, and local policies. Push and pull factors are largely opposite sides of the same coin – concentrated poverty.

Concentrated poverty is a highly racialized phenomenon. Nationally, almost twice as many residents of our metro areas are poor and white as those who are poor and black or poor and Hispanic. Yet poor whites rarely live in poor neighborhoods (where poverty rates exceed 20%). Nationally, only one quarter of poor whites live in poverty-impacted neighborhoods; three quarters live in working class or middle class neighborhoods scattered all over our metropolitan areas. By contrast, half of poor Hispanics and three quarters of poor blacks live in poor barrios and ghettos in inner cities and inner suburbs.

What does this mean? Most importantly, if you are poor and white, the odds are three out of four that at your neighborhood school your own

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children’s classmates will be primarily middle-class children. If you are poor and black, the odds are three out of four that your own children will be surrounded by other poor school children. The socioeconomic backgrounds of a child’s family and of a child’s classmates are the strongest influences shaping school outcomes. Where a child lives largely shapes the nature of the child’s educational opportunities – not in terms of how much money is spent but who are the child’s classmates. And, increasingly in the modern economy, education determines a child’s future.

Local Evidence

Sprawl: In 1950, the Denver urbanized region was a more compact community of 500,000 persons living within 105 square miles; the city itself contained 83 percent of the urbanized population and 74 percent of the urbanized land. Fifty years later the Denver urbanized area had grown almost five fold (374 percent) to 499 square miles and its urbanized population (almost 2 million) had grown almost four fold (298 percent); the city had dropped to one-quarter of the region’s population. However, average density (residents per square mile) of the entire urbanized area had only dropped by only one-sixth. By several common measures, the Denver area has actually sprawled less than most urbanized areas.

Does Denver have a sprawl problem? Many area residents would say “yes.” National comparisons would say “no.” However, such land use measures do not touch upon the issue that causes many residents to rebel against sprawl: traffic congestion. Denverites own a lot of cars. In 2000, the average household owned 1.79 vehicles (15th highest of 83 metro areas). And 87 percent of Denverites relied heavily on their cars to get to work. As a result, in 2000, Denverites averaged 26.5 minutes commuting to work (a 20 percent increase over average commute time in 1980). All trips totaled over 46 million vehicle miles per day, and every Denverite spent an estimated 34.6 hours per year in traffic delays (fifth highest of 59 large metro areas) – roughly 72 hours a year that local commuters spend stuck in traffic (almost two full work weeks!)

Increasing spatial separation between homes, jobs, and shopping; increasing numbers of working married women (generally at different job locations than their husbands); the shrinking ability of children to walk to school or to after-school activities (creating the phenomenon of the “soccer mom”); growing affluence that promotes greater vehicle ownership – all

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have combined together to create the most visible cost of sprawl in the Denver area as the challenge of getting from here to there.

Uneven Development: As new development moves constantly outward, many older communities decline. This occurs primarily because most new residential construction is for the upper end of the housing market; a region’s lower-income families are consigned to hand-me-down housing in older neighborhoods. Higher-quality retail and, increasingly, higher-wage jobs follow the intra-regional migration of higher-end families.

Though, by comparison, Denver remains one of the USA’s healthier central cities, city residents, who were once slightly wealthier than their suburban neighbors (102 percent of regional median family income in 1950), have still become poorer than their suburban neighbors (only 79 percent of regional median family income in 2000). Suburban counties have gone through successive cycles of relative growth and decline; Adams, Arapahoe, and Jefferson counties are now on an income down slope while Douglas County (the newest “place to be”) is shooting upward in relative wealth (145 percent of regional median family income in 2000).

These patterns are even more pronounced at the municipal level. Denver’s assets (many prestigious older neighborhoods, a strong downtown core, major high-quality employers anchored in the city, fine parks and museums, and a lively cultural and social scene and the growth of singles, couples without children (hetero and gay), and “empty nesters” – work in Denver’s favor. In 2000, 77 percent of Denver’s households were childless. The Lo-Do phenomenon should continue.

But many of Denver’s older suburbs lack such assets. Moreover, built in the 1950s, 1960s, and 1970s, their housing stock is too old to be competitive, and too young to be quaint. Commerce City is the region’s poorest community. Englewood, Wheat Ridge, and North Glenn are already in trouble. Lakewood, Arvada, Littleton, and (especially) Aurora (that is, yesterday’s winners) have all had their day in the sun; socio-economic and fiscal clouds are slowly forming over them.

Divided by Race: For greater Denver’s African American residents, the good news is that the Denver of today is not the Denver of yesteryear when the degree of hyper-segregation – a segregation index score of 85 as late as 1970 (on a scale of 100 = total apartheid) certainly echoed decades of more virulent discrimination. The bad news is that the Denver region’s neighborhoods and

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schools continue to be somewhat more segregated than its peer communities and the average of the 100 largest metro areas.

For greater Denver’s Hispanic residents, residential and school segregation are both rising and substantially higher than national averages (though generally in the same range as Denver’s peer communities). Is this largely a temporary phenomenon (driven by large-scale immigration) or will massive barrios become permanently institutionalized?

Divided by Income: If housing barriers based purely on race have been coming down, housing barriers based on income have been going up. During the 1970s and 1980s, economic segregation increased in almost 70 percent of major metropolitan areas, including the Denver region. By 1990, metro Denver was the 26th most economically segregated out of the 100 largest metropolitan areas, rising from an economic segregation index of 36 in 1970 to 40 in 1990.

Economic segregation ticked downward during the 1990s, lowering Denver’s from 40 to 39 (33rd out of 100). That downward movement may have been ephemeral. Census 2000 collected income and poverty data for 1999, the peak year of the economic boom. There could not have been a more favorable year to take an economic snapshot of America’s cities; poverty rates had reached historic lows for African Americans and Hispanics that year. A snapshot of America’s metropolitan areas would likely not find the same favorable picture in 2003 in the midst of current economic slump.

Housing Policy Is School Policy: Neighborhood residential segregation is magnified in enrollment patterns of neighborhood schools. Metro Denver elementary schools are no exception. At one extreme, in 2001 there were 39 elementary schools that were 90 to 100 percent black and Hispanic; 27 percent of the region’s black and Hispanic pupils attended these virtually all-minority schools. In fact, 68 percent of black and Hispanic pupils attended majority minority schools.

At the other extreme, in 2001 108 elementary schools were over 90 percent Anglo; they enrolled 43 percent of the region’s Anglo pupils. Ninety-one percent of Anglo pupils attended majority Anglo schools.

Progress has been slight in recent years. At the beginning of the decade, the black segregation index for the Denver region’s elementary schools was 65 (1989-91); by 1997-99, it had improved slightly to 62. But

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the trend was towards greater segregation of Hispanic pupils; the Hispanic school segregation index worsened from 47 to 50 during the decade.

Racially segregated schools are also economically segregated schools. Of the 39 schools that were 90-100 percent minority, all 39 had a majority of low-income pupils. In fact, 99 of the 124 majority minority schools also had a majority of low-income pupils that qualified for subsidized meals. The odds are four to one than a pupil in a majority-minority school will also be attending a majority low-income school.

The results are even more striking at the other end of the scale. None of 108 schools that are 90 percent or more Anglo have majorities of low-income pupils nor do any of the 64 schools that are 80 to 90 percent Anglo! In fact, only 11 of all 267 majority Anglo schools have majorities of low-income pupils. In other words, the odds are 24 to one that a child in a majority Anglo school will have a majority of middle-class classmates.

Economic segregation is getting worse with the school economic segregation index rising from 50 in 1989-91 to 57 in 1997-99. This was the 13th highest level of economic school segregation (and the eighth fastest increase) out of 81 major metro areas for which information for the full decade was available.

There was a very high correlation between a school’s socioeconomic profile and a school’s test scores on the Colorado School Assessment Program (CSAP): a school’s percentage of low-income pupils explained 77 percent of the school-by-school variation in CSAP results. In somewhat imprecise layman’s terms, knowing the percentage of low-income pupils, one can predict a school’s percentage scoring proficient or advanced on the CSAP tests and fall within 10 percentage points of the actual percentage about 95 percent of the time.

A study of the Denver Public Schools by Diane Lefly confirmed locally what other studies nationally have consistently found.

• Low-income students (as measured by eligibility for federal free or reduced-cost school lunches) perform significantly better in low-poverty schools than in schools where over half the students are poor. For example, on the 2001 CSAP reading test, 53 percent of low-income elementary school students scored proficient or advanced in schools where fewer than 25 percent of student qualified for free or

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reduced price lunch. However, in schools where over 75 percent of the students were poor, just 33 percent of the low-income students scored proficient or advanced.

• Non-poor students perform well on standardized tests in schools with low to moderate levels of poverty. However, the scores of non-poor students begin to deteriorate significantly in schools where over 50 percent of all students are poor. 83 percent of non-poor students scored proficient or advanced on the 2001 reading CSAP [in schools with less than 25 percent of low-income classmates]. However, in schools with more than 75 percent low-income students, only 49 percent of the non-poor students scored proficient or advanced.

• Proficient CSAP scores are far lower within the proficiency band in high-poverty schools than in low-poverty schools. In other words, even “good” test scores are less “good” in high-poverty schools than in low-poverty schools.”

Potential Solutions

Three key public policies, pioneered in other regions, would address these issues in the Denver region.

Urban growth boundary: The 2.1 million-person Denver region contains five counties and 29 municipalities. Colorado law delegates broad land use planning and zoning powers to each jurisdiction. Despite efforts to promote voluntary regional cooperation, the 34 local governments typically plan and implement development policies independent of each other. Colorado voters rejected an anti-sprawl initiative in November 2001.

The 1.5 million-person Portland region contains three counties and 24 municipalities. Oregon law delegates the same broad land use planning and zoning policies to local governments, but Oregon law also requires all local governments to plan together under the guidance of Portland Metro, a popularly-elected regional government. Among other anti-sprawl tools, Metro defines and enforces a regional “urban growth boundary.”

As a result, in the past two decades, the Portland region has evolved as a more compact, transit-oriented, pedestrian-friendly community. Portland must substitute deliberate public policy for the implicit discipline of

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a semi-arid climate (that necessitates most Denver area development’s hooking on to municipal water utilities). Though not yet a radical departure from America’s auto-centered culture, compared to Denver, Portlanders have slightly fewer vehicles per household, take a bus or street car or walk more to work, have cleaner air, safer streets, and a slightly less time-consuming daily commute, and spend one-third less time stuck in traffic. The Denver region would greatly benefit from a rigorous, anti-sprawl, land use and transportation planning regime like Portland’s.

Economically integrated schools: in recent years several local school districts – notably, La Crosse, Wisconsin; Wake County (Raleigh area), North Carolina; and Cambridge, Massachusetts – have implemented pupil assignment policies based on achieving socioeconomic balance in their elementary schools. Basically, they have sought to have every elementary school achieve the district-wide average of low-income children (plus/minus 15 percentage points). As a result, they have achieved substantially greater economic integration than would have been the case if enrollment reflected solely neighborhood residential patterns – and they have seen academic achievement improve, particularly for low-income pupils.

The economic segregation index for the Denver region’s 391 elementary schools for 2001-02 was a high 58.9 (13th highest of the 100 largest metro areas). Implementing a policy of socioeconomic balance as outlined above within the 17 school districts would lower the economic school segregation rate to 46.6 – about a 20 percent improvement.

These are policies well worth pursuing. However, the greatest economic segregation occurs not within each district but between school districts because of the great disparities created by economically segregated housing patterns.

Inclusionary zoning: Over 130 local communities have adopted inclusionary zoning ordinances that require that a certain proportion of all covered new housing developments must include a modest proportion of affordable housing. (The city of Denver adopted such a policy in 2002.) Montgomery County, Maryland’s program is the USA’s oldest and largest, since 1975 producing over 11,000 affordable homes integrated into middle class sub-divisions. Two-thirds are sold or rented to working class families; the other third are acquired by the county public housing authority. As a result, Montgomery County, the USA’s 13th wealthiest county and global

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center of biomedical and genetic industries, is also one of the most racially and economically integrated communities, with a top-quality school system.

What would have been the impact of an inclusionary zoning policy adopted throughout the Denver region? From 1980 to 2000, about 320,000 new homes were built in the Denver area. Applying Montgomery County’s formula (and assuming that half of all new homes were in developments too small for the inclusionary policy to apply), there would have been about 16,000 more affordable homes built for working class families and another 8,000 acquired by a regional housing authority (or collaborative network of local housing authorities).

On a school district basis, some 12,000 low-income children’s families would have opportunities to move out of eight higher-poverty, “sending” school districts into nine low-poverty, “receiving” school districts. (Almost 9,000 such children would leave the high-poverty Denver Public Schools.) The Jefferson County schools (plus 4,475), the Cherry Creek schools (plus 3,375), and the Douglas County schools (plus 3,100) would have been the largest “receiving” districts.

Hypothesizing that the region’s 17 school boards would carry out school assignment policies that would equalize low-income pupil enrollment among all elementary schools within each of the school districts, I calculated (in module 7) that the economic school segregation index would be reduced to 46.6 – about a 20 percent reduction in economic segregation.

However, reinforcing what school boards have the authority to do with an inclusionary zoning policy that city and county governments have the authority to do would reduce the school economic segregation index to 13.9 – a three-quarters reduction in economic school segregation! That would make metro Denver’s schools the third most economically integrated in the nation. By achieving just half that level (27.8), which is readily within the range of realistic implementation, greater Denver would have the second most economically integrated schools of any major metro area.

Housing policy is school policy.

[2,789 words]

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Box 1.1 Poll Finds “Astonishing” Local Concern about Sprawl

Sixty percent of area residents (unprompted by the pollsters) cited concerns about overdevelopment, sprawl, increasing traffic, and inadequate roads as the most important problem facing the Denver area, according to a 2000 poll sponsored by the Pew Center for Civic Journalism.1

The pollsters found this level of concern “astonishing” in light of the fact that only 18% of all persons polled in the Denver, Tampa, Philadelphia, and San Francisco regions combined labeled sprawl-related issues as their number 1 local concern.

Crime and violence (9 percent), education (6 percent), and the economy (3 percent) – top rated issues elsewhere – trailed far behind sprawl-related concerns locally.

Ranking sprawl-related issues as #1 occurred more among men (65 percent) than women (55 percent), among college-educated (66 percent) than high school graduates (50 percent), and among whites (62 percent) than minorities (47 percent).

“Ask Denver resident what the most important local problems are,” the pollsters noted, “and the answers can be summed up in four words: ‘Too much’ and ‘Not Enough.’

• Too much growth

• Too much development

• Too much traffic

• Not enough water

• Not enough schools

• Not enough services.”

1 The poll summary can be found at www.pewcenter.org/doingcj/research/r_ST2000denver1.html. The poll was taken presumably after the high-tech stock market bubble burst, but before the economy slid into recession and the terrorist attack on 9/11 a year later. Asked about national issues then, only 6 percent of Denver respondents listed the economy as the most important issue and only 1 percent listed national security and terrorism as top ranked.

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The pollsters continued: “But that might even understate the public’s concern. Asked in a separate question whether traffic congestion is a problem “in the community where you live,” a whopping 90 percent of Denver residents say it is a problem, with three-quarters of the public (73 percent) saying it is a big problem. And 17 percent say it is a small problem. Only 10 percent say traffic congestion is not a problem.”

Likewise, the pollsters noted, “’too much growth and development’ are labeled as a problem by 87 percent of Denver area residents, with 65 percent calling it a big problem. Twenty-two percent call it a small problem and 13 percent say it is not a problem at all.”

Asked to pinpoint the cause of traffic congestion, 59 percent said that the reason was simple population growth in the area. Sixteen percent blamed a lack of adequate planning. Eight percent said that not enough money has been spent on highways and transportation and 10 percent said overdevelopment. Seven percent were not sure.

“The issues of growth and development,” the Pew Center concluded, “are bedeviling local and state officials across the country and in Denver, in part, because there is a substantial division over how to deal with the problems. This split is evident in the answers to a question how local government should use its power to focus growth. About two in five residents (39 percent) say that local government should allow growth and development to continue to occur in all areas. But a bare majority (51 percent) says that growth and development should be limited to areas that are already built up, implicitly protecting those areas that are not yet developed.”

The confusion is encapsulated in a comment by one Denver resident cited by the researchers: “Urban sprawl is creating more problems than anything else right now. Too many people crammed too close together.”

Of course, if those “too many people” were spread out much more rather than being crammed “too close together,” traffic congestion would become much worse than it already is.

Unless Denver slams the door on further population growth (which is only accomplished by local economic collapse – ask the coal and steel regions of Pennsylvania and West Virginia), the challenge is to develop a more compact, less auto-dependent pattern of development. [583 words]

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Module 2: Today’s Winners Become Tomorrow’s Losers

(re-draft 9/5/03)

Summary: As new development moves constantly outward, most older communities decline. This occurs primarily because most new residential construction is for the upper end of the housing market; a region’s lower-income families are consigned to hand-me-down housing in older neighborhoods. Higher-quality retail and, increasingly, higher-wage jobs follow the intra-regional migration of higher-end families.

Though, by comparison, Denver remains one of the USA’s healthier central cities, city residents, who were once slightly wealthier than their suburban neighbors (102 percent of regional median family income in 1950), have still become poorer than their suburban neighbors (only 79 percent of regional median family income in 2000). Suburban counties have gone through successive cycles of relative growth and decline; Adams, Arapahoe, and Jefferson counties are now on an income down slope while Douglas County (the newest “place to be”) is shooting upward in relative wealth (145 percent of regional median family income in 2000).

These patterns are even more pronounced at the municipal level. Denver has long-term assets that many older, bedroom community suburbs lack – many prestigious older neighborhoods, a strong downtown core, major high-quality employers (universities, hospitals, etc.) anchored in the city, fine parks and museums, and a lively cultural and social scene. Denver’s assets and the growth of singles, couples without children (hetero and gay), and “empty nesters” – work in Denver’s favor. In 2000, 77 percent of Denver’s households were childless. The Lo-Do phenomenon should continue.

But many of Denver’s older suburbs lack such assets. Moreover, built in the 1950s, 1960s, and 1970s, their housing stock is too old to be competitive, and too young to be quaint. Commerce City is the region’s poorest community. Englewood, Wheat Ridge, and North Glenn are already in trouble. Lakewood, Arvada, Littleton, and (especially) Aurora (that is, yesterday’s winners) have all had their day in the sun; socio-economic and fiscal clouds are slowly forming over them.

* * *

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“Today’s winners become tomorrow’s losers.” That’s the Iron Law of Urban Sprawl. As new development moves constantly outward, most older communities decline. That occurs primarily because most new residential construction is for the upper end of the housing market; a region’s lower-income families are consigned to hand-me-down housing in older neighborhoods. Higher-quality retail and, increasingly, higher-wage jobs follow the intra-regional migration of higher-end families.

This pattern affects not just a region’s traditional central city but also successive generations of suburbs. The pattern is most pronounced in “little boxes” regions in the Northeast and Middle West. However, the Denver region is caught up in a similar cycle of winners and losers. Let’s look at the city of Denver, its older suburbs, and newer suburbs in turn.

Denver: the Central City

The best single measure of a city’s overall health is the average income of its residents compared to average income of residents of the region as a whole. We’ll use three measures of income. Median family income and median household income are those income levels at which half of all families (or households) receive more income and half receive less income; thus, median income does not reflect extremes of wealth and poverty.2 Per capita income, on the other hand, is the total income received by all persons divided by the number of persons. Per capita income does reflect income extremes and is a better measure of a community’s overall economic wealth than are median incomes. (Mean family and household incomes – the equivalents of per capita income – are not always readily available for all census years.)

Table 2.1 tracks changes in the city of Denver’s average income levels as a percentage of metropolitan averages over the past half century. It shows an almost unbroken downward trend. In 1950, the average (median) city resident had the same income level as the average suburban resident. By 2000, city median family and median household income were more than 20 percent below the regional median. 2 The census defines a household as including all persons who occupy a housing unit. A family consists of a householder and one or more other persons living in the same household who are related to the householder by birth, marriage, or adoption. Not all households contain families since a household may comprise a group of unrelated persons or one person living alone.

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Table 2.1 City of Denver’s average income

as percentage of region’s average income from 1950 to 20003

Type 1950 1970 1980 1990 2000 Median family income 102% 90% 83% 80% 79% Median household income 99% 82% 78% 76% 77% Per capita income na na 96% 94% 92% By 2000, per capita income had not fallen as far below suburban

levels as median family and household income had, which reflects the presence still of many wealthy residents in parts of the city. Surprisingly, considering the very visible success of revitalized neighborhoods like Lo-Do in re-attracting higher income households back to the city, city per capita income continued to decline (if slightly) as a percentage of regional per capita income during the 1990s.

All central cities are not fated to have average incomes below their suburbs. Very annexation-oriented cities often have incomes equal to or higher than suburban levels since such “elastic” cities incorporate many high-end, “suburban” subdivisions within their constantly expanding city limits.4 San Diego’s per capita income, for example, was 103 percent of its metropolitan average in 2000; Albuquerque’s, 104 percent; and Charlotte’s, 113 percent. These are quasi-metropolitan cities that have increased their land areas by three, four, and nine times as much, respectively, since 1950.

A handful of other cities have experienced such regentrification that, by 2000, their per capita income had also risen above the metropolitan average. Seattle’s per capita income, for example, was 109 percent of its metropolitan level. Most extraordinarily, over the past two decades, while Denver’s level was drifting downward from 96 percent to 92 percent, re-gentrification was driving Atlanta’s upward from 85 percent to 103 percent! 3 All census information on income actually records what was received the previous year. Thus, the 1950 census records income from 1949, etc. 4 See the author’s Cities without Suburbs. Woodrow Wilson Center/Johns Hopkins University Press: Washington, DC and Baltimore (1995) for a full discussion of elastic and inelastic cities and the social, economic, and fiscal consequences of urban elasticity.

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Denver’s downward slide hardly matches the plummeting of cities in “little boxes” regions like Cleveland (64 percent), Detroit (60 percent), or Newark (46 percent). But not being able to annex beyond its co-terminous county boundary, Denver has not been able to capture the lion’s share of sprawling growth like San Diego, Albuquerque, or Charlotte. And the movement of professional households back to the city, strong as it is, has not reversed Denver’s downward trend – much less produced an income resurgence yet comparable to Seattle’s or Atlanta’s.

Suburban Trends – Counties

According to Census 2000, half of the city of Denver’s current housing supply had been built by 1957. We can apply the same criterion to characterize the age of different suburbs. In general, newer suburbs will attract higher-income households. As communities age, the incomes of long-term residents typically shrink as they reach retirement; new households moving in typically do not represent the same higher-income cohort as the original residents did. In effect, the prestigious “places to be” have moved on to other, newer communities (typically farther out on the suburban fringe).5

A second factor might be called “Adams’ Rule:” suburban income patterns will be extensions of income patterns in the central city.6 That holds true for the Denver region. As of 1970, within Denver itself the poorest city neighborhoods were concentrated in North Denver abutting onto Adams County. West side neighborhoods bordering inner Jefferson County were fairly modest income. The city’s wealth was concentrated in its southwestern and southeastern sections, bordering Arapahoe County or reaching farther out in Jefferson County.

Age, Adams’ Rule, and race (which I’ll discuss in later modules) shape the socioeconomic status of Denver’s suburbs. Table 2.2 provides an

5 Just as the central city may maintain certain prestigious neighborhoods, there are suburban exceptions to the rule that newer is better. Certain highly exclusive suburbs may maintain that status through the decades. Two-thirds of Cherry Hills Village’s housing had been completed by 1979, yet in 2000 Cherry Hills Village was the region’s highest income municipality with average incomes over four times the regional average. 6 I’ve coined the term “Adams’ Rule” in recognition of the work of Professor John Adams, University of Minnesota geographer.

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overview of the region on a county-by-county basis.7 Bordering low- income North Denver, Adams County developed as a blue-collar suburban county with below average income levels; its day in the sun never really arrived. At mid-century both Jefferson and Arapahoe counties had average family incomes below the regional median, but developed rapidly in the next three decades. However, both counties clearly peaked by 1980. Though both maintain income levels above regional averages, both are slowly dropping down the scale as high-end development has moved elsewhere.

Table 2.2 Counties’ average income

as percentage of region’s average income from 1950 to 2000

County 1950* 1970* 1980 1990 2000

Adams: family 90% 97% 91% 86% 86% (1975) household na 112% 98% 93% 92% per capita na na 82% 76% 76% Jefferson: family 97% 112% 113% 110% 110% (1975) household na 131% 120% 119% 112% per capita na na 106% 105% 107% Arapahoe: family 95% 112% 114% 112% 104% (1978) household na 127% 119% 113% 105% per capita na na 115% 114% 107% Douglas: family 78% na 128% 135% 145% (1994) household na na 142% 157% 162% per capita na na 118% 127% 133% * Median household income for 1950 and 1970 was actually “median income of families and unrelated individuals” – a close but not exact equivalent to median household income This note applies to all succeeding tables and will not be repeated.. During the 1980s and 1990s, high-end development moved

spectacularly into Douglas County. By 2000, Douglas County had become the nation’s highest income county. Douglas County is also strikingly new. Half of its 83,333 housing units were built between 1995 and March 2000 – almost 500 new housing units a month! Depending on the measurement used, average incomes in Douglas County exceeded regional averages by one-third (per capita income) to two-thirds (median household income).

7 The year by which half of all housing units had been built is listed in parentheses.

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Suburban Trends – Municipalities

These patterns become even clearer by examining trends at the municipal level. Tables 2.3a, 2.3b, 2.3c, and 2.3d group major suburban municipalities by the decade in which half of their current housing stock had been built. This provides a simple measure of a city’s relative age. (Remember: half of Denver’s current housing stock was built by 1957.)

Table 2.3a groups cities that hit the halfway milestone in the 1950s and 1960s. Bordering some of Denver’s poorest areas, Commerce City (Adams County) is the region’s poorest jurisdiction, having much higher poverty rates than Denver itself. Moreover, unlike Denver, it lacks any high-end neighborhoods; its income is barely half the regional average.

Table 2.3a Old suburban cities’ average income

as percentage of region’s average income from 1950 to 2000

City 1950 1970 1980 1990 2000 Englewood: family 104% 93% 83% 76% 77% (1957) household na 102% 78% 77% 76% per capita na na 88% 82% 80% Commerce family na na 73% 60% 53% City: household na na 78% 62% 66% (1958) per capita na na 65% 52% 51% Wheat Ridge: family na 109% 94% 88% 78% (1961) household na 125% 93% 86% 76% per capita na na 105% 93% 86% Northglenn: family na 109% 108% 96% 86% (1968) household na 136% 117% 106% 94% per capita na na 88% 82% 77%

Englewood (Arapahoe) and Wheat Ridge (Jefferson) are First Suburbs. Along with North Glenn (Adams), they peaked by 1970. As a group, these older suburbs averaged three-quarters of metro income levels in 2000.

The 1970s suburbs (Table 2.3b) include three county seats: Brighton (Adams), Golden (Jefferson), and Littleton (Arapahoe). As county seats, these three have long municipal histories and Brighton and Golden appear to

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be on a slight upward trend from more modest beginnings as centers of rural counties. Lakewood (Jefferson), Arvada (Jefferson-Adams), Littleton (Arapahoe), and Aurora (Arapahoe-Adams) all peaked during the 1970s. (Aurora, in particular, was sliding steadily down the income scale.) By 2000, the group’s incomes averaged about 95 percent of metro averages.

Table 2.3b

1970’s cities’ average income as percentage of region’s average income

from 1950 to 2000

City 1950 1970 1980 1990 2000 Lakewood: family na 115% 112% 100% 93% (1972) household na 135% 116% 104% 94% per capita na na 88% 82% 80% Arvada: family na 111% 112% 109% 102% (1974) household na 131% 123% 119% 108% per capita na na 98% 95% 94% Brighton: family na na 85% 81% 87% (1975) household 95 na 89% 82% 91% per capita na na 73% 73% 68% Golden: family na na 97% 88% 110% (1975) household 80% na 88% 89% 96% per capita na na 91% 91% 96% Littleton: family na 118% 110% 109% 106% (1976) household 103% 134% 107% 104% 99% per capita na na 105% 111% 99% Aurora: family 98% 101% 104% 97% 86% (1978) household 115% 108% 111% 102% 91% per capita na na 102% 92% 80% Westminster (Adams-Jefferson), Thornton (Adams), and Broomfield

(Adams-Jefferson) are all outer suburbs Table 2.3c). As newer communities, their incomes collectively are about 105 percent of metro averages. Broomfield, like Arvada, may also benefit from access to the high-tech economy centered on the University of Colorado in nearby Boulder.

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Table 2.3c

1980’s cities’ average income as percentage of region’s average income

from 1950 to 2000

City 1950 1970 1980 1990 2000 Westminster: family na na 102% 103% 104% (1981) household na na 111% 112% 110% per capita na na 91% 94% 97% Thornton: family na na 94% 93% 96% (1982) household na na 104% 104% 106% per capita na na 83% 77% 82% Broomfield: family na na 95% 97% 115% (1983) household na na 112% 115% 125% per capita na na 85% 77% 101%

The phenomenon of Douglas County (site of over one-quarter of all new homes built in the region from 1995-00) has already been noted. Average incomes of the three municipalities (plus one “Census Designated Place”) are far above regional levels (Table 2.3d). In 2000 the four local communities averaged 143.5 percent of the metro median family income; 157 percent of the metro median household income; and 129 percent of the metro per capita income. (Per capita income is relatively lower than the two medians because of Douglas County’s high proportion of families with children, who, of course, are non-income earning “capitas”; 47 percent of Douglas County households are families with children compared to 32.5 percent for metro Denver overall).

However, even greater wealth is found in unincorporated new subdivisions. Per capita income for the balance of Douglas County was 153 percent of the regional per capita income. Increasingly, higher-end families are moving into Douglas County rather than more exclusive areas of Arapahoe and Jefferson counties. Some 86 percent of all housing units are detached, single-family homes with a median home value of $236,000. With a median monthly rent of $1,564 for 7,153 townhouses and apartments and only one-sixth of its rentals units priced at less than $750 per month, it is clear that Douglas County has set its policies to attract only well-off households – owners or renters.

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Table 2.3d

1990’s cities’ average income as percentage of region’s average income

from 1950 to 2000

City 1950 1970 1980 1990 2000 Castle Rock: family na na na na 119% (1993) household na na na na 125% per capita na na na na 102% Highlands: family na na na 154% 151% Ranch CDP household na na na 180% 170% (1996) per capita na na na 141% 132% Lone Tree: family na na na na 178% (1996) household na na na na 188% per capita na na na na 177% Parker: family na na na na 126% (1997) household na na na na 145% per capita na na na na 105%

Summing Up

As the central city, Denver is home to a disproportionate share of the region’s poor; with only 26 percent of the metro area’s population, it has 46 percent of the region’s poor. However, Denver has long-term assets that many older, bedroom community suburbs lack – many prestigious older neighborhoods, a strong downtown core, major high-quality employers (universities, hospitals, etc.) anchored in the city, fine parks and museums, and a lively cultural and social scene.

Also, America’s social structure is shifting increasingly to childless households; thirty years ago, 46 percent of metro Denver’s households were families with children; by 2000, families with children accounted for only 32.5% of all households in the metro area.

These two factors – Denver’s assets and the growth of singles, couples without children (hetero and gay), and “empty nesters” – work in Denver’s favor. In 2000, 77 percent of Denver’s households were childless. The Lo-Do phenomenon should continue.

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But many of Denver’s older suburbs lack such assets. Moreover, built in the 1950s, 1960s, and 1970s, their housing stock is too old to be competitive, and too young to be quaint. Commerce City is the region’s poorest community. Englewood, Wheat Ridge, and North Glenn are already in trouble. Lakewood, Arvada, Littleton, and (especially) Aurora (that is, yesterday’s winners) have all had their day in the sun; socio-economic and fiscal clouds are slowly forming over them.

These communities have to press for changes in the regional “rules of the game” if they are to avoid Commerce City’s fate in coming decades. They need strong, regional growth management laws to redirect new investment onto existing communities (as we’ll see in Module 6). They need mandatory, regional “fair share” housing laws to assure that their housing stock does not become the predominant inventory of lower-cost housing for low-income families; new communities must assume their “fair share” (Module 8). For every enclave of privilege, there is currently an enclave of poverty (as we’ll see in Module 4).

A just and successful region needs to promote racial, ethnic, and economic diversity everywhere if it is to avoid the Iron Law of Urban Sprawl: “Today’s winners become tomorrow’s losers.”

Suggested readings:

The seminal analysis of the rise and fall of suburbs is Myron Orfield’s American Metropolitics: the New Suburban Reality. Brookings Institution Press (Washington, DC: 2002), which maps trends in the USA’s 25 largest metropolitan areas, including Denver. His 94-page Denver report can be accessed on www.metroresearch.org (as well as 440 maps on socioeconomic, fiscal, racial, and land use trends on all 25 metro areas.

My own Cities without Suburbs: a Census 2000 Update (see footnote 3) is a concise (137 pages), but data-packed analysis of fifty years of demographic, social, economic, and fiscal trends, focusing on central cities like Denver, for 119 major metropolitan areas.

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Box 2.1 Housing Prices and Exclusionary Zoning

In Commerce City the average house cost $112,700 in 2000. That same year, in Cherry Hills Village the average house cost a staggering $893,000 – five times the metro average of $176,600! Disparities in housing values parallel, of course, disparities in residents’ incomes. But what accounts for such wide disparities?

One factor is that as we become more affluent, we consume more “house.” The table shows a substantial increase in the size and amenities of new, single-family homes constructed nationally over the past two decades. Average floor area increased by one-third. Over one-third of new homes built have four or more bedrooms despite the fact that family sizes are smaller. Having two and a half (or more) bathrooms has become a “necessity” now as has central air conditioning. Nine out of ten new homes have a garage (typically, a two-car garage, though three- and even four-car garages have become de rigeur in upscale markets.)8

Nation-wide characteristics of new single-family houses 1980-2001

characteristic 1980 2001 median size (in sq. ft.) 1,595 2,103 average size (in sq. ft.) 1,740 2,324 2 or less bedrooms 17% 11% 3 bedrooms 63% 52% 4 or more bedrooms 20% 37% 1 ½ or less bathrooms 27% 6% 2 bathrooms 48% 38% 2 ½ or more bathrooms 25% 56% central heating (1970) 71% 94% central air conditioning 63% 86% garage 69% 89% Similarly, renters consume more housing than they used to. In 2001,

the average rental unit contained 1,298 square feet, had four and a half rooms, and one and a half bathrooms. Two-thirds of all rental units were in multi-unit apartment buildings. That’s considerable growth in space and amenities over the classic cold water flat.

8 One out of five Denver households owns three or more cars, SUVs, trucks, and RVs.

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Thus, newer communities will typically have higher housing costs than older communities. Half of Commerce City’s housing was built before 1957. Half of Douglas County’s housing was built after 1994. One could anticipate Douglas County’s high average house value ($236,000) – more than twice Commerce City’s.

Building codes and subdivision standards adopted by local governments (often following national model codes) also contribute to rising housing costs. Many such requirements, each standing alone, seem like “a good thing.” But, collectively, they add to the cost of housing. Arguably, strict plumbing and electrical codes are justified by safety considerations. But requirements such as requiring deep set-backs from lot lines or off-street parking add measurably to housing costs by increasing g the amount of land consumed.

By far the greatest regulatory impact on the cost of housing is through exclusionary zoning. By escalating land costs, requiring minimum half-acre, one-acre, two-acre, five-acre, or ten-acre lots per housing unit has nothing to do with preserving open space (much less, preserving farmland) and everything to do with assuring that new houses will be built for only high-income households. Setting minimum square footage thresholds can have the same impact. And restrictions on townhouse and apartment construction (or even banning such outright) is a further attack on the affordability of housing.

Within the Denver context, Cherry Hills Village is a mature community; half of all houses were built before 1970. But it was designed to be a very exclusive community of big houses. Some 97 percent of all housing units are single-family, detached homes; 70 percent have more than nine rooms (not counting bathrooms). Census 2000 records only 18 townhouses and just 51 apartments (19 of which charge no rent – may be in-law quarters). Cherry Hills Village was zoned to be home only to the wealthy.

Once these patterns are set, they are tough to change. Commerce City, for example, cannot just zone undeveloped city land for another Cherry Hills Village. Perceptions help shape land use as well as public policy.

But exclusionary zoning practices best explain how the highest cost housing has become concentrated in a handful of communities. [573 words]

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Box 2.2 Belle Creek, Reunion Spur Commerce City’s Revival

“Commerce City now is a desirable place to live,” exulted Mayor Sean Ford about the new subdivisions springing up in the newly-annexed outskirts of the old industry town.

After voters in 1999 trounced a measure to limit growth, the city more than tripled its size to 62 square miles, annexing a wide swath of land along the west and north boundaries of the defunct Rocky Mountain Arsenal. According to a Rocky Mountain news story, more than 2,500 building permits have been issued in 16 subdivisions.9

By 2010, Commerce City will have more than tripled its population to 65,000 people, up from 19,000 in 2000 (52 percent of whom were Hispanic – a 50 percent increase from a decade before). “By 2020,” City manager Perry VanDeventer estimates, “we could very easily be 100,000 people.”

The biggest impact will come from a “new town” subdivision called Reunion. The 2,500-acree development will be home to 40,000 people when it is completed in 20 years. It includes the Buffalo Run Golf Course, a 22,000-square foot city recreation center and extensive trail systems.

Drawing the most attention, however, is the 170-acre Belle Creek development. Designed on “New Urbanist” principles, Belle Creek will have 950 housing units, including 350 rentals. It is a unique development for the Denver area because

• It will have a mixture of single-family homes, townhouses and rental apartments plus small parks, a multi-purpose community center, and 61,500 square feet of retail and office space.

• The nonprofit Rocky Mountain Mutual Housing Association is building the rental units. Rents are targeted to be affordable to those who earn between 30 percent and 60 percent of the area median income.

9 This article is adapted from three news stories: “Reinventing Commerce City” (Rocky Mountain News: June 30, 2003), “Big Cities Losing residents to North” (Rocky Mountain News: July 10, 2003), and “”Belle Creek Finding a Niche: Affordable Housing Market” (Denver Business Journal)

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• The plan is that 51 percent of all Belle Creek units will be affordable to those earning 80 percent of area median income.

• The community center (which receives a subsidy of $150,000 a year from Commerce City) has a gymnasium and fitness center, child care facility, meeting rooms and a technology center with 16 computers. Children can use the computers for homework, play games and take classes.

• It incorporates new urbanism design elements, such as a town square park, pedestrian friendly layouts, driveways and garages behind homes, and large alleys.

• The Belle Creek Charter School, abutting the community center, serves kindergarten through eighth grade.

• New home prices will range between $160,000 and $260,000.

Gary-Williams Energy Company, which owned the land, and New Town Builders are co-developers of Belle Creek. “Sam Gary really had a vision that it should be a community with a significant affordable housing component,” said Dave Younggren, senior vice president with Gary-Williams. “His vision was to build a community as opposed to just another housing development.

Belle Creek is an exemplary model development and a great boon for Commerce City. I would just one cautionary note. Belle Creek is located in Adams County, which, as we see in Module 2, is “the affordable housing side of town.”

There need to be more Belle Creeks in places like Douglas County and high-end areas of Arapahoe and Jefferson counties.

[552 words]

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Module 3: Divided by Race (re-draft 9-08-03)

Summary: For greater Denver’s African American residents, the good

news is that the Denver of today is not the Denver of yesteryear when the degree of hyper-segregation – a segregation index score of 85 as late as 1970 (on a scale of 100 = total apartheid) certainly echoed decades of more virulent discrimination. The bad news is that the Denver region’s neighborhoods and schools continue to be somewhat more segregated than its peer communities and the average of the 100 largest metro areas. And segregation of black elementary school pupils was rising during the 1990s.

For greater Denver’s Hispanic residents, residential and school segregation are both rising and substantially higher than national averages (though generally in the same range as its peer communities). One hopes that this is largely a function of greatly increased Hispanic immigration over the past decade and that when (or if) this trend stabilizes, more of the region’s Hispanics will be integrated into the larger society. Whether the area’s Hispanic barrios are largely temporary phenomena or become permanently institutionalized will be determined by future developments in the regional housing market.

* * *

On April 26, 2003 the Denver Public Library opened the first library and museum to highlight the experience of African Americans in the West.

The $16 million project, located in the Five Points area (“a neighborhood that resonates with African American history”), focused on the role of blacks who helped found Denver and other cities, as well as the Buffalo Soldiers who fought American Indians on the Great Plains.

“Many African Americans came to the West for freedom and opportunity, just like other people,” stated a city librarian.10

Whatever its historical content, the fact of the new library and museum reflects the view that many contemporary Westerners hold of themselves as tolerant and progressive on racial matters.

10 Reported by the Boston Globe (http://travel.boston.com/news/notes/120402_denver_library.html)

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An Internet search for the topic “black exclusion laws in Colorado” (which I vaguely – and mistakenly – recalled) failed to turn up any local counterpart to Oregon’s notorious black exclusion law in the 19th and 20th century.11 However, the first item listed did note that

“The Ku Klux Klan dominated Colorado and Denver politics in the 1920’s. It was well known that election results depended on a Klan blessing. Governor Clarence J. Morely (Governor of Colorado from 1925-27) was known as “the Ku Klux Klan governor.”12

Another website noted that

“Between 1921 and 1925, the Ku Klux Klan flourished politically in Colorado, part of a national resurgence amid a time of social unrest after World War I. Both Denver Mayor Benjamin Stapleton and Governor Clarence Morely are Klan members. [By 1924], the Ku Klux Klan secures domination of Republican Party in Colorado and elects a pro-Klan Governor and U.S. Senator.”13

I cite these two items (admittedly separated by eighty years) to show that the Denver area has hardly been exempt from the racial injustice that has stained American history since our inception.

Race and sprawl are major factors that have shaped all metro areas (except for about four dozen metro areas with proportions of racial minorities so small that I classify them as part of “White America”).14

General Population Trends

Let us examine the racial dimensions of these phenomena in the Denver area (with the discussion of poverty trends postponed for the next study module).

11 From 1857 to its repeal in 1926, the Oregon Constitution sought to prohibit African Americans from residing in Oregon. In the 19th century, black exclusion laws were also enacted in Missouri, Indiana, Illinois, and Ohio. 12 “Growing Up in Denver, Colorado 1915-1932.” (www.law.du.edu/jenkins/chapter1.htm) 13 http://www.ghostseekers.com/Timeline.htm 14 “Race” has no biological meaning. I use “race” in its social context to identify African Americans, Hispanics, Asians, and Native Americans – principally the first two minority groups.

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We’ll start with examining general population growth in the Denver area before moving on to its racial composition.

Table 3.1 charts the familiar pattern of metropolitan growth in the Age of Sprawl. At mid-century, Denver contained three-quarters of the region’s population. Over the next twenty years Denver seemed to peak as Arapahoe County tripled, and Adams and Jefferson counties quadrupled their populations. In the 1970s and 1980s, Denver’s population slowly declined while Arapahoe and Jefferson counties doubled their populations again. (During the same period, Adams County’s growth was steady but more modest.) However, in the 1990s, Denver added 87,000 net residents, and Adams County almost 100,000 (largely for the same reason, as we’ll see in Table 3.3). Meanwhile, Douglas County became the new “place to be,” tripling to 176,000 residents in just one decade.

Table 3.1 Population growth by county in Denver PMSA from 1950 to 2000

(in 1,000s)

Jurisdiction 1950 1970 1980 1990 2000 Total (in 1,000s) 567 1,096 1,429 1,623 2,109

Denver City/County 416 515 492 468 555 Adams County 40 186 246 265 364 Arapahoe County 52 162 294 392 488 Douglas County 4 na 25 60 176 Jefferson County 56 233 372 438 527

Black and Hispanic Population Trends

Table 3.2 charts residential patterns for the region’s relatively small African American population. Blacks (along with Asians and Native Americans) totaled 20,000 “nonwhites,” or 3.6 percent of the region’s total population in 1950. By 1970, their small numbers had more than doubled to almost 50,000; however, 95 percent of all African Americans were concentrated in the city. By deliberate federal policy, the growing suburbs were essentially reserved for whites only in the 1940s, 1950s, and 1960s.

Thereafter, with new civil rights laws in effect, the story was one of steady suburbanization of the growing black middle class – primarily into Arapahoe County. By 2000, barely half the region’s 131,000 blacks lived in the city.

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Table 3.2 Percentage distribution of the African American population

By jurisdiction in Denver PMSA from 1950 to 2000

Jurisdiction 1950* 1970 1980 1990 2000 Total (in 1,000s) 20 50 76 96 131 Pct of metro 3.6% 4.5% 5.3% 4.5% 6.2% Denver City 91% 95% 78% 63% 51% Adams County 6% 3% 8% 9% 10% Arapahoe County 2% 2% 11% 24% 32% Douglas County 0.1% na 0.1% 0.4% 2% Jefferson County 1% 1% 3% 3% 5% * “Nonwhite” population in 1950

Table 3.3 traces trends for the Hispanic population from 1970 to 2000. (The Census Bureau did not identify Hispanics as a group before 1970.) Historically, the Denver region’s Hispanic population was about twice the size of its black population – about 10 percent of the total population. Though two-thirds lived in the city, Hispanics were never as highly concentrated as African Americans. But neither were Hispanics typically “suburbanized” either as many were scattered in small towns and rural areas as traditional agricultural workers.

Table 3.3 Percentage distribution of the Hispanic population By jurisdiction in Denver PMSA from 1970 to 2000

Jurisdiction 1970 1980 1990 2000 Total (in 1,000s) 116 139 211 397 Pct of metro 10.6% 9.8% 10.0% 18.8% Denver City 68% 66% 51% 44% Adams County 20% 17% 23% 26% Arapahoe County 6% 9% 10% 15% Douglas County na 0.3% 1% 2% Jefferson County 7% 8% 15% 13%

The Denver region’s Hispanic population, however, doubled in the 1990s, adding 186,000. Some growth was attributable to a higher birth rate, but most of the growth came from immigration from Mexico and Central America. Census 2000 recorded over 131,000 foreign-born residents who entered the USA (and presumably the Denver region) between 1990 and March 2000. Almost half

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(60,000) settled in the city; another 26,000 headed for Adams County; yet another 26,000 settled in Aurora (primarily in its Arapahoe County portion).

I’ve commented that the City of Denver experienced a population resurgence of 87,000 net residents in the 1990s. The gentrification of LoDo and several other city neighborhoods by largely white, young professionals and empty nesters has been widely publicized.

Yet Denver’s net population rebound was almost entirely attributable to the growth of its Hispanic population (primarily immigrants). The city’s “Anglo” residents (non-Hispanic whites) increased from 287,162 in 1990 to only 287,997 in 2000 – a net increase of only 835 Anglos. In fact, the surge in Hispanic residents brought the city close to majority minority status.

The Segregation Index

Tables 3.2 and 3.3 summarize an overview of racial population trends from a jurisdictional perspective. What about trends at a more individual scale – the neighborhood level? For African Americans, Table 3.4 tracks changes in a common “segregation index” in which on a scale of 0 to 100, a value of 0 would equal total integration and 100 would be total apartheid.15

Following three decades of deliberate federal policies to segregate the burgeoning suburbs and the Great Migration of rural blacks into the nation’s cities, 1970 probably represented the peak of residential segregation of African Americans. Metro Denver’s segregation index was 82 in 1970 (15th highest out of 44 metro areas). Thereafter, local racial segregation steadily declined, reaching a value of 62 on the segregation index by 2000 (49th highest out of 100 large metro areas).

15 The “segregation index” used is a dissimilarity index that measures how evenly or unevenly a minority population is distributed compared to the majority population. On a scale of 0 to 100, the higher the value, the more segregated the region. Metro Denver’s index of 62 in 2000, for instance, means that 62 percent of all African Americans would have to move in order for every neighborhood to have the same percentage of blacks (6 percent) as the regional average.

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Table 3.4 Residential segregation of African Americans (index: 0 to 100; 100 = total racial apartheid)

metro area 1970 1980 1990 2000 Denver 85 69 65 62 San Francisco 80 68 65 61 San Jose na 49 45 41 Phoenix na 62 52 44 Austin na 66 56 52 Sacramento na 59 57 56 Detroit 88 88 88 85 Albuquerque 59 41 42 32 100 large metro areas 81* 69 65 60 * only 44 large metro areas

Table 3.4 also compares metro Denver’s trends with other comparably-sized metro areas that, like the Denver region, have relatively small African American populations (i.e. between 4 and 8 percent) and larger Hispanic populations. Metro Denver’s segregation levels have largely tracked metro San Francisco’s through the decades, but by 2000 African Americans in Denver remained substantially more segregated than in peer communities like Sacramento, Austin, Phoenix, and San Jose. The Denver region’s segregation index (62) was far below that of metro Detroit, the USA’s most racially segregated region. However, Denver was even farther above metro Albuquerque (32), the most integrated region for African Americans among the 100 most populous metro areas.

Table 3.5 tracks trends in residential segregation for Hispanics that contrasts with the black experience in two major respects. First, residential segregation of Hispanics has typically between much lower than of blacks; in 1980, the Hispanic index (40) was 29 points lower than the black index (69) for the USA’s 100 largest metro areas.

Second, though black residential segregation that has lessened everywhere (albeit from very high levels that were unparalleled in the history of other racial and ethnic groups in this country), Hispanic segregation has risen in many metro areas, particularly in the 1990s. Nationwide, the pattern was that where the Hispanic population was relatively stable, Hispanics steadily fanned out into a

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wider range of neighborhoods. Where the Hispanic population increased significantly from rapid immigration, the segregation index increased. Immigrants tended to bunch up in “port-of-entry” neighborhoods, often doubling or tripling up with relatives and friends. Such heavy concentrations of immigrants statistically offset the movement of longer-term Hispanic residents out of the traditional barrios.

Table 3.5 Residential segregation of Hispanics

(index: 0 to 100; 100 = total racial apartheid) metro area 1970 1980 1990 2000 Denver 46 49 47 50 San Francisco na 46 50 54 San Jose na 46 48 52 Phoenix na 53 49 53 Austin na 46 42 46 Sacramento na 35 37 40 Providence 50 62 68 Vallejo-Fairfield-Napa na 22 23 29 100 large metro areas na 40 45 45 note: “na” means “not available” However, the rate of progress on residential desegregation was slower

among black and Hispanic youth ages 18 and less than that which occurred among all age groups (Table 3.6). In 2000, Denver’s segregation index for African Americans of all ages was 62; for blacks 18 years old and less, the index was 65. Similarly, for Hispanics, the all-ages index was 50; for Hispanic youth, it was 55.

Some older, heavily minority city neighborhoods have retained a cadre of older white homeowners long after their own children have grown up and moved away. In addition, during the 1990s, most of the much-noted “back-to-the-city” movement was composed of white, professional households without children – singles, “mingles,” young married couples without children, gay couples, and empty nesters. Many re-gentrifying neighborhoods, such as Lo-Do, are less segregated largely at the adult level. The greatest disparities between all-ages and youth segregation indices occurred in the San Francisco area, where the greatest degree of city gentrification occurred.

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Table 3.6 Comparing residential segregation among minority youth ages 18 and less

and all ages groups in metro Denver and peer communities in 2000 index: 0 to 100; 100 = total apartheid)

Blacks Hispanics metro all youth all youth Denver 62 65 50 55 San Francisco 61 70 54 62 San Jose 41 44 52 56 Phoenix 44 46 53 55 Austin 52 57 46 53 Sacramento 56 58 40 43

100 metro areas 60 64 45 49

To illustrate this point, families with children constituted 32.5 percent of all households in metro Denver, and only 23.2 percent in the city itself. The disparities between all-ages and youth-only segregation indices were three points (for blacks) and five points (for Hispanics).

The San Francisco metro area had the widest index disparities: nine points (for blacks) and eight points (for Hispanics). Only 23.6 percent of all the San Francisco area’s households were families with children, and only 16.6 percent in the City-by-the-Bay.

At the other end of the scale, the Sacramento area’s indices had only two-three point differentials. Metro Sacramento’s proportion of families with children (34.0 percent) was higher than metro Denver’s (32.5 percent); in the city of Sacramento (where there is no discernible buzz about a yuppie return to downtown), the proportion of families with children (30.2 percent) was substantially higher than Denver’s (23.2).

Hence, across the Denver region children are more separated by race than are adults.

Racially segregated neighborhoods produce racially segregated neighborhood schools. Table 3.7 demonstrates two ominous trends (that will be discussed in greater detail in Module 5).

First, the Denver area’s public elementary schools are more segregated by race than are the region’s youth in their neighborhoods. In 2000, the black youth

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segregation index was 65; among black elementary school pupils, the segregation index was 69. Similarly, for Hispanic youth, the residential segregation index was 55; for Hispanic elementary school pupils, the index was 60.

Table 3.7 segregation of public elementary school pupils in the 1990s

index: 0 to 100; 100 = total apartheid)

Blacks Hispanics metro 1989-91 1997-99 1989-91 1997-99 Denver 68 69 56 60 San Francisco 70 71 59 61 San Jose 42 46 50 58 Phoenix 53 49 55 59 Austin 60* 63 50* 60 Sacramento 59* 59 45* 47

100 large metro areas 62 63 54 54 *period covered was 1991-93 Second, the level of racial segregation among elementary school pupils

increased in the Denver area throughout the 1990s. Indeed, for black pupils, segregation increased slightly in the San Francisco, San Jose, and Austin regions, though it was stable in the Sacramento area and decreased slightly in the Phoenix area. Nationally, the black pupil segregation index increased slightly (62 to 63), in part reflecting the work of an increasingly conservative federal judiciary that was dismantling many school desegregation plans. (During the 1970s and 1980s, southern schools, for example, were much more integrated than southern neighborhoods.)

For Hispanic pupils, school segregation increased both in metro Denver (56 to 60) and in all its peer regions (in some, such as San Jose and Austin, much more rapidly). In the 100 largest metro areas, however, the school segregation index for Hispanics was stable (54). As a non-weighted mean,16 regions where Hispanic school segregation decreased (where, typically, the Hispanic population was stable) counterbalanced regions where Hispanic school segregation increased (where, typically, Hispanic immigration was heavy).

16 A non-weighted average means that metro Spokane (417,000 residents) was given equal weight with metro Los Angeles (9.5 million residents).

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Summing Up

Whatever Colorado’s history, most contemporary Denverites see themselves as racially tolerant. Whatever personal and political attitudes may be, however, the way in which the great Denver housing market functions belies that self-image. For African Americans the Denver region is more segregated than both Denver’s peer regions and the average of the 100 largest metro areas. Though lower than black levels, segregation of Hispanics is rising steadily. Whether this is a temporary phenomenon (as new immigrants cluster in port-of-entry neighborhoods) or creation of a permanent barrio is an open question.

Suggested reading:

Douglas Massey and Nancy Denton’s American Apartheid: Segregation and the Making of the Underclass (1992) is a must read on the issue of black segregation. The early chapters are particularly effective in laying out the history of how residential segregation in the North and West accelerated as the result of federal housing policies during the 1930s, 1940s, 1950s, and 1960s.

Chapter 4 (“Pilot Small’s Airport and the RKO Keith’s Balcony: Sprawl and Race”) of my Inside Game/Outside Game covers the same ground in a more personal, concise (19 pages) but still analytical way.

For those who want to dive into statistics, An indispensable resource tracking racial, ethnic, and economic disparities is the Lewis Mumford Center for Comparative Urban and Regional Research at State University of New York at Albany. The Center’s website (http://mumford1.dyndns.org/cen2000/data.html) provides easy-to-view sortable lists and downloadable tables calculating various segregation indices for 331 metro areas. Topics covered include segregation of the whole population, children under 18, Hispanic and Asian groups, school segregation, homeowners and renters (by race), the New Americans, state of the cities, separate and unequal, and diversity in black and white. Separate calculations are available for the Denver metro area as a whole, the city of Denver, and its suburbs for 1980, 1990, and 2000.

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Box 3.1 Federal Government Segregated Suburbs

“For Whites Only” was the sign that the federal government hung out as America’s suburbs exploded with millions of new families in the post-war decades. The federal government didn’t create discrimination in America’s housing markets, but it institutionalized it on an unprecedented scale.17

In 1933, as millions of owners were losing their homes during the Great Depression, the New Deal created the Home Owners’ Loan Corporation (HOLC). To help struggling families meet mortgage payments, HOLC offered low-interest, long-term mortgage loans. HOLC developed a ratings system to evaluate the risks associated with loans made to specific urban neighborhoods. HOLC designated four categories of neighborhood risk; on its “residential security maps” the highest risk areas were colored red. Black neighborhoods were always coded red; even those with small black percentages were usually rated as “hazardous” and denied loans.

HOLC’s loan program was small, but the impact of its discriminatory practices was enormous. During the 1930s and 1940s, HOLC “residential security maps” were widely followed by private banks for their own loan practices. When the Federal Housing Administration (1937) and the Veterans Administration (1944) were founded, they embraced HOLC’s underwriting practices. The 1939 FHA Underwriting Manual, for example, stated that “if a neighborhood is to retain stability, it is necessary that the properties shall continue to be occupied by the same social and racial classes.”

FHA and VA largely financed the rapid suburbanization of the United States after World War II. The federal government’s regulations favored construction of single-family homes but discouraged the building of multi-family apartments. As a result, the vast majority of FHA and VA mortgages went to new, white, middle-class suburban neighborhoods, and very few were awarded to black neighborhoods in central cities. Historian Kenneth Jackson found that from 1934 to 1960 suburban St. Louis County received six times as much FHA mortgage money per capita as did the City 17 This discussion is adapted from Chapter 2 of Douglas S. Massey and Nancy A. Denton. American Apartheid: Segregation and the Making of the Underclass. Harvard University Press: Cambridge, Massachusetts (1993), which in turn cites extensively from Kenneth T. Jackson, Crabgrass Frontier: the Suburbanization of the United States. (1985).

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of St. Louis. Per capita FHA lending in suburban Long Island was eleven times greater than in Brooklyn and 60 times greater than in The Bronx.

Such government practices died hard. As late as 1950, FHA was still encouraging the use of restrictive racial covenants two years after the US Supreme Court had ruled them unconstitutional! FHA’s red-lining continued overtly until the mid-1960s, when Robert Weaver became the first African American HUD secretary. The weak Civil Rights Act of 1968 finally outlawed housing discrimination. However, the full extent of discrimination in mortgage lending was only revealed after passage of the Home Mortgage Disclosure Act (1975), and significant mortgage funds began to flow back into inner-city neighborhoods only with vigorous enforcement of the Community Reinvestment Act (1977).

Extreme segregation of America’s housing markets was not the result of some “natural” process of self-segregation. For decades it was force-fed by discriminatory “rules of the game” from federal, state, and local governments.

[517 words]

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Module 4: Divided by Income

(draft 9-8-03)

Summary: If housing barriers based purely on race have been coming down, housing barriers based on income have been going up. During the 1970s and 1980s, economic segregation increased in almost 70 percent of major metropolitan areas, including the Denver region. By 1990, metro Denver was the 26th most economically segregated out of the 100 largest metropolitan areas.

Happily, economic segregation ticked downward during the 1990s, lowering Denver’s index from 40 to 39 (33rd out of 100). That downward movement may have been ephemeral. Census 2000 collected income and poverty data for 1999, the peak year of the economic boom. There could not have been a more favorable year to take an economic snapshot of America’s cities; the Current Population Survey reported that poverty rates had reached historic lows for African Americans and Hispanics that year with favorable economic consequences for America’s cities. A snapshot of America’s metropolitan areas would probably not find the same favorable picture in 2003 in the midst of current economic slump.

* * *

In module 3 on race and ethnicity we have seen that, in the Denver region as across metropolitan America, the level of residential segregation for African Americans has slowly decreased from levels of hyper-segregation not experienced by any other ethnic group in our history. We have also seen that, though beginning at much lower levels than for African Americans, residential segregation has been increasing for Hispanics in regions characterized by a major influx of new immigrants.

What if we apply the same analysis to the issue of economic segregation – the degree to which poor persons are isolated from middle-class, mainstream communities?

Table 4.1 summarizes poverty rates by county over the past thirty years. As a region, the Denver area has had consistently lower poverty rates than the nation’s metropolitan average. Poverty, however, is dispropor-tionately concentrated in the city and, increasingly, in Adams County.

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Table 4.1 Poverty rates in metro Denver

from 1970 to 2000

County 1970 1980 1990 2000 Metro 9.6% 8.2% 9.7% 8.1% Denver 13.8% 13.7% 17.1% 14.3% Adams 6.8% 7.6% 10.4% 8.9% Arapahoe 5.9% 4.6% 5.9% 5.8% Jefferson 5.4% 4.6% 5.8% 2.1% Douglas na 4.1% 3.2% 5.2%

The degree of disproportion can best be seen by devising a “fair

share of poverty index” (Table 4.2) by simply dividing a jurisdiction’s poverty rate by the regional poverty rate. An index of 100 indicates that the jurisdiction has the same poverty rate as the region as a whole – that is, the jurisdiction has its “fair share” of poverty. An index number less than 100 means that the jurisdiction has less than its “fair share;” an index number greater than 100 means that the jurisdiction has more than its “fair share.”

Table 4.2 “Fair share of poverty” rates in metro Denver

from 1970 to 2000

County 1970 1980 1990 2000 Metro 100 100 100 100 Denver 144 167 176 177 Adams 71 93 107 110 Arapahoe 61 56 61 72 Jefferson 56 56 60 64 Douglas na 50 33 26

Regional trends in the fair share of poverty index tracked trends in relative income discussed in module 2. Just as Denver’s income has steadily declined relative to the regional average, Denver’s fair share of poverty index has steadily risen (that is, gotten worse). At an index of 177 in 2000, Denver is approaching having twice its fair share of poor people.

In like fashion, Adams County’s index as steadily risen from below its fair share in 1970 (71) to slightly above its fair share in 2000 (110). Sub-

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fair share Arapahoe and Jefferson counties have trended slightly upward, Douglas County’s high-end suburbanization policies have driven its fair share index to as low a level as I have found in any metro area.

Tables 4.1 and 4.2 summarize an overview of poverty trends from a jurisdictional perspective. What about trends at the neighborhood level? Table 4.3 tracks changes in the “segregation index” applied not to racial minorities but to another minority in our society – the poor. As in the racial segregation index, on a scale of 0 to 100, a value of 0 would equal total economic integration and 100 would be total economic apartheid.18 I’ll use the same set of peer regions that were used as comparisons to the Denver region for racial trends in module 4.

If housing barriers based purely on race have been coming down, barriers based on income have been going up. During the 1970s and 1980s, economic segregation increased in almost 70 percent of major metropolitan areas, including the Denver region. By 1990, metro Denver was the 26th most economically segregated out of the 100 largest metropolitan areas.

Table 4.3

Residential segregation of poor persons (index: 0 to 100; 100 = total economic apartheid)

metro area 1970* 1980 1990 2000 Denver 36 36 40 39 San Francisco 33 31 33 30 San Jose 29 29 33 30 Phoenix 36 34 39 40 Austin 34 37 39 41 Sacramento 27 24 32 37 Milwaukee 39 46 55 51 Johnson City-Kingsport-Bristol na 21 22 19 100 large metro areas 33 34 37 36 * some metro areas in 1970 were defined slightly differently than in succeeding years

18 The “segregation index” used is a dissimilarity index that measures how evenly or unevenly a minority population is distributed compared to the majority population. On a scale of 0 to 100, the higher the value, the more segregated the region. Metro Denver’s economic segregation index of 39 in 2000, for instance, means that 39 percent of all poor people would have to move in order for every neighborhood to have the same percentage of poor persons as the regional average (8.1 percent).

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Happily, economic segregation ticked downward during the 1990s, lowering Denver’s index from 40 to 39 (33rd highest out of 100). That downward movement may have been ephemeral. Census 2000 collected income and poverty data for 1999, the peak year of the economic boom. There could not have been a more favorable year to take an economic snapshot of America’s cities; the Current Population Survey reported that poverty rates had reached historic lows for African Americans and Hispanics that year with favorable economic consequences for America’s cities. With new jobs in hand, many formerly poor families’ incomes rose above the federally-defined poverty threshold (which was $17,400 for a family of four in 1999). Thus, poor neighborhoods became more economically integrated statistically because many still poor households now found many formerly poor neighbors now “not poor” without anyone having moved. A snapshot of America’s metropolitan areas would probably not find the same favorable picture in 2003 in the midst of current economic slump.

Of more permanent impact perhaps on lowering the degree of economic segregation, however, has been implementation of HUD’s HOPE VI program. During the 1990s, HUD made $3.7 billion in HOPE VI grants to 53 housing authorities in the USA’s largest metropolitan areas to tear down large public housing projects and rebuild them as mixed-income communities; these new developments often included substantial market rate housing. Those former public housing tenants that did not return to the rebuilt, economically more integrated developments were provided with housing vouchers and relocated to private rental housing. Though many former project tenants were not relocated into the low-poverty, less minority-impacted neighborhoods envisioned by HOPE VI advocates, almost all relocated households ended up in substantially less poverty-impacted surroundings than their former homes in the projects had been.

HUD awarded the Denver Housing Authority $52 million in HOPE VI grants. By April 2000 (the date of the census date), the housing authority had cleared the sites of the former Quigg Newton Homes, Curtis Park, and Arapahoe Courts and rebuilt them as more economically diverse developments.

Though far below Milwaukee’s index (51), the USA’s most economically segregated metro area in 2000, Denver’s economic segregation index (39) was still above the average for the 100 largest metro areas (36)

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and far above the level of economic segregation in Johnson City-Kingsport-Bristol TN-VA (19). Though Denver’s poverty rate (8.1 percent) was well below Milwaukee’s (10.6 percent), both were far below Johnson City-Kingsport-Bristol’s poverty rate (14.0 percent). Why should a region with such a high poverty rate like Johnson City-Kingsport-Bristol have the lowest level of economic segregation?

White Slums, Black Ghettos, Hispanic Barrios

That question brings us back to the central role of race in the phenomenon of the concentration of poverty. Located in the Great Smoky Mountain region of Eastern Tennessee and Southwestern Virginia, the Johnson City-Kingsport-Bristol region is virtually all white; in 2000, the region was 95.6 percent non-Hispanic white. There were plenty of poor people, but almost all were white, and poor whites rarely live highly clustered together in poor neighborhoods.

In America in 2000, there were 14.4 million poor whites compared with 8.0 million poor blacks and 7.7 million poor Hispanics. In a typical metropolitan area, however, three out of four poor whites lived in middle-class neighborhoods scattered widely across the whole region; three out of four poor blacks and one out of two poor Hispanics lived in poverty-impacted, inner-city neighborhoods. White slums were rare. Concentrated poverty was a phenomenon of black ghettos and Hispanic barrios.

As Table 4.4 shows, in the 1990 census,19 only 21 percent of the Denver region’s poor whites compared with 59 percent of its poor blacks and 61 percent of its poor Hispanics lived in high poverty neighborhoods (where poverty rates exceeded 20 percent). The disparities were even greater with regard to very high poverty neighborhoods (where poverty rates exceeded 40 percent). Only one out of 50 poor whites but 18 percent of poor blacks and 12 percent of poor Hispanics lived in such “killer neighborhoods.”

Thus, concentrated poverty is a racially-tinged phenomenon. In part, high-poverty black ghettos are a reflection of racial discrimination. Historically, American society segregated persons more by race than by income. With poverty rates much higher in Denver’s black community (24.6 percent in 1989) than in the Anglo community (6.5 percent in 1989), a

19 Census 2000 has not yet released income and poverty data by race. Wherever in this analysis updated census data are not presented, they have not yet been released.

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highly segregated society racially will throw together many poor persons who are black in a limited number of neighborhoods.

Table 4.4 Concentration of poverty by race in metro Denver in 1990 Census

percent percent

living in living in number high very high of poverty poverty poor tracts tracts Whites 80,469 21% 2% Blacks 22,710 59% 18% Hispanics 45,565 61% 12%

But such racially-tinged concentration of poverty is also a reflection of past public housing policy and practices. From the late 1930s through the mid-1970s city public housing authorities built large projects. In many cities, public housing projects were explicitly segregated. After federal civil rights laws forced integration of segregated projects, most formerly “white” city projects became overwhelmingly black.

Coming later to the game, suburban housing agencies almost never built projects (except apartment complexes exclusively for the elderly poor). Suburban housing assistance took the form of rent vouchers for use in private rental housing; thus, the suburban poor (primarily white) were more scattered within the suburban private apartment market.

Until Congress amended its rules in 1989 to allow “portability,” a housing authority restricted its clients to using Section 8 housing vouchers only within its jurisdiction. Thus, poor suburban families seeking assistance (largely white) were offered suburban rent vouchers; poor city families seeking assistance (largely black) were typically offered assignment to a city project or a rent voucher that could only be used within the city limits.

In various regions I have visited, I have found that a very high poverty neighborhood (an over 40 percent poverty rate) almost invariably has a large federal public housing project located in or adjacent to it (e.g. Quigg Newton

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Homes, Curtis Park, Arapahoe Courts, etc.) or has a high concentration of Section 8 rent vouchers.

To a lesser degree, the above observations apply to concentrated poverty within the Hispanic community, though the “ponding” together of recent immigrants (typically, with higher poverty rates than more established Hispanics) is also a factor. In 1990, the poverty rate among Hispanics was 30.6 percent – about one-quarter higher than for African Americans.

Higher poverty levels and significant degrees of housing segregation translate into high poverty neighborhoods. Table 4.5 charts the growth of high poverty neighborhoods (20-40 percent poverty rates) and very high poverty neighborhoods (more than 40 percent poverty rates).

Table 4.5 Growth of poverty neighborhoods in metro Denver

from 1970 to 1990

high poverty very high poverty County 1970 1990 1970 1990 Metro 29 44 9 11 Denver 22 29 9 10 Adams 3 9 0 0 Arapahoe 2 3 0 0 Jefferson 2 3 0 1 Douglas 0 0 0 0

With the drop in the regional poverty rate (from 9.7 percent in 1990 to 8.1 percent in 2000) and the slight lessening of economic segregation, the numbers of high poverty census tracts may have declined slightly. However, the pattern of a high concentration of poverty within the city but growing “hot spots” in older suburban jurisdictions probably has continued.

Table 4.6 speaks to another phenomenon: the feminization of poverty. It contrasts by racial group the percentage of single mothers who are poor with the percentage of married couples with young children who are poor. It is clear that the most successful anti-poverty strategy is to be the child of two married parents (who are often dual income earners as well). Some 97 percent of white married parents, 92 percent of black married parents, and 87 percent of Hispanic married parents were not poor in 1990. By contrast, being the child of a single mother is the surest path to poverty; 25 percent of

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white single mothers, 48 percent of black single mothers, and 54 percent of Hispanic single mothers were poor.20

Table 4.6 Poverty percentage by family structure

in metro Denver in 1990 Anglo black Hispanic Married couples with children 18 years or less 3% 8% 13% Single mothers with children 18 years or less 25% 48% 54% Ratio of married couples with children To single mothers 465:100 97:100 223:100

The decline of the traditional, two-parent family and the rise in single mothers has been occurring across racial groups and within all Western societies. The shifting proportions have been particularly sharp in metro Denver (Table 4.7). Thirty years ago a child in metro Denver was almost eight times as likely to have two married parents as to be a child of a single mother. Today the odds are less than four-to-one. For African American children (as Table 4.6 shows), the odds are less than 50-50. In1989, for every 100 black single mothers, there were only 97 black married couples with children. The ratio probably deteriorated further in the 1990s.

Table 4.7 Shifting family structure

in metro Denver from 1970 to 2000 ratio of number of number of married couples married single to single couples mothers mothers

1970 140,986 18,075 780:100 1980 157,413 33,617 468:100 1990 170,919 45,953 372:100 2000 197,582 52,574 376:100

20 Census 2000 reports that almost as many unmarried couples (who may also be reported as single mothers) are raising children as are married couples, having two incomes from such arrangements may help explain the degree to which single mothers are not poor.

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This discussion comes back to focus on Denver’s 11 very high poverty neighborhoods. In 1990, there were only 1,155 married couples with children compared with 2,262 single mothers in those 11 census tracts – in other words, barely one married couple for every two single mothers. In all the rest of the Denver metro area (that is, minus these 11 census tracts) there was an average of almost four married couples with children for every single mother. There was an eight to one swing in average family composition between the 11 poorest neighborhoods – that were substantially creations of federal public housing policy – and everywhere else. To be raised in such neighborhoods (and “educated” in such neighborhood schools) was to be cut off from significant exposure to successful married couples – a proven path to economic success.

Summing Up

Social policy or personal failure – we can argue about the relative weight that should be given to the causes of poverty in the Denver region. But one fact is unarguable: no child ever chooses into what family or into what community the child is born. Poverty creates heavy burdens for any family regardless of race. But only one out of five poor whites in the Denver area lives in a high poverty neighborhood – and only one out of fifty poor whites lives in a very high poverty neighborhood. For poor whites, poverty is a family crisis, not a community crisis.

For poor blacks and Hispanics, by contrast, six out of ten live in high poverty neighborhoods, and one out of five and one out of eight, respectively, live in very high poverty neighborhoods. Poverty is a community crisis.

Most poor white children (however marginalized) live in mainstream communities of opportunity. Most poor black and Hispanic children live in high poverty ghettoes and barrios where real educational and employment opportunity lies beyond their reach.

There’s a world of difference.

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Suggested reading: The definitive analysis of the concentration of poverty is Paul Jargowsky’s Poverty and Place: Ghettoes, Barrios, and the American City. Russell Sage Foundation: New York (1996). Its analysis, however, ends with the 1990 census.

Two important updates, analyzing a reduction in the concentration of poverty in Census 2000, are Jargowsky’s “Stunning Progress, Hidden Problems: the Dramatic Decline of Concentrated Poverty in the 1990s,” Center for Urban and Metropolitan Policy: The Brookings Institution (May 2003) (www.brookings.edu/urban) and G. Thomas Kingsley and Kathryn L. S. Pettit, “Concentrated Poverty: a Change in Course,” The Urban Institute (May 2003) (www.urban.org/nnip). Jargowsky finds “stunning progress” because a large number of previously very high poverty census tracts had dropped below the 40 percent threshold by 1999; Kingsley broadens the perspective to examine less encouraging trends for the 10-20 percent, 20-30 percent, and 30-40 percent tracts as well.

Finally, Chapter 6 (“The Poverty Machine”) in my Inside Game/Outside Game weighs various explanatory factors for poverty, including the feminization of poverty households.

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Module 5: Housing Policy Is School Policy

(draft 9-08-03)

Summary: Neighborhood residential segregation is magnified in enrollment patterns of neighborhood schools. Metro Denver elementary schools are no exception. At one extreme, in 2001 there were 39 elementary schools that were 90 to 100 percent black and Hispanic; 27 percent of the region’s black and Hispanic pupils attended these virtually all-minority schools. In fact, 68 percent of black and Hispanic pupils attended majority minority schools.

At the other extreme, there were 108 elementary schools that were over 90 percent Anglo; they enrolled 43 percent of the region’s Anglo pupils. Ninety-one (91) percent of Anglo pupils attended majority Anglo schools.

Progress has been slight in recent years. At the beginning of the decade, the black segregation index for the Denver region’s elementary schools was 65 (1989-91); by 1997-99, it had improved slightly to 62. But the trend was towards greater segregation of Hispanic pupils; the Hispanic school segregation index worsened from 47 to 50 during the decade.

Racially segregated schools are also economically segregated schools. Of the 39 schools that were 90-100 percent minority, all 39 had a majority of low-income pupils. In fact, 99 of the 124 majority minority schools also had a majority of low-income pupils that qualified for subsidized meals. The odds are four to one than a pupil in a majority-minority school will also be attending a majority low-income school.

The results are even more striking at the other end of the scale. None of 108 schools that are 90 percent or more Anglo have majorities of low-income pupils nor do any of the 64 schools that are 80 to 90 percent Anglo! In fact, only 11 of all 267 majority Anglo schools have majorities of low-income pupils. In other words, the odds are 24 to one that a child in a majority Anglo school will have a majority of middle-class classmates.

Economic segregation is getting worse with the school economic segregation index rising from 50 in 1989-91 to 57 in 1997-99. This was the 13th highest level of economic school segregation (and the eighth fastest

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increase) out of 81 major metro areas for which information for the full decade was available.

There was a very high correlation between a school’s socioeconomic profile and a school’s test scores on the Colorado School Assessment Program (CSAP): a school’s percentage of low-income pupils explained 77 percent of the school-by-school variation in CSAP results. In somewhat imprecise layman’s terms, knowing the percentage of low-income pupils, one can predict a school’s percentage scoring proficient or advanced on the CSAP tests and fall within 10 percentage points of the actual percentage about 95 percent of the time.

A study of the Denver Public Schools by Diane Lefly confirmed locally what other studies nationally have consistently found.

• Low-income students (as measured by eligibility for federal free or reduced-cost school lunches) perform significantly better in low-poverty schools than in schools where over half the students are poor. For example, on the 2001 CSAP reading test, 53 percent of low-income elementary school students scored proficient or advanced in schools where fewer than 25 percent of student qualified for free or reduced price lunch. However, in schools where over 75 percent of the students were poor, just 33 percent of the low-income students scored proficient or advanced.

• Non-poor students perform well on standardized tests in schools with low to moderate levels of poverty. However, the scores of non-poor students begin to deteriorate significantly in schools where over 50 percent of all students are poor. 83 percent of non-poor students scored proficient or advanced on the 2001 reading CSAP [in schools with less than 25 percent of low-income classmates]. However, in schools with more than 75 percent low-income students, only 49 percent of the non-poor students scored proficient or advanced.

• Proficient CSAP scores are far lower within the proficiency band in high-poverty schools than in low-poverty schools. In other words, even “good” test scores are less “good” in high-poverty schools than in low-poverty schools.”

* * *

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In 1966, sociologist James Coleman released his path-breaking study, Equality of Educational Opportunity. Sponsored by the then-US Office of Education, Coleman and his research team examined pupil, family, and school characteristics for over a million public school children in search of factors that were associated with academic success.

The Coleman Report concluded that the socioeconomic characteristics of a child and of the child’s classmates (measured principally by family income and parental education) were the overwhelming factors that accounted for academic success. Nothing else – expenditures per pupil, pupil-teacher ratios, teacher experience, instructional materials, age of school buildings, etc. – came close. “The educational resources provided by a child’s fellow students,” Coleman summarized, “are more important for his achievement than are the resources provided by the school board.” So important are fellow students, the report found, that “the social composition of the student body is more highly related to achievement, independent of the student’s own social background, than is any school factor.”21

For over three decades, educational researchers, including Coleman, have revisited, refined, and debated Coleman’s original findings. There has been no more consistent finding of educational research that the paramount importance of a school’s socioeconomic makeup on academic achievement. Summarizing the enormous body of research, the Century Foundation’s Richard D. Kahlenberg writes

“What makes a school good or bad is not so much the physical plant and facilities as the people involved in it – the students, the parents, and the teachers. The portrait of the nation’s high poverty schools is not just a racist or classist stereotype: high-poverty schools are often marked by students who have less motivation and are often subject to negative peer influences; parents who are generally less active, exert less clout in school affairs, and garner fewer financial resources for the school; and teachers who tend to be less qualified, to have lower expectations, and to teach a watered-down curriculum. Giving all students access to schools with a core of middle class

21 Quoted in Richard D. Kahlenberg. All Together Now: Creating Middle-Class Schools through Public School Choice. Brookings Institution Press: Washington, DC. (2001), page 28. Kahlenberg’s 33 pages of footnotes to chapters 3 and 4 catalogue most major studies on the effects of racial and economic school integration.

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students and parents will significantly raise the overall quality of schooling in America.”22

Enrollment Patterns in Metro Denver’s Schools

With their system of neighborhood schools, the Denver region’s school enrollment patterns reflect residential patterns by race and income. Table 5.1 summarizes overall enrollment trends over the past five years.

Table 5.1 Overall enrollment levels

in metro Denver school districts 1998-2002

School district 1998 2002 pct Denver City 68,790 71,972 + 5% Adams County 57,067 65,990 + 16% Mapleton 1 4,939 5,623 + 14% Northglenn-Thornton 12 27,955 33,522 + 20% Adams County 14 6,102 6,698 + 10% Brighton 27J 4,980 7,277 + 46% Bennett 29J 995 1,035 + 4% Strasburg 31J 592 823 + 39% Westminster 50 11,504 11,012 - 4% Arapahoe County 92,849 101,285 + 9% Englewood 1 4,568 4,200 - 8% Sheridan 2 2,102 1,936 - 8% Cherry Creek 5 40,089 45,738 + 14% Littleton 6 16,399 16,408 + 0.1% Deer Trail 26J 186 196 + 5% Adams-Arapahoe 28J 29,027 32,253 + 11% Byers 32J 478 554 + 16% Douglas County RE-1 29,847 40,511 + 36% Jefferson County R-1 88,654 87,925 - 1% Metro totals 337,207 367,683 + 9 % Contrary to many central city school systems, Denver Public Schools

gained enrollment slightly (+ 5 percent). Most older, more settled suburbs’ school enrollments either dropped (Englewood, Sheridan, all of Jefferson County Public Schools) or were stable (Littleton). Enrollment in

22 Op. cit., page 47.

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Douglas County schools exploded (+ 36 percent in just five years) as it did in Northglenn-Thornton (+ 20 percent) and Brighton (+ 46 percent), other outer suburbs.

Tables 5.2 traces a more complex pattern of enrollments by race, focusing on trends among black, Hispanic, and Anglo students. 23

Table 5.2 Black, Hispanic, and Anglo enrollment levels in metro Denver school districts 1998-2002

School district 1998 2002 pct Denver City 68,790 71,972 + 5% Black 14,471 13,749 - 5% Hispanic 34,230 40,395 + 18% Anglo 16,792 14,603 <- 13%> Adams County 57,067 65,990 + 16% Black 1,135 1,600 + 41% Hispanic 16,796 24,562 + 46% Anglo 35,752 36,011 + 0.7% Mapleton 1 4,939 5,623 + 14% Black 108 135 + 25% Hispanic 1,657 2,868 + 73% Anglo 2,885 2,333 <- 19%> Northglenn-Thornton 12 27,955 33,522 + 20% Black 590 859 + 46% Hispanic 5,549 8,451 + 52% Anglo 20,355 22,189 + 9% Adams County 14 6,102 6,698 + 10% Black 185 232 + 25% Hispanic 3,403 4,579 + 35% Anglo 2,365 1,710 <-28%> Brighton 27J 4,980 7,277 + 46% Black 35 85 + 143% Hispanic 1,981 2,991 + 51% Anglo 2,870 4,043 + 41%

23 Proportionally, the number of Asian and Native American students grew significantly during the decade but still only accounted for 5 percent of total enrollment by 2000. “Anglo” means “non-Hispanic white.”

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Table 5.2 (continued) Black, Hispanic, and Anglo enrollment levels in metro Denver school districts 1998-2002

School district 1998 2002 pct

Bennett 29J 995 1,035 + 4% Black 9 19 + 111% Hispanic 50 78 + 56% Anglo 917 924 + 1% Strasburg 31J 592 823 + 39% Black 2 8 + 300% Hispanic 28 50 + 79% Anglo 549 748 + 36% Westminster 50 11,504 11,012 - 4% Black 206 262 + 27% Hispanic 4,128 5,545 + 34% Anglo 5,811 4,064 <- 30%> Arapahoe County 92,849 101,285 + 9% Black 10,826 12,621 + 17% Hispanic 11,158 20,091 + 80% Anglo 66,101 62,821 <-5> Englewood 1 4,568 4,200 - 8% Black 138 173 + 25% Hispanic 770 963 + 25% Anglo 3,485 2,899 <- 17%> Sheridan 2 2,102 1,936 - 8% Black 70 79 + 13% Hispanic 798 1,052 + 32% Anglo 1,122 704 <- 37%> Cherry Creek 5 40,089 45,738 + 14% Black 2,253 4,924 + 119% Hispanic 2,387 4,271 + 79% Anglo 32,125 33,287 + 4% Littleton 6 16,399 16,408 + 0.1% Black 228 285 + 25% Hispanic 888 1,327 + 49% Anglo 14,798 14,217 <-4%> Deer Trail 26J 186 196 + 5% Black 2 2 0% Hispanic 5 3 - 40% Anglo 179 183 + 2% Adams-Arapahoe 28J 29,027 32,253 + 11% Black 7,129 7,152 + 0.3% Hispanic 6,295 12,450 + 98% Anglo 13,937 11,007 <-21%>

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Table 5.2 (continued)

Black, Hispanic, and Anglo enrollment levels in metro Denver school districts 1998-2002

School district 1998 2002 pct

Byers 32J 478 554 + 16% Black 6 6 0% Hispanic 15 25 + 67% Anglo 455 522 + 15% Douglas County RE-1 29,847 40,511 + 36% Black 371 663 + 79% Hispanic 1,223 2,360 + 93% Anglo 27,328 35,866 + 31% Jefferson County R-1 88,654 87,925 - 1% Black 1,110 1,430 + 29% Hispanic 9,117 12,419 + 36% Anglo 75,022 70,216 <-6%> Metro totals 337,207 367,683 + 9 % Black 27,913 30,063 + 8% Hispanic 75,524 99,827 + 32% Anglo 220,995 219,517 <-0.07> There are three notable trends. First, the enormous increase in

Hispanic students overall – almost one-third in just five years – and their rapid growth in the inner suburbs. In this five year period, Denver, Westminster, and Sheridan joined Adams County District 14 as majority Hispanic systems. And Adams-Arapahoe School District, which already had a substantial Hispanic enrollment (6,295 in 1998) saw that almost double to 12,450 in 2002.

Second, the steady dispersion of black students into primarily inner suburban school districts. In 1998, slightly over half (52 percent) of all black students attended Denver Public Schools. Having been the only district to lose black students, Denver Public Schools enrolled only 46 percent five years later.

Third, the stagnation in the number of Anglo (that is, non-Hispanic white) students region-wide. The Denver, Mapleton, Adams County 14, Westminster, Englewood, Sheridan, Littleton, Adams-Arapahoe, and Jefferson County school districts all experienced declining Anglo enrollment. While the city schools and inner-suburban districts were losing

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Anglo students, clearly Anglo, child-rearing families were decamping to the outer suburbs with Brighton and Douglas County posting double-digit increases in Anglo enrollment.

District-wide statistics tend to mask the very substantial degree of segregation by race that still exists in the area’s public schools. Tables 5.3a and 5.3b summarize racial enrollment patterns in the region’s 391 elementary schools in 2001.

Table 5.3a Enrollment by race in 124 majority minority elementary schools

in metro Denver in 2001

pct black no. of minority Anglo cumulative pct of and Hispanic schools pupils pupils all minority pupils 90-100% minority 39 17,981 764 27% 80-89.9% minority 23 9,063 1,085 41% 70-79.9% minority 18 6,037 1,728 50% 60-69.9% minority 20 6,103 2,759 59% 50-59.9% minority 24 6,138 4,367 68%

Table 5.3b Enrollment by race in 267 majority Anglo elementary schools

in metro Denver in 2001

pct no. of Anglo minority cumulative pct of Anglo schools pupils pupils all Anglo pupils 50-59.9% Anglo 23 4,929 4,492 91% 60-69.9% Anglo 25 6,445 3,843 86% 70-79.9% Anglo 47 14,476 5,094 80% 80-89.9% Anglo 64 25,238 4,439 66% 90-100% Anglo 108 45,742 3,208 43% For many phenomena in nature and society a “normal” distribution is

a bell-shaped curve. When dealing with most racial phenomena in American society, a bi-polar curve is typical with blacks and Hispanics clustered at one end and Anglos at the other. Metro Denver elementary schools are no exception. At one extreme, in 2001 there were 39 elementary schools that were 90 to 100 percent black and Hispanic; 27 percent of the region’s black and Hispanic pupils attended these virtually all-minority schools. In fact, 68 percent of black and Hispanic pupils attended majority minority schools.

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At the other extreme, there were 108 elementary schools that were over 90 percent Anglo; they enrolled 43 percent of the region’s Anglo pupils. Ninety-one (91) percent of Anglo pupils attended majority Anglo schools.

Progress has been slight in recent years. At the beginning of the decade, the black segregation index for the Denver region’s elementary schools was 68 (1989-91); by 1997-99, it had worsened slightly to 69; by 2001, there may have been a slight improvement to 67.24 But the trend was towards constantly greater segregation of Hispanic pupils; their school segregation index worsened from 56 (1989-91) to 60 (1997-99) to 62 (2001).

Racially segregated schools = economically segregated schools

Table 5.4 summarizes enrollment by students’ economic status. As is typical, the area’s school districts categorize students economically in just two groups: those who qualify for “Free And Reduced-price Meals” (FARM) and those who do not (non-FARM).25 In 2001 the school districts with the highest proportion of low-income students was Adams County #14 (65.2 percent), followed by Denver (64.3 percent) and Sheridan (54.9 percent). The districts with the lowest percentage of FARM students were Cherry Creek (10.7 percent), Littleton (9.8 percent), and Douglas County (1.9 percent – an extraordinarily low number).

Overall, the regional percentage of free-lunch only eligible pupils increased from an average of 19.9 percent in 1989-91 to 24.5 percent in 1997-99 (a statistic that omits those that were eligible for partially subsidized meals on a sliding scale of family income). The economic school segregation index rose from 50.0 in 1989-91 to 57.3 in 1997-99. This was the 13th highest level of economic school segregation (and the eighth fastest increase) out of 81 major metro areas for which information 24 These are slightly apples-and-oranges statistics in this paragraph. The first two segregation indices refer only to fully subsidized pupils (less than 135 percent of the poverty level). The most recent statistic includes partially subsidized pupils as well (between 135 percent and 185 percent of the poverty level). 25 The FARM group itself divides into two groups: students with family incomes up to 135 percent of the poverty level (who qualify for free meals) and students with family incomes from 135 percent to 185 percent of the poverty level, who qualify for subsidized meals on a sliding scale. Though many states report data separately for the two groups, Colorado’s school report cards do not..

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for the full decade was available.26 For 2001, the economic segregation index (including pupils receiving partially subsidized meals) had increased further to 59.

Table 5.4 Free-and reduced-price meals (FARM) pupils

in metro Denver school districts in 2001

School district number pct pct of total Denver City 44,148 64.3% 45.8% Adams County 19,183 31.3% 19.9% Mapleton 1 2,019 37.9% 2.1% Northglenn-Thornton 12 6,691 21.8% 6.9% Adams County 14 4,094 65.2% 4.2% Brighton 27J 1,904 29.8% 2.0% Bennett 29J 116 12.0% 0.1% Strasburg 31J 93 12.2% 0.1% Westminster 50 4,266 39.2% 4.4% Arapahoe County 19,591 20.2% 20.3% Englewood 1 1,101 26.7% 1.1% Sheridan 2 894 54.9% 0.9% Cherry Creek 5 4,632 10.7% 4.8% Littleton 6 1,594 9.8% 1.7% Deer Trail 26J 24 13.7% 0.02% Adams-Arapahoe 28J 11,199 36.3% 11.6% Byers 32J 147 29.3% 0.2% Douglas County RE-1 710 1.9% 0.7% Jefferson County R-1 12,762 14.8% 13.2% Metro totals 96,394 25.5% 100.0% Tables 5.5a and 5.5b illustrate the high correlation between racial

segregation and economic segregation.27 Of the 39 schools that were 90-100 percent minority, all 39 had a majority of FARM pupils; on average, 85 percent of pupils in these schools qualified for subsidized meals. In fact, 99 of the 124 majority minority schools also had a majority of low-income

26 Information comes from my study “Trends in School Segregation” in Divided We Fail: Coming Together through Public School Choice: The Report of the Century Foundation Task Force on the Common School. The Century Foundation Press: New York (2002) . 27 Using least-squares linear regression analysis, the adjusted r-square between percentage of black and Hispanic pupils (independent variable) and percentage of FARM pupils (dependent variable) is 0.74.

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pupils that qualified for subsidized meals. Combining the findings of Tables 5.3a and 6.5a, about 68 percent of all black and Hispanic pupils attended elementary schools with majorities of low-income pupils.

Table 5.5a Low-income (FARM) pupils in 124 majority minority elementary schools

in metro Denver in 2001

pct black no. of majority average and Hispanic schools FARM schools pct FARM 90-100% minority 39 39 85% 80-89.9% minority 23 21 74% 70-79.9% minority 18 13 61% 60-69.9% minority 20 15 58% 50-59.9% minority 24 11 48%

Table 5.5b Low-income (FARM) pupils in 267 majority Anglo elementary schools

in metro Denver in 2001

pct no. of Majority average Anglo schools FARM schools pct FARM 50-59.9% Anglo 23 6 38% 60-69.9% Anglo 25 4 35% 70-79.9% Anglo 47 1 23% 80-89.9% Anglo 64 0 15% 90-100% Anglo 108 0 4% The results are even more striking at the other end of the scale. None

of 108 schools that are 90 percent or more Anglo have majorities of FARM pupils nor do any of the 64 schools that are 80 to 90 percent Anglo! In fact, only 11 of all 267 majority Anglo schools have majorities of FARM pupils. In other words, the odds are 24 to one that a child in a majority Anglo school will have a majority of middle-class (non-FARM) classmates. In all, 91 percent of all Anglo pupils attended majority middle-class schools.

Racially segregated schools are economically segregated schools. What are the educational consequences?

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Income and Educational Achievement

I myself have recently studied the interrelationship of economic status and academic achievement for all 391 public elementary schools in metro Denver. From each school’s “report card” on the Internet, I tabulated each school’s percentage of students that achieved proficient and advanced levels on 3rd, 4th, and 5th grade reading, writing, and math tests of the Colorado School Assessment Program (CSAP) for 2000, 2001, and 2002. I then compared the percentage of pupils achieving proficient and advanced levels on the CSAP test battery with the average percentage of FARM pupils in 2001 (the only year for which such data was still available on the Internet).

There was a very high correlation; a school’s percentage of FARM pupils explained 77 percent of the school-by-school variation in CSAP results.28 In somewhat imprecise layman’s terms, knowing the percentage of FARM pupils, one can predict a school’s percentage scoring proficient or advanced on the CSAP tests and fall within 10 percentage points of the actual percentage about 95 percent of the time.

The Piton Foundation Study

The school report cards currently do not break down test scores by sub-group (e.g. FARM pupils, non-FARM pupils, etc.) However, Denver’s Piton Foundation commissioned research by Dianne Lefly, a Ph. D statistician and the research manager in the Denver Public Schools Assessment & Testing Department. Through her professional role within DPS, Dr. Lefly had access to data not otherwise available publicly. What follows are key sections of Dr. Lefly’s report for the Denver Public Schools only as presented in the Piton Foundation’s Term Paper (Vol. 1, No. 2, May 2002).

“Lefly looked at scores over the last three years of elementary students (grades three through five) on the Colorado Student Assessment Program (CSAP) and the Iowa Test of Basic Skills reading test. Lefly analyzed the performance of students who qualify for free or reduced-price lunches in schools with low, medium, and high rates of poverty. [Her] analysis also included non-subsidized lunch students in schools with varying levels of poverty.

28 Using linear regression analysis, the adjusted r-square was 0.77 with a standard error of .10. The relationship was statistically significant at a <0.01% level of significance.

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“Lefly’s analysis found a strong – 0.851 – correlation between student socioeconomic status and test scores. This means that 85 percent of the differences in test scores between high and low-performing student can be explained by socioeconomic status. She also performed a multi-variable “regression analysis,” seeking associations between other school factors and test score performance.

“But no other factor remotely approaches statistical significance. The other variables she tested were size of school, percent of English language learners, percent of stable students, percent of high- and low-experience teachers, and percent of stable teachers.

“Among the findings (the results are summarized in Table 5.6):

• Low-income students (as measured by eligibility for federal free or reduced-cost school lunches) perform significantly better in low-poverty schools than in schools where over half the students are poor. For example, on the 2001 CSAP reading test, 53 percent of low-income elementary school students scored proficient or advanced in schools where fewer than 25 percent of student qualified for free or reduced price lunch. However, in schools where over 75 percent of the students were poor, just 33 percent of the low-income students scored proficient or advanced.

• Non-poor students perform well on standardized tests in schools with low to moderate levels of poverty. However, the scores of non-poor students begin to deteriorate significantly in schools where over 50 percent of all students are poor. 83 percent of non-poor students scored proficient or advanced on the 2001 reading CSAP [in schools with less than 25 percent of low-income classmates]. However, in schools with more than 75 percent low-income students, only 49 percent of the non-poor students scored proficient or advanced.

• Proficient CSAP scores are far lower within the proficiency band in high-poverty schools than in low-poverty schools. In other words, even “good” test scores are less “good” in high-poverty schools than in low-poverty schools.”

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Table 5.6 Percentage of FARM and Non-FARM elementary school pupils

Achieving Proficient and Advanced Levels in CSAP tests in Denver Public Schools in 2000, 2001, and 2002

Pct of FARM FARM non-FARM < 25% 53% 83% 26-50% 54% 76% 51-75% 42% 67% >75% 33% 49%

Other National Research

That finding is remarkably parallel to the findings of other research, as summarized by Richard Kahlenberg (see footnote 1). However, matching the Piton Foundation study with others that I have done

• in my Albuquerque study, the average pupil from a public housing household increased their CTBS scores by 0.22 percentiles for every one percent increase in middle-class classmates;

• similarly, in my most recent study of 373 elementary schools in the seven-county Baltimore metro area, the average low-income pupil increased their CTBS scores by 0.19 percentiles for every one percent increase in middle-class classmates;

• in my study of 186 school districts in the five largest metro areas of Texas, for every one percent increase in middle-class pupils, its low-income pupils increase their chances of achieving a passing rate on the Texas state exams (Texas Assessment of Academic Skills, or TAAS) by 0.27 percentage points; and

• in my study of 60 elementary schools in Madison-Dane County, Wisconsin, for every one percent increase in middle-class classmates, a low-income pupil’s likelihood of scoring at the advanced/proficient score on that state’s WINSS tests (Wisconsin Successful Schools) increased by 0.64 percentage point in reading and 0.72 percentage point in math.

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Summing Up

Mixing low-income children into overwhelmingly middle-class schools produces significant gains in their academic achievement. Indeed, socioeconomic integration may be the best educational strategy for improving their low academic performance levels.

Suggested reading:

The literature on race, class, and academic achievement is voluminous. Richard Kahlenberg’s All Together Now, cited in footnote 1, would be the best introduction to the research.

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Module 6: Portland’s ‘Great Wall’ – It Works!

(draft 9-8-03)

Summary: The 2.1 million-person Denver region contains five counties and 29 municipalities. Colorado law delegates broad land use planning and zoning powers to each jurisdiction. Despite efforts to promote voluntary regional cooperation, the 34 local governments typically plan and implement development policies independent of each other. Colorado voters rejected an anti-sprawl initiative in November 2001.

The 1.5 million-person Portland region contains three counties and 24 municipalities. Oregon law delegates the same broad land use planning and zoning policies to local governments, but Oregon law also requires all local governments to plan together under the guidance of Portland Metro, a popularly-elected regional government. Among other anti-sprawl tools, Metro defines and enforces a regional “urban growth boundary.”

As a result, in the past two decades, the Portland region has evolved as a more compactly developed, transit-oriented, pedestrian-friendly community. Portland must substitute deliberate public policy for the implicit discipline of a semi-arid climate (that necessitates most Denver area development’s hooking on to municipal water utilities). Though not yet a radical departure from America’s auto-centered culture, compared to Denver, Portlanders have slightly fewer vehicles per household, take a bus or street car or walk more to work, have cleaner air, safer streets, and a slightly less time-consuming daily commute, and spend one-third less time stuck in traffic. The Denver region would greatly benefit from a rigorous, anti-sprawl, land use and transportation planning regime like Portland’s.

* * *

Working farms just seven miles from downtown; voter-approved bonds for extending light rail lines ($445 million) and buying open space ($138 million); $13 billion in new, high-tech, private investment; home values doubling in former slums — what in the world is happening in Portland, Oregon?

What’s happening is Portlanders are taming suburban sprawl. Oregon’s Statewide Land Use Planning Act gives local citizens the tools to shape a different — and better — future.

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Enacted in 1973, the state law requires every Oregon county and municipality to adopt a comprehensive land use plan. Every municipality must draw an Urban Growth Boundary. Urban Growth Boundaries must accommodate new homes, offices, factories, and shopping areas projected for the next 20 years.

But outside Urban Growth Boundaries land is zoned for “exclusive farm use” or “exclusive forest use.” No new water or sewer lines, no new four-lane roads, no new houses on 1-, 2-, or 5-acre lots. In Oregon, farms begin at city limits.

The Oregon side of the Portland region is big (1.6 million residents), wide (4,400 square miles), and complex (5 counties, xx municipalities). To address regional needs, the state legislature authorized — and local voters approved — establishing Portland Metro, a regional government.29

Portland Metro runs the Washington Park Zoo, Oregon Convention Center, and regional land fills. Its primary task, however, — emphasized by its voter-approved home rule charter — is regional land use planning.

And the citizens elect the planners. Metro is now governed by a 7-member Metro Council, elected from six districts, and an elected Council President, elected region-wide.30

In 1979 Portland Metro drew the region’s Urban Growth Boundary. Once confirmed by the Oregon Land Conservation and Development Commission, the boundary became law for all local governments.

The Urban Growth Boundary’s anti-sprawl impact was immediate. During the 1980s, the Portland area’s urbanized population (which includes urbanized portions of Vancouver-Clark County, Washington) grew 14 percent but urbanized land expanded only 11 percent; during the 1990s boom, urbanized population grew 35 percent but urbanized land expanded 29 Metro’s jurisdiction covers only all of Multnomah County and urbanizing portions of Clackamas and Washington counties. The Oregon legislature has never expanded Metro’s jurisdiction into Columbia and Yamhill counties, which have been added to Portland’s metro area since the 1990s. 30 From 1979 to 2002, Metro voters elected an Executive Officer as chief administrator. For 2002 the Metro charter was amended to have the presiding officer of the Metro Council elected region-wide and have the Metro Council hire a professional chief operating officer.

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by only 22 percent. The Portland area is becoming more densely developed by popular demand.

Updating the Urban Growth Boundary, in the mid-1990s Portland Metro held 182 public meetings recently, distributed 550,000 copies of alternative plans, and circulated explanatory videos to 17,000 households. To accommodate a projected 20 percent population growth, the Metro Council approved adding just two percent more land — but all 24 local municipalities had testified for zero UGB expansion.

Rebounding from a forest industry slump, Portland experienced a Denver-type boom in the 1990s. High-tech manufacturers like Intel, Fujitsu Microelectronics, and LSI Logic are drawn by the area’s high quality of life (good for recruiting highly skilled professionals) and fast-track methods (guaranteed, controversy-free, 120-day processing of all plans and permits).

With 60 percent of all commuters and visitors arriving by bus and light rail, Downtown Portland is thriving. Four department stores anchor Downtown’s retail sector.

Through private reinvestment, in just five years property values in Albina, Portland’s poorest neighborhood, doubled to $2.6 billion. Similar re-investment and rising property values are occurring in blue-collar suburbs like Gresham, Milwaukie, and Oregon City.

The region’s high-tech economic boom has driven a rapid escalation of home values in the 1990s. The Portland region’s housing market has shot upward from about 8% below national averages to about 23% above (see module 3), and Portland Metro is currently struggling with how to assure continued availability of affordable housing.

“Two sentences express our region’s strategic vision,” Mike Burton, Metro’s then-elected Executive Officer, once told me. “First, everyone will always be able to see Mt. Hood. Second, every child can always walk to a library.”

Think about what those two sentences say about land use, clean air, safe streets, and convenience. No wonder Portland’s emerging as one of America’s hottest areas to live and invest.

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The Oregon System in Detail The Oregon Land Use Act of 1973 dramatically reduced local

government autonomy over land-use decisions in order to achieve statewide growth management policies. At the same time, both the state legislature and local voters combined to create Portland METRO, the USA’s only directly elected regional government, as the land use and transportation planning agency.

The Portland area has the USA’s strongest anti-sprawl, growth management system because Portland METRO functions at the juncture of two powerful forces: strong direction from above (that is, from state government, which has the constitutional authority) and strong influence and accountability from below (that is, to the regional electorate – many of whom are extremely knowledgeable and active in land use and transportation planning issues).

The basic elements of the system can be summarized as follows: Direction from above (state goals, review, and approval):

1) The Oregon Land Use Act mandated that a) all 36 counties must develop comprehensive land use plans

that complied with 14 state goals, and b) all 242 municipalities must adopt comprehensive land use

plans that would be consistent with state goals, the county plan, and that would designate an Urban Growth Boundary (UGB). The UGB must draw a clear line between

i) land preserved exclusively for farming, forestry, and wilderness and recreation areas; no urbanization is allowed, and

ii) land that would be urbanized. Inside the UGB, sufficient land must be provided for 20 years of anticipated residential, commercial, and industrial growth.

2) The Act established a new state regulatory agency, the Land Conservation and Development Commission (LCDC). With seven members appointed by the governor (and confirmed by the state senate) and a professional staff, LCDC was charged with adopting detailed state goals and regulations, reviewing and approving county plans (with their component municipal

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plans), and reviewing and approving subsequent amendments to the approved local plans. In addition, LCDC was given authority to review and approve other state agency plans with land use impacts.

3) Subsequent legislation established the Land Use Board of Appeals (LUBA) as a quasi-judicial body to decide appeals of local government planning decisions. With three, full-time attorneys appointed by the governor (and confirmed by the state senate), LUBA provided a faster, less expensive path for adjudicating disputes than legal challenges in the state court system.

Accountability from below: (Portland Metro) Over a period of more than three decades, the state legislature and local citizens (through five charter referenda and a dozen elections) have collaborated to create Portland METRO, the USA’s only directly elected regional government.

1) Portland METRO’s jurisdiction covers the city of Portland, 23 suburban municipalities, all of Multnomah County, and substantial portions of Clackamas and Washington Counties. (Very rural portions of these two counties far from the urbanized area lie outside of METRO’s official authority.)

2) METRO is not an all-purpose government that replaces any of the 24 municipal and three county governments. It is a special purpose government, established by the legislature and the region’s voters, explicitly to be the regional land use and transportation planning agency. Periodically, METRO has been assigned management responsibility for certain regional functions (e.g. the Oregon Zoo, the Oregon Convention Center, the regional parks system, and a regional solid waste disposal and recycling program). These are major functions in terms of budget and number of employees but minor functions compared to METRO’s important planning powers in shaping the region’s future.

3) METRO is governed by seven-member Metro Council that is elected for four-year, staggered terms from the six districts into which the region is divided. The Council President, elected region-wide, is perhaps second only to the governor among Oregon’s elected officials. directs an agency with

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732 employees and an annual operating budget of $303 million in FY 2003. (Over two-thirds of its employees are involved in the service functions mentioned above.)

4) METRO is responsible for developing and periodically revising the region’s comprehensive land use plan, including designating the UGB. (The original UGB in 1979 was 342 sqaure miles; it was expanded by six square miles in 1998. By 1999 about 1.3 million people, or 90% of the population of the five-county PMSA, lived within the UGB. The remaining population lived in smaller towns and rural areas under the jurisdiction of the four more rural counties. (Multnomah County is totally urbanized.)

5) METRO also has overall responsibility for allocation of annual federal and state transportation subsidies (highway construction, the light rail system, bikeways, etc.).31 In addition, with bonds approved by voters, METRO acquires land for and manages the regional park system.32

6) METRO adopts specific ordinances to carry out its adopted plans. These ordinances are legally binding on local governments.33

7) METRO develops its plans and policies after extensive consultation with local governments and many public meetings and public hearings. METRO’s planning process is fundamentally democratic, not technocratic.

31 Under the federal Transportation Equity Act (TEA-21), METRO is designated as the “Metropoloitan Planning Agency (MPO).” 32 METRO currently manages 4,000 acres of regional parks and is acquiring 6,000 additional hectares under a $135 million bond issue approved by the region’s voters in 1995. 33 An example would be a METRO ordinance, adopted in 1998, that banned any new retail stores of more than 60,000 square feet in land zoned for industry. (In other words, no more superstores.) METRO wanted 1) to reserve the limited supply of industrial land for major, job-creating, high-wage industries, 2) to reduce air pollution by limiting vehicle miles traveled (superstores typically depend on a 25-mile radius customer area), and 3) to favor smaller, neighborhood-based retail stores as part of its plan for a more compact, pedestrian-oriented region.

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Summing Up Oregon’s Experience Since its birth the Oregon Land Use Act (and Portland METRO) have

been controversial, and have had their dedicated opponents. Three times Oregon voters have gone to the polls to defeat initiative referenda to repeal the law – by a 57 to 43 margin in 1976, by a 60 to 40 margin in 1978, and by a 55 to 45 margin in 1982. In 1999, an initiative was proposed to require that all administrative rules adopted by all state regulatory bodies would be voided unless submitted to and confirmed by the Oregon legislature. That was widely interpreted at being targeted primarily at LCDC and the state growth management program. That was defeated by a similar margin.

Nonetheless, Oregon voters are not exempt from being deceived or from doing stupid things. In 2000, the same ultra-conservative activists who have proposed many ballot initiatives (including the anti-state regulation ballot initiative that was defeated the previous year) were back with a so-called “property rights” amendment to the Oregon constitution. That would require that property owners be reimbursed for any government action, including zoning, that arguably would reduce the potential value of their property. If adopted, the constitutional amendment’s provisions would apply not only to future actions but also to all past actions. (A similar “property rights” amendment had been narrowly defeated in the neighboring state of Washington the previous year.)

Despite the opposition of many civic, business, and “good government” organizations, arguing that such a provision could cost the taxpayers billions of dollars, the “property rights” amendment was approved by a 54 to 46 margin statewide (though it lost within the Portland area).

Potentially, this action could seriously damage growth management in Oregon. However, growth management supporters are challenging the amendment before the Oregon Supreme Court.

Confronted with Oregon’s achievements, many elsewhere in the USA counter that “Oregonians are different.” It is true that many Oregonians (both natives and more recent arrivals) are strongly committed to protecting Oregon’s environment. (Oregon is a beautiful state. Oregonians have much to protect.)

But it is also true that many Oregonians are westerners with an anti-government, rugged individualism, “don’t fence me in” attitude. The two sides of the Oregon personality has been at war with each other over growth management for the past thirty years. The anti-government forces won the latest round.

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Winston Churchill once said: “We first shape our buildings. Then our buildings shape us.”

For thirty years Oregonians have been shaping their building – the Oregon Land Use Act, LCDC, METRO, etc. A dozen times since 1978, voters of the region have gone to the polls to elect the Metro Council and Executive Officer. Land use and transportation planning controversies are always the election issues.

Beyond the governmental institutions, Oregon has developed a powerful citizens lobby, 1,000 Friends of Oregon, that serves as a watchdog over the entire process. 1,000 Friends of Oregon has defended good planning principles and citizens’ right to be involved many times before LCDC, LUBA, the courts, and the legislature.

That intensely democratic process has, in turn, re-shaped the builders. There is broader and more knowledgeable citizen involvement in land use planning issues in Oregon (particularly, within Portland METRO communities) than in any other area of the USA.

To the extent that Oregonians are different, their institutions have helped to educate and shape them.

Suggested reading: Chapter 8 (Portland, Oregon: Taming Urban Sprawl) in my Inside Game/Outside Game is probably the liveliest telling of the Portland story. The websites for Portland Metro (www.metro-region.org) and 1,000 Friends of Oregon (www.friends.org) also provide a wealth of information about the Oregon/Portland system.

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Box 6.1 Are Growth Boundaries Anti-Affordable Housing? (draft 9/9/03)

In November 2000, Colorado voters defeated an initiative to

implement a strong, anti-sprawl, statewide growth management policy. A similar referendum was rejected in Arizona.

In both states one of the arguments of the opponents of the anti-sprawl initiative was that growth management policies would drive up the price of housing. Any restrictions on the supply of land, opponents argued, would work against the production of affordable housing. The allegation brought groups like Habitat for Humanity into an unlikely alliance with local homebuilders and realtors associations that are typically (but not invariably) opponents of growth management policies.

One of the “proofs” of that argument constantly broadcast by the National Association of Homebuilders (NAHB) is that home prices more than doubled in the 1990s in the Portland area which, with its urban growth boundary, has the nation’s toughest anti-sprawl laws.

That is certainly a fact. According to the National Association of Realtors data, the median price of homes sold in the Portland area from 1990 to 2000 did more than double (a 114 percent increase). As a matter of fact, Portland had the second highest percentage increase in selling prices in the nation during the 1990s.

But guess what metro area had the highest increase – Denver! The median price of homes sold in the Denver area increased by 128 percent during the same decade. Meanwhile, the median price of new homes sold in 51 major metro areas increased by “only” 63 percent. (The rise in the cost of living was 32 percent during the same period.)

The table lists the six metro areas with the highest increases in home prices for the decade: Denver, Portland, Salt Lake City, Detroit, Louisville, and Nashville.

A simple review highlights two facts. First, all began the decade with home prices below the national metropolitan average, ranging from Denver (10 percent below) to Louisville (37 percent below); in effect, their housing markets were somewhat depressed and they had ground to make up during the next decades. Second, of the six regions, only Portland had implemented

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an urban growth boundary (UGB) nor did the others have any meaningful growth management policies in effect.

Growth in median home sale prices 1990-00 in six fastest increasing housing markets out of 51 metro areas

Metro Area 1990 2000 Pct Growth UGB USA (51 areas) $95,500 $156,100 63% -- Denver, CO $86,400 $196,800 128% no Portland, OR-WA $79,500 $170,100 114% yes Salt Lake City-Ogden, UT $69,400 $141,500 104% no Detroit, MI $76,700 $147,800* 93% no Louisville, KY-IN $60,800 $116,700 92% no Nashville, TN $81,800 $147,500 80% no *estimated based on 1998-99 increase Something else must have been at work to accelerate the price

escalation (aside from the general 32 percent increase nationally in the cost-of-living). That factor was the regional economy. All had been in the economic doldrums in the 1980s: Denver (energy), Portland (forest products), Salt Lake City (real estate bust), Detroit (automotive industry), Louisville (manufacturing in general), and Nashville.

All their regional economies rebounded strongly during the 1990s (Table 2). Denver, Portland, Salt Lake City, and Nashville all created new jobs and saw their populations grow at twice the national average. Such rapid growth put tremendous short-term pressure on the housing supply, which tends to bid prices up. Detroit and Louisville had less explosive job and population growth, but, compared to where they had been for the previous two decades, it was a tremendous comeback.

In addition, all substantially exceeded the national average growth rate of 11.5 percent for the decade. The Denver area’s per capita personal income increased at almost twice the national rate. Many people became much wealthier – willing and able to purchase more expensive homes.

Examining housing price trends in 37 major metropolitan areas during the 1990s, researchers at Lewis and Clark College found that regional

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economic trends accounted for most of the price increases. Fast growing economies with rising incomes produced rapidly escalating housing costs. In fact, they estimated that Portland’s Urban Growth Boundary – that is, limiting somewhat the supply of buildable land – might have added about $10,000 per housing unit to the cost of housing.

[605 words]

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Module 7: Restoring the “Common School”

(draft 9/8/03)

Summary: in recent years several local school districts – notably, La Crosse, Wisconsin; Wake County (Raleigh area), North Carolina; and Cambridge, Massachusetts – have implemented pupil assignment policies based on achieving socioeconomic balance in their elementary schools. Basically, they have sought to have every elementary school achieve the district-wide average of low-income children (plus/minus 15 percentage points). As a result, they have achieved substantially greater economic integration than would have been the case if enrollment reflected solely neighborhood residential patterns – and they have seen academic achievement improve, particularly for low-income pupils.

The economic segregation index for the Denver region’s 391 elementary schools for 2001-02 was a high 58.9 (13th highest of the 100 largest metro area). Implementing a policy of socioeconomic balance as outlined above within the 17 school districts would lower the economic school segregation rate to 48.4 – about a 20 percent improvement. If every school board sought to equalize rate in all schools within the district, the metropolitan school segregation rate would only nudge down further to 46.6.

These are policies well worth pursuing. However, the greatest economic segregation occurs not within each district but between school districts because of the great disparities created by economically segregated housing patterns.

* * *

In September 2002 the Century Foundation issued Divided We Fail, the report of its Task Force on the Common School. Chaired by former US Senator and Connecticut Governor Lowell P. Weicker, Jr., the Task Force was composed of two dozen distinguished educators, researchers, civil rights attorneys, and former public officials.34 The Task Force’s report deserved 34 I served as a member of the Task Force and wrote one of the studies, “Trends in School Segregation,” that it commissioned. The Task Force report was drafted by Richard D. Kahlenberg, its staff director, and author of All Together Now: Creating Middle-Class schools through Public School Choice. Brookings Institution Press: Washington, DC (2001) that the Century Foundation had commissioned.

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far more public attention than it received, and I will draw upon it extensively for this module on achieving greater economic integration in the Denver region’s public schools. I cannot do better in characterizing greater Denver’s situation than to quote extensively the report’s introductory words.

Nearly forty years ago, Alabama Governor George Wallace declared in his inaugural address, “Segregation today, segregation tomorrow, segregation forever.” Today, almost no American would embrace what was once the reigning ethos, but the everyday reality lived by millions of schoolchildren is not too far from Wallace’s vision. No longer segregated by law, our nation’s schools are increasingly segregated in fact – both by race and ethnicity and, increasingly, by economic class. Our nation made great strides to eradicate segregated schooling from the early 1970s to the mid-1980s, but since then we have seen increasing racial and economic segregation, and almost no one – from either political party – has articulated a clear plan for addressing this disastrous trend.

The past twenty years have seen an explosion of education policy debates, over issues ranging from raising academic standards to lowering class size; from improving teacher training to promoting after-school programs. But current discussions largely ignore the central source of school inequality: segregation by race and class. All of history suggests that separate schools, particularly for poor and middle-class children, are inherently unequal. A child growing up in a poor family has reduced life chances, but attending a school with large numbers of low-income classmates poses a second, independent strike against him or her. While some look at the link between poverty and achievement and conclude that failure is inevitable, the members of the Task Force believe that poor children, given the right environment in school, can achieve at very high levels.

There exists today a solid consensus among researchers that school segregation perpetuates failure, and an equally durable consensus among politicians that nothing much can be done about it. Education reformers take as a given that schools will reflect residential segregation by class and race and therefore any solutions are narrowly conceived to make

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separate schools more equal. We believe that this approach is seriously flawed.

We fully recognize that the existing segregation of schools by class and race is not an accident, but is in some measure a reflection of political power. “Busing,” defined as compulsory assignment to non-neighborhood schools in order to achieve a given racial balance, is a political non-starter. But there is another set of alternatives that avoids the politically unacceptable choice of compulsory busing on the one hand and socially unconscionable alternative of school segregation on the other. The whole movement toward greater choice in public education represents an opportunity. If individual preferences are honored in a way that serves larger societal interests, the advent of choice would prove a boon for integration, because it would provide an opportunity to disentangle residential segregation and school assignment. Public school choice can help close the gap between the policy consensus on the need to integrate and the political consensus against compulsory busing…. In all, the report suggests some paths, grounded in real experience, toward restoring the integrated “common school” – envisioned by nineteenth-century educator Horace Mann as the “great equalizer” – for the twenty-first century.”

Written for a national audience, this introduction, it seems to me, aptly characterizes the situation in the Denver region as analyzed particularly in modules 3, 4, and 5. In 1954, the US Supreme Court (the Warren Court) unanimously (9-0) declared that racial school segregation was unconstitutional in its epochal Brown v. Board of Education. Just twenty years later, in 1974, a bitterly divided US Supreme Court (the Burger Court), by 5-4 vote in Milliken v. Bradley, declared, in effect, that suburban school districts had no obligation to cooperate with central city districts in area-wide racial desegregation plans unless each suburban district could be proven to have intentionally segregated. Twenty-one years after that, in 1995, the US Supreme Court (the Rehnquist Court) rejected in Missouri v. Jenkins state responsibility for segregation in schools and neighborhoods; the Court placed the blame for the deterioration and segregation of city schools on “normal pattern[s] of human migration.” The majority opinion never discussed the history of housing discrimination, lending bias, public

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housing construction, federal home loan mortgage practices, exclusionary zoning, or other governmental causes of racial and economic segregation.

Federal court decisions helped sanction the pattern of racial and economic segregation that characterizes the Denver area’s schools. In the spirit of Brown, the federal District Court found Denver Public Schools guilty of de facto racial segregation in the 1970s and ordered a racial desegregation plan into effect. But in the spirit of Milliken, suburban districts were exempted from playing any role in Denver’s school desegregation. This meant that parents resisting integration of the city schools could readily move to nearby suburbs.35 And after Jenkins an increasingly conservative federal judiciary has been washing its hands of the entire issue. The federal District Court dismantled Denver Public Schools’ desegregation plan in 1996 and returned it to neighborhood schools – that is, to largely segregated neighborhood schools.

But as legal scholar john a. powell has written,

The efforts of the federal courts to treat housing and school segregation as independent are counterfactual. State courts and policy makers, however, are not bound by the federal approach to segregated schools and housing. Policy makers have it within their power to address the interrelationship of housing and education.36

This module will explore what local school boards, as state-authorized policy makers, can achieve to create greater economic integration – the heart of the matter. It will explore briefly what three communities (La Crosse, WI; Wake County, NC; and Cambridge, MA) have done.37 Indeed, 35 Court-ordered busing programs were successful in county-wide school districts like North Carolina’s Charlotte-Mecklenburg County and Raleigh-Wake County that combined both central city and suburban neighborhoods. 36 john a. powell et al., eds. In Pursuit of a Dream Deferred: Linking Housing & Education Policy. Peter Land Publications: New York (2001), p. 19. powell is former national law director of the American Civil Liberties Union, former director of the University of Minnesota Law School’s Institute of Race and Poverty, and is now director of the Kirwan Institute for the Study of Race and Poverty at Ohio State University, 37 Each of these case studies is developed in greater detail in Divided We Stand. I have edited them substantially to reduce their length while retaining what I believe is the core of the story. However, whenever I felt that any paraphrasing of mine would not improve

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Cambridge has implemented the kind of controlled public school choice that the Task Force endorsed. Then the module will model the degree of economic integration that could be achieved if each of the 17 school boards pursued socioeconomic integration policies with each school district.

Three Examples of Economic School Integration

La Crosse, Wisconsin38

La Crosse is a city of 52,000, surrounded by a suburban area of about 37,000. Hemmed in by the Mississippi River on the west (forming the state line with Wisconsin) and suburban townships along the bluffs to the east, the city has annexed land modestly; since about 1970, the city’s population has been stagnant, and new subdivisions, shopping malls, and office complexes rose exclusively in its suburbs.

The region had few minorities until a large immigration of Hmong refugees from Viet Nam in the 1980s.39 By 2000, the La Crosse area was still 94 percent Anglo, but two-third of all minorities and almost 70 percent of Asians lived within the city of La Crosse.40 The constant suburbanization of more affluent families and growing concentration of lower-income minorities in the city brought the city’s per capita income to only 76 percent of suburban levels by 1999.

In the La Crosse public schools, however, minorities were proportionally greater; as of October 2000, there were 1,070 Asian students (13.9 percent), 255 black students (3.3 percent), 85 Native Americans (1.1 percent), and 73 Hispanic students (0.95 percent). Anglo students made up 80 percent of the total 7,605 student in the district.

upon the original authors’ words, I have included such sections without quotations, reserving quotations for important statements of local officials, educators, and parents. 38 This section has been freely edited from the chapter by Richard Mial: “One School District’s Drive To Create Socioeconomic Balance” in Divided We Fail, pp. 115-140. 39 The Hmongs were better known as the Montagnards, the hill peoples of Laos who were staunch American allies during the Vietnamese War. 40 The records of the La Crosse Hmong Mutual Assistance Association showed 3,491 Hmong residents of La Crosse County rather than the 2,282

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By the late 1980s, school leaders were worried about concentrations of low-income students (often minority) that were developing. District-wide, 30 percent of students qualified for free lunches. However, in 1991-92, Jefferson Elementary had 69 percent and Hamilton Elementary had 63 percent qualifying for free lunches. By contrast, State Road School in an affluent neighborhood had only 4.8 percent.

Faced with the need to redistrict because of the construction of two new elementary schools to meet the rising, immigration-driven enrollment, Superintendent Richard Swantz and his staff saw an opportunity to correct the big poverty imbalances in La Crosse’s elementary schools.

In May 1991, school board members approved ten guidelines for redistricting, including “redistricting shall attempt to establish a socio-economic percentage of poverty students in each school that represents the district’s average” although “when re-assigning students to achieve a socio-economic balance, an attempt shall be made to place them in the closest school.”

Realizing that achieving a 30 percent target in each school would be impossible, school officials set a goal of a range of from 15 percent to 45 percent low-income students in each school. Under the proposed plan, 45 percent of the district’s 3,700 elementary school students would have to be bused to another school, for the 1992-93 school year.

After months of deliberations and three public hearings, on January 7, 1992, the La Crosse School Board voted 8-1 to approve the plan to achieve socioeconomic balance in its eleven elementary schools through boundary changes and busing.

On January 22, a group named the Recall Alliance announced that it would soon begin collecting signatures for the recall of board members that supported the plan and that a new board would fire Superintendent Swantz. A counter group, the Coalition for Children, was formed the next day. At the regular election already scheduled for April two pro-plan incumbents were defeated and a third did not stand for re-election. All were replaced by anti-busing opponents.

With the recall campaign heating up, The New York Times, Washington Post, Boston Globe, news magazines, and TV networks descended upon La Crosse. They broadcast far and wide the news that on

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July 14 four incumbents were defeated and replaced by anti-busing opponents. Then the national news media disappeared and failed to report (to borrow radio commentator Paul Harvey’s phase) “the rest of the story.”

First, the new board could not fire Superintendent Swantz, whose contract had been extended for three years by the old board with a $250,000 buy-out provision.

Second, with school about to begin, the board found that rolling back the busing plan would be too disruptive. They contented themselves with adding a choice provision to the plan. Any parent who didn’t want to send a child to a different school for socioeconomic balance could opt out. Less than two hundred children changed schools (out of about 1,700 students being reassigned) under the parental choice option during that first year. All but two schools met the socio-economic targets that first year.

Third, most remarkably, just nine months after the recall election, in April 1993, three anti-busing board members were defeated, and were replaced by three members – two members of Coalition for Children and the first Hmong elected to public office in La Crosse – that supported the socioeconomic balance plan.

Fourth, the busing plan proceeded forward. Most parents and children adjusted to their new schools. As one board member said,

“People got to experience it, that it wasn’t awful. Moving to different schools wasn’t awful. Leaving your neighborhood school wasn’t awful. The kids benefited from it. People backed off. The staff at all the different schools made sure that it worked.”

Fifth, public support for the socioeconomic balance plan has grown. In 1994, just two years after the recall election, 60 percent of district residents surveyed said they favored “the idea of attempting socio-economic balance in the schools,” and 29 percent said they opposed it. In a follow-up survey in April 2001, 64 percent favored socioeconomic balance, while only 21 percent were opposed.

Finally, socioeconomic balance has been an academic success. La Crosse has a fairly high poverty rate with only Milwaukee County and two Native American reservations higher. Yet, according to former

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Superintendent Swantz, the district’s achievement levels are at 83 percent of the national average.

In 1992, La Crosse was in the forefront of a movement to look at the impact of socioeconomic balance in the schools and to create schools in which the majority of students were middle class with middle-class education values. Parents, however, were allowed to use school choice to opt out of the program, making socioeconomic balance potentially more difficult to achieve. Demographic changes over the years allowed some schools to slip back to high percentages of low-income students, and Hamilton School’s small and dense attendance area made that school’s income makeup particularly difficult to change.41

However, La Crosse’s new Superintendent, Thomas C. Downs, sums up La Crosse’s continuing challenge:

“We’ve got to do what we need to do to support socioeconomic balance. It raises the achievement of the lower-income kids and doesn’t in any way hurt the achievement of the more advantaged kids. I believe that it’s a higher value for me now.”

41 The impact of La Crosse’s socioeconomic balance plan was immediately evident in metropolitan segregation indices (that cover seven school districts) in the mid-1990s as well as the slow erosion since because of parents’ opting out and continuing neighborhood changes. The table lists annual averages for the three periods.

low-income Asian period segregation segregation index index 1988-92 33 61 1992-93 4 35 1993-95 21 40 1995-99 27 41

An economic segregation index of 4 for 1992-93 (the first year of the plan) is so low that it raises the possibility of missing data. However, the impact of the La Crosse district’s changing enrollment policies is clear on metropolitan trends.

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Wake County, North Carolina

With 105,000 students, Wake County Public Schools is one of the nation’s premier, “Big Box” school systems.42 It has also been one of the nation’s most racially integrated systems after local officials merged the county school system with the separate Raleigh city system in 1974 and instituted a county-wide policy of busing and magnet schools to achieve racial balance.

By 1999, however, Wake County school officials could see the handwriting on the wall in terms of their explicit student assignment policies to promote racial balance. The federal Fourth Circuit Court of Appeals (which includes the Raleigh area) was moving to strike the racially-based assignment policies in Arlington County, Virginia and Montgomery County, Maryland. In the adjacent Circuit Court district the federal judge was dismantling Charlotte-Mecklenburg’s racial balance plan that had been implemented since the historic Swann v. Charlotte-Mecklenburg School District case in which the US Supreme Court first authorized district-wide busing to achieve racial balance.

Reflecting on a tense meeting in which administrators wrestled with finding a workable alternative, one school official recalls that “What I remember most intensely was that a number of people would say, ‘It makes us sick to our stomach because we are walking away from 20 years of doing something that had been good for the school system and good for the community.”

A legal analysis summarized the evolving new federal judicial policy.

“In essence, the new decisions forbid all school boards (unless they are operating under federal desegregation decrees) from considering race or ethnicity as they assign children to public schools. The prohibition holds even if it leads to desegregated schools, even if most parents desire their children to attend racially diverse schools, and even if school boards are acting in good faith to ensure that students receive the educational benefits that may come from a diverse school environment.”

42 This section has been freely edited from “Wake County Schools: a Question of Balance” by Todd Silberman in Divided We Fail, pp. 141-166.

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School leaders had reviewed extensive local and national research regarding the linkage between socioeconomic status and educational achievement. They decided to replace the system of student assignment to achieve racial balance with a system of student assignment to achieve socioeconomic. For the 1999-2000, the school board adopted new student assignment criteria designed to assure that no school would have more than 40 percent low-income pupils nor more than 25 percent of students with low academic performance levels.

Before examining how housing patterns may increasingly frustrate progressive school policies, we should pause to compare the Denver and Raleigh areas. Denver is a five-county metro area with a single central city; the six-county Raleigh-Durham-Chapel Hill area, as the name conveys, has three central cities. However, all school districts are unified, county-wide “Big Box” districts, generally with deliberate school integration policies in effect. Table 7.1 compares both metro areas and the systems serving the principal central cities, though, unlike Denver Public Schools, Wake County Public Schools embraces Raleigh, its suburbs, and substantial rural areas.

Table 7.1 Racial and economic school segregation

in Denver and Raleigh area elementary schools in 1999-2000 Metro Denver Metro Wake Denver PS Raleigh County elementary pupils 197,165 43,572 136,442 55,844 Anglo 61% 22% 58% 63% Black 9% 20% 34% 28% Hispanic 26% 53% 5% 4% FARM 24% 68% 28% 22% Black segregation index 67 46 32 21 Hispanic segregation index 56 39 40 32 FARM segregation index 56 42 35 30 Avr. non-FARM/non-FARM classmates 80% 50% 70% 77% Avr. FARM/FARM classmates 56% 73% 50% 36%

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Demographically, Denver and Raleigh-Durham-Chapel Hill were somewhat comparable. Greater Denver had 45 percent more elementary school pupils in 1999-2000 but slightly fewer minority pupils (39 percent) than did “the Research Triangle” region (42 percent). The FARM rate was slightly higher in metro Raleigh-Durham-Chapel Hill (28 percent) than in metro Denver (24 percent).

However, in terms of racial and economic integration the North Carolina region bests the Colorado region by a substantial margin in every category. As a region, for example, the black school segregation index of metro Raleigh-Durham (with four times the proportion of black students) was less than half (32) the Denver region’s index (67). In like fashion, economic segregation was one-third lower in the Carolina region than the Colorado region. Perhaps the most decisive difference: in Denver Public Schools, the average low-income (FARM) pupil attended a school where 73 percent of classmates were also poor; in Wake County Public Schools the average low-income pupil attended a school with only 36 percent poor classmates. And that was the year before Wake County Public Schools implemented its economic integration plan.

Nevertheless, Wake County Public Schools has a tough challenge to attain its goals in the face of a regional housing market that promotes more and more economic segregation. Though Raleigh itself has expanded its boundaries rapidly (from 11 square miles in 1950 to 115 square miles in 2000), it continues to be home to 60 percent of Wake County’s African Americans. Meanwhile, the white population is exploding in four towns in western Wake County – most importantly, Cary, the bedroom community for Research Triangle Park. Their schools are geographically distant from minority neighborhoods in south Raleigh.

The early academic returns from Wake County’s new pupil assignment policy are encouraging. In 2001, 64 percent of Wake County students eligible for free and reduced-price meals performed at or above grade level, a rate that outpaces most low-income students in urban districts. As Wake County Superintendent of Schools Bill McNeal explains, “The reason that you want to create middle class schools is expectations as much as anything. How do you know what excellence is without seeing it. You’ve got to be able to touch it and feel it.”

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Cambridge, Massachusetts

In December 2001, the Cambridge School Committee adopted a policy of controlled school choice to achieve socioeconomic balance in the district’s 14 elementary schools.43 With 48 percent of elementary school pupils qualifying for subsidized meals, starting with kindergarten, the school board set a goal of having each school fall within fifteen percentage points of the district-wide average (that is, between 33 percent and 63 percent FARM) for 2002-03. The permissible range would be narrowed to ten percentage points for 2003-04 and to five percentage points for 2004-05.

There is, as yet, no readily available data for the implementation of the policy. However, the new policy builds on twenty years of experience in implementing a controlled choice policy to achieve racial balance in Cambridge’s elementary schools.44

Table 7.2 summarizes enrollment figures for the 2000-01 (the most recent year available) on the threshold of implementing the new policy.

Table 7.2 Enrollment by race and income

in Cambridge elementary schools in 2000-01

school AmerInd Asian Black Hispanic Anglo FARM Agassiz 1% 16% 31% 9% 43% 30% Cambridgeport 1% 8% 31% 10% 50% 19% Fitzgerald 1% 10% 39% 7% 43% 60% Graham & Parks 1% 8% 39% 6% 46% 31% Haggerty 1% 8% 35% 7% 48% 30% Harrington 0% 3% 36% 12% 48% 77% Kennedy 2% 3% 22% 43% 32% 64% King 0% 21% 45% 10% 24% 79% King Open 1% 14% 31% 5% 49% 25% Longfellow 0% 10% 29% 26% 35% 53% Morse 0% 26% 31% 8% 35% 51% Fletcher/Maynard Academy 0% 4% 52% 20% 25% 72% Peabody 1% 24% 25% 4% 46% 25% Tobin 0% 11% 44% 10% 34% 48% TOTAL 1% 11% 34% 14% 40% 48%

43 43 This section has been freely edited from “Controlled Choice in Cambridge, Massachusetts” by Edward B. Fiske in Divided We Fail, pp. 167-208. 44 Cambridge’s elementary schools cover K-8 and the district has a single high school.

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Just perusing Table 8.2 illustrates the wide ranging diversity of

Cambridge Public Schools. No school had a majority of any one racial group except Fletcher/Maynard Academy that was 52 percent black in 2000-01. (One-quarter of the Academy’s black enrollment was not African American, but Haitians, West Indians, and African immigrants.) Over all the district’s elementary schools were 40 percent Anglo (non-Hispanic whites), 34 percent black, 14 percent Hispanic, 11 percent Asian, and 1 percent Native American “AmerInd”).

Table 7.3 calculates the familiar segregation indices. Four facts stand out.

Table 7.3 School and neighborhood (ages 17 and less) segregation indices

(0 to 100; 100 = total apartheid)

group school neighborhood Anglo 15 10 Black 13 46 Hispanic 36 36 Asian 28 30 AmerInd 29 41

Low-income 35 36* Note: calculated for ages 5-11 (in effect, K-6)

• First, though the residential segregation of blacks (ages 5-17) was the highest (46) of any group, the controlled school choice program brought school segregation of black pupils down to an incredibly low index of 13. Many black parents clearly sought out “better” schools beyond the boundaries of the moderately segregated neighborhoods in which they lived.

• Second, Hispanic and Asian enrollments mirrored neighborhood patterns.

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• Third, Anglo pupils were grouped somewhat more in certain schools than they were in neighborhoods – again, a function of more aggressive parents utilizing the controlled choice system to their advantage. However, one-third of Anglo school age children were not attending Cambridge Public Schools. (Over 90 percent of school age children from all other groups attended the public schools.)

• Fourth, economic segregation was not diminished by the racially-based controlled choice policy. Schools were as economically segregated (35) as neighborhoods (36).45 The higher levels of economic school segregation can been seen intuitively in Table 8.2, where the percentage of FARM pupils ranged from a low of 19 percent (Cambridgeport) to a high of 79 percent (King).

Indeed, it was this disparity plus concern about the uncertain legal status of a race-based controlled choice plan plus growing understanding of the linkage between socioeconomic status and academic outcomes that caused the Cambridge School Committee to shift to controlled choice for socioeconomic balance in December, 2001. Nonetheless, with index values from the mid-forties down to the low-teens, Cambridge Public Schools were remarkably balance by race and ethnicity. How did the controlled school choice policy work to produce such a result?

Cambridge Public Schools abolished neighborhood schools and launched its controlled choice plan in 1981. The term “controlled choice” was adopted to signal that, while parents indicate their preferences, the school district makes the final decision. Parents list their first four choices in order of preference. Families can, of course, choose the nearby school to which the child would have been automatically assigned before neighborhood schools were abolished.

Placements are made by the district assignment officer with racial balance in mind, and the proportion of pupils from any racial group must be within 10 percent of that group’s representation in the district as a whole. Once a school’s enrollment reaches that proportion, no more pupils from 45 This is somewhat of an apples-to-oranges comparison. The two age groups are not identical as the schools K-8 range is compared with Census 2000’s 5-11 age grouping (roughly K-6). Of potentially more consequence, the residential calculation is based on children under the poverty line while FARM eligibility cuts off at 185 percent of the poverty line.

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that group will be admitted. In addition to parental preferences, other priorities include siblings and students who live within walking distance of the school.

In the event that there are still too many applicants from any racial group for a particular school or program, a lottery is held for the available places. Pupils not accommodated with one of their first three choices are assigned to another school where there are seats available consistent with diversity requirements; they are automatically put on a waiting list for the next suitable vacancy in one of their preferred schools.

For the assignment cycle that ended in January 2001, for 472 applicants for places in kindergarten, 407 (86 percent) received their first choice, 14 (3 percent), their second choice, 10 (2 percent) their third choice, and 41 (9 percent) were sent to schools their parents had not selected. Of those 41 kindergarteners receiving “mandated” assignments, 21 were eventually placed in one of their top three choices, 12 withdrew from the system, and 8 stayed in the school to which they were assigned.

There were shortcomings that developed in the controlled choice system (which are discussed in greater detail in Edward Fiske’s chapter in Divided We Fail). The primary shortcoming is that the system failed to improve significantly underperforming, under-selected schools. The result has been the emergence of almost permanent cadres of most favored and least favored schools – far more along socioeconomic rather than racial lines. Three of the four schools deemed most desirable – Cambridgeport, King Open, and Peabody – are among those that have the least proportion of FARM pupils, while three of the four least popular schools – Fitzgerald, Harrington, and Kennedy – are among those with the highest proportion of FARM pupils.

All in all, however, Cambridge’s system of controlled public choice has produced an unusual level of equity and access to opportunity and was endorsed by the national Task Force on the Common School for nationwide application.

Calculating Potential School Economic Integration

While some state courts may order region-wide socioeconomic integration plans (such as occurred in the case of Connecticut’s Sheff v. O’Neill), it is most unlikely that the current federal judiciary will do so.

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What are the limits of what could be achieved if each school board in the Denver area adopted socioeconomic balancing plans within each district?

Table 7.4 applies a uniform policy to Denver Region’s 17 school districts that somewhat parallels the formula used by both La Crosse and Cambridge in their socioeconomic balance plans. Within each district school officials would reassign elementary school pupils so that no school’s proportion of FARM pupils would be 15 percentage points greater or 15 percentage points less than that district-wide percentage of FARM pupils. That 30-point range would be altered only when insufficient seats in low-poverty schools would be available to accommodate transfers from higher poverty schools (e.g. Northglenn-Thornton, Cherry Creek, Littleton, Adams-Arapahoe, and Jefferson) when the floor would have to be raised higher.

Table 7.4 Projected impact of socioeconomic integration policy

within 17 Denver school districts in 2002

pct current projected pct pupils School district FARM pct range pct range reassigned

Denver City 68% 96%-6% 78%-48% 10.1%

Adams County Mapleton 1 46% 64%-32% 61%-31% 1.6% Northglenn-Thornton 25% 80%-1% 40%-17% 8.5% Adams County 14 74% 83%-66% 89%-59% 0.0% Brighton 27J 35% 68%-13% 50%-20% 5.3% Bennett 29J 16% na na na Strasburg 31J 14% na na na Westminster 50 42% 64%-3% 57%-27% 1% Arapahoe County Englewood 1 41% 52%-31% 56%-26% 0.0% Sheridan 2 68% 74%-61% 83%-53% 0.0% Cherry Creek 5 13% 49%-0% 28%-7% 3.6% Littleton 6 14% 56%-1% 29%-9% 6.1% Deer Trail 26J 16% na na na Adams-Arapahoe 28J 40% 80%-1% 55%-31% 7.5% Byers 32J 31% na na na Douglas County RE-1 2.5% 10%-0% 15%-0% 0.0% Jefferson County R-1 18% 76%-0% 33%-12% 7.0%

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Within this range, the policy’s impact would differ from district to district.

• Eight of the districts would have no transfers: four because they have only one elementary school (Bennett, Strasburg, Deer Trail, Byers); and four because all schools fall within the adopted range (high-poverty Adams County and Sheridan, medium-poverty Englewood, and no-poverty Douglas County);46

• Mapleton (one school) and Westminster (one school) would have minimal programs.

• Even the remaining systems would see relatively modest percentages of pupils reassigned (in both directions) through a combination of boundary changes and busing: Cherry Creek (3.6 percent), Brighton (5.3 percent), Littleton (6.1 percent), Jefferson County (7.0 percent), Adams –Arapahoe (7.5 percent), Northglenn-Thornton (8.5 percent), and Denver Public Schools (10.1 percent). In each case, pupils “bused” for socioeconomic balance would be a tiny small fraction of the pupils that the districts already transport to school.

The economic segregation index for the region’s 391 elementary schools for 2001-02 was a high 58.9. Implementing a policy of socioeconomic balance as outlined above (i.e. the district average plus/minus 15 percentage points) within the 17 school districts would lower the economic school segregation rate to 48.4 – about a 20 percent improvement. If every school board sought to equalize the FARM rate in all schools within the district, the metropolitan school segregation rate would only nudge down further to 46.6.

46 Douglas County’s highest FARM schools are South Street (9.5 percent), Castle Rock (8.6 percent), and Sedalia (5.2 percent). One-third of the county’s 39 elementary schools have less than 1 perfect FARM rates. If the school board wished to bring all schools below 3.5 percent FARM, less than 200 pupils would have to be reassigned.

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Summing Up

These are policies well worth pursuing. However, the greatest economic segregation occurs not within each district but among the school districts because of the great disparities created by economically segregated housing patterns.

Housing policy is school policy. That will be the focus of module 9.

Suggested Reading:

The best point of departure for further study would be the Century Foundation report cited in footnote 1 and other footnotes. Its formal title is Divided We Fail: Coming Together through Public School Choice. Brookings Institution Press: Washington, D.C. (2002).

john powell’s collection of essays, In Pursuit of a Dream Deferred: Linking Housing & Education Policy , cited in footnote 3 would be another excellent way of exploring these issues, particularly from a legal perspective.

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Module 8: Inclusionary Zoning: Mixing Up the Neighborhood

(draft 9-8-03)

Summary: Over 130 local communities have adopted inclusionary zoning ordinances that require that a certain proportion of all covered new housing developments must include a modest proportion of affordable housing. (The city of Denver adopted such a policy in 2002.) Montgomery County, Maryland’s program is the USA’s oldest and largest, since 1975 producing over 11,000 affordable homes integrated into middle class sub-divisions. Two-thirds is sold or rented to working class families; the other third is acquired by the county public housing authority. As a result, Montgomery County, the USA’s 13th wealthiest county and global center of biomedical and genetic industries, is also one of the nation’s most racially and economically integrated communities, with a top-quality school system.

From 1980 to 2000, about 320,000 new homes were built in the Denver area. Applying Montgomery County’s formula (and assuming that half of all new homes were in developments too small for the inclusionary policy to apply), there would have been about 16,000 more affordable homes built for working class families and another 8,000 acquired by a regional housing authority (or collaborative network of local housing authorities).

On a school district basis, some 12,000 low-income children’s families would have opportunities to move out of eight higher-poverty, “sending” school districts into low-poverty, “receiving” school districts. (Almost 9,000 such children could leave the high-poverty Denver Public Schools.) The Jefferson County schools (plus 4,475), the Cherry Creek schools (plus 3,375), and the Douglas County schools (plus 3,100) would have been the largest “receiving” districts.

Hypothesizing that the region’s 17 school boards would carry out school assignment policies that would equalize low-income pupil enrollment among all elementary schools within each of the school districts, I calculated that the economic school segregation index would be reduced from 58.9 to 46.6 – about a 20 percent reduction in economic segregation.

However, reinforcing what school boards have the authority to do with an MPDU policy that city and county governments have the authority to do would reduce the school economic segregation index to 13.9 – a three-quarters reduction in economic school segregation! That would make

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metro Denver’s schools the third most economically integrated in the nation.47 By achieving just half that level (27.8), which is readily within the range of realistic implementation, greater Denver would have the second most economically integrated schools of any major metropolitan area.48

* * *

Montgomery County, Maryland, a wealthy suburban county outside Washington, DC, has long been renowned as having the nation’s most progressive, mixed-income housing policies. The Housing Opportunities Commission (the county’s public housing authority and housing finance agency) owns, rents, or administers an inventory of over 40,000 housing units (most in mixed-income neighborhoods), or about 12 percent of the total housing supply.

One of Montgomery County’s key tools is its Moderately-Priced Dwelling Unit ordinance. Enacted in 1973, the MPDU law requires private developers to build mixed income housing everywhere.49 The law covers any new subdivision, townhouse complex, or apartment development with at least 35 housing units.

Under the county law, most of the new housing can be “market rate” (at whatever income level the builder targets), but at least 12.5-15 percent must be “affordable” housing, or MPDUs. To qualify for an MPDU, a family’s income cannot exceed 65 percent of the county’s average household income (which was $71,551 in 1999).

To help integrate the poorest households into middle-class society, the county law further specifies that one-third of the MPDUs, or 5 percent of the units built, must be available for rent or out-right purchase by the Housing Opportunities Commission.

47 Flagstaff, AZ (8.5) and Eau Claire, WI (10.6) ranked first and second in 1999-00. 48 Of the 100 largest metro areas, Scranton-Wilkes Barre, PA (27.5), which has no minority population to speak of, ranked first; Greenville-Spartanburg, SC (28.7) was second, and Charlotte, NC-SC (33.8) was third. 49 At the time that Montgomery County adopted its MPDU ordinance in 1973, it already had over 535,000 residents – more people than any suburban county of Denver has now! Though it had substantial undeveloped land at the time, with a total area of 495 square miles (and about 30 percent set-aside for permanent agriculatural and recreational use), Montgomery County even then had far less developable land than Denver’s suburban counties.

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Montgomery County never builds public housing projects. It simply buys standard housing scattered all over the county as rental housing for its poorest families.

Complying with the county’s ground rules, private homebuilders and apartment developers have produced 11,210 MPDUs — two-thirds for sale, one third for rent. Many buyers are local school teachers, county deputy sheriffs, office workers, super market clerks, fast food cooks — in short, the very civil servants, retail trade and service industry workers who serve local communities.50

To house welfare recipients and other poor residents, the Housing Opportunities Commission has purchased 1,699 of the new MPDUs and rents 1,521 more as of December 2002. (Church groups and private, non-profits have bought others.) The county-owned units are so scattered that HOC pays annual membership assessments to over 220 private homeowners associations.

Though compliance is mandatory, the county provides homebuilders with a significant cost-offset in the form of density bonuses up to 22 percent above the maximum allowed by the underlying zoning. Thus, if the applicable zoning allowed a builder to develop a maximum of 100 units on a plot of land, under the MPDU law the builder could build 122 units – 18 MPDUs and 104 market rate units. In effect, the builder picks up an additional four market rate units with no land cost – a profitable transaction.

The 85-10-5 income mix produces no social problems, according to HOC officials, police, and social agencies, and resale prices of market-rate homes are unaffected by being within mixed income housing developments.

With 873,000 residents in 2000, Montgomery County, Maryland is a governmental “Big Box.” In 1927 the Maryland General Assembly gave county government exclusive planning and zoning control throughout the county.51

50 All data are current through December 31, 2002 51 The legislature “grandfathered existing zoning powers for the cities of Rockville and Gaithersburg and five small villages (about 12 percent of the county’s population).

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Its progressive policies have produced a remarkable social and economic transformation. In 1970 Montgomery County has the look of a classic suburb – wealthy and White (92 percent). By 2000, Montgomery County had a “rainbow look” – 16 percent Black, 12 percent Hispanic, 12 percent Asian – and still the 13th wealthiest county in America while becoming one of the USA’s more racially and economically integrated communities.

By providing housing for all occupational levels, the county helped promote a diversified local economy centered on its I-270 “Technology Corridor.” In a generation the Montgomery County has become the global center of biomedical and genetic research.

Inclusionary Zoning for Greater Denver

Over 130 communities have enacted mandatory, inclusionary zoning ordinances. Most exist in relatively high cost housing markets like Denver’s. Provisions vary with local circumstances. Fairfax County, Virginia (second only to Douglas County in average income) requires at least 12.5 percent ADUs (Affordable Dwelling Units) in for-sale subdivisions of 50 or more units and 6.25 percent ADUs in low-rise garden apartments. (High rise apartments are exempt.) Cambridge, Massachusetts requires 10 percent affordable units for any development of 10 or more units; next door any development of seven or more units triggers the Town of Arlington’s 15 percent affordable requirement. Every fourth housing unit in developments in Santa Fe, New Mexico must be affordable.

Let us apply, however, Montgomery County’s time-tested MPDU formula to all jurisdictions in the Denver metropolitan area with one simplifying assumption: for each community the minimum number of units that would trigger the inclusionary requirement would be the median size such that half of all units built are covered. In other words, requiring 15 percent MPDUs really translates into only 7.5 percent of all new housing units constructed. Two thirds would be purchased or rented by low-income households (“workforce housing”) and one-third would be purchased or rented by a regional housing authority or consortium of local authorities for very low-income tenants (“welfare-to-workforce housing”).

Table 8.1 summarizes construction activity between 1980 and 2000 as reported by the latest census. A total of 320,296 were built during the twenty-year period (over one-third of all of the Denver area’s housing

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Table 8.1 Hypothetical MPDU production in metro Denver

from 1980 to 2000 welfare-to

total workforce workforce jurisdiction52 units MPDUs MPDUs built at 5% at 2.5% Denver PMSA 320,296 16,015 8,007 Adams County 52,962 2,648 1,324 Bennett town 427 21 11 Brighton city 2,755 138 69 Broomfield city 7,882 394 197 Commerce City 1,204 60 30 Federal Heights city 2,952 148 74 Northglenn city 2,439 122 61 Thornton city 16,604 830 415 Westminster city 21,627 1,081 541 Arapahoe County 91,415 4,571 2,285 Aurora city 13,305 665 333 Cherry Hills Village 661 33 17 Columbine Valley town 149 7 4 Englewood city 2,275 114 57 Foxfield town 132 7 3 Glendale city 908 45 23 Greenwood Village 2,191 110 55 Littleton city 7,757 388 194 Sheridan city 556 28 14 Denver City and County 41,337 2,067 1,033 Douglas County 55,096 2,755 1,377 Castle Rock city 6,028 301 151 Lone Tree city 1,911 96 48 Parker town 8,033 402 201 Jefferson County 79,486 3,974 1,987 Arvada city 11,804 590 295 Edgewater city 191 10 5 Golden city 2,613 131 65 Lakewood city 19,746 987 494 Wheat Ridge city 2,230 112 56

52 Where a municipality is split between two counties, I have listed that municipality under the county in which the larger share of its population lives.

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stock). Assuming that half of the housing built were individual “spec” homes or in small developments, a Montgomery County-type MPDU policy would have resulted in 16,015 “workforce” MPDUs and 8,007 “welfare-to-workforce” MPDUs.

How those MPDUs would have been distributed would have been entirely dependent on the level of homebuilding activity community by community. Aurora, for example, was largely built out before this period; new construction (13,305 homes) only accounted for 12 percent of its housing stock. As a result, an MPDU policy would have produced only 665 “workforce” MPDUs and 333 “welfare to workforce” MPDUs. On the other hand, an astounding 87 percent of Douglas County’s housing stock was built during these two decades. As modest as the percentage set-asides would have been, the policy would have produced 2,755 “workforce” MPDUs and 1,377 “welfare-to-workforce” MPDUs.

Under a regional “fair share” policy, the communities would break down into “sending” communities and “receiving” communities. In 1999, the metropolitan family poverty rate was 5.6 percent. With higher than average family poverty rates, the sending municipalities (and their family poverty rates) would have been Glendale (20.1%), Commerce City (15.3%), Denver (10.6%), Federal Heights (9.2%), Sheridan (9.0%), Edgewater (8.1%), Aurora (6.8%), Brighton (6.1%), and Wheat Ridge (5.9%).

All communities with family poverty rates lower than 5.9 percent would be receiving municipalities (or unincorporated areas under county governance). Basically, the receiving communities would be Douglas County (1.6%), Jefferson County, excluding Edgewater and Wheat Ridge (3.5%), Arapahoe County excluding Aurora, Glendale, and Sheridan (4.2%), and outer suburbs in Adams County such as Bloomfield (2.1%), Northglenn (3.8%), and Thornton (3.1%).

Table 8.2 translates this pattern roughly into local school districts. For family poverty rates I substitute eligibility for free and reduced-price meals (FARM). Children are eligible for free school meals with family incomes up to 135 percent of the poverty threshold (which was $17,400 nationally for a family of four in 1999). Children are eligible for partially subsidized school meals with family incomes up to 185 percent of the poverty threshold. With median household income having been $51,191 for metro Denver in 1999, the FARM eligibility ceiling falls at about 63 percent of median household income. Thus, setting the maximum income level at

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which a family could qualify for an MPDU at 65 percent of median household income (adjusted for family size) would roughly match FARM eligibility in the Denver area’s public schools.

Table 8.2 adopts several other assumptions. First, I assume that three-quarters of the MPDUs (both “workforce” and “welfare-to-workforce”) would be utilized by households with children; that assumption accommodates senior housing and eligible households without children. Second, I assume that the average MPDU family will have one child in the public elementary schools. (The average Denver area family with children had 2.1 children in 2000.) Third, MPDUs created within sending districts are used to achieve greater economic integration within those districts. Finally, the region-wide percentage of FARM pupils was 31.2 percent in 2001. I assume that the MPDU program would bring neither sending school districts below the regional average nor push receiving school districts above the regional average even though some receiving districts would have greater numbers of MDPUs (e.g. Northglenn-Thornton, Byers) that, if so utilized, could lift them beyond the regional FARM average.

Table 8.2 Hypothetical impact of MPDU on FARM pupils by district

pct net net pct school district FARM FARM FARM FARM current receivers senders w/MPDU Mapleton 1 46.5% -356 31.6% Northglenn-Thornton 12 24.9% 930 31.2% Adams County 14 73.9% -924 44.3% Brighton 27J 34.6% -107 31.2% Bennett 29J 16.3% 24 22.2% Strasburg 31J 14.1% 21 19.5% Westminster 50 42.0% -570 31.2% Englewood 1 40.5% -140 31.2% Sheridan 2 68.3% -154 44.1% Cherry Creek 5 12.9% 3,375 30.3% Littleton 6 14.1% 436 20.5% Deer Trail 28J 16.1% 2 18.6% Adams-Arapahoe 28J 39.8% -1,370 31.2% Byers 32J 30.5% 2 31.3% Denver Public Schools 67.9% -8,740 44.1% Douglas County RE-1 2.5% 3,099 16.9% Jefferson County R-1 18.2% 4,471 28.4% Totals 31.2% 12,361 -12,361 31.2%

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Before discussing the results illustrated in Table 8.2, we should pause to remember what this depicts. These are not the potential results of some metropolitan-wide busing program for economic integration. These are the effects that flow from creating much more economically diverse new neighborhoods in which larger numbers of low-income children attend predominantly middle-class neighborhood schools.

In Table 8.1 we saw that a MPDU-type inclusionary zoning policy region-wide would have produced an estimated 24,022 MPDUs. Some 7,738 would have been created in higher than average FARM school districts (Denver Public Schools et al.) that would serve to promote more economic balance within those districts. But another 16,284 MPDUs would have been built primarily in newer, low-poverty subdivisions in the Cherry Creek, Jefferson, and Douglas school districts. Under a region-wide eligibility list these MPDUs would have been available for low- and very-low income families who would have chosen to move into them. These families would otherwise have been limited to seeking older, low-cost housing in high poverty neighborhoods, thus sending their children to poverty-impacted neighborhood schools in primarily the Denver and Adams-Arapahoe districts.

By our assumptions, the families of more than 12,000 FARM pupils would have moved into MPDUs in the Northglenn-Thornton, Cherry Creek, Littleton, Douglas County, and Jefferson County school districts. One beneficial effect would have been to reduce very substantially the high concentration of FARM pupils in sending districts, particularly in Adams County 14 (73.9% to 44.3%), Denver Public Schools (67.9% to 44.1%), and Adams-Arapahoe (39.8% to 31.2%).

There would, of course, have been an increase in FARM pupils in the receiving districts – in the case of Douglas County, a more than six-fold increase (2.5% to 16.9%). By our assumptions, many of those new pupils would have been eligible for fully subsidized meals – that is, their family incomes would have been less than $23,490 for a family of four in 2000. Undoubtedly, some would have been from very poor families receiving public assistance, but most would have had parents who worked full-time in low-paying jobs. Many other new pupils whose parents earned up to $32,190 (for a family of four) would have been eligible for only partially subsidized meals. Their parents would have worked in jobs paying up to $15.50 an hour – a wide range of jobs in the retail trades, service industries, and local government.

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All this would have flowed from a change in public zoning policies whose net effect would have required just 2.5 percent of all new housing built to be acquired by a regional public housing authority for very low-income families and just 5.0 percent of all new housing to be affordable to persons in what used to be described as the “working class.”

Indeed, this analysis illustrates not just the hypothetical effect of inclusionary zoning but how relentlessly and thoroughly local governments in Douglas County (as the most extreme example) have actually practiced exclusionary zoning.

Thoughts about Re-gentrification

Implicit in the mathematics of Table 8.2 is also an assumption that, as families with FARM-eligible children move into new suburban subdivisions, their places in the city and older suburbs are taken by middle-class families with children moving back into closer-in neighborhoods. That, of course, is a heroic assumption. Though re-gentrification is occurring in Denver as in many cities, as discussed in module 4, the middle-class newcomers are overwhelmingly households without children or they choose to send their children to parochial or private schools. I know of no central city that has yet succeeded in re-attracting substantial numbers of middle-class children back into its public school system.

Nonetheless, the city of Denver has some strong assets around which it could rebuild its middle-class pupil population school-by-school. The city continues to be the location of major, high-quality employment centers – a strong downtown with its corporate headquarters, banks, utilities, law, accounting, and other business services firms, and, of course, state and city-county office complexes; major medical centers; and major university and college campuses, like the University of Denver and Metro State University.

Across the country there are many examples of major private and public employers that use their own corporate or institutional funds to provide grants for down payments and to subsidize lower-interest mortgages for employees who will buy homes in surrounding neighborhoods.53 Such “employer-assisted housing benefits” are becoming increasingly common both to reduce employees’ commuter times and costs and as a strategy to re-gentrify declining neighborhoods in which many such hospitals and college 53 Indeed, as part of its Smart Growth policies, the state of Maryland has established a multi-million “Walk-to-Work” fund to match

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campuses are located. Surrounding your institution with friendly, law-abiding neighbors is more cost effective than paying hundreds of thousands or millions of dollars annually for large security services.

Such programs may still not succeed in encouraging employee-residents to enroll their children in neighborhood schools with very high percentages of low-income children. Many middle-class parents hesitate to have their child be among the few non-poor children. They are seeking some “critical mass” – typically, a majority middle-class pupil population that is unattainable based on current neighborhood demographics.

However, those major employer institutions (that may be providing employer-assisted housing benefits) have hundreds of employees with children – many more than will take advantage of employer-assisted housing inducements – who continue to live in homes scattered across the region. Some employees may prefer to have their children attend a high-quality, full-day school near their employment location rather than face “latchkey” problems 10, 20, or 30 miles away. This is especially true with the growth of both single parent and two working parent families.

In Albuquerque the city government and school district collaborated on creating two elementary schools – Longfellow and Lew Wallace – with special enrollment policies. Both schools are located in predominantly poor, but slowly re-gentrifying neighborhoods surrounding downtown Albuquerque. The school district provided an enriched, magnet-school type curriculum. The city covered the costs of an extended day program. A smaller neighborhood attendance zone was created so that no more than half of each school’s capacity would be filled by neighborhood children. The rest of the enrollment was reserved for children of downtown office workers who would drop their children off at school on the way to work and pick them up again at the end of the work day. Both schools have been very popular with working parents.

Albuquerque Public Schools is a unified, countywide system (larger than Jefferson County Public Schools) that covers both the city and outlying areas. APS easily accommodates such intra-district transfers. But within New Mexico’s system of educational finance, even inter-district mobility raises no fiscal issues; the state funds 100 percent of the operating budgets of all school districts. Hence, dollars follow children.

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In greater Denver any inter-district transfers, such as might be the result of creating Longfellow/Lew Wallace-type schools, could raise fiscal issues. Some special program of state aid might be required. The state of Missouri, for example, provides special funding both to 16 suburban districts that enroll 12,500 black students annually from the city of St. Louis and to the city school district that enrolls 1,500 suburban students annually in its magnet high schools as part of a long-standing, “voluntary,” cross-district integration program that was brokered in the shadow of a civil rights suit.

As I stated, on a school-by-school basis, such creative policies might rebuild the middle-class enrollment of Denver Public Schools. Achieving the same for the Adams-Arapahoe district would be more problematic. Suburban communities like Aurora typically don’t have the major employer institutions, cultural facilities, and historic, once (or still) prestigious neighborhoods. Most suburbs that developed in the 1950s and 1960s have housing stock that is “too old to be competitive and too young to be quaint,” as I was once told about Reading, Pennsylvania’s first-ring suburbs.

Summing Up

Some may view the preceding analysis as simply an exercise in mathematics. Tables 8.1 and 8.2 depict the results of flawless implementation (which is rarely achieved).54 However, this analysis frames the outer limits of what could be achieved by such policies.

But, critics of my proposals usually argue, changing housing patterns as you recommend would take too long. Shouldn’t all efforts be concentrated on providing low-income children with the best possible quality education in their current neighborhood schools?

I agree that we have a responsibility to do the best that we can by low-income children wherever they are right now. I would not advocate simply abandoning such efforts.

But, at the federal level, we have been following a conscious remediation strategy for almost forty years, principally through $7.2 billion a

54 Montgomery County’s MPDU program, however, has come very close to hitting its policy targets. The 11,210 MPDUs built by private, for-profit homebuilders represent 7.4 percent of 152,000 units built. The Housing Opportunities Commission has bought or rents 29 percent of the MPDUs (close to its one-third target allocation).

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year in Chapter I support for poverty-impacted schools. The most comprehensive federally-sponsored evaluation of Chapter I, tracking the progress of 40,000 students over four years, found that Chapter 1 intervention failed to narrow the learning gap between the low-income students it served and non-low-income students.55

“High-poverty schools put disadvantaged students in double jeopardy,” the researchers concluded. “School poverty depresses the scores of all students in schools where at least half of the students are eligible for [federally] subsidized lunch, and seriously depresses the scores when over 75 percent of students live in low-income households.”

To the response that some high-poverty schools do succeed, “the authors warned that the sample of successful schools was too small to be scientifically reliable.”

A recent book, No Excuses, published by the Heritage Foundation of Washington, DC, focused on case studies of 21 high-poverty schools around the country that were succeeding in raising low-income children’s academic achievement. “Quite true,” the Century Foundation’s Richard Kahlenburg commented to me. They usually reflect special circumstances where an inspired principal, given a largely free hand, has recruited a corps of talented, highly motivated teachers, corralled additional resources, and successfully engaged parents in school activities. But if that magic could be bottled and spread throughout whole school districts,” he concluded, “there wouldn’t be a need for books like No Excuses.”

That conclusion was confirmed several years ago when Education Week dispatched a reporter on a nationwide tour to find a successful “urban” school district with (like Denver Public Schools) more than 60 percent low-income pupils. The reporter’s finding: there are no successful urban school districts.

Federal funds represent only about 7 percent of all public school finance, remediation advocates contend; even in Chapter 1-eligible schools, federal funds don’t add 25 percent to the schools’ resources. We need to spend much more to offset the handicaps low-income children face.

55 David J. Hoff, “Chapter 1 Study documents Impact of Poverty,” in Education Week (April 16, 1997) (www.edweek.org).

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The experience of the Netherlands with remedial funding for low-income pupils is instructive.56 Since 1919, the Dutch national government has provided 100 percent of the funding not only for non-sectarian public schools but also for all Catholic, Protestant, Jewish, Muslim, and other religiously-based schools. Moreover, all parents are constitutionally guaranteed total freedom of choice in where to send their children to school. De facto tax-funded vouchers, freedom of choice, and tax support for religious educational institutions – controversies that wrack the American political scene – have been established Dutch public policy for almost a century.

Recognizing the special problems that low-income children must often overcome, the national funding formula provides a 25 percent bonus per student for “low-income” ethnic Dutch students (so-called “1.25 students) and a 90 percent bonus per student for “low-income” ethnic minority students (so-called “1.9” students).

Universal school choice is the hallmark of the Dutch educational system. However, school choice is hardly the cure-all that American conservatives envision. After all parental choices are made, Dutch schools are much more segregated than Dutch neighborhoods and even somewhat more segregated (ethnically and economically) than schools in American metro areas with similar ethnic profiles. Academic performance of “black schools” (i.e. majority immigrant schools) is particularly low and seemingly resistant to more funds.

A recent report by the Dutch Court of Audit concluded that it is unclear whether or not an annual expenditure of 1.2 billion guilders in compensatory education for 1.25 and 1.90 students has had any positive impact. Educational goals are not clearly established nor are adequate administrative controls in effect. However, after 35 different evaluation

56 See my report for the Dutch government that compares sprawl and segregation in matched Dutch and American metro areas. It is also called “Inside Game/Outside Game: Segregation and Spatial Planning in Metropolitan Areas” in collaboration with ABF Strategie (Dirk Frieling and Leon Groenemeijer) Washington, DC/Delft/Amsterdam (February 2001). The report was commissioned by three Dutch ministries (Interior and Kingdom Relations; Economic Affairs; and Agriculture, Nature Preserves, and Fisheries) and the municipalities of Arnhem and The Hague. A draft is available on my website (www.davidrusk.com).

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studies over the course of two decades, the review found, “the results of substantial compensatory funding are unclear.”

And nobody in the United States is contemplating spending almost twice as much to educate low-income minority pupils as is spent on educating white middle-class children, as the Dutch do.

Socioeconomic integration, the Dutch find, works as well in Dutch society as it does in American society. While we seek to deal responsibility with immediate need (through compensatory programs), we must change the systems that increasingly isolate poor children from mainstream educational and employment opportunities. Otherwise, why, if we continue to do the same old thing in the same old way, should we expect anything other than the same old results?

Suggested reading: In addition to the education sources citied, Chapter 9 (Montgomery County: Mixing Up the neighborhood) in Inside Game/Outside Game is a case study of their pioneering inclusionary zoning policy.

An invaluable summary of 107 local inclusionary zoning laws in California, where one-fifth of the state’s cities and counties have adopted such measures, is the Non-Profit Housing Association of Northern California and the California Coalition for Rural Housing’s new report, Inclusionary Zoning in California: 30 years of Innovation (www.nonprofithousing.org).

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Box 8.1 Denver Enacts Colorado’s First Inclusionary Zoning Law

In August 2002, after nearly three years of study and debate, the Denver City Council adopted its own inclusionary zoning ordinance, Colorado’s first and the Mountain West’s second (after Santa Fe, New Mexico).

The law requires that all for-sale developments of 30 dwelling units or more include at least 10 percent of “Moderately Priced Dwelling Units (MPDUs)” that are affordable to households earning nor more than 80 percent of the Denver area medium income (AMI).57

For buildings greater than three stories, with elevators, and with at least 60 percent of the parking provided underground, the maximum income ceiling is raised to 95 percent of AMI.

To ensure long-term affordability, MPDUs are subject to maximum re-sale price for a 15-year control period.

Under the MPDU law, the city of Denver will pay a developer a standard subsidy of $5,000 for each MPDU constructed (or $10,000 if the MPDU is affordable to households earning no more than 60 percent of AMI) up to a maximum of half of the total number of units in a development.

In an effort to help developers recoup some of the costs of providing MPDUs, the law also provides expedited processing of development applications and supplemental incentives for developers building in certain zone districts in the form of i) a density bonus of up to 10 percent, and ii) a parking reduction of up to 20 percent.

For example, if a new development is proposed to consist of 200 units as permitted “by right” under existing zoning for the underlying land, 20 units would have to be designated as MPDUs that are dispersed and integrated within the overall development (that is, no clustering of MPDUs, which are required to be “indistinguishable” from an exterior design standpoint).

Further, under the density bonus incentive, this developer would be permitted to build an additional 20 units (two of which would also have to

57 For 2003, metro Denver’s AMI is $xx,xxx for a family of four.

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be MPDUs). The developer would also be permitted to construct up to 20 percent less parking than would otherwise be required.

The MPDU law does provide alternatives to developers in lieu of building the required number of MPDUs, subject to approval by the Denver Community Planning and Development Agency: i) to build the required number of MPDUs off-site in the same neighborhood, or ii) contribute to a special revenue fund an amount equal to 50 percent of the price per MPDU not provided.

It is currently estimated that this payment in-lieu option will cost developers approximately $75,000 per MPDU not provided. Monies deposited in the special revenue fund are top be used to make the $5,000-$10,000 per MPDU standard incentive payments to developers.58

* * *

Denver’s MPDU ordinance is a commendable first step into inclusionary zoning for the Greater Denver region. It is, however, targeted very narrowly. As a for-sale only policy, it does not address the affordable housing needs of renters. With an eligibility ceiling of 80 percent (or even 95 percent) of AMI, it will assist middle-level workers, including undoubtedly many lower-ranking municipal employees.

But in the absence of lower income targets or any policy for direct acquisition of MPDUs by the Denver Housing Authority (as Montgomery County’s Housing Opportunities Commission does), it will help few (if any) very low-income working families. Since the income eligibility cut-off for subsidized school lunches is about 60 percent AMI, the policy will have little impact on integrating low-income pupils into more affluent neighborhoods even within Denver Public Schools.

[607 words]

58 The foregoing description of Denver’s MPDU law is slightly edited from an excellent article by Timothy N. Devlin of Fairfield and Woods, P.C. (www.fwlaw.com/housing.html).

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Box 8.2 Inclusionary Zoning Now in 131 Communities

Following Montgomery County, Maryland’s lead, at least 130 cities, towns, and counties have enacted inclusionary zoning (IZ) ordinances. Almost 13 million people (about 5 percent of the USA’s population) live in communities where the local government mandates mixed-income housing.

IZ jurisdictions range in population size from giant Fairfax County, Virginia (945,717) to the tiny Town of Isleton, California (818). Some 107 counties and municipalities in California have enacted IZ laws (about one-fifth of all local governments in that state), but there are other clusters of IZ communities in the Washington, DC and Boston regions (also high-cost housing markets). In September 2003, Highland Park, a suburb of Chicago, passed the first IZ law in the Midwest.

Municipal governments have adopted IZ laws in at least 31 counties. The 31 pioneers averaged only 16 percent of their counties’ population at the time they adopted their area’s first IZ law. However, additional neighbors have followed suit and a dozen county governments have enacted IZ laws covering unincorporated land so that, on average, IZ requirements now cover over half (54 percent) of the 31 counties’ populations.

For example, Pleasanton was less than 5 percent of the population in California’s Alameda County when it adopted its IZ ordinance in 1978. However, similar laws enacted by San Leandro (1980), Berkeley (1986), Livermore (1986), Emeryville (1990), Dublin (1996), Union City (2001), Fremont (2002) and Alameda County itself (2000) have raised IZ coverage to 55 percent of that East Bay county’s population.

Each community tailors its ordinance to its own housing needs and building industry scale. The key issues are minimum project scale (“trigger point”), percentage of inclusionary units required (“set-aside”), maximum income for eligible households, size of density bonus, and length of control period for re-sale prices or rents.

Inclusionary requirements are triggered by housing developments as low as a minimum of five units and as large as a minimum of 50 units. The most common threshold at which IZ is required is ten or more units.

Set-aside percentages for affordable housing range from as low as 5 percent to as high as 35 percent. Almost three-quarters of the communities

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require setting aside between 10 and 15 percent of the total units in eligible developments as affordable housing.

Maximum eligible income ceilings range from 30% AMI (area median income) to 120% AMI. (The federal Department of Housing and Urban Development provides annual AMI calculations for all metro areas.) Many communities apportion units among different income levels (for example, 25 percent of the units for less than 50% AMI, 50 percent of the units for less than 80% AMI, and 25 percent of the units for less than 120% AMI).

About 40 percent of all jurisdictions target all or a portion of the inclusionary housing for households under 80% AMI. Many of these allocate an addition proportion for households from 81% - 120% AMI. (All this communities are in Northern and Southern California and the Boston area, with their sky-housing housing costs.)

One fifth of all jurisdictions target all or a portion of the units for very low income households (50% AMI). Reaching even lower on the income scale typically requires funneling public housing subsidies into the program through actions such as having the public housing authority purchase affordable units outright or using housing vouchers in rental properties.

Density bonuses are utilized by 95 percent of all IZ ordinances as a primary cost-offset for homebuilders, though other cost-offsets are also common. In California, 44 percent of IZ laws offer fast-track processing, 42 percent waive certain fees, 42 percent allow reduction of certain standards (like parking requirements), and 38 percent provide direct cash subsidies (like Denver’s policy).

Re-sale price and rent control periods generally are quite long in order to maintain a stable, long-term inventory of affordable housing. Only 14 programs have control periods of only 10 or 15 years. Twenty (20) communities require a minimum 20-year control period; 47, a 30-year control period; seven, 40 to 45 years; 20, 50 to 55 years; five, 59 to 60 years; four, 99 years; and 23 require IZ housing to be permanently affordable. Thus, somewhere in the USA, there are communities whose current IZ policies would match the needs and housing industry scale of any of greater Denver’s five counties and 29 municipalities.

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CONCLUDING REMARKS (draft 9/7/03)

“Social engineering!”

I can hear the disparaging, dismissive response already.

What is inclusionary zoning but just another liberal exercise in “social engineering”?

In my experience, “social engineering” is what opponents label laws and regulations that would produce results that they don’t agree with.

Efforts to change laws and regulations that produce outcomes that they disagree with are un-American plots to interfere with the workings of the “free market.”

If inclusionary zoning is viewed as “social engineering,” what is one to call local zoning regulations that require large minimum lots or ample minimum square footage for single family homes or require expensive, on-site, covered parking for all vehicles or limit the number of bedrooms in apartments (no families with children, please) or ban apartment construction entirely (as some suburban counties in greater Atlanta do)? All these are examples of “exclusionary zoning.”

In fact, certainly at a county level, I cannot think of a greater example of “social engineering” that Douglas County’s emergence as the nation’s wealthiest county – and 90 percent Anglo in a region that that is 30 percent African American, Hispanic, and other minorities.

Unlike Fairfax County, Virginia (number 2 and the global capital of the Internet) or Montgomery County, Maryland (number 13 and the world center of biomedical and genetic research), Douglas County is not itself a generator of wealth. Its planning and zoning policies are designed to skim off the cream from wealth created elsewhere in the region, most notably, in the city of Denver itself.

And unlike Fairfax County (1,735 Affordable Dwelling Units produced since 1990) or Montgomery County (11,210 Moderately Priced Dwelling Units produced since 1975), Douglas County has nothing resembling a mandatory inclusionary zoning policy. These two counties recognized the value of a fundamental concept of economic development

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(not to mention basic social fairness), namely “anybody who is good enough to work in our community (at whatever level of skill and income) is good enough to live in our community.”

And what of this notion that policies like inclusionary zoning are “interfering with the workings of the ‘free market?’”

Aside from the defense industry, I cannot think of a sector of the American economy that is more shaped by public policy and more dependent on public investment than land development and housing construction.

But let me turn to an independent expert witness on this point. “Public policy dictates where development occurs,” states the National Association of Home Builders (no overt champions of public regulation).59

Certainly, homebuilders and land developers lobby city councils, county commissions, and state legislatures hard to adopt “rules of the game” that favor their goals regarding market-derived profitability. Thus, it is a little disingenuous for the NAHB to assert that “public policy dictates where development occurs” when homebuilders have so much to do with what those public policies are.

But changing the “rules of the game” can be a mission for other civic interests and civic activists as well.

Well, local doubters will say, Portland had all those tree-hugging environmentalists or Montgomery County was just a liberal bastion of New Frontiersmen. Passing a strong, anti-sprawl, state land use law or a county-wide inclusionary zoning policy was easy there. It can’t happen here.

That’s nonsense. Changing the “rules of the game” is never easy in the face of the entrenched opposition of those who benefit from the current regime, the inertia of familiar way, and deep-seated fears about race, class, or “Big Government.”

Enacting land use reform in Oregon and inclusionary zoning in Montgomery County were both long, hard political battles that required courageous political leadership.

59 Smart Growth: Building Better Places To Live, Work, and Play. Washington, DC (1999), p. 8.

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The Oregon Land Use Act of 1973 wasn’t primarily the accomplishment of tree-hugging, liberal environmentalists from Portland. Republic Governor Tom McCall led the charge. Conservative Republican farmer-legislators (determined not to let the Willamette Valley be paved over by Portland’s sprawl) fought for the reform in the legislative trenches.

A six-year campaign, led by the League of Women Voters, Suburban Maryland Fair Housing, and a coalition of forty local churches ultimately convinced the Montgomery County Council to adopt its inclusionary zoning ordinance (also in 1973). Success came only after an election in which progressive Democrats won all nine seats on the county council and the former president of the League of Women Voters, Ida Mae Garrott, was elected chair of the county council.

Saying “it can’t happen here” is merely an excuse for not undertaking the arduous, long-term task of political organization to make it happen.

Effective, region-wide, anti-sprawl, land use planning probably will require state action. Despairing of ever succeeding in the Colorado legislature, Smart Growth advocates unsuccessfully sought a constitutional amendment in 2000. Proponents should learn the necessary lessons from its defeat at the polls and renew the effort.

Inclusionary zoning would be most effective if it were adopted region-wide (as projected in Module 8). But if metropolitan-wide coverage were the political pre-condition, there would not be an inclusionary zoning law in the country. Even on a county basis, the only two “county-wide” inclusionary zoning laws are Denver and San Francisco’s (which are consolidated city-counties). Even Montgomery County’s policy covers only 90 percent of its county’s population (with seven municipal hold-outs) and Fairfax County’s, only 96 percent (with two municipal hold-outs).

However, by my latest tabulation, 128 cities and counties have enacted mandatory inclusionary zoning, covering almost 13 million residents (about five percent of the USA’s population). In fact, the first jurisdictions to enact inclusionary zoning averaged only 19 percent of their county’s population at the time of enactment (including ten that averaged less than five percent of their county’s population). Their good example was followed by neighboring jurisdictions such that local inclusionary zoning laws now average 51 percent coverage of their county’s population. The oft-raised argument that if just one jurisdiction only adopts inclusionary

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zoning, builders will just abandon it and transfer their activity to neighboring communities falls into the category of “urban legend.” There is no evidence that such has happened anywhere.

Thus, within the Denver metro area, there are plenty of opportunities for local citizen campaigns to convince the five county commissions and remaining 28 cities to follow the City of Denver’s lead and adopt mandatory, inclusionary zoning ordinances.

I have presented exemplary policies that have worked elsewhere to confront urban sprawl, increasing economic segregation of regional housing markets, and growing economic segregation in public schools.

The Bridges to the Future study groups may come forward with other proposals.

I can only guarantee one thing. These problems will not take care of themselves just by doing nothing. The current “rules of the game” work to fragment and divide the greater Denver community.

The central challenge is: will we cross those Bridges to the Future together?