Race, Ethnicity and Residential Intermixing in

US MSAs

Lawrence A. Brown and Madhuri SharmaDepartment of GeographyThe Ohio State University

International Conference on Population Geographies IV

Hong Kong

Population Growth and Increasing Diversity

Total US Population1990: 248.7 million2000: 281.4 million2006: 300.0 million (Oct 17th)

Pct of Total US Pop Foreign Born1950: 06.5%1990: 09.5%*2000: 13.0%

Pct Pop Foreign Born, Selected MSAs (from 49 largest)Miami: 40.2%Los Angeles: 31.0%New York: 24.4%Houston: 19.2%Chicago: 16.0%Cincinnati 02.6%

Over past half-century –

Non-Hispanic Caucasians Fell – 83% of the Population in 1970 to 67% in 2003

Foreign-Born Rose – 6.2% of the Population in 1980 to 12.5% in 2005

Today –More than 11 million undocumented Foreign Born

Racial/Ethnic Intermixing has Increased Notably – in Places of Consumption, Work, Residence – and Trend is Ongoing

Research Questions How Does Intermixing Vary Among MSAs?

~94% percent of foreign-born in 2000?Usually raised in context of two-group comparisons; e.g., Caucasians vs African Americans, Asians, Hispanics Measures such as the aDissimilarity IndexHere –

Intermixing of All Groups Together, Theil Entropy IndexLink Degree of Intermixing to MSA Characteristics,

a particularly geographic, or spatial, approach. MSAs > 1 million pop in 2000, neither entire range nor

few largest gateway cities.Strong Evidence that R/E Minorities increasingly Locate

where Caucasian historically dominant, but some claim simply results in new R/E Enclaves, not heterogeneity Theil Entropy Index can address this directly

Measures: Integration/Segregation, Intermixing

Single Group or Two Group Measures:Dissimilarity / Exposure Indices

MSA Level - most commonly usedSpatially-Modified Dissimilarity Indices

MSA Level - not usedLocal Moran’s I, Location Quotient, Getis G

Tract/Block Group Level - less used

Multiple Groups Simultaneously:Theil’s Entropy Index

Can be decomposed into its component parts – e.g., MSA, Census Tract, Block Group; or races/ethnicities such as AA-A-C-H

Two Components: Diversity Score + Entropy Index

D = Diversity Score for MSA/CityD(i) = Diversity Score for Census Tract/Block Group iPr(g) = proportion of R/E group g

Summed over all R/E groups in MSA/Census Tract iYields Diversity Score for the MSA/Census Tract i

Diversity Scores measure R/E Diversity for the spatial unit

}Pr(/1{)Pr(1

g

g

gLngD

}Pr(/1{)Pr(1

g

giii

i

gLngD

D values differ depending onnumber of groups (g) proportion (Pr) of each group.

Bounds of the Diversity Score

Upper Bound represents Equal Proportions of Each Group; Depends on the Number of Groups

6 R/E groups, each with Pr = 0.167; D = 1.7995 R/E groups, each with Pr = 0.200; D = 1.600 4 R/E groups, each with Pr = 0.250; D = 1.386

Lower Bound D = 0 (only single group)

Entropy Index measures Intermixing at MSA level --

How evenly groups are distributed across MSA neighborhoods relative to their proportions in the MSA overall

E = Entropy Index for MSA/Cityt(i) = Population of Census Tract/Block Group i D, D(i)= Diversity Scores for MSA, Tract/Block Group iT = Population of MSA/City

n

i

ii

DTDDtE

1

)(

E Computation -- The deviation of each unit’s (i) diversity score from MSA-wide diversity is weighted by the population of i (relative to the population of the MSA) and summed for all i

E Boundaries -- From 0 = high intermixing; 1 = high clustering

Present Study49 MSAs > 1 Million in 2000; Tract Level DataFrom Louisville (1.0 million) to New York (21.2 million); Distinct break at Philadelphia (6.2 million ); only San Francisco (7.0 million), Washington (7.6 million), Chicago (9.2 million), Los Angeles (16.4 million), New York are larger.Focus, then, on Mid-Sized MSAsFive Racial/Ethnic Groups -- African Americans, Asians (HW-Pac Islanders), Caucasians, Hispanics, American Indians;Data Source: US Census

Diversity Entropy (Intermixing) Most San Francisco, D = 1.21 Most Seattle, E = 0.12

Los Angeles, D = 1.20 Salt Lake, E = 0.13Houston, D = 1.18 Portland, E = 0.13

Least Pittsburgh, D = 0.41 Least Detroit, E = 0.50

Medium Jacksonville, D = 0.82 Medium Columbus, E = 0.29Denver, D = 0.84 Boston, E = 0.28Philadelphia. D = 0.86 Houston, E = 0.28

Los Angeles, E = 0.28

Correlation Between Diversity and Entropy = -0.17!!Not What Might be Expected!!

Important Dimension of Entropy Index

Can be Decomposed to Gauge Contribution from Components

E.g., Decompose Intermixing at MSA Level into that Portion Contributed by Block Group Compared to Census Tract Level

Here -- Gauge Role of Intermixing of Caucasians vs Minorities as a Group, Compared to Role of Intermixing Among Minority Groups Alone

First -- Compute D and E as in Equations Shown Earlier, symbolized as DC/M and EC/M for Caucasians vs Minorities-as-a-group & DAA/AI/A/H and EAA/AI/A/H for minorities among themselves.

These combine to form E at MSA (EMSA) level as follows --

EMSA =

(DC/M / DMSA) * EMSA + PrM * (DAA/AI/A/H / DMSA) * EAA/AI/A/H

where – EMSA and DMSA are E and D in equations shown earlier

PrM is proportion of MSA population minorities (or non-Caucasians).

Hence --CM term indicates the portion of MSA intermixing attributable to Caucasians living separately from, or intermixing with, minorities-as-a-group

AA/AI/A/H term indicates the portion of MSA intermixing attributable to minorities living separately from, or intermixing with, one another.

MSA Profiling

StatisticsDiversity

Score 2000 (D)

Entropy Index

2000 (E)

Median 0.82 0.28

Minimum 0.41 0.12

Maximum 1.21 0.50

Percentiles 35 0.73 0.24

50 0.82 0.28

65 0.91 0.32

Hi Diversity if D = 0.91 or Greater Hi Intermixing if E = 0.24 or LessMed Diversity if D < 0.91, > 0.73 Med Intermixing if E < 0.32, > 0.24Low Diversity if D = 0.73 or Less Low Intermixing if E = 0.32 or Greater

Nine Groups --HI-I/LO-D; HI-I/MED-D; HI-I/HI-DMED-I/LO-D; MED-I/MED-D; MED-I/HI-DLO-I/LO-D; LO-I/MED-D; LO-I/HI-D

MSACateg.

MSAChar. # MSAs

HI/LD  Sun Belt 3Minneapolis--St. Paul, Portland-Salem, Salt lake

HI/MD Hi

Hispanic6 Charlotte, Denver, Norfolk, Oklahoma City, Raleigh-

Durham, Seattle-Tacoma

HI/HD HiMinority

8Austin, Las Vegas, Orlando, Phoenix, Sacramento, San

Antonio, San Diego, San Francisco,

MI/LD 

6 Boston, Columbus, Grand Rapids, Nashville, Providence, Rochester

MI/MD   5Greensboro, Hartford, Jacksonville, Tampa, West Palm

MI/HD   3 Dallas, Houston, Los Angeles.

LI/LD LargelyAMB/

8Buffalo, Cincinnati, Cleveland, Indianapolis, Kansas

City, Louisville, Pittsburgh, St. Louis

LI/MD Rust Belt 4Detroit, Memphis, Milwaukee, Philadelphia.

LI/HD Gateways 6 Atlanta, Chicago, Miami, New Orleans, New York,

Washington DC

Categories of 49 MSAs based on Level of Intermixing and Diversity

Tend to be LI/LD, LI/MD

Scattered Between HI/HD, MI/MD, LI/HD

Tend to be HI/LD, HI/MD, HI/HD, MI/HD

Scattered Between HI/LD, HI/MD, MI/LD, LI/LD, LI/HD

Dimensions That Differentiate These Maps

Era of Immigration:Pre World War II, Early 20th Century (I); 1960s and Later (II, III); 1980s and Later (IV)

Destination Areas of Immigrants:American Manufacturing Belt (I), Florida (II), West of the Mississippi (Great Plains + West) (III), East of the Mississippi (Mid-West + Southeast (IV)

Origin Areas of Immigrants:Europe, especially South and East (I), Caribbean and South America (II), Central America, largely Mexico (III), South Central Asia, East Asia, Africa (IV)

Place Characteristics Drawing Immigrants:Industrial Centers (I), Accessibility + Contiguity (II), Accessibility + Contiguity initially w/ Recruitment for Agric + Industry and “Wetbacks” (III), Refugee Resettlement Programs, Foreign Direct Investment, Universities (IV)

Foreign Born Profiles of Largest MSAs (> 5 million, except Miami):Chicago, Dallas, Los Angeles, San Francisco – strong Central American, largely Mexican; New York, Miami – strong Caribbean, South American; Boston, Detroit, Philadelphia – Strong European; Washington – strong South Central Asian, East Asian, African

Can extrapolate from relationship between Brown et al MSA groups, based on immigration data, and MSA groups, based on Diversity Scores and Entropy Indices on R/E intermixing. Suggests variables/aspect/factors related to residential intermixing in urban areas.

From Group I, seems that –► Intermix muted in MSAs strong in Fordist mfg era► Largely European foreign-born► Foreign-born in US for longer time span► Foreign-born relatively small share of MSA pop

Group II relationships -- scattered + uninformative

Group III relationships –► Hi intermix MSAs large share US Mex/CentAM pop► Sun Belt MSAs w/ post-Ford econ activity, post-indl► Immigration recent, from 1960s onwards► Urban growth since mid-20th century substantial

E.g., Of 21 Group III MSAs, 1980-00, 17 grew 25% or more, 11 exceeded MSA avg growth of 43%; one (Las Vegas) 237%

Group IV relationships –► Low intermix in Cincin, Indianapolis, Washington

Like Group I MSAs, in AMB, Fordist, early waves immig, largely European► Hi/Med intermix in Charltte (61% growth), MSP (38%),

Nash (45%), Raleigh (87%), CMH (27%); ~ Group III, urb growth substantial, Sun Belt MSAs, post-Ford/indust, immig 1960s onwards

► CMH in mid AM/Rust Belt, but grew in later era than typical AMB MSA, distinctly diff econ base, “sun belt city in the rust belt”

► Hi/Med intermixing MSAs a focal point for refugee resettlement efforts + new economic activity -- technology (CMH, MSP, Raleigh), foreign auto mfg (CMH, Nash), organizational innov in finance and/or banking (Charlotte, CMH).

 E-Indices (All)

E-Indices (Cauc. vs. Minor.)

E-Indices(Among Minor.)

Entropy Indices for MSA (All Groups) 1 .939(**) .569(**)Entropy Indices (Cauc. vs. Minor.) .939(**) 1 0.3Entropy Indices (Among Minor.) .569(**) 0.3 1Diversity Scores for MSA (All Groups) -0.172 -.398(**) .469(**)Diversity Scores (Among Minor.) -.473(**) -.580(**) 0.1

Correlation Values for Entropy Indices and Diversity Scores for 49 MSAs in 2000

NN

Diversity Overall contributes little to Intermixing OverallDiversity Among Minorities-as-a-group significantly to Intermixing OverallDiversity Among Minorities highly related to Intermixing of C

vs MinoritiesIn Overall Intermixing, that of C vs Minorities More Important than Among Minorities themselvesSuggests that Hi Intermixing is Minorities in C Areas

  Socio-Economic Characteristics r-ValuesPer Capita Income (Total Population) -0.008

Per Capita Income (Total Population) Logged 0.001

Per Capita Income (African American) Logged -0.347(**)

High School or Less Education (2000, Percent) 0.511(**)

Some College or Associate Degree (2000, Percent) -0.567(**)

Bachelors Degree (2000, Percent) -0.307(*)

Graduate or Professional Degree (2000, Percent) 0.023

Some College, Associate, or Bachelors Degree (2000, Percent -0.626(**)

Owner Occupied HHs in MSA (2000, Percent) 0.202

African American Owner Occupied HHs ( 2000, Percent) 0.398(**)

Asian Owner Occupied HHs (2000, Percent) -0.323(*)

Hispanic Owner Occupied HHs (2000, Percent) -0.238

African American Rented HHs (2000, Percent) 0.550(**)

Asian Rented HHs (2000, Percent) -0.298(*)

Hispanic Rented HHs (2000, Percent) -0.291(*)

Change in African American Owner Occupied HHs (90-00, Percent) 0.252

Change in Asian Owner Occupied HHs (90-00, Percent) -0.014

Change in Hispanic Owner Occupied HHs (90-00, Percent) -0.084

Change in African American Rented HHs (90-00, Percent) 0.310(*)

Change in Asian Rented HHs (90-00, Percent) 0.212

Change in Hispanic Rented HHs (90-00, Percent) -0.098

Correlation Values for Entropy Index (Overall) for MSAs

NB: Significant Correlations Among Socio-Economic Characteristics

Income: ► Per Capita Income of AA relates to Greater Intermixing (-0.35)

Education: ► High School or Less relates to Less Intermixing (+0.51)► Some College (or Assoc) or BS/BA relates to Greater Intermixing

(-0.57, -0.31, -0.63 when combined)

Home Ownership (O) and Renting (R):► African American O+ R relates to Less Intermixing (+0.40, 0.55); Inertia

or Enclave Effect??► Asian O+R relates to Greater Intermixing (-0.32, -0.30)► Hispanic R relates to Greater Intermixing (-0.29); O same direction, not

signif

Home Ownership (O) and Renting (R) Change 1990-2000► African American Change, O or R, relates to Less Intermixing

(+0.25 (but not signif), +0.31 (signif)); Inertia or Enclave effect??

Demographic Characteristics r-ValuesDiversity Score for MSAs (Overall) -0.172Diversity Score (Minorities-Among-Themselves) -0.473(**)Diversity Score (Caucasians vs. Minorities) -0.081MSA Population (2000) 0.231MSA Population LN (2000) 0.239Change in Population (1980-2000, Percent) -0.588(**)Change in Population (1990-2000, Percent) -0.392(**)African Americans Portion of MSA Population (2000) 0.463(**)Asians Portion of MSA Population (2000) -0.362(*)Hispanics Portion of MSA Population (2000) -0.269Change in Caucasian Population (1990-2000, Percent) -0.549(**)Change in African American Population (1990-2000, Percent) -0.572(**)Change in Asian Population (1990-2000, Percent) -0.211Change in Hispanic Population (1990-2000, Percent) -0.309(*)Foreign-Born Portion of MSA Population (2000, Percent) -0.187Change in Foreign-Born Population, 1990-2000 (Percent) -0.420(**)Population who Lived in Different House in 1995 (Percent) -0.684(**)

Correlation Values for Entropy Index (Overall) for MSAs

NB: Significant Correlations Among Demographic CharacteristicsMSA Diversity: ► Diversity for Minorities-among-themselves relates to Greater

Intermixing (-0.47); Diversity Overall + Caucasians vs Minorities, likewise, but not significantPopulation Characteristics: ► Higher proportion of Asians relates to Greater Intermixing (-0,36);

likewise Hispanics but not significant; Higher proportion of AArelates to Less Intermixing (Inertia or Enclave effect??)

Migration Dynamics:► Growth Overall 80-00 + 90-00 relates to Greater Intermixing (-0.59, -0.39)► Change in the proportion of African Americans, Hispanics, and

Foreign-Born relates to Greater Intermixing (-0.57, -0.31, -0.42);likewise Asians but not significant

► What does it mean that a high proportion of AA relates to LessIntermixing, while a positive change in that proportion relates to MoreIntermixing??

► Proportion of the population who Lived in a Different House in 1995relates to Greater Intermixing (-0.68)

Built-Environment Characteristics r-Values Foreign-Born Entered Before 1965 as Percent Total F-B 0.475(**)Foreign-Born Entered 1980-2000 as Percent Total F-B -0.412(**)Median Value of Owner Occupied HH (2000) -0.227Median Year Housing Structure Built -0.644(**)Houses Built Before 1970 as Percent of 2000 Stock 0.651(**)Houses Built Between 1970-1990 as Percent of 2000 Stock -0.641(**)Houses Built Between 1990-2000 as Percent of 2000 Stock -0.547(**)Manufacturing Employment 1980 (Percent Total Employment) 0.347(*)Managerial/Professional Employment 1980 (Percent Employment) -0.310(*)Manufacturing Employment 1990 (Percent Total Employment) 0.382(**)Managerial/Professional Employment 1990 (Percent Employment) -0.050Manufacturing Employment 2000 (Percent Total Employment) 0.346(*)Managerial/Professional Employment 2000 (Percent Employment) -0.095

Correlation Values for Entropy Index (Overall) for MSAs

NB: Significant Correlations Among Built-Environment Characteristics

ERA of Growth; Fordist (F) vs Post-Fordist (P-F) ► Foreign-Born Entering Before 1965 (F) relates to Less Intermixing;

Foreign-Born Entering 1980-2000 (P-F) relates to Greater Intermixing (+0.48, -0.41)

► Higher Employment in Manufacturing (F) 1980, 1990, 2000 relates to Less Intermixing (+0.35, +0.38, +0.35)► Higher Employment in Managerial/Professional (P-F) 1980 relates to

Greater Intermixing (-0.31); also 1990 and 2000 but not significant

Housing Characteristics: ►Median Year Housing Built Relates Inversely to Intermixing (-0.64)

(i.e., higher the year, higher the intermixing) ►More Housing Built 1970-1990 and 1990-2000 relates to Greater

Intermixing (-0.64, -0.55)► More Housing Built Before 1970 relates to Less Intermixing (+0.65)

Backward Step-Wise Regression14 Variables initially; Chosen from original 51 on basis of --(i) Strength of zero-order r;(ii) Intercorrelations among candidate variables (threshold of 0.60)(iii) Relevance in terms of Explanatory Frameworks and Research Criteria: F value of 0.05 for Entry; 0.06 for Removal

Correlation among Independent VariablesDiversity Score (Minorities-Among-Themselves) and

African American Portion of MSA Population (2000) = -0.61

Change in Population (1980-2000, Percent) andPopulation who Lived in Different House in 1995 (Percent) = +0.68Houses Built Between 1990-2000 as Percent of 2000 Stock = +0.61

Change in Foreign-Born Population, 1990-2000 (Percent) andForeign-Born Entered 1980-2000 as Percent Total F-B = +0.81Houses Built Between 1990-2000 as Percent of 2000 Stock = +0.80

Population who Lived in Different House in 1995 (Percent) andHouses Built Between 1990-2000 as Percent of 2000 Stock = +0.84Foreign-Born Entered 1980-2000 as Percent Total F-B = +0.60

Foreign-Born Entered 1980-2000 as Percent Total F-B andHouses Built Between 1990-2000 as Percent of 2000 Stock = +0.62

In Short –

Great Deal of Interrelationship between

Diversity Score (Minorities-Among-Themselves)

African American Portion of MSA Population (2000)

Change in Population (1980-2000, Percent)

Population who Lived in Different House in 1995 (Percent)

Houses Built Between 1990-2000 as Percent of 2000 Stock

Change in Foreign-Born Population, 1990-2000 (Percent)

Foreign-Born Entered 1980-2000 as Percent Total F-B

Hence, Population Change Overall and Dynamics related to the Foreign Born appear to be a significantDriver of Racial/Ethnic Intermixing

Zero-OrderCorrelations

 Multiple Regression Analysis

R-squared = 0.77 b-ValuesBeta

Values t-test Sign.

Constant 0.506 3.664 0.001

DEMOGRAPHIC CHARACTERISTICS

Diversity Score (Minorities-Among-Themselves) -0.473(**)

African American Portion of MSA Population (2000) 0.463(**) 0.307 0.289 2.976 0.005

Asian Portion of MSA Population (2000) -0.362(**) -0.442 -0.166 -1.673 0.103

Hispanic Portion of MSA Population (2000) -0.269(**)

Change, Population (1980-2000, Percent) -0.588(**)

Change, African American Population (1990-00, Percent) -0.572(**) -0.077 -0.178 -1.501 0.142

Change in Foreign-Born Population (1990-00, Percent) -0.42(**) -0.064 -0.605 -2.602 0.013

Population, Lived in Different House, 1995 (Percent) -0.684(**) -0.544 -0.369 -1.711 0.095

BUILT ENVIRONMENT CHARACTERISTICS

Foreign-Born Entered 1980-00 as Percent Total F-Born -0.412(**) 0.246 0.255 1.537 0.133

Managerial Employment 1990 (Percent Total Employment) -0.05

Manufacturing Employment 1990 (Percent Total Employment) 0.382(**) 0.486 0.283 2.593 0.014

Houses Built Between 1990-00 as Percent of 2000 Stock -0.547(**) 0.387 0.337 1.21 0.234

SOCIO-ECONOMIC CHARACTERISTICS

Some College, Associate or Bachelors Degree (2000, Percent) -0.626(**) -0.513 -0.238 -2.134 0.04

Per capita Income (African American) Logged -0.366(**)

Regression Analyses with Intermixing (Entropy Index)

Final Model Variables:Education and Income:► Some College or Greater Ed relates to More Intermixing ► African American Income relates to More Intermixing

(but didn’t enter; r=+0.45 w/ Education)Diversity:► Higher Asian Element relates to More Intermixing► Greater Change in the African American or Foreign-Born Elements

relates to More Intermixing► Higher African American Element relates to Less Intermixing► Higher Hispanic Element and Increasing Population relate

to More Intermixing (but didn’t enter; r=high w/ other diversityvariables)

Built Environment Characteristis► More Manufacturing in 1990 relates to Less Intermixing► More Mobility (Changing Houses) relates to More Intermixing► More Recently Built Housing relates to More Intermixing (but wrong

sign; r= high with diversity variables)► More Recent Entry of Foreign-Born relates to More Intermixing; i.e.,

MSA is a F-B magnet (but wrong sign; r=high with diversity variables)

Generalizations I: Empirical

Overall, Housing Market for R/E Minorities Opened Up (M-LP) everywhere. But place-to-place differences are found; e.g., Distinct difference between Rust/Sun Belt MSAs; Why?? What are some Common Denominators??MSA Growth:

Above avg growth Last Quarter 20th Century = > IntermixingPost-Fordist Economic ActivityMore open landscapes (Older MSAs often enclosed

(choked) with strong, long-standing municipalities;Institutionalized barriers??)

Expansion of Housing StockE.g. 17 MSAs with High Intermixing, within 29 Higest

Growth 1980-00, 30% or greaterMSAs in Flux = Greater Intermixing

High levels of Housing Turnover Minorities gaining greater share of MSA population; inflow

Generalizations II: Empirical (Continued)

Population CompositionMSAs w/ long-standing Europe component = < Intermixing

Older MSAs? More Institutionalized?? Fordist Swoon??Substantial In-Migration of Others Less Effect??

MSAs w/ long-stand non-Europe diversity = > Intermixing?Substantial in-migration = > Intermixing (e.g.,

Hispanics)Higher Education and Minority Incomes = > IntermixingHousing Tenure:

Owning vs Renting doesn’t impact Intermixing; R/E Presence seems more important??Diversity:

Alone doesn’t relate to IntermixingDiversity Among Minorities = > IntermixingSeems to be intermixing w/ Caucasians; not new enclaves

Population Change/Flux + Dynamics related to Foreign Born appear to be a significant Driver of Racial/Ethnic Intermixing

Generalizations III: Empirical (Continued)

Enclave Effect??AA Presence (Proportn; point in time) relates to < Intermixing

AA Change, also A + H, relate to > intermixingSuggests (i) Inertia Effect; (ii) Traditional Urban Enclaves

continue; but (iii) New Enclaves not being formed.What about Ethnoburbs; Is their omission a scale effect??

Frameworks:Consistent w/ Assimilation (salt + pepper effect)Consistent w/ Market-Led Pluralism (R/E intermixing, spread)Not Consistent with Stratification (R/E intermixing, spread)Not Consistent with Resurgent Ethnicity (but could be result

of scale and/or broad scope of analysis)

Suggests Class- rather than Culture-Process

And So It Goes --

At the Frontier!!

Thanks for Your Attention

Map of 49 Metropolitan AreasRegional Variations

Northeast and Midwest with low to medium diversity and low intermixing.South and West with high to medium diversity and high and medium intermixing.Chicago and New York – Low Intermixing yet High DiversityWhat is happening in large MSAs?Does Population size decrease intermixing ?

Why are West and South doing better in terms of racial residential intermixing???

Fig.4: Diversity and Entropy Indices

Major Patterns of Residential Intermixing

Fig.5 : Regional Variations for Spatial Dispersion

Source: Frey, W.H., Brookings Institution Living Cities Census Series, September 2005

Frey (2005) maps the Metropolitan areas loosingpopulation and gaining population (1990~2000)• Rustbelt with mostly low-medium diversity andlow intermixing.

• These areas have slow economic growth and slow or losing population.

• South and Southwest with High-medium diversity and Intermixing

• South & Southwest have fast growing population and Economy

Diversity & Intermixing - View of Regional Spatial Variation

Fig.6a,b : Regional Variations for Spatial DispersionSource: Frey, W.H., Brookings Institution Living Cities Census Series, September 2005

Fast growing Areas HIHD, MIMD, MIHD

Slow Growing Areas MILD, LIMD, LILD

Interesting Patterns

Inertia of RustbeltSlow Growing EconomySlow Growing populationLow Diversity

Fig. 8: Regional Variation Characteristics

Fast Economic GrowthPopulation Growth New Construction Medium to High Diversity and Intermixing

Micro-level Analyses – 3 MSAs in Ohio

1.1110.2890.2600.6871540157Columbus 1.1280.4440.3930.7152945831Cleveland

1.0080.3750.3450.5531979202Cincinnati

Index Ratio = Eb/Et

Theil’s Entropy Index (Eb) based on block-group

data

Theil’s Entropy Index (Et) based

on tract level data

Diversity Score (D)

MSA Size

3 MSAs in Ohio

• All the 3 MSAs are more clustered at levels of block-groups than at tracts, Index Ratio greater than 1.• Block-level clustering-highest for Cleveland, lowest for Cincinnati. • Columbus – MSA shows more mixing (0.289) in comparison to other two, yet block-level clustering in Columbus > Cincinnati.• It shows how different each MSA is in terms of their overall representation of mixing patterns at different scales.

Fig. 12: Micro-level Clustering

Variables and Entropy Indices

Rust Belt – Slow Economy

Fast Growing PopulationNew Economic DevelopmentIncreasing Minorities

What such pattern?

Growing Population, New Constructions, Economic Growth and Medium to High Diversity and Intermixing

Why do patterns differ ???

Inertia of RustbeltSlow Growing EconomySlow Growing opulationLow Diversity

Fast Economic Growth Population Growth New Construction Medium to High Diversity and Intermixing

Interesting Patterns

Fig. 8: Regional Variation Characteristics

Categories Counts 

Metropolises1: LDHI 2 Minneapolis and Salt Lake 2: MDHI

6Seattle, Raleigh-Durham, Portland, Orlando, Oklahoma,

Norfolk 3: HDHI 4 Las-Vegas, Austin, San-Diego and Sacramento 4: LDMI

6Rochester, Columbus, Grand-Rapids, Indianapolis,

Louisville, Providence 5: MDMI

West Palm Beach,, Tampa, San Antonio, Phoenix,

Nashville, Kansas-City, Jacksonville, Hartford, Greensboro, Denver, Boston, Atlanta, Charlotte-SC13

6: HDMI 6 Dallas, Houston, LA, Miami, San Francisco, W. DC. 7: LDLI 4 St. Louis, Pittsburgh, Cincinnati, Buffalo, Buffalo, 8: MDLI

6Memphis, Milwaukee, New Orleans, Philadelphia,

Detroit, Cleveland, 9: HDLI 2 Chicago, New-York

  Socio-Economic Characteristics r-ValuesPer Capita Income (Total Population) .348(*)

Per Capita Income (African American) 0.141

High School or Less Education (2000, Percent) -.431(**)

Some College or Associate Degree (2000, Percent) 0.23

Bachelors Degree (2000, Percent) .335(*)

Graduate or Professional Degree (2000, Percent) 0.255

Owner Occupied HHs in MSA (2000, Percent) -0.214

African American Owner Occupied HHs ( 2000, Percent) -.618(**)

Asian Owner Occupied HHs (2000, Percent) .381(**)

Hispanic Owner Occupied HHs (2000, Percent) -0.008

African American Rented HHs (2000, Percent) -.638(**)

Asian Rented HHs (2000, Percent) .465(**)

Hispanic Rented HHs (2000, Percent) 0.171

Non-Caucasian HHs in MSA (2000, Percent) -.338(*)

Change in Non-Caucasian HHs in MSA (90-00, Percent) 0.027

Change in African American Owner Occupied HHs (90-00, Percent) -.556(**)

Change in Asian Owner Occupied HHs (90-00, Percent) .382(**)

Change in Hispanic Owner Occupied HHs (90-00, Percent) -.485(**)

Change in African American Rented HHs (90-00, Percent) -.593(**)

Change in Asian Rented HHs (90-00, Percent) .499(**)

Change in All Other Races Rented HHs (90-00, Percent) -.478(**)

Correlation Values for Diversity Score (Among Minorities) for MSAs

Demographic Characteristics r-ValuesDiversity Score for MSAs (Overall) 0.116Diversity Score (Minorities-Among-Themselves) 1Diversity Score (Caucasians vs. Minorities) -0.138MSA Population (2000) 0.186MSA Population LN (2000) 0.201Change in Population (1980-2000, Percent) 0.176African Americans Portion of MSA Population (2000) -.614(**)Asians Portion of MSA Population (2000) .445(**)Hispanics Portion of MSA Population (2000) 0.079Change in Caucasian Population (1980-2000, Percent) -.395(**)Change in African American Population (1980-2000, Percent) -0.278Change in Hispanic Population (1980-2000, Percent) .353(*)Change in Asian Population (1980-2000, Percent) .525(**)Foreign-Born Portion of MSA Population (2000, Percent) .327(*)Change in Foreign-Born (2000-90, Percent) .356(*)Population (>5 yrs) Lived in a Different House in 1995 (Percent) 0.152

Correlation Values for Diversity Score (Among Minorities) for MSAs

Correlation Values for Diversity Score (Among Minorities) for MSAs

Built-Environment Characteristics r-ValuesForeign-Born Entered Before 1965 as Percent Total F-B -0.127Foreign-Born Entered 1980-2000 as Percent Total F-B 0.098Median Value of Owner Occupied HH (2000) .424(**)Median Year Housing Structure Built -0.026Houses Built Before 1970 as Percent of 2000 Stock -0.013Houses Built Before 1970-1990 as Percent of 2000 Stock 0.045Houses Built Before 1990-2000 as Percent of 2000 Stock -0.038Manufacturing Employment 1980 (Percent Total Employment) 0.036Managerial/Professional Employment 1980 (Percent Employment) .357(*)Manufacturing Employment 1990 (Percent Total Employment) -0.041Managerial/Professional Employment 1990 (Percent Employment) 0.095Manufacturing Employment 2000 (Percent Total Employment) 0.01Managerial/Professional Employment 2000 (Percent Employment) 0.271Change in Manufacturing Employment (1990-2000, Percent) -0.129Change in Managerial/Professional Employment (1990-2000, Percent) -0.087Change in Manufacturing Employment (1980-2000, Percent) 0.034Change in Managerial/Professional Employment (1980-2000, Percent) -0.083