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Mapping Poverty and Mobility Patterns in Baltimore City Nichole Stewart ACS Data Users Group Conference May 2014

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Page 1: American Community Survey Data Users Group_Nichole Stewart

Mapping Poverty and Mobility Patterns in Baltimore City

Nichole StewartACS Data Users Group Conference

May 2014

Page 2: American Community Survey Data Users Group_Nichole Stewart

Migration

• ACS collects data every month and asks about residence one year earlier.

• Many Census resources for State-to-State and County-to-County migration– Detailed Tables– Census Flows Mapper

Page 3: American Community Survey Data Users Group_Nichole Stewart

Census Flows Mapper

Page 4: American Community Survey Data Users Group_Nichole Stewart
Page 5: American Community Survey Data Users Group_Nichole Stewart

Migration by Census Tracts

• 2005-2009 5-year ACS (No Characteristics).• 2006-2010 5-year ACS (Crossed by Age, Sex,

Race, or Hispanic or Latino Origin).• 2007-2011 5-year ACS (Crossed by Educational

Attainment, Household Income, or Individual Income, Poverty).

• Variable: B07012

Page 6: American Community Survey Data Users Group_Nichole Stewart

Intersecting Migration and Poverty

Migration• Current Residents

– Living in Same House 1 Year Ago– Different House 1 Year Ago

• In Baltimore City• In Different County in Maryland• In Different State

Poverty• Below Poverty• 100-149% Poverty• 150% and Above Poverty

Page 7: American Community Survey Data Users Group_Nichole Stewart

What Questions Can We Answer?

• How many current residents lived in a different house in Baltimore City? Another county in Maryland? Another state? (Recent Movers)

• How many recent movers have incomes below poverty? (Recent Movers Below Poverty)

• How many current residents with incomes below poverty are recent movers? (Below Poverty Recent Movers)

Page 8: American Community Survey Data Users Group_Nichole Stewart

Data Downloaded (and Calculated)

Page 9: American Community Survey Data Users Group_Nichole Stewart

Recent Movers

Page 10: American Community Survey Data Users Group_Nichole Stewart

Percent Movers

0.2% - 14.2%

14.3% - 25.5%

25.6% - 47.4%

Tract 101

Page 11: American Community Survey Data Users Group_Nichole Stewart

Movers Below Poverty

Page 12: American Community Survey Data Users Group_Nichole Stewart

Percent Movers Below Poverty

0.0% - 21.5%

21.6% - 50.5%

50.6% - 100.0%

Tract 101

Page 13: American Community Survey Data Users Group_Nichole Stewart

Below Poverty Movers

Page 14: American Community Survey Data Users Group_Nichole Stewart

Percent Below Poverty Movers

0.0% - 19.6%

19.7% - 41.4%

41.5% - 88.8%

Tract 101

Page 15: American Community Survey Data Users Group_Nichole Stewart

What Can This Tell Us??Percent Movers• Highly transitional neighborhoods

Percent Movers Below Poverty• Areas where the majority of movers

have incomes below poverty -or-• Might reflect patterns of poverty

Percent Below Poverty Movers• Current residents with incomes below

poverty are recent movers, indicating neighborhood change

TractsPercent Total

Movers

Percent Movers Below

Poverty

Percent Below

Poverty Movers

101 27.7% 39.4% 88.8%1204 43.2% 24.8% 38.2%

2711.02 0.2% 100.0% 2.4%2803.02 4.9% 100.0% 15.9%

2713 7.7% 15.3% 71.7%

Page 16: American Community Survey Data Users Group_Nichole Stewart

Tableau

• Free Data Visualization Tool• Create data visualizations and dashboards that

can be embedded in a website or shared• No need for coding• Tutorials and user community

Page 17: American Community Survey Data Users Group_Nichole Stewart

Baltimore City CSAs

• Aggregate– 200 census tracts TO– 55 CSAs

• Why?– Easier to see patterns– Common

neighborhood names2606.05

2506

2505

2712

2505

2713

1304

2604.04

902

2802

2102

2715.01

2801.02

2803.01

2605.01

2401

2006

1511

2717

2714

801.01

401

2501.032502.06

2706

1510

1509

2705.01

2502.05

2719

2708.03

2303

2101

2404

2720.03

2503.01

2201

802

2804.03

908

1508

2008

903

1307

1207

2604.03

1201

16052804.01

1308.05

2601.01

2602.01

905

1607

1505

1506

2705.02

2702

2002

1513

2805

909

103

2704.01

2601.02

203

901

1306

2801.01

1308.06

2716

2604.02

2604.01

1504

2711.02

1512

2708.05

2607

1608.02

1102

2603.03

2007.01

2704.02

2504.01

2703.012709.02

2708.02

302

2005

2709.03

2503.03

2711.01

2701.02

2602.02

2707.03

1202.02

1507.012803.02

2501.01

2701.01

2710.02

907

402

604

1401

2720.05

301

2502.03

2502.07

1606

2603.02

2609

906

2502.04

1205

101

2707.02

104

2708.01

1702

102

904

805

2501.02

1001

2720.06

806

2708.04

808

2720.04

704

1502

702

1203

1503 8071403

2004

701

1901

2603.01

1501

1302

602

1801

601

2608

2710.01

2606.04

1002

1301

1803

1507.02

2602.03

2804.04

1206

2720.07

2715.03

1308.04

2504.02

2402

1308.03

2709.01

1604

1402

1601

1903

1602

1303

2718.01

2804.02

2301

804

2718.02

1101

803.02

2703.02

2610

1703703

2505

1902

1701

1204

801.02

2001202

1603

6031608.01

2707.01

2003

1802 201

2611

2302

1202.01

105

2403

803.01

2007.02

1003

Legend

Community Statistical Areas

Baltimore Census Tracts

Page 18: American Community Survey Data Users Group_Nichole Stewart

Visualization Components

• Filled Maps with Custom Boundaries– Custom boundaries based on lat/long using ET

GeoWizards– TabGeoHack and GDAL– shape2tab

• Worksheets and Dashboards• Actions

Page 19: American Community Survey Data Users Group_Nichole Stewart
Page 21: American Community Survey Data Users Group_Nichole Stewart

NICHOLE M. STEWART

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Data Analyst and Researcher Public Policy Doctoral Candidate

[email protected]

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