Texas Poverty Rate by County

Data Item State
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Persons below poverty level, percent, 2009-2013 - (Percent)
County Value
Anderson 20.3
Andrews 12.5
Angelina 19.3
Aransas 19.6
Archer 11.3
Armstrong 11.1
Atascosa 16.4
Austin 10.1
Bailey 13.0
Bandera 15.3
Bastrop 16.5
Baylor 15.4
Bee 22.2
Bell 15.3
Bexar 17.6
Blanco 9.3
Borden 0.9
Bosque 14.7
Bowie 19.7
Brazoria 11.2
Brazos 29.8
Brewster 12.4
Briscoe 18.6
Brooks 38.3
Brown 18.4
Burleson 15.0
Burnet 16.3
Caldwell 18.7
Calhoun 17.6
Callahan 15.2
Cameron 34.8
Camp 21.8
Carson 7.2
Cass 20.9
Castro 24.1
Chambers 9.7
Cherokee 24.5
Childress 15.9
Clay 10.3
Cochran 15.1
Coke 11.0
Coleman 27.6
Collin 7.8
Collingsworth 20.4
Colorado 16.6
Comal 10.2
Comanche 26.4
Concho 16.5
Cooke 14.8
Coryell 13.4
Cottle 15.4
Crane 13.8
Crockett 16.7
Crosby 26.5
Culberson 25.2
Dallam 18.1
Dallas 19.1
Dawson 21.9
Deaf Smith 18.9
Delta 17.9
Denton 8.7
DeWitt 13.5
Dickens 18.8
Dimmit 26.5
Donley 16.7
Duval 19.7
Eastland 19.0
Ector 15.9
Edwards 18.4
El Paso 23.3
Ellis 11.9
Erath 22.3
Falls 20.9
Fannin 17.2
Fayette 11.6
Fisher 17.1
Floyd 20.3
Foard 15.4
Fort Bend 8.4
Franklin 14.4
Freestone 15.6
Frio 24.0
Gaines 16.8
Galveston 13.3
Garza 15.5
Gillespie 12.0
Glasscock 4.2
Goliad 14.7
Gonzales 21.9
Gray 14.6
Grayson 15.7
Gregg 17.6
Grimes 19.1
Guadalupe 9.7
Hale 22.3
Hall 23.8
Hamilton 12.6
Hansford 17.0
Hardeman 26.6
Hardin 10.9
Harris 18.5
Harrison 16.0
Hartley 8.6
Haskell 18.9
Hays 17.0
Hemphill 11.7
Henderson 18.9
Hidalgo 34.8
Hill 17.0
Hockley 15.7
Hood 12.1
Hopkins 19.3
Houston 19.7
Howard 15.3
Hudspeth 44.1
Hunt 19.9
Hutchinson 15.8
Irion 8.7
Jack 16.7
Jackson 12.7
Jasper 17.8
Jeff Davis 7.4
Jefferson 21.0
Jim Hogg 14.0
Jim Wells 21.7
Johnson 12.0
Jones 18.5
Karnes 23.3
Kaufman 13.3
Kendall 9.3
Kenedy 32.8
Kent 8.6
Kerr 14.9
Kimble 19.5
King 5.9
Kinney 25.7
Kleberg 24.5
Knox 20.8
La Salle 21.7
Lamar 19.1
Lamb 22.1
Lampasas 16.9
Lavaca 8.3
Lee 12.4
Leon 17.7
Liberty 18.4
Limestone 21.5
Lipscomb 10.9
Live Oak 17.1
Llano 14.1
Loving 12.0
Lubbock 20.4
Lynn 20.2
Madison 25.2
Marion 23.2
Martin 15.8
Mason 13.6
Matagorda 21.1
Maverick 30.5
McCulloch 16.6
McLennan 22.0
McMullen 19.2
Medina 17.7
Menard 23.5
Midland 10.4
Milam 19.2
Mills 13.1
Mitchell 11.7
Montague 15.6
Montgomery 12.4
Moore 15.4
Morris 20.6
Motley 25.5
Nacogdoches 25.7
Navarro 21.1
Newton 16.1
Nolan 18.5
Nueces 18.4
Ochiltree 17.3
Oldham 14.2
Orange 14.4
Palo Pinto 18.5
Panola 12.7
Parker 10.9
Parmer 21.3
Pecos 16.7
Polk 20.2
Potter 23.1
Presidio 24.8
Rains 13.6
Randall 10.3
Reagan 9.5
Real 20.2
Red River 16.1
Reeves 21.9
Refugio 16.2
Roberts 3.0
Robertson 20.7
Rockwall 5.9
Runnels 21.9
Rusk 17.8
Sabine 25.8
San Augustine 26.4
San Jacinto 20.1
San Patricio 17.0
San Saba 15.2
Schleicher 22.8
Scurry 15.7
Shackelford 16.1
Shelby 22.1
Sherman 13.7
Smith 16.7
Somervell 9.3
Starr 39.2
Stephens 18.8
Sterling 15.1
Stonewall 16.6
Sutton 7.3
Swisher 23.1
Tarrant 15.2
Taylor 17.4
Terrell 10.0
Terry 14.0
Throckmorton 13.7
Titus 22.0
Tom Green 16.2
Travis 17.4
Trinity 16.1
Tyler 17.4
Upshur 15.8
Upton 17.1
Uvalde 26.5
Val Verde 22.1
Van Zandt 16.4
Victoria 16.9
Walker 26.0
Waller 20.4
Ward 20.4
Washington 14.9
Webb 31.4
Wharton 18.8
Wheeler 14.3
Wichita 15.6
Wilbarger 20.7
Willacy 40.0
Williamson 7.0
Wilson 11.5
Winkler 12.8
Wise 10.8
Wood 14.6
Yoakum 11.7
Young 16.0
Zapata 34.7
Zavala 35.0

Value for Texas (Percent): 17.6%

Data item: Persons below poverty level, percent, 2009-2013

Source: U. S. Census Bureau, American Community Survey, 5-Year Estimates. Updated every year. http://factfinder2.census.gov

Definitions:

Poverty statistics in ACS products adhere to the standards specified by the Office of Management and Budget in Statistical Policy Directive 14. The Census Bureau uses a set of dollar value thresholds that vary by family size and composition to determine who is in poverty. Further, poverty thresholds for people living alone or with nonrelatives (unrelated individuals) vary by age (under 65 years or 65 years and older). The poverty thresholds for two-person families also vary by the age of the householder. If a family's total income is less than the dollar value of the appropriate threshold, then that family and every individual in it are considered to be in poverty. Similarly, if an unrelated individual's total income is less than the appropriate threshold, then that individual is considered to be in poverty.

How the Census Bureau Determines Poverty Status

Poverty status is determined by comparing annual income to a set of dollar values called poverty thresholds that vary by family size, number of children and age of householder. If a family's before tax money income is less than the dollar value of their threshold, then that family and every individual in it are considered to be in poverty. For people not living in families, poverty status is determined by comparing the individual's income to his or her poverty threshold.

The poverty thresholds are updated annually to allow for changes in the cost of living using the Consumer Price Index (CPI-U). They do not vary geographically. The ACS is a continuous survey and people respond throughout the year. Since income is reported for the previous 12 months, the appropriate poverty threshold for each family is determined by multiplying the base-year poverty threshold (1982) by the average of monthly CPI values for the 12 months preceding the survey month.

Scope and Methodology:

These data are collected in the American Community Survey (ACS). The data for each geographic area are presented together with margins of error at factfinder2.census.gov. The data are period estimates, that is, they represent the characteristics of the population over a specific 60-month data collection period.

Since answers to income questions are frequently based on memory and not on records, many people tended to forget minor or sporadic sources of income and, therefore, underreport their income. Underreporting tends to be more pronounced for income sources that are not derived from earnings, such as public assistance, interest, dividends, and net rental income.

Margins of Error (MOE). ACS estimates are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a MOE. The MOE used with ACS estimates can be interpreted as providing a 90 percent probability that the interval defined by the estimate plus the MOE and the estimate minus the MOE (the upper and lower confidence bounds) contains the full population value of the estimate.

For example, suppose the 5-year ACS reported the percentage of people 25 years and older in Birmingham, Alabama who had a bachelor's degree was 21.3 percent and that the MOE associated with this estimate is plus or minus (+/-) 0.9 percent. By adding and subtracting the MOE from the estimate, we can calculate the 90-percent confidence interval for this estimate at 21.3%, +/-0.9%:


21.3% - 0.9% = 20.4% = Lower-bound estimate
21.3% + 0.9% = 22.2% = Upper-bound estimate

Therefore, we can be 90 percent confident that the percent of the population in Birmingham, Alabama of age 25 years and older having a bachelor's degree in 2007-2011 falls somewhere between 20.4 percent and 22.2 percent.

For this Fact and other 5-year Economic Characteristic Facts (listed below), their estimates and margins of error or percents and percent margins of errors can be found on Data Profile - Economic Characteristics. This profile is displayed by geography. Click on the link for "Browse for Data sets (geography picked)" near the top of the Quick facts profile page, click on the link for People QuickLinks/American Community Survey - "Economic Characteristics" for the data profile.


Mean travel time to work (minutes), workers age 16 and over;
Per capita money income in the past 12 months,
Median household income,
Persons below poverty level, percent

More Information: