Texas Median value of owner-occupied housing units, 2014-2018 by County

Embed this in your blog

Preview
About this application: This application provides summary profiles showing frequently requested data items from various US Census Bureau programs. Profiles are available for the nation, states, and counties.
Recommended:
Data Item
State
Loading map...
Median value of owner-occupied housing units, 2014-2018 - (US Dollars)
County Value
Anderson 92,900
Andrews 135,600
Angelina 100,600
Aransas 158,400
Archer 133,500
Armstrong 137,700
Atascosa 100,200
Austin 188,900
Bailey 68,600
Bandera 167,600
Bastrop 160,100
Baylor 70,500
Bee 88,200
Bell 141,200
Bexar 152,400
Blanco 235,700
Borden 113,100
Bosque 110,600
Bowie 113,300
Brazoria 173,900
Brazos 186,000
Brewster 134,300
Briscoe 65,400
Brooks 64,000
Brown 97,500
Burleson 109,800
Burnet 182,600
Caldwell 127,800
Calhoun 115,000
Callahan 89,000
Cameron 83,300
Camp 87,500
Carson 111,100
Cass 86,200
Castro 81,900
Chambers 185,700
Cherokee 100,700
Childress 80,000
Clay 90,200
Cochran 34,100
Coke 79,100
Coleman 70,000
Collin 288,900
Collingsworth 51,800
Colorado 116,300
Comal 262,400
Comanche 101,400
Concho 93,500
Cooke 145,700
Coryell 110,100
Cottle 41,500
Crane 91,900
Crockett 79,900
Crosby 57,800
Culberson 56,900
Dallam 82,800
Dallas 161,500
Dawson 67,300
Deaf Smith 91,800
Delta 78,400
Denton 255,300
DeWitt 106,200
Dickens 54,100
Dimmit 73,800
Donley 69,500
Duval 49,800
Eastland 68,500
Ector 133,900
Edwards 75,300
El Paso 119,100
Ellis 172,900
Erath 146,000
Falls 66,200
Fannin 113,200
Fayette 165,000
Fisher 60,100
Floyd 63,900
Foard 45,200
Fort Bend 251,100
Franklin 137,300
Freestone 98,800
Frio 75,300
Gaines 122,800
Galveston 185,100
Garza 76,400
Gillespie 276,100
Glasscock 221,700
Goliad 128,900
Gonzales 112,200
Gray 77,600
Grayson 125,000
Gregg 132,000
Grimes 124,500
Guadalupe 183,900
Hale 80,300
Hall 48,200
Hamilton 127,000
Hansford 97,400
Hardeman 38,100
Hardin 120,000
Harris 165,300
Harrison 124,600
Hartley 160,000
Haskell 51,400
Hays 222,300
Hemphill 135,000
Henderson 102,500
Hidalgo 84,000
Hill 98,700
Hockley 88,800
Hood 180,900
Hopkins 100,100
Houston 84,500
Howard 93,100
Hudspeth 46,000
Hunt 114,500
Hutchinson 77,300
Irion 137,500
Jack 83,000
Jackson 103,300
Jasper 104,600
Jeff Davis 112,900
Jefferson 107,800
Jim Hogg 66,800
Jim Wells 76,300
Johnson 144,700
Jones 75,400
Karnes 97,800
Kaufman 161,600
Kendall 326,800
Kenedy 31,400
Kent 39,700
Kerr 170,600
Kimble 165,000
King 38,300
Kinney 72,800
Kleberg 88,200
Knox 43,800
La Salle 81,600
Lamar 94,800
Lamb 64,700
Lampasas 142,900
Lavaca 155,600
Lee 125,700
Leon 110,100
Liberty 101,200
Limestone 90,000
Lipscomb 86,300
Live Oak 94,700
Llano 186,100
Lubbock 130,800
Lynn 79,300
Madison 112,800
Marion 93,000
Martin 133,100
Mason 163,600
Matagorda 107,500
Maverick 94,800
McCulloch 85,600
McLennan 133,400
McMullen 106,600
Medina 139,800
Menard 57,000
Midland 197,400
Milam 97,100
Mills 123,400
Mitchell 70,000
Montague 112,700
Montgomery 223,900
Moore 115,100
Morris 86,300
Motley 55,800
Nacogdoches 119,700
Navarro 95,000
Newton 74,600
Nolan 72,000
Nueces 130,700
Ochiltree 99,300
Oldham 95,700
Orange 107,600
Palo Pinto 95,900
Panola 98,300
Parker 198,400
Parmer 92,300
Pecos 75,100
Polk 94,300
Potter 90,100
Presidio 58,400
Rains 121,100
Randall 162,700
Reagan 94,100
Real 103,000
Red River 67,200
Reeves 62,200
Refugio 82,500
Roberts 132,100
Robertson 104,000
Rockwall 244,400
Runnels 77,600
Rusk 118,500
Sabine 101,200
San Augustine 86,700
San Jacinto 109,000
San Patricio 117,700
San Saba 97,900
Schleicher 69,800
Scurry 88,100
Shackelford 80,300
Shelby 72,600
Sherman 98,400
Smith 153,500
Somervell 191,600
Starr 68,300
Stephens 71,400
Sterling 64,700
Stonewall 58,200
Sutton 95,700
Swisher 73,800
Tarrant 170,300
Taylor 119,100
Terrell 72,100
Terry 76,100
Throckmorton 68,000
Titus 97,600
Tom Green 130,800
Travis 298,800
Trinity 79,700
Tyler 85,400
Upshur 123,800
Upton 65,700
Uvalde 80,700
Val Verde 95,900
Van Zandt 121,900
Victoria 136,900
Walker 149,100
Waller 174,900
Ward 86,100
Washington 170,900
Webb 119,900
Wharton 122,900
Wheeler 85,800
Wichita 96,000
Wilbarger 73,200
Willacy 56,800
Williamson 245,100
Wilson 181,200
Winkler 64,400
Wise 154,000
Wood 130,200
Yoakum 100,000
Young 89,000
Zapata 69,500
Zavala 48,500

Value for Texas (US Dollars): $161,700

Sources: U.S. Census Bureau, American Community Survey (ACS) and Puerto Rico Community Survey (PRCS), 5-Year Estimates. The PRCS is part of the Census Bureau's ACS, customized for Puerto Rico. Both Surveys are updated every year.

Definition

Value is the respondent's estimate of how much the property (house and lot) would sell for if it were for sale.

This tabulation includes only specified owner-occupied housing units--one-family houses on less than 10 acres without a business or medical office on the property. These data exclude mobile homes, houses with a business or medical office, houses on 10 or more acres, and housing units in multi-unit structures. Certain tabulations elsewhere include the value of all owner-occupied housing units and vacant-for-sale housing units. Also available are data on mortgage status and selected monthly owner costs.

The median divides the value distribution into two equal parts: one-half of the cases falling below the median value of the property (house and lot) and one-half above the median. Median value calculations are rounded to the nearest hundred dollars.

Owner-Occupied - A housing unit is owner-occupied if the owner or co-owner lives in the unit, even if it is mortgaged or not fully paid for. The owner or co-owner must live in the unit and usually is Person 1 on the questionnaire. The unit is "Owned by you or someone in this household with a mortgage or loan" if it is being purchased with a mortgage or some other debt arrangement such as a deed of trust, trust deed, contract to purchase, land contract, or purchase agreement. The unit also is considered owned with a mortgage if it is built on leased land and there is a mortgage on the unit. Mobile homes occupied by owners with installment loan balances also are included in this category. For the complete definition, go to ACS subject definitions "Tenure."

Source and Accuracy

This Fact is based on data collected in the American Community Survey (ACS) and the Puerto Rico Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed each year over a 12 month period. This Fact (estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection.

Statistics from all surveys are subject to sampling and nonsampling error. Sampling error is the uncertainty between an estimate based on a sample and the corresponding value that would be obtained if the estimate were based on the entire population (as from a census). Measures of sampling error are provided in the form of margins of error for all estimates included with ACS and PRCS published products. The Census Bureau recommends that data users incorporate this information into their analyses, as sampling error in survey estimates could impact the conclusions drawn from the results. The data for each geographic area are presented together with margins of error at Using margins of error. A more detailed explanation of margins of error and a demonstration of how to use them is provided below.

For more information on sampling and estimation methodology, confidentiality, and sampling and nonsampling errors, please see the Multiyear Accuracy (US) and the Multiyear Accuracy (Puerto Rico) documents at "Documentation - Accuracy of the data."

Margin of Error

As mentioned above, ACS estimates are based on a sample and are subject to sampling error. The margin of error measures the degree of uncertainty caused by sampling error. The margin of error is used with an ACS estimate to construct a confidence interval about the estimate. The interval is formed by adding the margin of error to the estimate (the upper bound) and subtracting the margin of error from the estimate (the lower bound). It is expected with 90 percent confidence that the interval will contain the full population value of the estimate. The following example is for demonstrating purposes only. Suppose the ACS reported that the percentage of people in a state who were 25 years and older with a bachelor's degree was 21.3 percent and that the margin of error associated with this estimate was 0.7 percent. By adding and subtracting the margin of error from the estimate, we calculate the 90-percent confidence interval for this estimate:

21.3% - 0.7% = 20.6% => Lower-bound estimate
21.3% + 0.7% = 22.0% => Upper-bound estimate

Therefore, we can be 90 percent confident that the percent of the population 25 years and older having a bachelor's degree in a state falls somewhere between 20.6 percent and 22.0 percent.

For this Fact, its estimates and margins of error along with percents and percent margins of errors can be found on American Community Survey, Data Profiles-Housing Characteristics

More Information