ML21158A204
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| Site: | HI-STORE |
| Issue date: | 03/15/2021 |
| From: | Headwaters Economics |
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Text
A Demographic Profile Combined Area Selected Geographies:
Andrews County, TX; Gaines County, TX; Lea County, NM United States Comparison Geographies:
U.S.
Produced by Headwaters Economics' Economic Profile System (EPS) https://headwaterseconomics.org/eps March 15, 2021
Demographics Combined Area About the Economic Profile System (EPS)
EPS is a free web tool created by Headwaters Economics to build customized socioeconomic reports of U.S. counties, states, and regions. Reports can be easily created to compare or aggregate different areas. EPS uses published statistics from federal data sources, including the U.S. Census Bureau, Bureau of Economic Analysis, and Bureau of Labor Statistics.
The Bureau of Land Management and Forest Service have made significant financial and intellectual contributions to the operation and content of EPS.
See https://headwaterseconomics.org/eps for more information about the capabilities of EPS. For technical questions, contact Patty Hernandez Gude at eps@headwaterseconomics.org or telephone 406-599-7425.
headwaterseconomics.org Headwaters Economics is an independent, nonprofit research group. Our mission is to improve community development and land management decisions.
www.blm.gov The Bureau of Land Management, an agency within the U.S. Department of Interior, administers 249.8 million acres of America's public lands, located primarily in western states. It is the mission of the Bureau of Land Management to sustain the health, diversity, and productivity of public lands for the use and enjoyment of present and future generations.
www.fs.fed.us The Forest Service, an agency of the U.S. Department of Agriculture, administers national forests and grasslands encompassing 193 million acres. The Forest Services mission is to sustain the health, diversity, and productivity of the nations forests and grasslands to meet the needs of present and future generations.
Find more reports like this at headwaterseconomics.org/eps About EPS
Demographics Combined Area Table of Contents Demographics Population 4 Age and Gender 6 Race 10 Ethnicity 12 Tribal 14 Employment Occupations and Industries 18 Labor 20 Commuting 22 Income Income 24 Poverty Prevalence 26 Poverty by Race and Ethnicity 28 Household Earnings 30 Social Characteristics Education 32 Language 34 Housing Housing Characteristics 36 Housing Affordability 38 Benchmarks Comparisons 40 Data Sources & Methods 42 Endnotes 43 Note to Users:
This is one of 14 reports that can be created and downloaded from EPS. Topics include land use, demographics, specific industry sectors, the role of non-labor income, the wildland-urban interface, the role of amenities in economic development, and payments to county governments from federal lands. The EPS reports are downloadable as Excel or PDF documents. See https://headwaterseconomics.org/eps.
Find more reports like this at headwaterseconomics.org/eps TOC
Demographics Combined Area Population Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Population (2019*) 18,036 20,706 70,277 109,019 324,697,795 Population (2010*) 14,048 16,658 62,503 93,209 303,965,272 Population Change (2010*-2019*) 3,988 4,048 7,774 15,810 20,732,523 Population Pct. Change (2010*-2019*) 28.4% 24.3% 12.4% 17.0% 6.8%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Percent Change in Population, 2010*-2019*
30.0% 28.4%
- From 2010* to 2019*, Andrews 24.3%
County, TX had the smallest estimated 25.0%
absolute change in population (3,988).
20.0% 17.0%
15.0% 12.4%
10.0% 6.8%
- From 2010* to 2019*, Andrews County, TX had the largest estimated 5.0%
relative change in population (28.4%),
and United States had the smallest 0.0%
(6.8%). Andrews Gaines Lea County, Combined United States County, TX County, TX NM Area
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019; 2010 represents 2006-2010.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 4
Demographics Combined Area Population What do we measure on this page?
This page describes the total population and change in total population.1, 2 Data in this report comes from the U.S. Census Bureau's American Community Survey (ACS).3 The ACS is conducted nationwide every year by the U.S. Census Bureau to collect demographic, social, economic, and housing information. For more information about ACS data and accuracy, see the Methods section at the end of this report.
Why is it important?
Population growth is generally an indication of a healthy economy. No growth or long-term decline generally occur when an area is struggling.
Growth can benefit the general population of a place, especially by providing economic opportunities, but it can also stress communities and lead to income stratification. When considering the benefits of growth, it is important to distinguish between standard of living (such as earnings per job and per capita income) and quality of life (such as leisure time, crime rate, and sense of well-being).
The size of a population and economy (metropolitan, micropolitan, or rural) can have an important bearing on economic activities as well as opportunities and challenges for area businesses.
CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 5
Demographics Combined Area Age and Gender Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Total Population, 2019* 18,036 20,706 70,277 109,019 324,697,795 Under 5 years 1,551 2,272 5,522 9,345 19,767,670 5 to 9 years 1,599 1,961 6,081 9,641 20,157,477 10 to 14 years 1,613 2,089 6,234 9,936 20,927,278 15 to 19 years 1,380 1,801 5,429 8,610 21,208,186 20 to 24 years 1,193 1,264 4,831 7,288 22,015,108 25 to 29 years 1,314 1,465 5,002 7,781 23,069,320 30 to 34 years 1,400 1,427 5,297 8,124 21,961,095 35 to 39 years 1,400 1,302 5,107 7,809 21,071,305 40 to 44 years 876 1,199 3,769 5,844 19,907,526 45 to 49 years 1,118 1,009 3,966 6,093 20,727,770 50 to 54 years 988 1,122 3,853 5,963 21,344,850 55 to 59 years 723 1,068 3,983 5,774 21,654,255 60 to 64 years 1,071 907 3,433 5,411 20,102,159 65 to 69 years 656 527 2,626 3,809 16,840,799 70 to 74 years 405 532 1,903 2,840 12,701,467 75 to 79 years 220 336 1,247 1,803 8,913,936 80 to 84 years 309 237 1,098 1,644 6,058,577 85 years and over 220 188 896 1,304 6,269,017 Total Female 8,862 10,150 34,008 53,020 164,810,876 Total Male 9,174 10,556 36,269 55,999 159,886,919 Change in Median Age, 2010*-2019*
Median Age^ (2019*) 30.8 27.8 31.8 na 38.1 Median Age^ (2010*) 34.6 29.2 31.6 na 36.9 Median Age % Change -11.0% -4.8% ¨0.6% na 3.3%
^ Median age is not available for metro/non-metro or regional aggregations.
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Median Age, 2010* & 2019*
- From 2010* to 2019* , the median age 45 40 36.9 38.1 estimate increased the most in United 34.6 35 30.8 31.6 31.8 States (36.9 to 38.1, a 3.3% increase) 29.2 27.8 and decreased the most in Andrews 30 25 County, TX (34.6 to 30.8, a 11.0%
20 decrease).
15 10 5 na na 0
Andrews Gaines County, Lea County, Combined Area United States County, TX TX NM Median Age^ (2010*) Median Age^ (2019*)
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019; 2010 represents 2006-2010.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 6
Demographics Combined Area Age and Gender What do we measure on this page?
This page describes population distribution by age and gender, and the change in median age.
Median Age: The age that divides the population into two numerically equal groups (half the people are younger than this age and half are older).
Why is it important?
Different locations have different age distributions. For example, in counties with a large number of retirees, the age distribution may be skewed toward categories 65 years and older.4 In counties with universities, the age distribution will be skewed toward 18- to 29-year-olds. In many counties, the largest segment of the population is the Baby Boomer generation (people born between 1946 and 1964).
The change in median age is one indicator of whether the population has gotten older or younger.5 CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 7
Demographics Combined Area Age and Gender 2010* 2019*
Total Population, 2010*-2019* 93,209 109,019 Under 18 27,769 34,285 18-34 22,534 26,440 35-44 11,655 13,653 45-64 21,131 23,241 65 and over 10,120 11,400 Percent of Total Under 18 29.8% 31.4%
18-34 24.2% 24.3%
35-44 12.5% 12.5%
45-64 22.7% 21.3%
65 and over 10.9% 10.5%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
2019* Breakout Change 2010*-2019*
- In 2019*, the age category with the highest estimate for number of women 6,278 was Under 18 (16,612), and the age 65 and over 1,280 category with the highest estimate for 5,122 number of men was Under 18 (17,673).
11,216 45-64 2,110 12,025
- From 2010* to 2019*, the age category with the largest estimated increase was Under 18 (6,516), and the age category 6,624 with the smallest estimated increase was 35-44 1,998 65 and over (1,280). 7,029 12,290 18-34 3,906 14,150 16,612 Under 18 6,516 17,673 0 10,000 20,000 0 5,000 10,000 Male Female
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019; 2010 represents 2006-2010.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 8
Demographics Combined Area Age and Gender What do we measure on this page?
This page describes the change in age and gender distribution over time, and the change in age distribution, with five age-group categories.6 Why is it important?
Understanding the age distribution can help highlight whether policy changes and management actions might affect some age groups more than others. It also may highlight the need to understand the different needs, values, and attitudes of different age groups. If an area has a large retired population or soon-to-be-retired population, for example, the needs and interests of the public may differ than an area with a large number of minors or young adults.
For many locations, a significant development is the aging of the population, and in particular the retirement of the Baby Boomer generation (those born between 1946 and 1964).7, 8, 9 As this generation continues to enter retirement age, their mobility, spending patterns, and consumer demands (for health care and housing, for example) can affect how communities develop economically.10, 11, 12 CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 9
Demographics Combined Area Race Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Total Population, 2019* 18,036 20,706 70,277 109,019 324,697,795 White alone 16,108 19,578 62,117 97,803 235,377,662 Black or African American alone ¨122 522 2,692 3,336 41,234,642 American Indian alone ¨0 ¨57 716 773 2,750,143 Asian alone ¨65 ¨102 402 569 17,924,209 Native Hawaii & Other Pacific Is. alone ¨31 ¨9 ¨20 ¨60 599,868 Some other race alone 1,094 378 3,111 4,583 16,047,369 Two or more races 616 ¨60 1,219 1,895 10,763,902 Percent of Total White alone 89.3% 94.6% 88.4% 89.7% 72.5%
Black or African American alone ¨0.7% 2.5% 3.8% 3.1% 12.7%
American Indian alone ¨0.0% ¨0.3% 1.0% 0.7% 0.8%
Asian alone ¨0.4% ¨0.5% 0.6% 0.5% 5.5%
Native Hawaii & Other Pacific Is. alone ¨0.2% ¨0.0% 0.0% ¨0.1% 0.2%
Some other race alone 6.1% 1.8% 4.4% 4.2% 4.9%
Two or more races 3.4% ¨0.3% 1.7% 1.7% 3.3%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Population by Race, Percent of Total, Combined Area, 2019*
100%
- In the 2015-2019 period, the racial 90%
category with the highest estimated percent of the population in the 80%
Combined Area was white alone 70%
(89.7%), and the racial category the 60%
lowest estimated percent of the population was native hawaii & other 50%
pacific is. alone (0.1%). 40%
30%
20%
10%
0%
Some other race** Two or more races White**
American Indian**
Black or African Asian**
Native Hawaiian & Other American**
Pacific Is.**
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
- Percentages are by an individual race alone unless otherwise noted Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
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Demographics Combined Area Race What do we measure on this page?
This page describes the number of people who self-identify as belonging to a particular race.
Race: Race is a self-identification data item in which respondents choose the race or races with which they most closely identify. In 1997 the U.S. Office of Management and Budget (OMB) revised the standards for how the federal government collects and presents data on race and ethnicity.13 Race Alone Categories: The minimum five race categories required by the OMB, plus the some-other-race-alone categories included by the U.S. Census Bureau with the approval of the OMB. The categories are: White alone, Black or African-American alone, American Indian or Alaska Native alone, Asian alone, Native Hawaiian or Other Pacific Islander alone, and Some Other Race alone.
Some Other Race: All other responses not included in the "White," "Black or African American," "American Indian and Alaska Native," "Asian," and "Native Hawaiian or Other Pacific Islander" race categories described above. Respondents providing write-in entries such as multiracial, mixed, interracial, or a Hispanic/Latino group (for example, Mexican, Puerto Rican, or Cuban) in the Some Other Race write-in space are included in this category.
Two or More Races: People may have chosen to provide two or more races either by checking two or more race response check boxes, by providing multiple write-in responses, or by a combination of check boxes and write-in responses.
Race categories include both racial and national-origin groups. The concept of race is separate from the concept of Hispanic origin, which is discussed elsewhere in this report.14 Percentages for the various race categories add to 100 percent and should not be combined with the percent Hispanic.
Why is it important?
The United States hit a tipping point in 2015 in its racial and ethnic make-up: more toddlers under the age of five are now minorities than non-Hispanic whites.15 The racial composition of a place can indicate different needs, values, and attitudes sometimes held by different racial groups.
Federal agencies use information on race and ethnicity to implement a number of programs and to promote and enforce equal opportunities, such as in employment or housing, under the Civil Rights Act.
According to the U.S. Census Bureau, many federal programs are put into effect based on Census race data (i.e., promoting equal employment opportunities; assessing racial disparities in health and environmental risks).16 It is important to consider whether proposed policies and management actions could have disproportionately high and adverse effects on minority populations. This consideration, broadly referred to as "environmental justice," is a requirement of Executive Order 12898.17 The Social Science Research Council hosts a useful resource on the health and welfare of racial and ethnic groups.18 CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 11
Demographics Combined Area Ethnicity Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Total Population, 2019* 18,036 20,706 70,277 109,019 324,697,795 Hispanic or Latino (of any race) 10,151 8,591 41,230 59,972 58,479,370 Not Hispanic or Latino 7,885 12,115 29,047 49,047 266,218,425 White alone 7,246 11,493 24,885 43,624 197,100,373 Black or African American alone ¨122 450 2,386 2,958 39,977,554 American Indian alone ¨0 ¨57 570 627 2,160,378 Asian alone ¨65 ¨102 402 569 17,708,954 Native Hawaii & Oth.Pacific Is. alone ¨31 ¨9 ¨11 ¨51 540,511 Some other race ¨0 ¨0 ¨144 ¨144 789,047 Two or more races 421 ¨4 649 1,074 7,941,608 Percent of Total Hispanic or Latino (of any race) 56.3% 41.5% 58.7% 55.0% 18.0%
Not Hispanic or Latino 43.7% 58.5% 41.3% 45.0% 82.0%
White alone 40.2% 55.5% 35.4% 40.0% 60.7%
Black or African American alone ¨0.7% 2.2% 3.4% 2.7% 12.3%
American Indian alone ¨0.0% ¨0.3% 0.8% 0.6% 0.7%
Asian alone ¨0.4% ¨0.5% 0.6% 0.5% 5.5%
Native Hawaii & Oth.Pacific Is. alone ¨0.2% ¨0.0% 0.0% ¨0.0% 0.2%
Some other race ¨0.0% ¨0.0% ¨0.2% ¨0.1% 0.2%
Two or more races 2.3% 0.0% 0.9% 1.0% 2.4%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Hispanic Population, Percent of Total, Combined Area, 2019*
70%
58.7%
- In the 2015-2019 period, Lea County, 60% 56.3% 55.0%
NM had the highest estimated percent 50%
of the population that self-identify as 41.5%
Hispanic or Latino of any race 40%
(58.7%), and United States had the lowest (18.0%). 30%
18.0%
20%
10%
0%
Andrews Gaines Lea County, Combined United States County, TX County, TX NM Area
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 12
Demographics Combined Area Ethnicity What do we measure on this page?
This page describes the number of people who self-identify as Hispanic. The information also is presented according to race. The term Hispanic refers to a cultural identification; Hispanics can be of any race.
Ethnicity: There are two minimum categories for ethnicity: Hispanic or Latino, and Not Hispanic or Latino. The federal government considers race and Hispanic origin to be two separate and distinct concepts. Hispanics and Latinos may be of any race.13, 19 Hispanic or Latino Origin: People who identify with the terms "Hispanic" or "Latino" are those who classify themselves in one of the specific Hispanic or Latino categories listed on the U.S. Census Bureau questionnaire (Mexican, Puerto Rican, or Cuban, as well as those who indicate that they are "other Spanish, Hispanic, or Latino"). Origin can be viewed as the heritage, nationality group, lineage, or country of birth of the person or the person's parents or ancestors before their arrival in the United States. People who identify their origin as Spanish, Hispanic, or Latino may be of any race.14 Why is it important?
Hispanics are one of the fastest growing segments of the U.S. population. The U.S. Census Bureau reported that 17.3 percent of the population in the U.S. self-identified as being Hispanic in 2016. The Census Bureau predicts that 28.6 percent of the population in the U.S. will be Hispanic by 2060.20 The ethnic composition of a place can indicate different needs, values, and attitudes sometimes held by different ethnic groups.
According to the Census Bureau: Data on ethnic groups are important for putting into effect a number of federal statutes (i.e.,
enforcing bilingual election rules under the Voting Rights Act; monitoring and enforcing equal employment opportunities under the Civil Rights Act). Data on Ethnic Groups are also needed by local governments to run programs and meet legislative requirements (i.e., identifying segments of the population who may not be receiving medical services under the Public Health Act; evaluating whether financial institutions are meeting the credit needs of minority populations under the Community Reinvestment Act).
CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 13
Demographics Combined Area Tribal Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Total Population, 2019* 18,036 20,706 70,277 109,019 324,697,795 Total Native American, 2019* ¨0 ¨57 716 773 2,750,143 American Indian Tribes ¨0 ¨13 535 548 2,111,167 Alaska Native Tribes ¨0 ¨0 ¨0 ¨0 116,314 Non-Specified Tribes ¨0 ¨44 ¨97 ¨141 441,329 Percent of Total Total Native American ¨0.0% ¨0.3% 1.0% 0.7% 0.8%
American Indian Tribes ¨0.0% ¨0.1% 0.8% 0.5% 0.7%
Alaska Native Tribes ¨0.0% ¨0.0% ¨0.0% ¨0.0% 0.0%
Non-Specified Tribes ¨0.0% ¨0.2% ¨0.1% ¨0.1% 0.1%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Native American Population, Percent of Total, Combined Area, 2019*
- In the 2015-2019 period, Lea County, 1.2%
NM had the highest estimated percent 1.0%
of the population that self-identified as 1.0%
0.8%
American Indian and Alaska Native (1.0%) and Andrews County, TX had 0.8% 0.7%
the lowest (0.0%).
0.6%
0.4% 0.3%
0.2%
0.0%
0.0%
Andrews Gaines Lea County, Combined United States County, TX County, TX NM Area
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 14
Demographics Combined Area Tribal What do we measure on this page?
This page describes, in general terms, the number of people who self-identify as American Indian and Alaska Native alone or in combination with one or more other races.21 American Indian: This category shows self-identification among people of American Indian descent. Census data are available for 36 tribes or Selected American Indian categories: Apache, Arapaho, Blackfeet, Cherokee, Cheyenne, Chickasaw, Chippewa, Choctaw, Colville, Comanche, Cree, Creek, Crow, Delaware, Hopi, Houma, Iroquois, Kiowa, Lumbee, Menominee, Navajo, Osage, Ottawa, Paiute, Pima, Potawatomi, Pueblo, Puget Sound Salish, Seminole, Shoshone, Sioux, Tohono O'Odham, Ute, Yakama, Yaqui, Yuman, and "All other tribes." In this report, people who self-identified as members of the Delaware, Houma, Menominee, and Ottawa tribes are included in the "All other tribes" category, along with all other federally recognized tribes not separately listed.22 Alaska Native: This category shows self-identification among people of Alaska Native descent. U.S. Census Bureau data are available for seven Alaska Native race and ethnic categories: Alaska Athabaskan, Aleut, Inupiat, Tlingit-Haida, Tsimshian, Yupik, and All other tribes.
Non-Specified Tribes: This category includes respondents who checked the American Indian or Alaska Native response category on the U.S. Census questionnaire or wrote in the generic term American Indian or Alaska Native," or tribal entries not elsewhere classified.
International Indian Tribes: This category shows people who self-identified as Canadian and French American Indian, Central American Indian, Mexican American Indian, South American Indian, or Spanish American Indian.
Why is it important?
The American Indian and Alaska Native identity of a place can indicate different needs, values, and attitudes sometimes held by different groups.
Many tribal people have unique historical and current ties to the land,23, 24 and some tribes have unique legal rights to certain activities, such as hunting, fishing, and plant-gathering.
Policies and management actions may have disproportionately high and adverse effects on tribes and it is helpful to know whether native peoples live in a particular area.25, 26 CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 15
Demographics Combined Area Tribal Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Total Population, 2019* 18,036 20,706 70,277 109,019 324,697,795 Total Native American ¨0 ¨57 716 773 2,750,143 American Indian Tribes; Specified ¨0 ¨13 535 548 2,111,167 Apache ¨0 ¨0 ¨23 ¨23 74,702 Arapaho ¨0 ¨0 ¨0 ¨0 8,449 Blackfeet ¨0 ¨0 ¨0 ¨0 29,575 Cherokee ¨0 ¨6 ¨79 ¨85 292,555 Cheyenne ¨0 ¨0 ¨0 ¨0 11,171 Chickasaw ¨0 ¨0 ¨35 ¨35 27,699 Chippewa ¨0 ¨0 ¨0 ¨0 119,229 Choctaw ¨0 ¨0 ¨87 ¨87 100,605 Colville ¨0 ¨0 ¨0 ¨0 8,957 Comanche ¨0 ¨7 ¨0 ¨7 12,268 Cree ¨0 ¨0 ¨0 ¨0 2,414 Creek ¨0 ¨0 ¨0 ¨0 44,041 Crow ¨0 ¨0 ¨0 ¨0 11,812 Hopi ¨0 ¨0 ¨0 ¨0 17,164 Iroquois ¨0 ¨0 ¨0 ¨0 47,230 Kiowa ¨0 ¨0 ¨0 ¨0 8,196 Lumbee ¨0 ¨0 ¨0 ¨0 75,903 Navajo ¨0 ¨0 196 196 332,389 Osage ¨0 ¨0 ¨0 ¨0 9,085 Paiute ¨0 ¨0 ¨0 ¨0 12,966 Pima ¨0 ¨0 ¨0 ¨0 24,121 Potawatomi ¨0 ¨0 ¨0 ¨0 21,297 Pueblo ¨0 ¨0 ¨39 ¨39 61,221 Puget Sound Salish ¨0 ¨0 ¨0 ¨0 14,850 Seminole ¨0 ¨0 ¨0 ¨0 14,229 Shoshone ¨0 ¨0 ¨13 ¨13 10,802 Sioux ¨0 ¨0 ¨0 ¨0 118,850 Tohono O'Odham ¨0 ¨0 ¨0 ¨0 25,996 Ute ¨0 ¨0 ¨0 ¨0 9,486 Yakama ¨0 ¨0 ¨0 ¨0 8,334 Yaqui ¨0 ¨0 ¨0 ¨0 28,348 Yuman ¨0 ¨0 ¨0 ¨0 8,129 All other tribes ¨0 ¨0 ¨14 ¨14 283,073 American Indian; Not Specified ¨0 ¨0 ¨39 ¨39 86,050 Alaska Native Tribes; Specified ¨0 ¨0 ¨0 ¨0 116,314 Alaska Athabaskan ¨0 ¨0 ¨0 ¨0 17,461 Aleut ¨0 ¨0 ¨0 ¨0 13,677 Inupiat ¨0 ¨0 ¨0 ¨0 30,307 Tlingit-Haida ¨0 ¨0 ¨0 ¨0 15,160 Tsimshian ¨0 ¨0 ¨0 ¨0 2,359 Yupik ¨0 ¨0 ¨0 ¨0 37,350 Alaska Native; Not Specified ¨0 ¨44 ¨58 ¨102 355,279 American Indian or Alaska Native; Not Specified ¨0 ¨44 ¨97 ¨141 441,329 International Indian Tribe ¨0 ¨0 ¨20 ¨20 202,150 High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
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Demographics Combined Area Tribal What do we measure on this page?
This page describes, in general terms, the number of people who self-identify as American Indian and Alaska Native alone or in combination with one or more other races.21 American Indian: This category shows self-identification among people of American Indian descent. Census data are available for 36 tribes or Selected American Indian categories: Apache, Arapaho, Blackfeet, Cherokee, Cheyenne, Chickasaw, Chippewa, Choctaw, Colville, Comanche, Cree, Creek, Crow, Delaware, Hopi, Houma, Iroquois, Kiowa, Lumbee, Menominee, Navajo, Osage, Ottawa, Paiute, Pima, Potawatomi, Pueblo, Puget Sound Salish, Seminole, Shoshone, Sioux, Tohono O'Odham, Ute, Yakama, Yaqui, Yuman, and "All other tribes." In this report, people who self-identified as members of the Delaware, Houma, Menominee, and Ottawa tribes are included in the "All other tribes" category, along with all other federally recognized tribes not separately listed.22 Alaska Native: This category shows self-identification among people of Alaska Native descent. U.S. Census Bureau data are available for seven Alaska Native race and ethnic categories: Alaska Athabaskan, Aleut, Inupiat, Tlingit-Haida, Tsimshian, Yupik, and All other tribes.
Non-Specified Tribes: This category includes respondents who checked the American Indian or Alaska Native response category on the U.S. Census questionnaire or wrote in the generic term American Indian or Alaska Native," or tribal entries not elsewhere classified.
International Indian Tribes: This category shows people who self-identified as Canadian and French American Indian, Central American Indian, Mexican American Indian, South American Indian, or Spanish American Indian.
Why is it important?
The American Indian and Alaska Native identity of a place can indicate different needs, values, and attitudes sometimes held by different groups.
Many tribal people have unique historical and current ties to the land,23, 24 and some tribes have unique legal rights to certain activities, such as hunting, fishing, and plant-gathering.
Policies and management actions may have disproportionately high and adverse effects on tribes and it is helpful to know whether native peoples live in a particular area.25, 26 CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 17
Demographics Combined Area Occupations and Industries Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Civilian employees > 16 years, 2019* 8,167 8,228 28,876 45,271 154,842,185 Management, professional, & related 1,837 2,311 7,252 11,400 59,647,283 Service 1,339 1,016 4,289 6,644 27,489,501 Sales and office 1,781 1,505 6,027 9,313 33,491,626 Farming, fishing, and forestry ¨85 278 212 575 1,047,109 Construction, extract, maint, & repair 1,290 1,284 4,130 6,704 7,891,884 Production, transportation 1,319 1,224 5,405 7,948 20,499,979 Percent of Total Management, professional, & related 22.5% 28.1% 25.1% 25.2% 38.5%
Service 16.4% 12.3% 14.9% 14.7% 17.8%
Sales and office 21.8% 18.3% 20.9% 20.6% 21.6%
Farming, fishing, and forestry ¨1.0% 3.4% 0.7% 1.3% 0.7%
Construction, extract, maint, & repair 15.8% 15.6% 14.3% 14.8% 5.1%
Production, transportation 16.2% 14.9% 18.7% 17.6% 13.2%
Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Civilian employees > 16 years, 2019* 8,167 8,228 28,876 45,271 154,842,185 Ag, forestry, fishing & hunting, mining 2,128 1,538 5,617 9,283 2,743,687 Construction 528 1,605 2,447 4,580 10,207,602 Manufacturing 611 400 810 1,821 15,651,460 Wholesale trade 142 330 1,218 1,690 4,016,566 Retail trade 979 692 3,010 4,681 17,267,009 Transport, warehousing, and utilities 550 626 2,067 3,243 8,305,602 Information ¨145 ¨146 352 643 3,114,222 Finance and ins, and real estate 282 275 1,110 1,667 10,151,206 Prof, mgmt, admin, & waste mgmt 398 149 1,576 2,123 17,924,655 Edu, health care, & social assistance 1,259 1,452 5,082 7,793 35,840,954 Arts, entertain, rec, accomod, & food 683 387 2,804 3,874 14,962,299 Other services, except public admin 286 400 1,397 2,083 7,522,777 Public administration 176 228 1,386 1,790 7,134,146 Percent of Total Ag, forestry, fishing & hunting, mining 26.1% 18.7% 19.5% 20.5% 1.8%
Construction 6.5% 19.5% 8.5% 10.1% 6.6%
Manufacturing 7.5% 4.9% 2.8% 4.0% 10.1%
Wholesale trade 1.7% 4.0% 4.2% 3.7% 2.6%
Retail trade 12.0% 8.4% 10.4% 10.3% 11.2%
Transport, warehousing, and utilities 6.7% 7.6% 7.2% 7.2% 5.4%
Information ¨1.8% ¨1.8% 1.2% 1.4% 2.0%
Finance and ins, and real estate 3.5% 3.3% 3.8% 3.7% 6.6%
Prof, mgmt, admin, & waste mgmt 4.9% 1.8% 5.5% 4.7% 11.6%
Edu, health care, & social assistance 15.4% 17.6% 17.6% 17.2% 23.1%
Arts, entertain, rec, accomod, & food 8.4% 4.7% 9.7% 8.6% 9.7%
Other services, except public admin 3.5% 4.9% 4.8% 4.6% 4.9%
Public administration 2.2% 2.8% 4.8% 4.0% 4.6%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
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Demographics Combined Area Occupations and Industries What do we measure on this page?
This page describes what people do for work in terms of the type of work (by occupation) and where they work (by industry).
Employment by Occupation: Refers to the Standard Occupational Classification (SOC) system in which workers are classified into occupations with similar job duties, skills, education, and/or training, regardless of industry.27, 28 Employment by Industry: Refers to employment by industry, listed according to the North American Industry Classification System (NAICS). For a more detailed analysis of long-term employment and personal income earned by industry, run an EPS Measures report. See https://headwaterseconomics.org/eps.
Why is it important?
Employment statistics are usually reported by industry. This is a useful way to show the relative diversity of the economy and the degree of dependence on certain sectors. Employment by occupation offers additional information that describes what people do for a living and the type of work they do, regardless of the industry. For example, management and professional occupations generally offer higher wages and require formal education, and these occupations could exist in any number of industries. Managers could be working for a software firm, a mine, or a construction company. Occupation information describes what people do, while employment by industry describes where people work.29 CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 19
Demographics Combined Area Labor Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Population 16 to 64, 2019* 11,261 12,095 43,619 66,975 208,879,084 WEEKS WORKED PER YEAR:
Worked 50 to 52 weeks 6,461 6,693 23,742 36,896 123,292,263 Worked 27 to 49 weeks 1,180 1,107 3,229 5,516 20,091,098 Worked 1 to 26 weeks 918 989 3,907 5,814 17,015,445 Did not work 2,702 3,306 12,741 18,749 48,480,278 HOURS WORKED PER WEEK:
Worked 35 or more hours per week 7,073 7,442 25,052 39,567 124,431,118 Worked 15 to 34 hours3.935185e-4 days <br />0.00944 hours <br />5.621693e-5 weeks <br />1.2937e-5 months <br /> per week 1,263 1,099 4,795 7,157 28,807,925 Worked 1 to 14 hours1.62037e-4 days <br />0.00389 hours <br />2.314815e-5 weeks <br />5.327e-6 months <br /> per week 223 248 1,031 1,502 7,159,763 Did not work 2,702 3,306 12,741 18,749 48,480,278 Mean usual hours worked for workers 44.5 43.3 43.1 43.4 38.8 Percent of Total WEEKS WORKED PER YEAR:
Worked 50 to 52 weeks 57.4% 55.3% 54.4% 55.1% 59.0%
Worked 27 to 49 weeks 10.5% 9.2% 7.4% 8.2% 9.6%
Worked 1 to 26 weeks 8.2% 8.2% 9.0% 8.7% 8.1%
Did not work 24.0% 27.3% 29.2% 28.0% 23.2%
HOURS WORKED PER WEEK:
Worked 35 or more hours per week 62.8% 61.5% 57.4% 59.1% 59.6%
Worked 15 to 34 hours3.935185e-4 days <br />0.00944 hours <br />5.621693e-5 weeks <br />1.2937e-5 months <br /> per week 11.2% 9.1% 11.0% 10.7% 13.8%
Worked 1 to 14 hours1.62037e-4 days <br />0.00389 hours <br />2.314815e-5 weeks <br />5.327e-6 months <br /> per week 2.0% 2.1% 2.4% 2.2% 3.4%
Did not work 24.0% 27.3% 29.2% 28.0% 23.2%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Weeks Worked per Year, 2019*
- In the 2015-2019 period, United States 100%
had the highest estimated percent of 50%
people that worked 50 to 52 weeks per year (59.0%), and Lea County, NM 0%
had the lowest (54.4%). Andrews Gaines Lea County, Combined United States County, TX County, TX NM Area Worked 50 to 52 weeks Worked 27 to 49 weeks Worked 1 to 26 weeks Did not work Hours Worked per Week, 2019*
- In the 2015-2019 period, Andrews 100%
County, TX had the highest estimated percent of people that worked 35 or 50%
more hours per week (62.8%), and 0%
Lea County, NM had the lowest Andrews Gaines Lea County, Combined United States (57.4%). County, TX County, TX NM Area
>35 Hours/Week 15-34 Hours/Week 1-14 Hours/Week Did not work
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 20
Demographics Combined Area Labor What do we measure on this page?
This page describes workers by hours worked per week and by weeks worked per year.
Weeks worked per year and hours worked per week are irrespective of each other. For example, regardless of whether an individual worked 10 or 40 hours4.62963e-4 days <br />0.0111 hours <br />6.613757e-5 weeks <br />1.522e-5 months <br /> per week, if (s)he worked 50 weeks per year, (s)he will be recorded as having "worked 50 to 52 weeks per year."
Labor force participation should be not confused with the unemployment rate, which is a measure of the people who are jobless and looking for work. To see long-term trends of unemployment, run an EPS Measures report. See https://headwaterseconomics.org/eps.
Why is it important?
Fewer hours worked per week or weeks worked per year may indicate that the local economy is suffering from underemployment which results in lower real incomes and a lower standard of living.30 For example, labor incomes in agriculture and other seasonal employment are consistently among the lowest incomes in industrial classes as reported by the U.S. Census.
However, shorter work weeks and fewer weeks worked per year also can be indicative of worker preference. Part-time jobs (those that average fewer than 35 hour4.050926e-4 days <br />0.00972 hours <br />5.787037e-5 weeks <br />1.33175e-5 months <br />s/week) are often ideal for students, people who are responsible for taking care of their dependents, and the elderly who wish to remain active in the workplace but do not want to work a full schedule. Advances in computer technologies enable workers to telecommute and work shorter and more flexible hours. And, in some cases, young adults seek out seasonal-, tourism-, or recreation-related employment by choice.
The Bureau of Labor Statistics offers data tables on workers by category.31 For example, in 2006, before the Great Recession, 3.9 million people in the county were employed part-time for economic reasons (slack work or business conditions or could only find a part-time job). By 2008, toward the end of the recession, this number had risen to 7.3 million people.32 Data on age and income distribution should be examined to better understand the degree to which the data on this page are related to under-employment and economic hardship versus worker preference.
Most employment statistics count full-time, part-time, and seasonal employment as the samethat is, a single job. In places where a relatively large percent of the employment base is either part-time or seasonally employed, this may explain falling wages or rates of employment that outpace population change.
For more information about changes in wages, employment, and population over time, create an EPS Socioeconomic Measures report. See https://headwaterseconomics.org/eps.
CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 21
Demographics Combined Area Commuting Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Workers 16 years and over, 2019* 8,130 8,098 28,672 44,900 152,735,781 PLACE OF WORK:
Worked in county of residence 6,020 6,087 26,379 38,486 110,334,054 Worked outside county of residence 2,110 2,011 2,293 6,414 42,401,727 TRAVEL TIME TO WORK:
Less than 10 minutes 3,350 2,824 6,772 12,946 17,735,996 10 to 14 minutes 1,463 1,385 5,851 8,699 19,200,268 15 to 19 minutes 430 859 6,284 7,573 21,935,522 20 to 24 minutes ¨96 578 2,489 3,163 20,782,841 25 to 29 minutes 132 240 731 1,103 9,375,527 30 to 34 minutes 515 790 1,952 3,257 19,960,362 35 to 39 minutes 149 ¨13 223 385 4,439,691 40 to 44 minutes 277 157 296 730 5,786,807 45 to 59 minutes 673 215 821 1,709 12,079,094 60 or more minutes 936 861 2,607 4,404 13,541,097 Mean travel time to work (minutes) 23.3 20.6 20.8 21.2 25.5 Percent of Total PLACE OF WORK:
Worked in county of residence 74.0% 75.2% 92.0% 85.7% 72.2%
Worked outside county of residence 26.0% 24.8% 8.0% 14.3% 27.8%
TRAVEL TIME TO WORK:
Less than 10 minutes 41.2% 34.9% 23.6% 28.8% 11.6%
10 to 14 minutes 18.0% 17.1% 20.4% 19.4% 12.6%
15 to 19 minutes 5.3% 10.6% 21.9% 16.9% 14.4%
20 to 24 minutes ¨1.2% 7.1% 8.7% 7.0% 13.6%
25 to 29 minutes 1.6% 3.0% 2.5% 2.5% 6.1%
30 to 34 minutes 6.3% 9.8% 6.8% 7.3% 13.1%
35 to 39 minutes 1.8% ¨0.2% 0.8% 0.9% 2.9%
40 to 44 minutes 3.4% 1.9% 1.0% 1.6% 3.8%
45 to 59 minutes 8.3% 2.7% 2.9% 3.8% 7.9%
60 or more minutes 11.5% 10.6% 9.1% 9.8% 8.9%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Place of Work, 2019*
- In the 2015-2019 period, United States 100%
had the highest estimated percent of 80%
people that worked outside the county 60%
of residence (27.8%), and Lea County, 40%
NM had the lowest (8.0%).
20%
0%
Andrews Gaines Lea County, Combined United States County, TX County, TX NM Area Worked in county of residence Worked outside county of residence
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
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Demographics Combined Area Commuting What do we measure on this page?
This page describes workers by place of work and by travel time to work. These data do not include those who work from home.
Why is it important?
The longest commute times tend to occur in larger metro areas or in counties surrounding metro areas. However, fast-growing micropolitan communities or some rural areas, such as resort communities, where the cost of living has gone up, are also experiencing large commute times.33 Economic development is sometimes affected by commuting in unanticipated ways: strategies aimed at increasing jobs in a community will not necessarily mean jobs for residents. Conversely, creating job opportunities for residents does not always require bringing jobs into that community.
High out-commuting rates can also separate tax revenues from demands for services, which complicates fiscal planning for local governments. "Bedroom communities"those with high levels of out-commutingmay struggle to provide social services, housing, and water and sewer facilities without an adequate source of business tax revenue. Higher levels and longer distance of commuting likely indicate a housing-job imbalance. This can result from unaffordable housing prices or other residential constraints.34 CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 23
Demographics Combined Area Income Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Per Capita Income (2019 $s) $30,673 $23,533 $25,585 na $34,103 Median Household Income^ (2019 $s) $76,158 $63,054 $60,546 na $62,843 Total Households, 2019* 5,573 5,812 22,523 33,908 120,756,048 Less than $10,000 272 476 1,487 2,235 7,302,871
$10,000 to $14,999 188 269 1,201 1,658 5,189,583
$15,000 to $24,999 260 297 2,029 2,586 10,760,144
$25,000 to $34,999 505 787 1,795 3,087 10,792,134
$35,000 to $49,999 645 540 2,784 3,969 14,822,045
$50,000 to $74,999 828 1,103 4,761 6,692 20,789,890
$75,000 to $99,999 1,003 846 3,157 5,006 15,374,617
$100,000 to $149,999 1,046 826 3,199 5,071 18,286,811
$150,000 to $199,999 401 420 1,250 2,071 8,173,563
$200,000 or more 425 248 860 1,533 9,264,390 Gini Coefficient^ 0.42 0.46 0.44 na 0.48 Percent of Total Less than $10,000 4.9% 8.2% 6.6% 6.6% 6.0%
$10,000 to $14,999 3.4% 4.6% 5.3% 4.9% 4.3%
$15,000 to $24,999 4.7% 5.1% 9.0% 7.6% 8.9%
$25,000 to $34,999 9.1% 13.5% 8.0% 9.1% 8.9%
$35,000 to $49,999 11.6% 9.3% 12.4% 11.7% 12.3%
$50,000 to $74,999 14.9% 19.0% 21.1% 19.7% 17.2%
$75,000 to $99,999 18.0% 14.6% 14.0% 14.8% 12.7%
$100,000 to $149,999 18.8% 14.2% 14.2% 15.0% 15.1%
$150,000 to $199,999 7.2% 7.2% 5.5% 6.1% 6.8%
$200,000 or more 7.6% 4.3% 3.8% 4.5% 7.7%
^ Median Household Income and Gini Coefficient are not available for metro/non-metro or regional aggregations.
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
- In the 2015-2019 period, the income Household Income Distribution, Combined Area, 2019*
category in the Combined Area with the most households was $50,000 to
$74,999 (19.7% of households). The $200,000 or more 4.5%
income category with the fewest $150,000 to $199,999 6.1%
households was $200,000 or more $100,000 to $149,999 15.0%
(4.5% of households).
$75,000 to $99,999 14.8%
$50,000 to $74,999 19.7%
- In the 2015-2019 period, the bottom $35,000 to $49,999 11.7%
40% of households in the Combined $25,000 to $34,999 9.1%
Area accumulated approximately $15,000 to $24,999 7.6%
11.0% of total income, and the top $10,000 to $14,999 4.9%
20% of households accumulated Less than $10,000 6.6%
approximately 59.7% of total income.
0% 5% 10% 15% 20% 25%
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
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Demographics Combined Area Income What do we measure on this page?
This page describes per capita income and the distribution of household income.
Per Capita Income: Total personal income divided by total population of an area.50 Household: All the people who occupy a housing unit as their usual place of residence.
Gini Coefficient: A summary value of the inequality of income distribution. A value of 0 represents perfect equality and a value of 1 represents perfect inequality. The lower the Gini coefficient, the more equal the income distribution.
The per capita income shown on this page is from the U.S. Census Bureau. The U.S. Census Bureau and Bureau of Economic Analysis (BEA) define income differently and derive the estimates using different techniques.51 Why is it important?
One important consideration of proposed policies and management actions is whether low-income populations could experience disproportionately adverse effects as a result. Analyzing income differences within and between locations helps to highlight areas where the population or a sub-population may be experiencing economic hardship.
The distribution of income is related to important aspects of economic well-being. Large numbers of households in the lower end of income distribution indicate economic hardship. A bulge in the middle can be interpreted as the size of the middle class. A figure that shows a proportionally large number of households at both extremes indicates a location characterized by haves and "have-nots. 35 Income distribution has always been a central concern of economic theory and economic policy. Classical economists were mainly concerned with the distribution of income among the main factors of production: land, labor, and capital. Modern economists have also addressed this issue but have been more concerned with the distribution of income across individuals and households.36 According to the Census Bureau, Researchers believe that changes in the labor market and household composition affected the long-run increase in income inequality. The wage distribution has become considerably more unequal with workers at the top experiencing real wage gains and those at the bottom real wage losses.... At the same time, long-run changes in society's living arrangements have taken place also tending to exacerbate household income differences. For example, divorces, marital separations, births out of wedlock, and the increasing age at first marriage have led to a shift away from married-couple households to single-parent families and nonfamily households. Since non-married-couple households tend to have lower income and less equally distributed income than other types of households... changes in household composition have been associated with growing income inequality. 37 CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 25
Demographics Combined Area Poverty Prevalence Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX People, 2019* 17,927 20,597 67,623 106,147 316,715,051 Families, 2019* 4,273 4,545 16,588 25,406 79,114,031 People Below Poverty 1,647 3,143 10,698 15,488 42,510,843 Families below poverty 312 520 2,063 2,895 7,541,196 Percent of Total People Below Poverty 9.2% 15.3% 15.8% 14.6% 13.4%
Families below poverty 7.3% 11.4% 12.4% 11.4% 9.5%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Individuals & Families Below Poverty, 2019*
- In the 2015-2019 period, Lea County, 18%
15.3% 15.8%
NM had the highest estimated percent 16% 14.6%
13.4%
of individuals living below poverty 14% 12.4%
(15.8%), and Andrews County, TX had 11.4% 11.4%
12%
the lowest (9.2%). 9.2% 9.5%
10%
7.3%
8%
- In the 2015-2019 period, Lea County, 6%
NM had the highest estimated percent 4%
of families living below poverty 2%
(12.4%), and Andrews County, TX had 0%
the lowest (7.3%). Andrews Gaines Lea County, Combined United States County, TX County, TX NM Area People Below Poverty Families below poverty Poverty Rate by Age & Family Type~
Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX People, 2019* 9.2% 15.3% 15.8% 14.6% 13.4%
Under 18 years 11.9% 17.6% 21.1% 18.8% 18.5%
65 years and older 10.7% 20.7% 13.8% 14.4% 9.3%
Families, 2019* 7.3% 11.4% 12.4% 11.4% 9.5%
Families with related children < 18 years 10.4% 14.2% 17.2% 15.5% 15.1%
Married couple families 5.5% 8.5% 7.3% 7.2% 4.8%
with children < 18 years 7.3% 10.9% 9.3% 9.3% 6.6%
Female householder, no husband present ¨18.1% 45.5% 32.7% 32.1% 26.5%
with children < 18 years ¨22.9% ¨50.9% 42.7% 40.5% 36.1%
~Poverty rate by age and family type is calculated by dividing the number of people by demographic in poverty by the total population of that demographic.
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 26
Demographics Combined Area Poverty Prevalence What do we measure on this page?
This page describes the number of individuals and families living below the poverty line.
Family: A group of two or more people who reside together and who are related by birth, marriage, or adoption.
Poverty: Following the Office of Management and Budget's Directive 14, the U.S. Census Bureau uses a set of income thresholds that vary by family size and composition to detect who is poor. If the total income for a family or an unrelated individual falls below the relevant poverty threshold, then the family or an unrelated individual is classified as being "below the poverty level."
Why is it important?
Poverty is an important indicator of economic well-being. Understanding the extent of poverty is important for several reasons. For example, people with limited income may have different needs and values. Also, proposed policies and activities may need to be analyzed in the context of whether people who are economically disadvantaged could experience disproportionately adverse effects.
Poverty rates are often reported in aggregate, which can hide important differences. The bottom table shows poverty for various types of individuals and families. This is important because aggregate poverty rates (for example, families below poverty) may hide some important information (for example, the poverty rate for single mothers with children).38, 39 CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 27
Demographics Combined Area Poverty by Race and Ethnicity Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Total Population in Poverty, 2019* 1,647 3,143 10,698 15,488 42,510,843 White alone 1,412 2,954 9,016 13,382 25,658,220 Black or African American alone ¨0 ¨100 1,072 1,172 9,114,217 American Indian alone ¨0 ¨0 ¨77 ¨77 660,695 Asian alone ¨0 ¨0 ¨0 ¨0 1,922,319 Native Hawaii & Other Pacific Is. alone ¨0 ¨0 ¨0 ¨0 101,826 Some other race ¨225 ¨89 426 740 3,313,183 Two or more races ¨10 ¨0 ¨107 ¨117 1,740,383 All Ethnicities in Poverty, 2019*
Hispanic or Latino (of any race) 1,408 1,501 7,175 10,084 11,256,244 Not Hispanic or Latino (of any race) 239 1,614 2,588 4,441 18,525,349 Percent of Total^
White alone 85.7% 94.0% 84.3% 86.4% 60.4%
Black or African American alone ¨0.0% ¨3.2% 10.0% 7.6% 21.4%
American Indian alone ¨0.0% ¨0.0% ¨0.7% ¨0.5% 1.6%
Asian alone ¨0.0% ¨0.0% ¨0.0% ¨0.0% 4.5%
Native Hawaii & Other Pacific Is. alone ¨0.0% ¨0.0% ¨0.0% ¨0.0% 0.2%
Some other race ¨13.7% ¨2.8% 4.0% 4.8% 7.8%
Two or more races ¨0.6% ¨0.0% ¨1.0% ¨0.8% 4.1%
Hispanic or Latino (of any race) 85.5% 47.8% 67.1% 65.1% 26.5%
Not Hispanic or Latino (of any race) 14.5% 51.4% 24.2% 28.7% 43.6%
^ Percent of total population in poverty by race and ethnicity is calculated by dividing the number of people in poverty in each racial or ethnic category by the total population.
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Percent of People by Race and Ethnicity Who Are Below Poverty~, 2019*
Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX White alone 8.8% 15.2% 15.1% 14.0% 11.1%
Black or African American alone ¨0.0% ¨20.1% 42.5% 37.5% 23.0%
American Indian alone na ¨0.0% ¨13.1% ¨11.9% 24.9%
Asian alone ¨0.0% ¨0.0% ¨0.0% ¨0.0% 10.9%
Native Hawaiian & Oceanic alone ¨0.0% ¨0.0% ¨0.0% ¨0.0% 17.5%
Some other race alone ¨20.6% ¨23.5% 13.8% 16.2% 21.0%
Two or more races alone ¨1.6% ¨0.0% ¨9.1% ¨6.3% 16.7%
Hispanic or Latino alone 13.9% 17.5% 18.1% 17.3% 19.6%
Non-Hispanic/Latino alone 3.3% 14.1% 10.7% 10.4% 9.6%
~Poverty prevalence by race and ethnicity is calculated by dividing the number of people by race in poverty by the total population of that race.
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 28
Demographics Combined Area Poverty by Race and Ethnicity What do we measure on this page?
This page describes the number of people living in poverty by race and ethnicity. It also shows the share of all people living in poverty by race and ethnicity, and the share of each race and ethnicity living in poverty.
Race: Race is a self-identification data item in which U.S. Census respondents choose the race or races with which they most closely identify.
Race categories include both racial and national-origin groups. The concept of race is separate from the concept of Hispanic origin.
Percentages for the various race categories add to 100 percent and should not be combined with the percent Hispanic.
Ethnicity: There are two minimum categories for ethnicity: Hispanic or Latino, and Not Hispanic or Latino. The federal government considers race and Hispanic origin to be two separate and distinct concepts. Hispanics and Latinos may be of any race.
Poverty: Following the Office of Management and Budget's Directive 14, the Census Bureau uses a set of income thresholds that vary by family size and composition to detect who is poor. If the total income for a family or an unrelated individual falls below the relevant poverty threshold, then the family or an unrelated individual is classified as being "below the poverty level."
Poverty thresholds are updated every year by the U.S. Census Bureau to reflect changes in the Consumer Price Index. The poverty thresholds are the same for all parts of the country. They are not adjusted for regional, state or local variations in the cost of living.40 Why is it important?
Understanding levels of poverty for different races and ethnicities can be important. People with limited income and from different races and ethnicities may have different needs and values. Proposed policies and activities may need to be analyzed in the context of whether minorities and people who are economically disadvantaged could be disproportionately impacted.41, 42 CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 29
Demographics Combined Area Household Earnings Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Total households, 2019* 5,573 5,812 22,523 33,908 120,756,048 Labor earnings 4,866 4,747 18,376 27,989 93,762,883 Social Security (SS) 1,163 1,328 5,787 8,278 37,664,988 Retirement income 616 538 2,301 3,455 23,985,063 Supplemental Security Income (SSI) 255 190 969 1,414 6,443,122 Cash public assistance income ¨43 ¨34 481 558 2,853,791 SNAP (previously Food Stamps) 359 390 3,476 4,225 14,171,567 Percent of Total^
Labor earnings 87.3% 81.7% 81.6% 82.5% 77.6%
Social Security (SS) 20.9% 22.8% 25.7% 24.4% 31.2%
Retirement income 11.1% 9.3% 10.2% 10.2% 19.9%
Supplemental Security Income (SSI) 4.6% 3.3% 4.3% 4.2% 5.3%
Cash public assistance income ¨0.8% ¨0.6% 2.1% 1.6% 2.4%
SNAP (previously Food Stamps) 6.4% 6.7% 15.4% 12.5% 11.7%
^ Total may add to more than 100% due to households receiving more than 1 source of income.
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Percent of Households Receiving Earnings, by Source, 2019*
- In the 2015-2019 period, the highest estimated percent of public assistance 90% 82.5%
in the Combined Area was in the form 80%
of Social Security (SS) (24.4%), and 70%
the lowest was in the form of Cash 60%
public assistance income (1.6%). 50%
40%
30% 24.4%
20% 10.2% 12.5%
10% 4.2% 1.6%
0%
Labor earnings Social Security SNAP (previously Supplemental Cash public Retirement assistance income Security Income (SS) income (SSI) Food Stamps)
Mean Annual Household Earnings by Source Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Mean earnings, 2019 (2019 $s) $93,239 $85,746 $78,891 $82,548 $90,514 Mean Social Security income $19,869 $16,062 $17,697 $17,740 $19,792 Mean retirement income $40,933 $19,494 $21,428 $24,605 $27,793 Mean Supplemental Security Income $9,739 $9,744 $11,057 $10,643 $10,073 Mean cash public assistance income ¨$2,391 ¨$5,215 $2,322 $2,504 $3,163
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 30
Demographics Combined Area Household Earnings What do we measure on this page?
This page describes household earnings by source.
Labor Earnings: Refers to households that receive wage or salary income and also those that receive net income from self-employment.
Social Security: Households that receive income that includes Social Security pensions and survivor benefits, permanent disability insurance payments made by the Social Security Administration before deductions for medical insurance, and Railroad Retirement insurance. It does not include Medicare reimbursement.
Retirement Income: Households that receive: 1) retirement pensions and survivor benefits from a former employer, labor union, U.S.
military, or federal, state, or local government; 2) disability income from companies, unions, the U.S. military, or federal, state, or local government; 3) periodic receipts from annuities and insurance; and 4) regular income from IRA and Keogh plans. It does not include Social Security income.
Supplemental Security Income (SSI): Households that receive assistance from the Social Security Administration that guarantees a minimum level of income for needy aged, blind, or disabled individuals.
Cash Public Assistance Income: Households that receive public assistance that includes general assistance and Temporary Assistance to Needy Families (TANF). It does not include separate payments received for hospital or other medical care (vendor payments) or Supplemental Security Income (SSI) or noncash benefits such as Supplemental Nutrition Assistance Program (SNAP).
Supplemental Nutrition Assistance Program (SNAP): Households that receive coupons or cards that can be used to purchase food. Prior to 2008, this program was referred to as Food Stamps. The U.S. Census Bureaus American Community Survey (ACS) does not report mean dollar amounts for this item.
Why is it important?
Earnings are not the only source of income, and for many families and communities a significant portion of income can be in the form of additional sources such as retirement and Social Security. While some payments may be an indication of an aging population or an influx of retirees (retirement payments), other measures (for example, SSI or SNAP) are an indication of economic hardship.
Additional information on non-labor sources of include are available by running an EPS Non-labor report: See https://headwaterseconomics.org/eps.
CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 31
Demographics Combined Area Education Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Total Population 25 yrs or older, 2019* 10,700 11,319 42,180 64,199 220,622,076 No high school degree 2,969 4,322 10,856 18,147 26,472,261 High school graduate 7,731 6,997 31,324 46,052 194,149,815 Associates degree 623 750 3,127 4,500 18,712,207 Bachelor's degree or higher 1,306 1,295 5,740 8,341 70,920,162 Graduate or professional 492 365 2,214 3,071 27,274,058 Percent of Total No high school degree 27.7% 38.2% 25.7% 28.3% 12.0%
High school graduate 72.3% 61.8% 74.3% 71.7% 88.0%
Associates degree 5.8% 6.6% 7.4% 7.0% 8.5%
Bachelor's degree or higher 12.2% 11.4% 13.6% 13.0% 32.1%
Graduate or professional 4.6% 3.2% 5.2% 4.8% 12.4%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
- In the 2015-2019 period, United States Educational Attainment, 2019*
had the highest percent of people over 50% 38.2%
age 25 with a bachelor's degree or 40% 32.1%
27.7% 25.7% 28.3%
higher (32.1%), and Gaines County, 30%
TX had the lowest (11.4%). 20% 12.2% 11.4% 13.6% 13.0% 12.0%
- In the 2015-2019 period, Gaines 10%
0%
County, TX had the highest percent of Andrews Gaines Lea County, Combined United States people over age 25 with no high County, TX County, TX NM Area school degree (38.2%), and United States had the lowest (12.0%). No high school degree Bachelor's degree or higher Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Total Population over 3 years old, 2019* 17,124 19,255 67,008 103,387 313,082,053 Enrolled in school: 4,893 5,430 18,966 29,289 81,084,866 Enrolled in nursery school, preschool 321 371 954 1,646 4,976,762 Enrolled in kindergarten 304 269 1,046 1,619 4,048,970 Enrolled in grade 1 to grade 4 1,265 1,519 5,274 8,058 16,144,177 Enrolled in grade 5 to grade 8 1,276 1,793 5,051 8,120 16,594,786 Enrolled in grade 9 to grade 12 1,283 1,037 4,115 6,435 16,991,221 Enrolled in college 444 441 2,526 3,411 22,328,950 Not enrolled in school 12,231 13,825 48,042 74,098 231,997,187 Percent of Total Enrolled in school: 28.6% 28.2% 28.3% 28.3% 25.9%
Enrolled in nursery school, preschool 1.9% 1.9% 1.4% 1.6% 1.6%
Enrolled in kindergarten 1.8% 1.4% 1.6% 1.6% 1.3%
Enrolled in grade 1 to grade 4 7.4% 7.9% 7.9% 7.8% 5.2%
Enrolled in grade 5 to grade 8 7.5% 9.3% 7.5% 7.9% 5.3%
Enrolled in grade 9 to grade 12 7.5% 5.4% 6.1% 6.2% 5.4%
Enrolled in college 2.6% 2.3% 3.8% 3.3% 7.1%
Not enrolled in school 71.4% 71.8% 71.7% 71.7% 74.1%
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 32
Demographics Combined Area Education What do we measure on this page?
This page describes levels of educational attainment.
Educational Attainment: This refers to the level of education completed by people 25 years and over in terms of the highest degree or the highest level of schooling completed.
School Enrollment: The U.S. Census Bureaus American Community Survey (ACS) defines people as enrolled in school if they were attending a public or private school or college at any time during the three months prior to taking the survey. People enrolled in vocational, technical, or business school such as post-secondary vocational, trade, hospital school, and on-the-job training were not reported as enrolled in school.
Why is it important?
Education is one of the most important indicators of the potential for economic success, and lack of education is closely linked to poverty. Studies show that areas with a higher-than-average-educated workforce grow faster, have higher incomes, and suffer less during economic downturns than other areas.43, 44 In 2017, the Bureau of Labor Statistics reported that the higher the rate of educational achievement, the lower the unemployment rate and the higher the wages.45 Understanding differences in education levels can highlight whether certain people might be disproportionately impacted by policies, plans, and management actions, and can inform communication and outreach efforts.
School enrollment can be an important indicator of the level of access to education, a communitys potential for economic growth, and the number of dependents in a community that are not of working age. Some government agencies also use this information for funding allocations.
CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 33
Demographics Combined Area Language Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Population 5 yrs or older, 2019* 16,485 18,434 64,755 99,674 304,930,125 Speak only English 9,286 7,805 40,562 57,653 238,982,352 Speak a language other than English 7,199 10,629 24,193 42,021 65,947,773 Spanish or Spanish Creole 7,053 5,651 23,525 36,229 40,709,597 Other Indo-European languages ¨113 4,889 347 5,349 11,136,849 Asian and Pacific Island languages ¨28 ¨58 ¨136 222 10,727,303 Other languages ¨0 ¨31 154 185 3,300,792 Speak English less than "very well" 2,529 3,857 8,136 14,522 25,615,365 Percent of Total Speak only English 56.3% 42.3% 62.6% 57.8% 78.4%
Speak a language other than English 43.7% 57.7% 37.4% 42.2% 21.6%
Spanish or Spanish Creole 42.8% 30.7% 36.3% 36.3% 13.4%
Other Indo-European languages ¨0.7% 26.5% 0.5% 5.4% 3.7%
Asian and Pacific Island languages ¨0.2% ¨0.3% ¨0.2% 0.2% 3.5%
Other languages ¨0.0% ¨0.2% 0.2% 0.2% 1.1%
Speak English less than "very well" 15.3% 20.9% 12.6% 14.6% 8.4%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Percent of Population that 'Speaks English Less Than Very Well',
2019*
- In the 2015-2019 period, Gaines 25%
20.9%
County, TX had the highest estimated 20%
percent of people that spoke English 15.3% 14.6%
less than 'very well' (20.9%), and 15% 12.6%
United States had the lowest (8.4%).
10% 8.4%
5%
0%
Andrews Gaines Lea County, Combined United States County, TX County, TX NM Area
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 34
Demographics Combined Area Language What do we measure on this page?
This page measures the primary language people speak at home.
Language Spoken at Home: The language used by respondents five years and older at home, either "English only" or a non-English language which is used in addition to English or in place of English.46 Why is it important?
If a significant portion of the population is classified as speaking English "less than very well," public outreach, meetings, plans, and implementation may need to be conducted in multiple languages. Community leaders and policy makers should be prepared to use interpreters of languages other than English to communicate effectively with diverse publics.
CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 35
Demographics Combined Area Housing Characteristics Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Total Housing Units, 2019* 6,296 6,501 26,610 39,407 137,428,986 Occupied 5,573 5,812 22,523 33,908 120,756,048 Vacant 723 689 4,087 5,499 16,672,938 For rent ¨136 ¨139 1,069 1,344 2,793,023 Rented, not occupied ¨0 ¨0 ¨112 ¨112 604,804 For sale only ¨38 ¨69 160 267 1,257,737 Sold, not occupied ¨34 ¨4 164 202 654,889 Seasonal, recreational, occasional ¨71 ¨152 217 440 5,440,455 For migrant workers ¨0 ¨4 ¨137 ¨141 37,983 Other vacant 444 321 2,228 2,993 5,884,047 Year Built Built 2010 or later 634 835 2,039 3,508 7,089,880 Built 2000 to 2009 554 925 2,104 3,583 19,186,932 Built 1990 to 1999 593 662 2,043 3,298 19,072,607 Built 1980 to 1989 856 985 3,784 5,625 18,455,307 Built 1970 to 1979 1,034 1,073 4,506 6,613 20,877,555 Built 1940 to 1969 2,579 1,949 11,397 15,925 35,417,575 Median year structure built^ 1975 1982 1973 na 1978 Percent of Total Occupancy Occupied 88.5% 89.4% 84.6% 86.0% 87.9%
Vacant 11.5% 10.6% 15.4% 14.0% 12.1%
For rent ¨2.2% ¨2.1% 4.0% 3.4% 2.0%
Rented, not occupied ¨0.0% ¨0.0% ¨0.4% ¨0.3% 0.4%
For sale only ¨0.6% ¨1.1% 0.6% 0.7% 0.9%
Sold, not occupied ¨0.5% ¨0.1% 0.6% 0.5% 0.5%
Seasonal, recreational, occasional ¨1.1% ¨2.3% 0.8% 1.1% 4.0%
For migrant workers ¨0.0% ¨0.1% ¨0.5% ¨0.4% 0.0%
Other vacant 7.1% 4.9% 8.4% 7.6% 4.3%
Year Built Built 2010 or later 10.1% 12.8% 7.7% 8.9% 5.2%
Built 2000 to 2009 8.8% 14.2% 7.9% 9.1% 14.0%
Built 1990 to 1999 9.4% 10.2% 7.7% 8.4% 13.9%
Built 1980 to 1989 13.6% 15.2% 14.2% 14.3% 13.4%
Built 1970 to 1979 16.4% 16.5% 16.9% 16.8% 15.2%
Built 1940 to 1969 41.0% 30.0% 42.8% 40.4% 25.8%
^ Median year structure built is not available for metro/non-metro or regional aggregations.
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
Percent of Housing Vacant (incl. seasonal homes), 2019*
- In the 2015-2019 period, Lea County, 20.0% 15.4% 14.0%
11.5% 10.6% 12.1%
NM had the highest estimated percent 10.0%
of the vacant housing (15.4%), and Gaines County, TX had the lowest 0.0%
Andrews Gaines Lea County, Combined United States (10.6%). County, TX County, TX NM Area
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 36
Demographics Combined Area Housing Characteristics What do we measure on this page?
This page describes whether housing is occupied or vacant, for rent or seasonally occupied, and the year built.
Rent: The number of homes for rent was defined as occupied housing units that were for rent, vacant housing units that were for rent, and vacant units rented but not occupied at the time of interview.
Seasonal, Recreational, or Occasional Use: Refers to vacant units used or intended for use only in certain seasons or for weekends or other occasional use throughout the year.
For Migrant Workers: Refers to housing units intended for occupancy by migratory workers employed in farm work during the crop season.
Why is it important?
Vacancy status is an indicator of the housing market and provides information on the stability and quality of housing for certain areas. The data is used to assess the demand for housing, to identify housing turnover within areas, and to better understand the population within the housing market over time. These data also serve to aid in the development of housing programs to meet the needs of persons at different economic levels.
Seasonal or recreational homes (i.e., second homes) are often an indicator of the desirability of a place for recreation and tourism. This could also be used as an indicator of recreational and scenic amenities, which can be a source of economic growth.
While the late 1990s and early 2000s were a period of rapid home development throughout the country, there have been other periods when housing grew at a fast rate (the late 1970s, for example, in many parts of the country). The relative growth rate of housing is an indicator of overall economic growth but may indicate challenges such as the need to prepare for risk of wildfire, flooding, and other natural disasters. The year the home was built also provides information on the age of the housing stock, which can be used to forecast future demand of services such as energy consumption and fire protection.
Housing that is classified as available for migrant workers can be used as an indicator of a certain type of economic activity, in particular crop agriculture.
CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 37
Demographics Combined Area Housing Affordability Andrews Gaines County, Lea County, NM Combined Area United States County, TX TX Owner-occupied mortgaged homes, 2019* 1,779 2,002 6,817 10,598 48,416,627 Cost >30% of household income 278 548 1,274 2,100 13,400,012 Specified renter-occupied units, 2019* 1,443 1,319 7,478 10,240 43,481,667 Rent >30% of household income 455 278 2,374 3,107 20,002,945 Median monthly mortgage cost^, 2019* $1,459 $1,266 $1,181 na $1,595 Median gross rent^, 2019* $1,028 $722 $895 na $1,062 Percent of Total Cost >30% of household income 15.6% 27.4% 18.7% 19.8% 27.7%
Rent >30% of household income 31.5% 21.1% 31.7% 30.3% 46.0%
^ Median monthly mortgage cost and median gross rent are not available for metro/non-metro or regional aggregations.
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
- In the 2015-2019 period, United States Housing Costs as a Percent of Household Income, 2019*
had the highest percent of owner-occupied households where > 30% of 46.0%
50%
household income was spent on 40% 31.5% 31.7%
mortgage costs (27.7%), and Andrews 30.3% 27.7%
27.4%
County, TX had the lowest (15.6%). 30% 21.1% 18.7% 19.8%
20% 15.6%
10%
- In the 2015-2019 period, United States had the highest percent of renter- 0%
Andrews Gaines Lea County, Combined United States occupied households where > 30% of County, TX County, TX NM Area household income was spent on gross rent (46.0%), and Gaines County, TX Cost >30% of household income had the lowest (21.1%). Rent >30% of household income Median Monthly Mortgage Costs and Gross Rent, 2019*
- In the 2015-2019 period, United States had the highest estimated monthly mortgage costs for owner-occupied $1,800 $1,595
$1,459
$1,600 homes ($1,595), and Lea County, NM $1,266 $1,181
$1,400 had the lowest ($1,181). $1,200 $1,028 $1,062
$895
$1,000 $722
$800
$600
- In the 2015-2019 period, United States $400 had the highest estimated monthly $200 na na
$0 gross rent for renter-occupied homes Andrews Gaines Lea County, Combined United States
($1,062), and Gaines County, TX had County, TX County, TX NM Area the lowest ($722).
Median monthly mortgage cost^, 2019* Median gross rent^, 2019*
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 38
Demographics Combined Area Housing Affordability What do we measure on this page?
This page describes whether housing is affordable for homeowners and renters.47 Owner-Occupied Housing Unit: 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.
Renter-Occupied Housing Unit: All occupied units that are not owner-occupied are classified as renter-occupied, whether they are rented for cash rent or occupied without payment of cash rent.
Household: A household includes all the people who occupy a housing unit as their usual place of residence.
Monthly Costs (owner-occupied): The sum of payment for mortgages, real estate taxes, various insurances, utilities, fuels, mobile home costs, and condominium fees.
Gross Rent: The amount of the contract rent plus the estimated average monthly cost of utilities (electricity, gas, and water and sewer) and fuels (oil, coal, kerosene, wood, etc.) if these are paid for by the renter (or paid for the renter by someone else).
The lowest ownership costs and gross rent share of household income reported in the U.S. Census Bureaus American Community Survey is 15 percent. Many government agencies define as excessive (or unaffordable) housing costs that exceed 30 percent of monthly household income.
Why is it important?
An important indicator of economic hardship is whether housing is affordable.48 This page measures housing affordability in terms of the share of household income that is devoted to a mortgage and related costs (for homeowners) and rent and related costs (for renters). An income share devoted to housing that is below 15 percent is a good proxy for highly affordable, while the income share devoted to housing that is above 30 percent is a good proxy for unaffordable.
CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 39
Demographics Combined Area Comparisons Combined Percent difference Combined Area vs.
Indicators Area United States United States Population Growth (% change, 2010*-2019*) 17.0% 6.8%
Median Age (2019*) na 38.1 Demographics Percent Population White Alone (2019*) 89.7% 72.5%
Percent Population Hispanic or Latino (2019*) 55.0% 18.0%
Percent Population American Indian or Alaska 0.7% 0.8%
Native (2019*)
Percent of Population 'Baby 19.2% 24.6%
Boomers' (2019*)
Median Household Income (2019*) na $62,843 Per Capita Income (2019*) na $34,103 Percent Individuals Below Poverty (2019*) 14.6% 13.4%
Income Percent Families Below Poverty (2019*) 11.4% 9.5%
Percent of Households with Retirement and Social 34.6% 51.1%
Security Income (2019*)
Percent of Households with Public Assistance 18.3% 19.4%
Income (2019*)
Percent Population 25 Years or Older without High 28.3% 12.0%
School Degree (2019*)
Percent Population 25 Years or Older with 13.0% 32.1%
Bachelor's Degree or Higher (2019*)
Percent Population That Speak English Less Than Structure 14.6% 8.4%
'Very Well' (2019*)
Percent of Houses that are Seasonal Homes (2019*) 1.1% 4.0%
Owner-Occupied Homes where > 30% of Household 19.8% 27.7%
Income Spent on Mortgage (2019*)
Renter-Occupied Homes where > 30% of Household 30.3% 46.0%
Income Spent on Rent (2019*)
-200% -100% 0% 100% 200%
High Reliability: Data with coefficients of variation (CVs) < 12% are in black to indicate that the sampling error is relatively small.
Medium Reliability: Data with CVs between 12 & 40% are in orange to indicate that the values should be interpreted with caution.
Low Reliability: Data with CVs > 40% are displayed in red to indicate that the estimate is considered very unreliable.
- ACS 5-year estimates used. 2019 represents average characteristics from 2015-2019; 2010 represents 2006-2010.
Data Sources: U.S. Department of Commerce. 2020. Census Bureau, American Community Survey Office, Washington, D.C.
Find more reports like this at headwaterseconomics.org/eps Data and Graphics l Page 40
Demographics Combined Area Comparisons What do we measure on this page?
This page compares key demographic, income, and social indicators from the selected region to the United States overall.
The term "benchmark" in this report should not be construed as having the same meaning as in the National Forest Management Act.
Race: Race is a self-identification data item in which respondents choose the race or races with which they most closely identify. In 1997 the U.S. Office of Management and Budget (OMB) revised the standards for how the Federal government collects and presents data on race and ethnicity.
Poverty: Following the Office of Management and Budget's Directive 14, the U.S. Census Bureau uses a set of income thresholds that vary by family size and composition to detect who is poor. If the total income for a family or an unrelated individual falls below the relevant poverty threshold, then the family or an unrelated individual is classified as being "below the poverty level."
Baby Boomers: Baby boomers are defined as having been born between 1946-1964. The reported percent of population that are "Baby Boomers" has some associated error since ACS generally reports age classes in 5-year increments (55 to 59 years, 60 to 64 years, etc.).
Social Security: Refers to households that receive income that includes Social Security pensions and survivor benefits, permanent disability insurance payments made by the Social Security Administration before deductions for medical insurance, and Railroad Retirement insurance. It does not include Medicare reimbursement.
Retirement Income: Consists of households that receive: 1) retirement pensions and survivor benefits from a former employer, labor union, U.S. military, or federal, state, or local government; 2) disability income from companies, unions, the U.S. military, or federal, state, or local government; 3) periodic receipts from annuities and insurance; and 4) regular income from IRA and Keogh plans. It does not include Social Security income.
Median Age, Median Household Income, and Per Capita Income are not calculated for multi-location regions due to data availability.
Why is it important?
This page shows a quick comparison of indicators covered in this report and shows how the region is different from the selected comparison area. If no custom comparison area was selected, EPS defaults to comparing against the U.S.
The chart offers an at-a-glance view of whether groups of indicators are atypical compared to the comparison area. For example, this page may show that a selected area has an older population, relatively unaffordable housing, and language barriers. In combination, these indicators can help community leaders, local government staff, policy makers and others improve outreach strategies and consider whether the impacts of projects and policies could have disproportionate impacts on certain segments of the population.
CHANGES IN BOUNDARIES: Data describing change over time can be misleading when geographic boundaries have changed.
The Census provides documentation about changes in boundaries at this site: www.census.gov/geo/reference/boundary-changes.html Find more reports like this at headwaterseconomics.org/eps Study Guide l Page 41
Demographics Combined Area Data Sources & Methods EPS uses national statistics from public government sources. All data used in EPS can be readily verified with the original sources:
- American Community Survey U.S, Census Bureau, U.S. Department of Commerce https://www.census.gov/programs-surveys/acs/
https://www.census.gov/acs/www/data/data-tables-and-tools/index.php Contacts:
https://www.census.gov/about/contact-us.html EPS core approaches: EPS is designed to focus on long-term trends across a range of important measures. Trend analysis provides a more comprehensive view of changes than spot data for select years. We encourage users to focus on major trends rather than absolute numbers. EPS displays detailed industry-level data to show changes in the composition of the economy over time and the mix of industries at points in time. EPS employs cross-sectional benchmarkingcomparing smaller areas such as counties to larger regions, states, and the nationto give a sense of relative performance. EPS allows users to aggregate data for multiple locations to allow for more sophisticated cross-sectional comparisons.
About the American Community Survey (ACS): All data used in this report is based on the U.S. Census Bureaus American Community Survey (ACS), a nationwide survey conducted annually by the U.S. Census Bureau that provides current demographic, social, economic, and housing information about communities. The ACS is not the same as the Decennial U.S.
Census, which is conducted every 10 years.
Estimates based on five years of sampling are available for all areas, whereas estimate based on annual and three-year sampling are only available for areas with larger population sizes. Data used in this report are five-year ACS estimates which are consistently available for locations with small populations such as towns. Five-year estimates are displayed for all locations because data obtained using the same survey technique is ideal for comparisons. The disadvantage is that multi-year estimates cannot be used to describe any particular year in the period, only the average value over the full period.
Data Accuracy: ACS is based on a survey and is subject to error. The U.S. Census Bureau reports the accuracy of the data by providing margins of error. In this report, we alert the user to the data accuracy using color-coded text and symbols in the tables:
BLACK indicates a coefficient of variation <12%; ORANGE (preceded with one dot) indicates between 12 and 40%; and RED BOLD (preceded with two dots) indicates a coefficient of variation >40%. The coefficient of variation is a measure of relative error in the estimate and is calculated directly from the margin of error as the ratio of the standard error to the estimate itself. Less populated areas tend to have lower accuracy. If data have consistently low accuracy throughout a report, we suggest running another demographics report at a larger geographic scale.
Find more reports like this at headwaterseconomics.org/eps Data Sources & Methods
Demographics Combined Area Endnotes 1- A useful resource on rural population change is the U.S. Department of Agricultures Economic Research Service web page: https://www.ers.usda.gov/topics/rural-economy-population/population-migration/.
2- William H. Frey's website provides links to publications, issues, media stories, data tools and resources on migration, population redistribution, and demography of both rural and urban populations in the U.S.: frey-demographer.org.
3- For a description of the U.S. Census Bureau's ACS methodology and data accuracy, see https://www.census.gov/programs-surveys/acs/methodology.html.
4- The U.S. Department of Health and Human Services Administration on Aging has a host of resources about older Americans at https://aoa.acl.gov/.
5- The U.S. Census Bureau publishes age data estimates for the U.S., states, counties, and metropolitan areas. See https://www.census.gov/topics/population/age-and-sex.html.
6- The non-profit Population Reference Bureau offers a helpful video on population pyramids at http://www.prb.org/Multimedia/Video/2009/distilleddemographics1.aspx.
7- Grayson KV and Victoria VA. 2010. The Next Four Decades: Older Population in the United States: 2010 to 2050. U.S. Census Bureau. https://www.census.gov/prod/2010pubs/p25-1138.pdf.
8- Jacobsen LA and Mather M. 2010. U.S. Social and Economic Trends Since 2000. Population Bulletin 65(1):1-16. Washington DC: Population Reference Bureau.
9- Cromartie J and Nelson P. 2009. Baby Boom Migration and Its Impact on Rural America. USDA-ERS Report No. 79. Washington, DC: USDA Economic Research Service.
https://permanent.access.gpo.gov/lps125026/ERR79.pdf.
10 - The U.S. Census Bureau has many resources that describe the trends in aging in the U.S. and its implications. See for example: An Aging Nation: The Older Population in the United States https://www.census.gov/prod/2014pubs/p25-1140.pdf; and The Graying of America: More Adults Than Kids by 2035 https://www.census.gov/library/stories/2018/03/graying-america.html?eml=gd.
11 - Frey WH. 2006. Americas Regional Demographics in the 00 Decade: The Role of Seniors, Boomers and New Minorities. Washington, DC: The Brookings Institution. https://www.brookings.edu/research/americas-regional-demographics-in-the-00s-decade-the-role-of-seniors-boomers-and-new-minorities/
12 - Frey WH. 2007. Mapping the Growth of Older America. Washington, DC: Brookings Institution.
https://www.brookings.edu/research/mapping-the-growth-of-older-america/.
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Demographics Combined Area Endnotes 13 - OMB. 1997. Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity.
Federal Register 62(210):58782-58790. https://www.gpo.gov/fdsys/pkg/FR-1997-10-30/pdf/97-28653.pdf.
14 - For a primer on how the Census 2010 handles race and Hispanic origin, see: Humes KR, Jones NA, and Ramirez RR. 2011. Overview of Race and Hispanic Origin. U.S. Census Bureau.
https://www.census.gov/prod/cen2010/briefs/c2010br-02.pdf.
15 - https://www.census.gov/newsroom/press-releases/2017/school-enrollment.html 16 - https://data.census.gov/cedsci/all?q=ethnic%20groups 17 - https://www.archives.gov/files/federal-register/executive-orders/pdf/12898.pdf 18 - A Century Apart: New Measures of Well-Being for U.S. Racial and Ethnic Groups is available at http://www.measureofamerica.org/acenturyapart/.
19 - Additional U.S. Census Bureau information on the Hispanic population (Whos Hispanic in America?) is available at https://www.census.gov/newsroom/cspan/hispanic/2012.06.22_cspan_hispanics.pdf.
20 - U.S. Census Bureau. Facts for Features: Hispanic Heritage Month 2016 https://census.gov/newsroom/facts-for-features/2016/cb16-ff16.html.
21 - See U.S. Census Bureau Tribal Affairs at https://www.census.gov/aian/.
22 - The U.S. Department of Interiors Indian Affairs oversees the Bureau of Indian Affairs and Bureau of Indian Education. Indian Affairs resources and contacts are available at https://bia.gov/index.htm.
23 - The U.S. Forest Service Office of Tribal Relations, formed in 2004, is a useful source of information and policies related to agency-tribal relations. See https://www.fs.fed.us/spf/tribalrelations/index.shtml.
24 - In 2016 the Bureau of Land Management published a Tribal Relations Manual and Handbook. See https://www.blm.gov/programs/cultural-heritage-and-paleontology/tribal-consultation.
25 - The American Indian Heritage Foundation hosts an American Indian Resource Directory with a list of all American Indian tribes, including Federally recognized tribes. This and other resources are available at http://www.indians.org/index.html.
26 - For an indispensable publication on environmental justice, see: Council on Environmental Quality. 1997.
Environmental Justice: Guidance under the National Environmental Policy Act. Washington, DC: CEQ.
https://www.epa.gov/sites/production/files/2015-02/documents/ej_guidance_nepa_ceq1297.pdf.
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Demographics Combined Area Endnotes 27 - The Census Bureau provides industry and occupation code lists and definitions:
https://www.census.gov/topics/employment/industry-occupation/guidance/code-lists.html.
28 - Occupations are also defined by U.S. Bureau of Labor Statistics: https://www.bls.gov/soc/.
29 - The Bureau of Labor Statistics provides The Occupational Outlook Handbook, which is an analysis of the prospects for different types of jobs, including training and education needed, earnings, working conditions, and what workers do on the job: https://www.bls.gov/ooh/.
30 - Maynard DC and Feldman DC. (Eds.) 2011. Underemployment: Psychological, economic and social challenges. New York, NY: Springer.
31 - Labor Force Statistics from Current Population Survey. Bureau of Labor Statistics.
https://www.bls.gov/cps/lfcharacteristics.htm.
32 - Involuntary Part-Time Work on the Rise. Bureau of Labor Statistics.
https://www.bls.gov/cps/lfcharacteristics.htm.
33 - https://www.census.gov/newsroom/press-releases/2017/acs-5yr.html 34 - Aldrich L, Beale C, and Kasse K. 1997. Commuting and the Economic Functions of Small Towns and Places. Rural Development Perspectives 12(3):26-31. https://naldc.nal.usda.gov/download/34577/PDF.
35 - For useful remarks and scholarly references on the level and distribution of economic well-being, see Federal Reserve System Chairman Ben S. Bernankes speech on February 6, 2007:
https://www.federalreserve.gov/newsevents/speech/Bernanke20070206a.htm.
36 - For an analysis of trends in the distribution of wealth in the U.S., see Saez E and Zucman G. 2016. Wealth inequality in the United States since 1913: Evidence from capitalized income tax data. The Quarterly Journal of Economics 131(2):519-578.
37 - Income Inequality. U.S. Census Bureau. 2010. https://www.census.gov/topics/income-poverty/income-inequality/about/middle-class.html.
38 - The University of Michigans National Poverty Center has a range of resources on poverty in the United States at http://www.npc.umich.edu/poverty/.
39 - For more information on rural poverty, see USDA Economic Research Service Briefing Room, Rural Income, Poverty, and Welfare: High Poverty Counties at https://www.ers.usda.gov/topics/rural-economy-population/rural-poverty-well-being/.
40 - The specific thresholds used for tabulation of income for particular years are shown at https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.
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Demographics Combined Area Endnotes 41 - The University of Michigans National Poverty Center hosts a body of research on race and ethnicity as they relate to poverty. See http://npc.umich.edu/research/ethnicity/.
42 - The U.S. Census Bureau briefing on Poverty Areas shows that Blacks and Hispanics are disproportionately affected by poverty. Four times as many Blacks and three times as many Hispanics lived in poverty areas than lived outside them. For more information, see https://www.census.gov/prod/1/statbrief/sb95_13.pdf.
43 - The Bureau of Labor Statistics shows a tight relationship between employment projections and educational attainment. See https://www.bls.gov/emp/documentation/education-training-system.htm.
44 - Card D. 1999. The Causal Effect of Education on Earnings in Ashenfelter O and Card D, eds., Handbook of Labor Economics, Vol. 3A. New York: Elsevier. Pp. 1801-63.
45 - Employment Projections. 2017. Bureau of Labor Statistics. https://www.bls.gov/emp/chart-unemployment-earnings-education.htm.
46 - The Modern Language Association has developed an online mapping tool that shows languages spoken for most areas of the United States. See https://apps.mla.org/map_main.
47 - The U.S. Census Bureaus American Housing Survey has additional information on housing and housing affordability. See https://www.census.gov/programs-surveys/ahs/.
48 - For current calculations on housing affordability, see the National Association of Realtors Housing Affordability Index, available at https://www.nar.realtor/topics/housing-affordability-index.
49 - Federal Register 59(32). See https://www.gpo.gov/fdsys/pkg/FR-1994-02-16/html/94-3685.htm.
50- For a description of the U.S. Census Bureau's ACS definition of per capita income, see https://www.census.gov/quickfacts/fact/note/US/INC910216.
51- For an explanantion of the discrepancies between the Census Bureau and the Bureau of Economic Analysis, see http://www.incontext.indiana.edu/2003/jan-feb03/details.asp.
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