Blog 4 - San Antonio, Texas a Demographic & Socio-economic review from 2000 - 2020

Author

B.A. Flores

Introduction

This analysis is a continuation of the following observations of American Community Survey data of Bexar County which was a focus on family poverty in Bexar County from 2010-2020 here.

In this analysis of Bexar County we observe three waves of data. For the year of 2020 we observe the American Community Survey 5-year estimates (2016-2020). For the year of 2010 we observe the American Community Survey 5-year estimates (2006-2010). For the year of 2000 we will observe the US Decennial Census survey. We will observe various socio-economic and demographic variables spatially amongst census tracts within Bexar county. All statistical analyses are conducted using R.

A focus will be on the Westside of San Antonio to be able to observe visually how that region of the city of San Antonio has changed in comparison with the rest of the city throughout those two decades. The Westside of San Antonio has been subjected to policy creation that benefited the downtown area of San Antonio and the development of what is now the Northside of San Antonio.

From the policies put in place that favored various parts of the city over the Westside such as the issues of flooding to the exposed hunger that has taken place within that area of the city; the Westside of San Antonio, Texas has experienced extreme poverty for many generations (Davies, 2018; Miller, 2021). With this analysis we will observe the state of poverty that the Westside and San Antonio as a whole is in and how it has changed over the two decades.

Variables Used

Bexar 2020

Code

bexar2020<-get_acs(geography = "tract",
                state="TX",
                county = c("Bexar"),
                year = 2020,
                variables=c("B07013_005E", #Estimate!!Total!!Same house 1 year ago!!Householder lived in owner-occupied housing units

                             "B07013_004E", 
#summary_var Estimate!!Total!!Same house 1 year ago GEOGRAPHICAL MOBILITY IN THE PAST YEAR BY TENURE FOR CURRENT RESIDENCE IN THE UNITED STATES

                             "B06011_001E",
#Median Income in past 12 months

"B01003_001",
#Total Population

"B01001I_001",
#Total Hispanics/Latinos

"B17013_002E",
#Estimate!!Total:!!Income in the past 12 months below poverty level: (Families) 

"B17013_001E",
#summary_var Estimate!!Total:POVERTY STATUS IN THE PAST 12 MONTHS OF FAMILIES BY HOUSEHOLD TYPE BY NUMBER OF PERSONS IN FAMILY


"B15003_022E",
#Estimate!!Total:!!Bachelor's degree 

"B15003_001E", 
#summary_var Estimate!!Total:EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 YEARS AND OVER


"B05002_013E",
#Estimate!!Total:!!Foreign born

"B05002_001E"), 
#summary_var Estimate!!Total:PLACE OF BIRTH BY NATIVITY AND CITIZENSHIP STATUS

                geometry = T, output = "wide")

Getting data from the 2016-2020 5-year ACS

Downloading feature geometry from the Census website.  To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.

Code

#create a county FIPS code - 5 digit
bexar2020$county<-substr(bexar2020$GEOID, 1, 5)

Bexar 2010

Code

bexar2010<-get_acs(geography = "tract",
                state="TX",
                county = c("Bexar"),
                year = 2010,
                variables=c("B07013_005E", #Estimate!!Total!!Same house 1 year ago!!Householder lived in owner-occupied housing units

                             "B07013_004E", 
#summary_var Estimate!!Total!!Same house 1 year ago GEOGRAPHICAL MOBILITY IN THE PAST YEAR BY TENURE FOR CURRENT RESIDENCE IN THE UNITED STATES

                             "B06011_001E",
#Median Income in past 12 months

"B01003_001",
#Total Population

"B01001I_001",
#Total Hispanics/Latinos

"B17013_002E",
#Estimate!!Total:!!Income in the past 12 months below poverty level: (Families) 

"B17013_001E",
#summary_var Estimate!!Total:POVERTY STATUS IN THE PAST 12 MONTHS OF FAMILIES BY HOUSEHOLD TYPE BY NUMBER OF PERSONS IN FAMILY


"B15002_015E",
#Estimate!!Total!!Male!!Bachelor's degree 

"B15002_032E",
#Estimate!!Total!!Female!!Bachelor's degree

"B15002_002E", 
#summary_var Estimate MALES!!Total:EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 YEARS AND OVER
"B15002_019E",
#summary_var Estimate FEMALES!!Total:EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 YEARS AND OVER


"B05002_013E",
#Estimate!!Total:!!Foreign born

"B05002_001E"), 
#summary_var Estimate!!Total:PLACE OF BIRTH BY NATIVITY AND CITIZENSHIP STATUS

                geometry = T, output = "wide")

Getting data from the 2006-2010 5-year ACS

Downloading feature geometry from the Census website.  To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.

Code

#create a county FIPS code - 5 digit
bexar2010$county<-substr(bexar2010$GEOID, 1, 5)

Bexar 2000

Code

bexar2000<-get_decennial(geography = "tract",
                state="TX",
                county = c("Bexar"),
                year = 2000,
                sumfile = "sf4",
                variables=c("PCT001001", #total population,
                            "PCT064015", #male bachelors total 
                            "PCT064032", #womans bachelors total
                            "PCT064001", #Total SEX BY EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 YEARS AND OVER [35]
                            "PCT157001", #POVERTY STATUS IN 1999 OF FAMILIES BY FAMILY TYPE BY PRESENCE OF RELATED CHILDREN UNDER 18 YEARS BY AGE OF RELATED CHILDREN [41]
                            "PCT157002", #Total!!Income in 1999 below poverty level of ^
                            "PCT039002", # Total!!Native NATIVITY BY LANGUAGE SPOKEN AT HOME BY ABILITY TO SPEAK ENGLISH FOR THE POPULATION 5 YEARS AND OVER [45]
                            "PCT039004", #Total!!Native!!Speak Spanish of ^

                            "HCT002001", #Total housing
                            "HCT002002", #Total!!Owner occupied
                            "PCT133001", #Median Income men
                            "PCT133004" #Median Income women
 ),

                geometry = T, output = "wide")

Getting data from the 2000 decennial Census

Downloading feature geometry from the Census website.  To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.

Code

#create a county FIPS code - 5 digit
bexar2000$county<-substr(bexar2000$GEOID, 1, 5)

Variables Recoded For 2020

Code

#rename variables and filter missing cases
bexar2020_1<-bexar2020%>%
  mutate(
homeown2020= (B07013_005E/B07013_004E)*100,
#Percentage of those who are homeowners in Bexar County per census tract

Latinos2020=(B01001I_001E/B01003_001E)*100,
#Percentage of Latinos in Bexar County per census tract

bachelors2020= (B15003_022E/B15003_001E)*100,
#Percentage of bachelors degrees in Bexar County per census tract

medincome2020=B06011_001E, 
#Median income in Bexar County per census tract

fampov2020=(B17013_002E/B17013_001E)*100, 
#Percentage of family poverty in Bexar County per census tract

foreignb2020=(B05002_013E/B05002_001E)*100) %>%

  na.omit()

Variables Recoded For 2010

Code

#rename variables and filter missing cases
bexar2010_1<-bexar2010%>%
  mutate(
homeown2010= (B07013_005E/B07013_004E)*100,
#Percentage of those who are homeowners in Bexar County per census tract

Latinos2010=(B01001I_001E/B01003_001E)*100,
#Percentage of Latinos in Bexar County per census tract

bachelors2010= ((B15002_015E+B15002_032E)/(B15002_002E+B15002_019E))*100,
#Percentage of bachelors degrees in Bexar County per census tract 

bachelors2010men=(B15002_015E/B15002_002E)*100,

bachelors2010women=(B15002_032E/B15002_019E)*100,

medincome2010=B06011_001E, 
#Median income in Bexar County per census tract

fampov2010=(B17013_002E/B17013_001E)*100, 
#Percentage of family poverty in Bexar County per census tract

foreignb2010=(B05002_013E/B05002_001E)*100) %>%
  
  na.omit()

Variables Recoded For 2000

Code

#rename variables and filter missing cases
bexar2000_1<-bexar2000%>%
  mutate(
homeown2000= (HCT002002/HCT002001)*100,
#Percentage of those who are homeowners in Bexar County per census tract

spainish2000=(PCT039004/PCT039002)*100,
#Percentage of those who are native born that primarily speak Spainish in the home in Bexar County per census tract

bachelors2000= ((PCT064015+PCT064032)/PCT064001)*100,
#Percentage of bachelors degrees in Bexar County per census tract 

medincome2000=(PCT133001+PCT133004),
#Median income in Bexar County per census tract

fampov2000=(PCT157002/PCT157001)*100)  %>%
#Percentage of family poverty in Bexar County per census tract
  
  na.omit()

#Results

Descriptive Statistics

Code

library(skimr)

Warning: package 'skimr' was built under R version 4.2.3

Code

skim(bexar2000_1Des)

Warning: Couldn't find skimmers for class: sfc_MULTIPOLYGON, sfc; No
user-defined `sfl` provided. Falling back to `character`.

Data summary
Name	bexar2000_1Des
Number of rows	275
Number of columns	6
_______________________
Column type frequency:
character	1
numeric	5
________________________
Group variables	None

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
geometry	0	1	235	3317	0	275	0

Variable type: numeric

skim_variable	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
homeown2000	1	60.72	22.28	0.00	48.45	65.70	75.88	97.45	▂▂▅▇▅
spainish2000	1	38.13	22.85	4.19	17.48	31.97	57.78	85.25	▇▆▃▅▃
bachelors2000	1	13.40	10.25	0.00	4.45	11.14	20.53	41.28	▇▃▃▂▁
medincome2000	1	42443.42	18413.56	17517.00	28199.00	38289.00	52008.00	107672.00	▇▅▂▁▁
fampov2000	1	14.12	11.10	0.00	4.45	11.66	21.93	60.67	▇▅▂▁▁

Code

skim(bexar2010_1Des)

Warning: Couldn't find skimmers for class: sfc_MULTIPOLYGON, sfc; No
user-defined `sfl` provided. Falling back to `character`.

Data summary
Name	bexar2010_1Des
Number of rows	362
Number of columns	9
_______________________
Column type frequency:
character	1
numeric	8
________________________
Group variables	None

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
geometry	0	1	240	3642	0	362	0

Variable type: numeric

skim_variable	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
homeown2010	1	71.30	20.58	0.00	61.51	74.95	86.31	100.00	▁▁▃▇▇
Latinos2010	1	58.51	24.40	1.72	36.96	56.95	82.12	99.29	▁▇▇▆▇
bachelors2010	1	15.57	11.44	0.00	5.17	13.30	24.41	46.90	▇▅▃▃▁
bachelors2010men	1	15.76	12.16	0.00	5.03	13.11	24.02	50.53	▇▅▃▂▁
bachelors2010women	1	15.37	11.55	0.00	5.10	12.31	23.92	50.42	▇▅▃▂▁
medincome2010	1	26616.41	12484.67	4609.00	17008.50	23996.00	32706.25	89458.00	▇▇▂▁▁
fampov2010	1	14.49	12.04	0.00	4.46	11.39	21.70	68.94	▇▃▂▁▁
foreignb2010	1	12.78	6.36	1.11	8.53	11.22	16.31	40.02	▅▇▃▁▁

Code

skim(bexar2020_1Des)

Warning: Couldn't find skimmers for class: sfc_MULTIPOLYGON, sfc; No
user-defined `sfl` provided. Falling back to `character`.

Data summary
Name	bexar2020_1Des
Number of rows	371
Number of columns	7
_______________________
Column type frequency:
character	1
numeric	6
________________________
Group variables	None

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
geometry	0	1	262	3705	0	371	0

Variable type: numeric

skim_variable	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
homeown2020	1	65.63	21.69	0.00	54.23	69.75	81.61	98.80	▁▂▃▇▆
Latinos2020	1	61.04	22.51	11.71	42.51	58.88	82.24	99.67	▂▇▇▆▇
bachelors2020	1	17.15	11.19	0.02	7.22	15.12	26.04	52.16	▇▆▅▂▁
medincome2020	1	30766.34	12392.80	8580.00	21842.00	28250.00	37220.50	101338.00	▇▇▂▁▁
fampov2020	1	13.25	10.98	0.00	4.25	10.92	20.65	67.38	▇▃▁▁▁
foreignb2020	1	13.13	6.12	1.43	8.59	12.15	16.63	36.65	▅▇▃▁▁

From the years of 2000 to 2020 it is shown that homeownership overall in Bexar county has fluctuated over the decade remaining relatively stable at about a median percentage of almost 70% of overall occupied homeowners in San Antonio. The percentage of Latinx is increasing over the years to continuing to be the majority in Bexar county. The amount of those with a bachelors degree has increased over the decade from about 13% to 17%. The overall median income in San Antonio had a slight decline over the decade staying about $28,000 for the median of the observed median income in 2020. Family poverty from 2000 to 2020 had a extremely slight decline from 14% to 13% but relatively constant. The foreign born population slightly increased from 2010 to 2020.

Code

library(tmap)
library(tmaptools)

Spatial Analysis

Percentage of Family Poverty

Code

bexar2020fampov <- tm_shape(bexar2020_1)+
  tm_polygons("fampov2020", title="Percentage of Family Poverty per census tract", palette="Blues", style="pretty", n=5 )+
  tm_format("World", title="Percentage of Family Poverty per Census Tract in Bexar County (2020)", legend.outside=T)+
  tm_scale_bar()+
  tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
  tm_compass()

bexar2000fampov <- tm_shape(bexar2000_1)+
  tm_polygons("fampov2000", title="Percentage of Family Poverty per census tract", palette="Blues", style="pretty", n=5 )+
  tm_format("World", title="Percentage of Family Poverty per Census Tract in Bexar County (2000)", legend.outside=T)+
  tm_scale_bar()+
  tm_credits("US Decennial Census (1996-2000) \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
  tm_compass()

bexar2010fampov <- tm_shape(bexar2010_1)+
  tm_polygons("fampov2010", title="Percentage of Family Poverty per census tract", palette="Blues", style="pretty", n=5 )+
  tm_format("World", title="Percentage of Family Poverty per Census Tract in Bexar County (2010)", legend.outside=T)+
  tm_scale_bar()+
  tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
  tm_compass()


fampovcomb<- tmap_arrange(bexar2020fampov, bexar2010fampov, bexar2000fampov)

fampovcomb

When observing family poverty in Bexar County from 2000 to 2020 you can see that the majority of those census tracts that exhibited family poverty of atleast 40% or higher also experienced that same level of family poverty in 2020. You can also observe that family poverty seems to be concentrating more in the Westside of San Antonio over the decade. The Northside of San Antonio is seen to have increased family poverty from 2000 to 2020 with a concentration forming in the northwest side of San Antonio. But overall the Northside of San Antonio does not experience the level of family poverty that those areas in the Westside, the Eastside, and the Southside experience.

Percentage that is Latino/Spainish Speaking

Code

bexar2020latino <- tm_shape(bexar2020_1)+
  tm_polygons("Latinos2020", title="Percentage of Latinos per census tract", palette="Blues", style="pretty", n=5 )+
  tm_format("World", title="Percentage of Latinos in San Antonio, TX (2020)", legend.outside=T)+
  tm_scale_bar()+
  tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
  tm_compass()

bexar2010latino<-tm_shape(bexar2010_1)+
  tm_polygons("Latinos2010", title="Percentage of Latinos per census tract", palette="Blues", style="pretty", n=5 )+
  tm_format("World", title="Percentage of Latinos in San Antonio, TX (2010)", legend.outside=T)+
  tm_scale_bar()+
  tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
  tm_compass()

bexar2000spainish<-tm_shape(bexar2000_1)+
  tm_polygons("spainish2000", title="Percentage of those born in the US that live in Spainish speaking households per census tract", palette="Blues", style="pretty", n=5 )+
  tm_format("World", title="Percentage of those born in the US that live in Spainish speaking households in San Antonio, TX (2000)", legend.outside=T)+
  tm_scale_bar()+
  tm_credits("US Decennial Census (1996-2000) \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
  tm_compass()

tmap_arrange(bexar2020latino, bexar2010latino, bexar2000spainish)

When observing the percentage of the population per census tract that is Latino from 2010 to 2020 we can see that the majority of San Antonio’s Latino population is found in the Westside and Southside of the city. For the year 2000 the proper variables to measure this were not found so we measured the population of those that were native born and how many households primarily spoke Spanish. This is to be used as a proxy for the percentage of the city that is Latino during the year of 2000. It is seen that those same areas seen in 2010 and 2020 are also highlighted here in the year 2000. Overtime it does seem that the Latino population is truly increasing and possibly in the Northwest side of the city but the majority of those who are Latinx live in the Westside and Southside of San Antonio.

Percentage with a Bachelors Degree

Code

bexar2020bachelors <- tm_shape(bexar2020_1)+
  tm_polygons("bachelors2020", title="Percentage of those 25 years of age or older with a bachelors degree per census tract (2016-2020)", palette="Blues", style="pretty", n=5 )+
  tm_format("World", title="San Antonio Educational Attainment; Percentage of those 25 years or older with a bachelors degree", legend.outside=T)+
  tm_scale_bar()+
  tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
  tm_compass()

bexar2010bachelors<-tm_shape(bexar2010_1)+
  tm_polygons("bachelors2010", title="Percentage of those with a bachelors degree per census tract (2006-2010)", palette="Blues", style="pretty", n=5 )+
  tm_format("World", title="Percentage of those 25 years and older with a bachelors degree", legend.outside=T)+
  tm_scale_bar()+
  tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
  tm_compass()

bexar2000bachelors<-tm_shape(bexar2000_1)+
  tm_polygons("bachelors2000", title="Percentage of those 25 years and older with a bachelors degree per census tract (2006-2010)", palette="Blues", style="pretty", n=5 )+
  tm_format("World", title="Percentage of those 25 years and older with a bachelors degree (2000)", legend.outside=T)+
  tm_scale_bar()+
  tm_credits("US Decennial Census (1996-2000) \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
  tm_compass()

tmap_arrange(bexar2020bachelors, bexar2010bachelors, bexar2000bachelors)

When observing the percentage of those who are 25 years of age or older that has a bachelors degree per census tract we can see an increase primarily being found in the northwest side of San Antonio. Whereas those areas that have experienced generational poverty such as the Westside, the Eastside, and the Southside maintained the lowest percentages of the population within those census tracts that earned a bachelors degree. Also there is no true increase being found over the two decades within those same areas.

Conclusion

When observing these findings we can see that the Westside of San Antonio as well as other areas of the city such as the Eastside and the Southside have experienced persistent poverty from the year of 2000 to 2020. The only true growth that was found were in areas either north or northwest of San Antonio.

Although increased family poverty is seen in the northwest of San Antonio this could be due to the growth of the Main Campus at the University of Texas at San Antonio off of 1604. With the urban sprawl and population growth that the university has caused in that area it seems family poverty tended to rise around that area of the northwest side.

Whereas in areas of San Antonio such as the Westside, the Eastside, and the Southside experienced family poverty consistently from 2000 to 2020. With some areas experiencing family poverty 3 times higher than the worst family poverty that is being experienced in any census tract in the year of 2020.

Public policy must be passed at the local level here in San Antonio for those areas such as the Westside, the Eastside, and the Southside so that they can truly experience the positive effects of the growth of San Antonio from the years of 2000 to 2020. Areas of the city where the majority of the population lives yet its the Northside of San Antonio that has seen some of the largest gains in educational attainment where the Westside seen none despite the building of the Downtown campus at the University of Texas at San Antonio. Further research must be conducted to help address how we can uplift these areas of San Antonio that has experienced multiple generations of poverty so that they can truly benefit from the fruits that San Antonio has to offer its community.

References

Davies., D.M. (2018, June 8) Documentary That Exposed San Antonio Poverty. Texas Public Radio. https://www.tpr.org/san-antonio/2018-06-08/hunger-in-america-the-1968-documentary-that-exposed-san-antonio-poverty

Miller, C. (2021). Westside Rising: How San Antonio’s 1921 Flood Devastated a City and Sparked a Latino Environmental Justice Movement. 1st edition. Trinity University Press.