Income Inequality

To investigate income inequality over time, we consider the American Community Survey (ACS). The ACS provides data at the county level from 2005-2018. However, we will also consider national and state-level estimates. The main variable of interest is Total Household Income, although Age is used to filter out individuals under 15, and Group Quarters Status to filter out individuals living in group quarters. I also replace missing values and code negative incomes as 0.

# clean the acs data
acs_data <- acs_data %>%
  mutate(hh_inc = na_if(HHINCOME, 9999999)*CPI99 %>%
                     replace(HHINCOME < 0, 0) %>% # # setting bottom code to 0 for now
                     replace(AGE < 15 | GQ == 2, NA)) # only consider population 15 yrs and older

print("ACS Data Summary - All Years (2005-2018), All Counties")
## [1] "ACS Data Summary - All Years (2005-2018), All Counties"
summary(acs_data)
##       YEAR          SAMPLE           SERIAL           CBSERIAL        
##  Min.   :2000   Min.   :200004   Min.   :      1   Min.   :1.000e+00  
##  1st Qu.:2007   1st Qu.:200701   1st Qu.: 275696   1st Qu.:4.207e+05  
##  Median :2011   Median :201101   Median : 596335   Median :8.414e+05  
##  Mean   :2011   Mean   :201066   Mean   : 633023   Mean   :2.996e+11  
##  3rd Qu.:2015   3rd Qu.:201501   3rd Qu.: 983824   3rd Qu.:1.262e+06  
##  Max.   :2018   Max.   :201801   Max.   :1410976   Max.   :2.018e+12  
##                                                    NA's   :5027734    
##       HHWT           CLUSTER              CPI99          STATEFIP    
##  Min.   :   1.0   Min.   :2.000e+12   Min.   :0.663   Min.   : 1.00  
##  1st Qu.:  58.0   1st Qu.:2.007e+12   1st Qu.:0.703   1st Qu.:12.00  
##  Median :  83.0   Median :2.011e+12   Median :0.741   Median :27.00  
##  Mean   : 114.5   Mean   :2.011e+12   Mean   :0.761   Mean   :27.68  
##  3rd Qu.: 133.0   3rd Qu.:2.015e+12   3rd Qu.:0.803   3rd Qu.:41.00  
##  Max.   :4331.0   Max.   :2.018e+12   Max.   :0.967   Max.   :56.00  
##                                                                      
##    COUNTYFIP          MET2013          MET2013ERR           PUMA        
##  Min.   :  0       Min.   :    0     Min.   :0         Min.   :  100    
##  1st Qu.:  0       1st Qu.:    0     1st Qu.:0         1st Qu.:  803    
##  Median : 13       Median :25540     Median :1         Median : 1906    
##  Mean   : 47       Mean   :22597     Mean   :2         Mean   : 3456    
##  3rd Qu.: 67       3rd Qu.:36740     3rd Qu.:4         3rd Qu.: 3704    
##  Max.   :810       Max.   :49740     Max.   :6         Max.   :77777    
##  NA's   :5027734   NA's   :5027734   NA's   :5027734   NA's   :5027734  
##      STRATA          CPUMA0010             GQ           HHINCOME      
##  Min.   :      1   Min.   :   1      Min.   :1.000   Min.   : -39996  
##  1st Qu.:  50056   1st Qu.: 251      1st Qu.:1.000   1st Qu.:  34500  
##  Median : 160045   Median : 531      Median :1.000   Median :  64500  
##  Mean   : 309526   Mean   : 541      Mean   :1.085   Mean   : 415963  
##  3rd Qu.: 350042   3rd Qu.: 853      3rd Qu.:1.000   3rd Qu.: 110000  
##  Max.   :7777722   Max.   :1078      Max.   :5.000   Max.   :9999999  
##                    NA's   :5027734                                    
##      PERNUM           PERWT             AGE            hh_inc        
##  Min.   : 1.000   Min.   :   1.0   Min.   : 0.00   Min.   :      0   
##  1st Qu.: 1.000   1st Qu.:  59.0   1st Qu.:19.00   1st Qu.:  25410   
##  Median : 2.000   Median :  86.0   Median :40.00   Median :  47165   
##  Mean   : 2.104   Mean   : 119.8   Mean   :39.96   Mean   :  62421   
##  3rd Qu.: 3.000   3rd Qu.: 140.0   3rd Qu.:58.00   3rd Qu.:  78353   
##  Max.   :20.000   Max.   :5419.0   Max.   :97.00   Max.   :2640257   
##                                                    NA's   :10424104

First, we look at the number of local areas with full information available for each state.

# state level
df.state <- acs_data %>%
  filter(PERNUM == 1  &
           STATEFIP <= 56) %>% # restrict to 50 states + DC  
  group_by(YEAR, STATEFIP) %>%
  summarise(mean = weighted.mean(hh_inc, na.rm = T, w = HHWT), 
            median = weighted.median(hh_inc, na.rm = T, w = HHWT),
            gini = weighted.gini(hh_inc[!is.na(hh_inc)], 
                                 HHWT[!is.na(hh_inc)])$Gini,
            n_hh = sum(PERNUM*HHWT)/1000000) %>%
  group_by(STATEFIP) %>%
  mutate(avg_n_hh = mean(n_hh)) %>% # average n_hh over time
  ungroup() %>%
  mutate(rank_n_hh = dense_rank(desc(avg_n_hh))) # rank states by size

# county level
df.county <- acs_data %>%
  filter(PERNUM == 1  & !is.na(hh_inc) &
           !is.na(COUNTYFIP) & COUNTYFIP != 0) %>%
  mutate(State = paste0(as_factor(STATEFIP), " (", STATEFIP, ")"),
         STATEFIP = paste0(
            strrep("0",(2  - nchar(as.character(STATEFIP)))),
            as.character(STATEFIP)),
         COUNTYFIP = paste0(
            strrep("0",(3  - nchar(as.character(COUNTYFIP)))),
            as.character(COUNTYFIP)),
         FIP = paste(STATEFIP, COUNTYFIP)) %>%
  group_by(YEAR, FIP) %>%
  summarise(State = first(State),
            mean = weighted.mean(hh_inc, na.rm = T, w = HHWT), 
            median = weighted.median(hh_inc, na.rm = T, w = HHWT),
            gini = weighted.gini(hh_inc[!is.na(hh_inc)], 
                                 HHWT[!is.na(hh_inc)])$Gini,
            n_hh = sum(PERNUM*HHWT)/1000000) %>%
  group_by(FIP)

For now, we consider Public Use Microdata Areas (PUMAs), or areas of at least 100,000 people. From 2005-2018, there are 1,078 PUMAs with no missing 1-year data in IPUMS. In the five most populous states (CA, FL, NY, PA, TX) there are 397 PUMAs. We will use this set of 397 PUMAs as the baseline in subsequent analyses.

# add number of years variable
df.county <- df.county %>%
  group_by(FIP) %>% 
  mutate(n_years = n()) %>%
  ungroup()

# look at counties with all data for each year

df.county.long <- df.county %>% 
  mutate(all_years = c(n_years == 14)*1) %>%
  filter(all_years == 1) %>% 
  group_by(State) %>%
  summarise(`n (county variable estimates)` = n()/14) 
# use test data, and compute the whole thing on Sherlock
acs_puma <- acs_data %>%
  filter(PERNUM == 1 & YEAR > 2004) %>%
  mutate(State = paste0(as_factor(STATEFIP), " (", STATEFIP, ")"),
    PUMA2k = paste0(
      strrep("0",(5  - nchar(as.character(PUMA)))),
      as.character(PUMA)),
    STATEFIP = paste0(
    strrep("0",(2  - nchar(as.character(STATEFIP)))),
    as.character(STATEFIP)),
    PUMA_ID = paste0(STATEFIP, PUMA2k)) %>%
  dplyr::select(-c(COUNTYFIP))


### reconstruct weights for county level estimates
acs_data_county_pre2012 <- acs_puma %>%
  filter(YEAR < 2012) %>%    # pre 2012 PUMA boundaries
  left_join(dplyr::select(county_to_puma_pre2012, 
                          COUNTYFIP, n_pumas, PUMA_ID, STATEFIP, FIP, 
                          contains_puma, wgt_puma, afact))

acs_data_county_post2012 <- acs_puma %>% # post 2012 PUMA boundaries
  filter(YEAR > 2011) %>%
  left_join(dplyr::select(county_to_puma_post2012, 
                          COUNTYFIP, n_pumas, PUMA_ID, STATEFIP, FIP, 
                          contains_puma, wgt_puma, afact))

acs_data_county <- bind_rows(acs_data_county_pre2012, acs_data_county_post2012) %>%
  mutate(HHWT_new = HHWT/n_pumas) %>%
  filter(!is.na(n_pumas)) %>%
  group_by(FIP) %>%
  mutate(n_years = length(unique(YEAR))) %>%
  filter(n_years == 14)



df.puma.county <- acs_data_county  %>% 
  dplyr::select(YEAR, FIP, State) %>% 
  distinct() %>%
  group_by(FIP) %>%
  mutate(n_years = length(unique(YEAR)),
         all_years = c(n_years == 14)*1) %>%
  filter(all_years == 1 & !duplicated(FIP)) %>% 
  group_by(State) %>%
  summarise(`n (PUMA estimates)` = n()) 


df.puma <- acs_puma %>%
  dplyr::select(YEAR, PUMA_ID, State) %>%
  distinct() %>%
  group_by(PUMA_ID) %>%
  mutate(n_years = length(unique(YEAR)),
         all_years = c(n_years == 14)*1) %>%
  filter(all_years == 1) %>%
  group_by(State) %>%
  summarise(`n PUMAs` = n()/14)
df.puma <- read.csv("df.puma.csv") %>%
  dplyr::select(-X)

kable(df.puma, caption = paste("Number of counties with complete data in each state (2005-2018)")) %>%
  kable_styling() %>%
  scroll_box(width = "800px", height = "500px")
Number of counties with complete data in each state (2005-2018)
State n.PUMAs
Alabama (1) 18
Alaska (2) 4
Arizona (4) 11
Arkansas (5) 15
California (6) 110
Colorado (8) 15
Connecticut (9) 22
Delaware (10) 4
District of Columbia (11) 3
Florida (12) 59
Georgia (13) 20
Hawaii (15) 8
Idaho (16) 1
Illinois (17) 47
Indiana (18) 24
Iowa (19) 7
Kansas (20) 9
Kentucky (21) 23
Louisiana (22) 15
Maine (23) 5
Maryland (24) 36
Massachusetts (25) 15
Michigan (26) 44
Minnesota (27) 27
Mississippi (28) 7
Missouri (29) 16
Montana (30) 1
Nebraska (31) 11
Nevada (32) 7
New Hampshire (33) 4
New Jersey (34) 38
New Mexico (35) 6
New York (36) 123
North Carolina (37) 27
North Dakota (38) 2
Ohio (39) 44
Oklahoma (40) 8
Oregon (41) 17
Pennsylvania (42) 55
Rhode Island (44) 6
South Carolina (45) 10
South Dakota (46) 1
Tennessee (47) 28
Texas (48) 49
Utah (49) 8
Vermont (50) 4
Virginia (51) 15
Washington (53) 22
West Virginia (54) 4
Wisconsin (55) 21
Wyoming (56) 2
Total 1078

To examine variation across states and counties, it is necessary to consider the complex survey design of the ACS. Looking at states and PUMAs, we must consider survey strata and household weights.

The following displays PUMA-level Gini estimates and standard errors.

#############################################
### State and county variance estimates #####
#############################################



county_state_gini <- data.frame(matrix(nrow = 0, ncol = 9))
names(county_state_gini) <- c("hh_inc", "se", "gini.moe", "STATEFIP",
                              "YEAR", "LEVEL", 
                              "COUNTYFIP", "FIP", "se_squared")

########### STATE LEVEL ##################

for(i in c("06", "12", "36", "42", "48")){
### estimate gini coefficients and variance using complex survey design
des_acs <- svydesign(ids = ~CLUSTER, weights = ~HHWT , strata = ~STRATA,
                     data = acs_data %>%
                       filter(!is.na(hh_inc) & STATEFIP == i ) %>%
                       dplyr::select(CLUSTER, HHWT, STRATA, YEAR, STATEFIP, PUMA, hh_inc,
                                     State))
des_acs <- convey_prep(des_acs)

svygini( ~hh_inc , design = des_acs )

puma_gini <- svyby(~hh_inc, by = ~interaction(YEAR, STATEFIP, PUMA), design = des_acs, FUN = svygini, deff = FALSE)


state_gini <- svyby(~hh_inc, by = ~interaction(YEAR, STATEFIP), design = des_acs, FUN = svygini, deff = FALSE)

state_gini <- state_gini %>%
  mutate(gini.moe = paste0(round(hh_inc, 4), " (", round(se, 4), ")"),
         STATEFIP = substr(`interaction(YEAR, STATEFIP)`, 6, 7),
         YEAR = substr(`interaction(YEAR, STATEFIP)`, 0, 4),
         LEVEL = "State")

########### COUNTY LEVEL ###################

# if a county = puma, weights won't change
# otherwise, pumas that only make up a portion of the county will be downweighted


des_acs <- svydesign(ids = ~CLUSTER, weights = ~HHWT_new , strata = ~STRATA,
                     data = acs_data_county %>%
                       filter(!is.na(hh_inc) & STATEFIP == i ) %>%
                       dplyr::select(CLUSTER, HHWT_new, STRATA, YEAR, STATEFIP, PUMA, hh_inc, FIP))
des_acs <- convey_prep(des_acs)

county_gini <- svyby(~hh_inc, by = ~interaction(YEAR, FIP), design = des_acs, FUN = svygini, deff = FALSE)

county_gini <- county_gini %>%
  mutate(gini.moe = paste0(round(hh_inc, 4), " (", round(se, 4), ")"),
         STATEFIP = substr(`interaction(YEAR, FIP)`, 6, 7),
         COUNTYFIP = substr(`interaction(YEAR, FIP)`, 8, 12),
         YEAR = substr(`interaction(YEAR, FIP)`, 0, 4), 
         LEVEL = "County")


puma_list <- acs_puma %>%
    dplyr::select(YEAR, CPUMA0010, State) %>%
    distinct() %>%
    group_by(CPUMA0010) %>%
    mutate(n_years = length(unique(YEAR)),
           all_years = c(n_years == 14)*1) %>%
    filter(all_years == 1) %>% dplyr::select(CPUMA0010) %>% 
  unlist() %>%
  unique()

acs_data %>%
  filter(CPUMA0010 %in% puma_list)



####### join county and state estimates
county_state_gini <- bind_rows(county_state_gini, 
                               dplyr::select(state_gini, -starts_with("interact")),
                               dplyr::select(county_gini, -starts_with("interact"))) %>%
  mutate(FIP = paste0(STATEFIP, COUNTYFIP),
         se_squared = se^2)

}
# run this to give acs_data correct state labels
acs_data <- acs_data %>%
  filter(PERNUM == 1 & YEAR > 2004) %>%
  mutate(State = paste0(as_factor(STATEFIP), " (",
                        STATEFIP,
    ")"),
    STATEFIP = paste0(
    strrep("0",(2  - nchar(as.character(STATEFIP)))),
    as.character(STATEFIP)),
    COUNTYFIP = paste0(
      strrep("0",(5  - nchar(as.character(COUNTYFIP)))),
      as.character(COUNTYFIP)),
    PUMA2k = paste0(
      strrep("0",(5  - nchar(as.character(PUMA)))),
      as.character(PUMA)),
    PUMA_ID = paste0(STATEFIP, PUMA2k))

puma_state_gini <- read.csv("puma_state_gini.csv") %>%
  dplyr::select(-X) %>%
  mutate(STATEFIP = paste0(
    strrep("0",(2  - nchar(as.character(STATEFIP)))),
    as.character(STATEFIP)))

# run second loop to output ses
for(i in c("06", "12", "36", "42", "48")){
df.state.puma.wide <- puma_state_gini %>%
  filter(STATEFIP == i & YEAR > 2004) %>%
  dplyr::select(YEAR, se, PUMA, LEVEL) %>%
  mutate(PUMA = replace(as.character(PUMA), LEVEL == "State", 
                       first(acs_data$State[acs_data$STATEFIP == i]))) %>%
  dplyr::select(YEAR, se, PUMA) %>%
  group_by(YEAR) %>%
  pivot_wider(names_from = PUMA, values_from = se) 

print(kable(df.state.puma.wide, caption = "Gini standard errors for the five most populous states and their PUMAs with complete data (2005-2018)") %>%
  kable_styling() %>%
  scroll_box(width = "900px", height = "500px"))

}
Gini standard errors for the five most populous states and their PUMAs with complete data (2005-2018)
YEAR California (6) 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158
2005 0.0012740 0.0175566 0.0158571 0.0152273 0.0238119 0.0192410 0.0160332 0.0195127 0.0185182 0.0130023 0.0122855 0.0129967 0.0133535 0.0231022 0.0068103 0.0128721 0.0146393 0.0078690 0.0214774 0.0149719 0.0085642 0.0223949 0.0181853 0.0104228 0.0073620 0.0197085 0.0068355 0.0138938 0.0191520 0.0162579 0.0180701 0.0196789 0.0262962 0.0078435 0.0151735 0.0202614 0.0111046 0.0197980 0.0125703 0.0241060 0.0174864 0.0188439 0.0203217 0.0153702 0.0105480 0.0168136 0.0104983 0.0127653 0.0097884 0.0208145 0.0170502 0.0145437 0.0185695 0.0157123 0.0122006 0.0119268 0.0100403 0.0355828 0.0043611 0.0142441 0.0103301 0.0120285 0.0061537 0.0148956 0.0059890 0.0067407 0.0114461 0.0080661 0.0116720 0.0079246 0.0091117 0.0146930 0.0127525 0.0160379 0.0175084 0.0176455 0.0153672 0.0161149 0.0172561 0.0187432 0.0156827 0.0096846 0.0126033 0.0153811 0.0160916 0.0185810 0.0183703 0.0154296 0.0148465 0.0103882 0.0111236 0.0086473 0.0235671 0.0191348 0.0091254 0.0203551 0.0164730 0.0119476 0.0158558 0.0184474 0.0246478 0.0160612 0.0149828 0.0144002 0.0173589 0.0155112 0.0165364 0.0211546 0.0118663 0.0076507 0.0133710
2006 0.0011427 0.0151727 0.0161285 0.0145950 0.0171685 0.0120929 0.0182625 0.0228932 0.0155049 0.0160846 0.0122773 0.0193224 0.0136716 0.0149365 0.0061503 0.0124783 0.0134380 0.0082622 0.0148980 0.0176217 0.0081928 0.0150458 0.0148859 0.0087448 0.0061256 0.0159408 0.0065547 0.0114334 0.0155974 0.0128072 0.0082835 0.0194018 0.0167231 0.0065999 0.0172025 0.0159424 0.0120987 0.0159479 0.0100928 0.0142933 0.0100088 0.0287043 0.0229599 0.0109928 0.0106865 0.0148638 0.0109817 0.0143059 0.0098340 0.0178391 0.0151596 0.0110213 0.0261542 0.0174739 0.0138261 0.0138593 0.0113129 0.0176629 0.0041755 0.0113182 0.0093901 0.0091280 0.0051348 0.0165017 0.0060611 0.0064246 0.0095215 0.0066666 0.0112710 0.0076941 0.0089731 0.0158412 0.0092966 0.0185721 0.0194116 0.0152688 0.0169215 0.0157298 0.0170707 0.0197113 0.0164060 0.0082875 0.0148402 0.0141728 0.0148903 0.0164741 0.0143599 0.0146435 0.0150110 0.0096981 0.0101903 0.0073628 0.0178469 0.0191207 0.0101439 0.0161620 0.0174797 0.0153573 0.0162334 0.0151597 0.0157569 0.0183086 0.0128155 0.0254944 0.0155320 0.0108670 0.0171963 0.0193970 0.0131753 0.0068706 0.0136389
2007 0.0011499 0.0152690 0.0162656 0.0133149 0.0172824 0.0158514 0.0151707 0.0169435 0.0147962 0.0140425 0.0124919 0.0147937 0.0127861 0.0169643 0.0058032 0.0116015 0.0152500 0.0074939 0.0184915 0.0211461 0.0103376 0.0154131 0.0164379 0.0082417 0.0062696 0.0150704 0.0063961 0.0138081 0.0179493 0.0157806 0.0080294 0.0186704 0.0211654 0.0071909 0.0169713 0.0305620 0.0124228 0.0134548 0.0092356 0.0445047 0.0094859 0.0191681 0.0131640 0.0136015 0.0101375 0.0138279 0.0110805 0.0123861 0.0117108 0.0236807 0.0158787 0.0121036 0.0233848 0.0154619 0.0130111 0.0160957 0.0106778 0.0160700 0.0039546 0.0109020 0.0093557 0.0090953 0.0057854 0.0150052 0.0054305 0.0055008 0.0099332 0.0068081 0.0082732 0.0080617 0.0081695 0.0152159 0.0096508 0.0149448 0.0148328 0.0162921 0.0155864 0.0147709 0.0172132 0.0203478 0.0190018 0.0109453 0.0131139 0.0151390 0.0204930 0.0175102 0.0156883 0.0143475 0.0142198 0.0097518 0.0110194 0.0076429 0.0156233 0.0183309 0.0082641 0.0220062 0.0173196 0.0123562 0.0170238 0.0155073 0.0145335 0.0141824 0.0146570 0.0186979 0.0191830 0.0124755 0.0159182 0.0217537 0.0117667 0.0070515 0.0127005
2008 0.0011414 0.0130155 0.0150498 0.0132278 0.0144146 0.0137099 0.0169719 0.0148367 0.0134356 0.0130822 0.0124079 0.0125987 0.0120554 0.0212633 0.0060890 0.0115671 0.0135779 0.0072744 0.0228068 0.0183933 0.0079952 0.0120794 0.0177151 0.0084224 0.0063647 0.0156695 0.0060653 0.0121070 0.0186338 0.0138609 0.0087706 0.0170065 0.0185219 0.0065726 0.0148010 0.0162662 0.0117661 0.0154568 0.0113831 0.0164156 0.0104263 0.0183572 0.0156210 0.0173058 0.0111613 0.0150194 0.0105075 0.0152130 0.0112581 0.0139831 0.0205582 0.0111923 0.0214920 0.0174187 0.0135487 0.0143856 0.0099348 0.0220692 0.0041269 0.0111052 0.0106523 0.0099060 0.0048859 0.0135222 0.0052281 0.0068618 0.0093076 0.0068853 0.0091670 0.0078831 0.0095703 0.0145728 0.0092989 0.0206862 0.0154809 0.0147202 0.0158375 0.0141349 0.0206501 0.0180207 0.0188391 0.0082167 0.0116758 0.0135379 0.0153523 0.0169228 0.0146469 0.0143613 0.0139643 0.0093781 0.0098862 0.0073693 0.0150410 0.0189197 0.0086096 0.0227360 0.0173508 0.0120514 0.0154382 0.0135613 0.0159755 0.0184768 0.0137328 0.0189629 0.0146170 0.0084466 0.0181532 0.0144403 0.0144745 0.0072888 0.0152555
2009 0.0010907 0.0151986 0.0137176 0.0131516 0.0289504 0.0158522 0.0132575 0.0155939 0.0147062 0.0125349 0.0143250 0.0124565 0.0118198 0.0157151 0.0062165 0.0127987 0.0115044 0.0075870 0.0183510 0.0157328 0.0078603 0.0211389 0.0171714 0.0075337 0.0059777 0.0211035 0.0061137 0.0097896 0.0162523 0.0165495 0.0067604 0.0200774 0.0141517 0.0065291 0.0154952 0.0159531 0.0119964 0.0160618 0.0085899 0.0152107 0.0092706 0.0236129 0.0135258 0.0124140 0.0110730 0.0153806 0.0112264 0.0129282 0.0102395 0.0181786 0.0179256 0.0102806 0.0214232 0.0153063 0.0110970 0.0173723 0.0091937 0.0135149 0.0039158 0.0113087 0.0135917 0.0109240 0.0048564 0.0130843 0.0057972 0.0060299 0.0098628 0.0061970 0.0097751 0.0076250 0.0082912 0.0163305 0.0095036 0.0174392 0.0157059 0.0133895 0.0150812 0.0146923 0.0173286 0.0169089 0.0177632 0.0078469 0.0120823 0.0140110 0.0156472 0.0141108 0.0144086 0.0119928 0.0143678 0.0100121 0.0110491 0.0071372 0.0138654 0.0169047 0.0079481 0.0160887 0.0122400 0.0115750 0.0178023 0.0160199 0.0154289 0.0135652 0.0126281 0.0147168 0.0139392 0.0085604 0.0213330 0.0174254 0.0120277 0.0066292 0.0126803
2010 0.0010522 0.0135106 0.0151071 0.0131822 0.0163821 0.0138189 0.0143008 0.0159025 0.0132569 0.0134200 0.0125600 0.0116917 0.0190929 0.0161240 0.0058410 0.0112813 0.0138268 0.0072824 0.0186685 0.0142770 0.0071988 0.0145117 0.0163626 0.0079997 0.0059607 0.0134795 0.0059679 0.0106208 0.0170175 0.0128856 0.0065942 0.0148657 0.0172874 0.0060549 0.0127666 0.0166964 0.0117605 0.0133105 0.0081118 0.0151949 0.0108502 0.0176484 0.0145038 0.0123401 0.0150678 0.0159762 0.0101977 0.0138608 0.0098074 0.0206538 0.0166463 0.0098368 0.0248944 0.0168227 0.0116038 0.0185519 0.0098383 0.0182063 0.0037839 0.0113002 0.0100626 0.0089761 0.0049707 0.0159170 0.0053356 0.0054320 0.0099930 0.0063382 0.0088630 0.0076591 0.0081567 0.0151077 0.0086710 0.0183276 0.0157130 0.0142903 0.0150168 0.0143385 0.0139676 0.0170654 0.0207563 0.0077548 0.0137738 0.0127907 0.0144956 0.0145842 0.0132778 0.0158614 0.0135837 0.0091993 0.0120845 0.0074534 0.0153507 0.0144342 0.0076573 0.0158007 0.0141690 0.0107317 0.0141513 0.0132000 0.0182942 0.0145628 0.0130572 0.0132068 0.0142378 0.0099358 0.0143974 0.0173536 0.0115065 0.0064536 0.0137064
2011 0.0011797 0.0167572 0.0138558 0.0129226 0.0172096 0.0136056 0.0169239 0.0171527 0.0156078 0.0143670 0.0117875 0.0215373 0.0148667 0.0153019 0.0083103 0.0136983 0.0135790 0.0071229 0.0174437 0.0164094 0.0077841 0.0234851 0.0153079 0.0081145 0.0066700 0.0194684 0.0060490 0.0107672 0.0224971 0.0132604 0.0082725 0.0135116 0.0141346 0.0074705 0.0169787 0.0216594 0.0108866 0.0201022 0.0083982 0.0138997 0.0087532 0.0196354 0.0194904 0.0121578 0.0186394 0.0153409 0.0097381 0.0131241 0.0086360 0.0146856 0.0188601 0.0097895 0.0199978 0.0204018 0.0130490 0.0152993 0.0101873 0.0162115 0.0039453 0.0144821 0.0113365 0.0119089 0.0057739 0.0167397 0.0065276 0.0069515 0.0118565 0.0068930 0.0103830 0.0083662 0.0081043 0.0129867 0.0085303 0.0128916 0.0137528 0.0164903 0.0161940 0.0146474 0.0161149 0.0189814 0.0175820 0.0083495 0.0125913 0.0150600 0.0155996 0.0167266 0.0145264 0.0129689 0.0141361 0.0089288 0.0105299 0.0078052 0.0144348 0.0173082 0.0089715 0.0180633 0.0169389 0.0108174 0.0126579 0.0133735 0.0200976 0.0192137 0.0144648 0.0154873 0.0158128 0.0091367 0.0174053 0.0153942 0.0099782 0.0074336 0.0132007
2012 0.0011265 0.0149824 0.0116825 0.0133340 0.0154107 0.0141138 0.0159759 0.0160830 0.0150525 0.0145417 0.0133158 0.0171513 0.0151235 0.0173488 0.0056087 0.0118446 0.0147704 0.0084491 0.0156837 0.0188390 0.0088509 0.0236514 0.0140763 0.0081151 0.0058388 0.0144182 0.0062988 0.0130751 0.0153119 0.0118708 0.0070871 0.0243873 0.0149599 0.0065658 0.0126892 0.0187434 0.0111134 0.0136476 0.0083351 0.0141264 0.0098380 0.0181873 0.0143142 0.0133389 0.0110567 0.0179405 0.0120676 0.0134974 0.0093367 0.0141449 0.0212519 0.0099087 0.0201696 0.0182935 0.0128939 0.0129587 0.0087301 0.0144554 0.0041792 0.0124502 0.0086612 0.0085983 0.0051578 0.0162821 0.0061012 0.0064017 0.0094393 0.0078730 0.0100610 0.0082825 0.0090601 0.0170092 0.0096842 0.0171161 0.0156381 0.0169880 0.0168487 0.0153919 0.0166386 0.0179516 0.0176467 0.0122286 0.0153579 0.0244608 0.0176207 0.0139112 0.0144794 0.0139009 0.0154911 0.0101238 0.0114685 0.0076719 0.0184083 0.0196823 0.0078198 0.0148104 0.0134657 0.0129352 0.0119564 0.0135941 0.0170183 0.0173035 0.0127261 0.0157897 0.0174410 0.0092812 0.0162215 0.0161129 0.0114319 0.0075145 0.0154586
2013 0.0011442 0.0151787 0.0124223 0.0117633 0.0191274 0.0151295 0.0153104 0.0181082 0.0154014 0.0130191 0.0116940 0.0154652 0.0140653 0.0284211 0.0057363 0.0117318 0.0159753 0.0079912 0.0166344 0.0163271 0.0083065 0.0202160 0.0174349 0.0075807 0.0058831 0.0143434 0.0065120 0.0122331 0.0162084 0.0149885 0.0084535 0.0180826 0.0143887 0.0068039 0.0153174 0.0210093 0.0117166 0.0161766 0.0089565 0.0155856 0.0118800 0.0172487 0.0140504 0.0114639 0.0112191 0.0153384 0.0115532 0.0133553 0.0092109 0.0187471 0.0168729 0.0098355 0.0208065 0.0180251 0.0115895 0.0115420 0.0096593 0.0137974 0.0040119 0.0120408 0.0098725 0.0103701 0.0053440 0.0155115 0.0062578 0.0058966 0.0107873 0.0103917 0.0095428 0.0087672 0.0087961 0.0141390 0.0105666 0.0136103 0.0142811 0.0195447 0.0221581 0.0149048 0.0214560 0.0166134 0.0157990 0.0098383 0.0126397 0.0176898 0.0152136 0.0151295 0.0155152 0.0132686 0.0140269 0.0098441 0.0101498 0.0075195 0.0150133 0.0177198 0.0079685 0.0154815 0.0120342 0.0125804 0.0149247 0.0143018 0.0155837 0.0150658 0.0119877 0.0189975 0.0147247 0.0098632 0.0147389 0.0245941 0.0128745 0.0068325 0.0135798
2014 0.0011600 0.0146915 0.0122690 0.0144800 0.0184583 0.0182188 0.0153784 0.0149926 0.0149643 0.0122242 0.0147944 0.0136207 0.0164143 0.0387237 0.0063329 0.0151382 0.0146623 0.0078271 0.0153609 0.0209405 0.0087991 0.0183121 0.0174469 0.0080973 0.0059146 0.0168284 0.0058262 0.0127963 0.0261893 0.0153807 0.0083095 0.0193507 0.0174273 0.0064620 0.0125652 0.0155647 0.0134998 0.0282409 0.0079752 0.0268857 0.0081779 0.0238659 0.0132758 0.0114059 0.0109606 0.0156802 0.0116953 0.0150657 0.0092980 0.0143330 0.0169504 0.0116556 0.0193896 0.0177006 0.0122703 0.0228956 0.0102019 0.0170682 0.0044642 0.0119277 0.0102111 0.0106246 0.0052942 0.0167467 0.0074325 0.0059643 0.0100027 0.0073102 0.0088893 0.0083855 0.0101358 0.0153768 0.0111227 0.0170023 0.0146759 0.0158002 0.0152763 0.0145699 0.0207288 0.0176850 0.0156062 0.0085005 0.0129784 0.0174278 0.0170087 0.0156960 0.0148813 0.0133523 0.0133672 0.0113974 0.0102041 0.0072693 0.0175866 0.0176930 0.0080208 0.0182470 0.0173709 0.0126869 0.0127442 0.0140730 0.0151045 0.0140144 0.0143455 0.0183893 0.0156008 0.0129650 0.0183236 0.0230738 0.0156415 0.0069581 0.0138386
2015 0.0011187 0.0140768 0.0107615 0.0136471 0.0183899 0.0136810 0.0140798 0.0174378 0.0124086 0.0114628 0.0124300 0.0198026 0.0160279 0.0193664 0.0061100 0.0133987 0.0146351 0.0074857 0.0179509 0.0138931 0.0099185 0.0167272 0.0259237 0.0079270 0.0061351 0.0164838 0.0058766 0.0115470 0.0166337 0.0143619 0.0072805 0.0160225 0.0174851 0.0066846 0.0146485 0.0226667 0.0116048 0.0179159 0.0076741 0.0220689 0.0115083 0.0174842 0.0131932 0.0122390 0.0111872 0.0147865 0.0093014 0.0141641 0.0089275 0.0171696 0.0135607 0.0112315 0.0217464 0.0214831 0.0123383 0.0135427 0.0113331 0.0132922 0.0040547 0.0112826 0.0099026 0.0099380 0.0047950 0.0140026 0.0059307 0.0060840 0.0090338 0.0068931 0.0097562 0.0079666 0.0081225 0.0142715 0.0094761 0.0176834 0.0129737 0.0148540 0.0185209 0.0147857 0.0169943 0.0182657 0.0216198 0.0081455 0.0122768 0.0155048 0.0165672 0.0172932 0.0150414 0.0127037 0.0148412 0.0101503 0.0122716 0.0079075 0.0154489 0.0152839 0.0079361 0.0144190 0.0146698 0.0139796 0.0113839 0.0129118 0.0177436 0.0171022 0.0124688 0.0191146 0.0158624 0.0100596 0.0150023 0.0218469 0.0125329 0.0070835 0.0133472
2016 0.0011292 0.0135162 0.0139880 0.0132254 0.0246015 0.0134673 0.0140232 0.0156488 0.0138181 0.0122900 0.0115683 0.0163873 0.0161929 0.0197483 0.0058814 0.0154519 0.0173680 0.0080133 0.0310538 0.0221368 0.0094286 0.0171482 0.0195836 0.0080502 0.0060146 0.0184784 0.0066085 0.0118845 0.0212641 0.0145814 0.0076506 0.0148574 0.0144519 0.0064366 0.0137053 0.0165400 0.0127862 0.0159467 0.0087051 0.0170547 0.0119581 0.0165064 0.0149362 0.0155161 0.0109939 0.0123400 0.0132832 0.0118763 0.0087411 0.0164641 0.0180010 0.0132016 0.0203389 0.0173239 0.0117621 0.0166007 0.0100245 0.0152251 0.0043689 0.0134365 0.0108912 0.0090965 0.0052870 0.0127669 0.0055516 0.0057011 0.0102480 0.0065614 0.0100384 0.0087310 0.0093316 0.0178706 0.0102546 0.0147070 0.0149491 0.0149170 0.0164534 0.0139375 0.0160895 0.0215181 0.0169664 0.0110637 0.0127326 0.0192441 0.0159840 0.0137405 0.0166213 0.0151441 0.0135150 0.0096432 0.0111462 0.0073521 0.0148736 0.0170861 0.0079871 0.0173578 0.0140186 0.0126955 0.0142247 0.0143242 0.0157712 0.0175198 0.0139003 0.0189551 0.0154854 0.0097381 0.0167964 0.0298431 0.0141348 0.0068554 0.0160161
2017 0.0010991 0.0123177 0.0123034 0.0132707 0.0168207 0.0150001 0.0139320 0.0187761 0.0133648 0.0129792 0.0136688 0.0214580 0.0149172 0.0172523 0.0058890 0.0139743 0.0129551 0.0081178 0.0223547 0.0202160 0.0078719 0.0151898 0.0193378 0.0076166 0.0058279 0.0194200 0.0060764 0.0104961 0.0162032 0.0151233 0.0071390 0.0163773 0.0153767 0.0066771 0.0137289 0.0181038 0.0101310 0.0143521 0.0104860 0.0242843 0.0083087 0.0311366 0.0198581 0.0137836 0.0152011 0.0169501 0.0107920 0.0121635 0.0096110 0.0174009 0.0190820 0.0096638 0.0174288 0.0167918 0.0124359 0.0150547 0.0091989 0.0129694 0.0041456 0.0121326 0.0098401 0.0092561 0.0052247 0.0178983 0.0053562 0.0063326 0.0089973 0.0065097 0.0098669 0.0074012 0.0088939 0.0138521 0.0163345 0.0141308 0.0153781 0.0145232 0.0149322 0.0143070 0.0179940 0.0151481 0.0175661 0.0083273 0.0118902 0.0131929 0.0170629 0.0143885 0.0136013 0.0137898 0.0134439 0.0101308 0.0108392 0.0072097 0.0181157 0.0165213 0.0078656 0.0146817 0.0128798 0.0125590 0.0145139 0.0144032 0.0147681 0.0149909 0.0128503 0.0160472 0.0179754 0.0092535 0.0158294 0.0210275 0.0115385 0.0082757 0.0129002
2018 0.0011469 0.0137910 0.0124778 0.0143506 0.0159537 0.0130115 0.0177226 0.0153131 0.0123891 0.0128603 0.0113360 0.0156867 0.0149418 0.0253065 0.0058616 0.0154188 0.0193413 0.0070496 0.0174533 0.0205664 0.0092818 0.0178445 0.0177774 0.0079104 0.0061105 0.0191957 0.0066250 0.0121249 0.0188802 0.0150671 0.0069788 0.0245770 0.0210044 0.0064981 0.0139695 0.0169032 0.0113446 0.0141802 0.0087954 0.0178001 0.0109794 0.0190006 0.0175431 0.0136373 0.0124843 0.0202763 0.0109549 0.0161857 0.0095619 0.0199899 0.0173228 0.0102464 0.0204278 0.0178091 0.0124382 0.0139489 0.0104013 0.0128470 0.0042490 0.0135065 0.0096618 0.0119093 0.0060647 0.0175903 0.0057533 0.0079569 0.0084774 0.0083007 0.0106479 0.0082150 0.0079898 0.0183392 0.0108334 0.0174930 0.0148631 0.0138792 0.0158737 0.0153205 0.0207748 0.0163863 0.0197393 0.0086100 0.0135776 0.0164163 0.0184358 0.0158070 0.0132901 0.0146442 0.0142422 0.0101015 0.0115125 0.0076100 0.0151720 0.0155043 0.0084934 0.0171755 0.0125664 0.0118141 0.0118694 0.0138153 0.0140504 0.0143573 0.0140462 0.0160684 0.0171349 0.0142134 0.0160415 0.0256240 0.0157372 0.0070279 0.0131858
Gini standard errors for the five most populous states and their PUMAs with complete data (2005-2018)
YEAR Florida (12) 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261
2005 0.0016341 0.0124953 0.0059409 0.0128422 0.0142351 0.0165227 0.0140057 0.0145948 0.0065609 0.0078546 0.0149164 0.0090730 0.0136468 0.0105818 0.0136474 0.0161554 0.0166100 0.0146255 0.0078011 0.0159171 0.0145107 0.0149842 0.0130817 0.0148290 0.0158688 0.0298637 0.0141304 0.0278129 0.0080042 0.0114750 0.0106374 0.0157276 0.0076406 0.0135781 0.0076016 0.0143009 0.0153078 0.0078953 0.0189828 0.0130559 0.0116061 0.0193102 0.0127475 0.0147887 0.0172537 0.0170658 0.0162630 0.0147171 0.0150759 0.0098317 0.0138100 0.0082948 0.0273454 0.0138819 0.0160374 0.0211969 0.0162404 0.0158257 0.0092973 0.0096405
2006 0.0015906 0.0134263 0.0049428 0.0140714 0.0240762 0.0161901 0.0170064 0.0151082 0.0068364 0.0085196 0.0173296 0.0083834 0.0112849 0.0094080 0.0117496 0.0207521 0.0205388 0.0179924 0.0100137 0.0138853 0.0159602 0.0165699 0.0126648 0.0168322 0.0183594 0.0213828 0.0104073 0.0157520 0.0081989 0.0094829 0.0107600 0.0158735 0.0072297 0.0128812 0.0069070 0.0145489 0.0225056 0.0077966 0.0212023 0.0138841 0.0106022 0.0184968 0.0198534 0.0147757 0.0140873 0.0163691 0.0137001 0.0155577 0.0124230 0.0088909 0.0109748 0.0077295 0.0143043 0.0147398 0.0145973 0.0153508 0.0113046 0.0157465 0.0096094 0.0096803
2007 0.0015849 0.0130440 0.0050453 0.0118064 0.0139540 0.0169913 0.0209045 0.0160421 0.0074272 0.0071218 0.0181710 0.0090769 0.0167268 0.0109689 0.0124894 0.0236868 0.0172482 0.0166319 0.0072956 0.0153279 0.0133802 0.0152757 0.0159881 0.0128632 0.0192964 0.0210797 0.0118305 0.0154506 0.0080491 0.0095103 0.0105866 0.0150424 0.0076243 0.0125453 0.0065298 0.0164700 0.0159644 0.0080399 0.0188256 0.0152181 0.0122203 0.0216352 0.0358648 0.0161579 0.0173586 0.0137698 0.0140281 0.0159689 0.0130728 0.0093877 0.0119041 0.0080168 0.0190045 0.0169122 0.0157353 0.0148479 0.0114384 0.0239719 0.0090589 0.0102509
2008 0.0015254 0.0116658 0.0052320 0.0129061 0.0124361 0.0163187 0.0196194 0.0148908 0.0065069 0.0071753 0.0153929 0.0109847 0.0136436 0.0095768 0.0111777 0.0209776 0.0153548 0.0142463 0.0072327 0.0127734 0.0140462 0.0128496 0.0174799 0.0192524 0.0146201 0.0157942 0.0107465 0.0144888 0.0079408 0.0109144 0.0170210 0.0123705 0.0066444 0.0111447 0.0069885 0.0113876 0.0229186 0.0066596 0.0160774 0.0126585 0.0117390 0.0180768 0.0147199 0.0169250 0.0138758 0.0186622 0.0130210 0.0159759 0.0126743 0.0087848 0.0133426 0.0075057 0.0172427 0.0125159 0.0245501 0.0174324 0.0104701 0.0147598 0.0099113 0.0088473
2009 0.0014901 0.0138440 0.0046910 0.0105931 0.0154197 0.0156230 0.0165695 0.0157465 0.0072833 0.0075629 0.0143703 0.0077921 0.0138355 0.0099483 0.0107638 0.0176706 0.0170797 0.0133235 0.0068825 0.0155718 0.0137554 0.0135820 0.0152964 0.0169218 0.0162410 0.0149997 0.0126957 0.0134579 0.0075296 0.0095886 0.0122070 0.0133487 0.0072857 0.0111663 0.0077099 0.0114456 0.0171946 0.0072847 0.0171667 0.0116812 0.0106706 0.0166722 0.0148889 0.0148694 0.0134325 0.0143125 0.0124497 0.0171431 0.0126250 0.0089327 0.0122814 0.0071594 0.0160743 0.0137514 0.0180248 0.0149028 0.0127926 0.0152246 0.0090382 0.0091067
2010 0.0014865 0.0138245 0.0049843 0.0114372 0.0157974 0.0183650 0.0158902 0.0172443 0.0065580 0.0072325 0.0128478 0.0070700 0.0129045 0.0100678 0.0107776 0.0168640 0.0153834 0.0138937 0.0077238 0.0150164 0.0152394 0.0140315 0.0178909 0.0153118 0.0145072 0.0147684 0.0131884 0.0148304 0.0075992 0.0113705 0.0106979 0.0161696 0.0072420 0.0103694 0.0066611 0.0125527 0.0133470 0.0067634 0.0159343 0.0127263 0.0126300 0.0169345 0.0209372 0.0161239 0.0139104 0.0162679 0.0128592 0.0151777 0.0130583 0.0079704 0.0117589 0.0067597 0.0146680 0.0193874 0.0178707 0.0193598 0.0130145 0.0160881 0.0094055 0.0089385
2011 0.0016499 0.0122076 0.0055486 0.0150531 0.0147367 0.0159369 0.0178982 0.0144621 0.0068400 0.0082180 0.0294757 0.0107620 0.0344552 0.0125291 0.0123519 0.0186429 0.0161314 0.0172411 0.0083617 0.0135696 0.0126181 0.0134020 0.0191906 0.0148343 0.0154813 0.0171902 0.0135559 0.0129872 0.0083250 0.0115207 0.0138505 0.0162229 0.0073337 0.0135690 0.0067962 0.0130350 0.0165632 0.0079760 0.0147302 0.0151484 0.0108820 0.0179517 0.0163387 0.0144771 0.0121162 0.0146458 0.0123839 0.0162798 0.0135540 0.0118804 0.0106999 0.0066496 0.0121342 0.0164124 0.0159719 0.0199779 0.0178495 0.0228622 0.0087081 0.0120791
2012 0.0015956 0.0155357 0.0050119 0.0140960 0.0152938 0.0172373 0.0164689 0.0200285 0.0071687 0.0079996 0.0156371 0.0107112 0.0159451 0.0110659 0.0130348 0.0189949 0.0200319 0.0128184 0.0076049 0.0138570 0.0204471 0.0119955 0.0186221 0.0139680 0.0181135 0.0235854 0.0150994 0.0128703 0.0083039 0.0122290 0.0136554 0.0146144 0.0072923 0.0130553 0.0063653 0.0123390 0.0205872 0.0078630 0.0161898 0.0153895 0.0111480 0.0162301 0.0149516 0.0158472 0.0132064 0.0128911 0.0129678 0.0255783 0.0122173 0.0093902 0.0109687 0.0069607 0.0135622 0.0140321 0.0154416 0.0226442 0.0139004 0.0248417 0.0095314 0.0093742
2013 0.0015789 0.0134597 0.0047280 0.0141927 0.0144325 0.0136766 0.0134698 0.0159898 0.0071874 0.0086009 0.0147284 0.0097694 0.0221755 0.0103982 0.0132709 0.0167956 0.0232939 0.0223427 0.0071649 0.0125716 0.0113887 0.0126300 0.0153035 0.0158890 0.0206466 0.0189305 0.0117585 0.0127884 0.0077419 0.0124129 0.0107706 0.0143374 0.0076929 0.0098252 0.0072039 0.0140836 0.0156599 0.0077982 0.0160695 0.0164659 0.0106753 0.0168625 0.0176400 0.0183958 0.0144610 0.0132806 0.0136778 0.0162240 0.0114119 0.0079749 0.0134265 0.0076058 0.0139304 0.0161401 0.0178674 0.0169286 0.0160970 0.0174296 0.0095696 0.0097195
2014 0.0015471 0.0129251 0.0051327 0.0141346 0.0163254 0.0225494 0.0169715 0.0178268 0.0075338 0.0072186 0.0142111 0.0120563 0.0179484 0.0093912 0.0112316 0.0146189 0.0199715 0.0137640 0.0074140 0.0150685 0.0147917 0.0135422 0.0148751 0.0144393 0.0158779 0.0160086 0.0111837 0.0137104 0.0074430 0.0100229 0.0132204 0.0164520 0.0067938 0.0106208 0.0066563 0.0140710 0.0276505 0.0080903 0.0165131 0.0137135 0.0104819 0.0154836 0.0213077 0.0206511 0.0151543 0.0149561 0.0130557 0.0184603 0.0126605 0.0080660 0.0127709 0.0073563 0.0119882 0.0195440 0.0173732 0.0145528 0.0138631 0.0178245 0.0095997 0.0109542
2015 0.0016633 0.0128693 0.0054156 0.0146455 0.0172876 0.0189466 0.0158145 0.0178687 0.0071882 0.0085482 0.0170776 0.0095190 0.0196200 0.0096466 0.0134859 0.0241231 0.0202101 0.0137003 0.0075303 0.0171051 0.0144836 0.0128185 0.0147321 0.0178566 0.0154467 0.0146748 0.0142649 0.0118533 0.0079053 0.0100465 0.0123616 0.0166944 0.0084158 0.0098988 0.0071106 0.0136492 0.0237349 0.0121889 0.0181884 0.0152029 0.0102410 0.0217043 0.0143316 0.0177028 0.0129822 0.0138901 0.0145936 0.0153601 0.0130461 0.0083625 0.0116390 0.0069330 0.0195220 0.0124296 0.0190887 0.0162989 0.0156928 0.0178580 0.0095257 0.0090077
2016 0.0015543 0.0149351 0.0050244 0.0119249 0.0143417 0.0141943 0.0182308 0.0188902 0.0073242 0.0083173 0.0160879 0.0090920 0.0139638 0.0094728 0.0153346 0.0176578 0.0188681 0.0148562 0.0071131 0.0122838 0.0150604 0.0121460 0.0155480 0.0143444 0.0156370 0.0154560 0.0116279 0.0120591 0.0077745 0.0107695 0.0160260 0.0163799 0.0074247 0.0105524 0.0063434 0.0132593 0.0190831 0.0087709 0.0160992 0.0131074 0.0118845 0.0150925 0.0167910 0.0194579 0.0174133 0.0167557 0.0130652 0.0159180 0.0128224 0.0096983 0.0116879 0.0063311 0.0156618 0.0204220 0.0170726 0.0135567 0.0154899 0.0149021 0.0097869 0.0099112
2017 0.0015809 0.0144891 0.0057884 0.0127800 0.0149635 0.0179731 0.0174961 0.0167550 0.0068607 0.0103879 0.0144813 0.0092303 0.0173863 0.0087934 0.0110566 0.0194364 0.0159840 0.0137526 0.0065891 0.0136944 0.0127343 0.0140636 0.0151445 0.0144592 0.0171429 0.0155592 0.0133655 0.0110256 0.0089470 0.0105941 0.0124260 0.0172775 0.0071252 0.0095447 0.0065204 0.0127030 0.0155635 0.0080248 0.0165350 0.0146696 0.0106745 0.0191365 0.0197810 0.0160388 0.0144589 0.0168710 0.0126302 0.0178164 0.0136196 0.0079471 0.0115685 0.0068274 0.0158048 0.0164466 0.0169841 0.0158052 0.0132261 0.0159329 0.0090840 0.0108240
2018 0.0015908 0.0136409 0.0053086 0.0119962 0.0122951 0.0165051 0.0208668 0.0168476 0.0076328 0.0089074 0.0174427 0.0111554 0.0137969 0.0108349 0.0153614 0.0166445 0.0164834 0.0145481 0.0067843 0.0177204 0.0189611 0.0125593 0.0143930 0.0167119 0.0170327 0.0154245 0.0129220 0.0119129 0.0084698 0.0109207 0.0148290 0.0140675 0.0070209 0.0106057 0.0068669 0.0133372 0.0165831 0.0084531 0.0172024 0.0143843 0.0101253 0.0173676 0.0232324 0.0166431 0.0146353 0.0144619 0.0144919 0.0190884 0.0119506 0.0081548 0.0121113 0.0067933 0.0150642 0.0130779 0.0178000 0.0267053 0.0152550 0.0234287 0.0091880 0.0094101
Gini standard errors for the five most populous states and their PUMAs with complete data (2005-2018)
YEAR New York (36) 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755
2005 0.0020670 0.0161731 0.0121643 0.0214713 0.0064505 0.0223748 0.0149806 0.0144182 0.0091554 0.0164633 0.0177174 0.0155391 0.0321598 0.0182375 0.0210540 0.0138642 0.0311862 0.0187744 0.0218283 0.0241198 0.0122873 0.0133256 0.0133700 0.0209450 0.0079814 0.0148010 0.0183896 0.0247418 0.0223465 0.0131104 0.0216615 0.0178722 0.0261981 0.0171896 0.0108697 0.0142006 0.0134123 0.0158407 0.0149117 0.0172554 0.0303760 0.0229142 0.0124504 0.0139026 0.0155029 0.0213180 0.0183299 0.0193089 0.0162881 0.0136873 0.0116439 0.0176023 0.0188331 0.0172148 0.0145928 0.0190325 0.0198354 0.0181760 0.0201984 0.0203787 0.0209201 0.0174988 0.0203006 0.0191004 0.0139564 0.0186085 0.0197294 0.0183705 0.0170475 0.0162025 0.0191570 0.0139038 0.0383326 0.0163557 0.0212831 0.0170844 0.0161007 0.0158048 0.0181393 0.0164447 0.0223158 0.0234667 0.0228146 0.0272047 0.0111004 0.0123096 0.0151427 0.0132235 0.0152433 0.0138511 0.0556374 0.0199022 0.0222268 0.0169242 0.0238919 0.0146407 0.0211511 0.0186201 0.0218679 0.0201653 0.0170753 0.0113253 0.0177695 0.0471473 0.0179333 0.0484542 0.0147806 0.0203283 0.0155416 0.0146268 0.0223290 0.0121748 0.0143638 0.0117201 0.0162348 0.0125307 0.0147498 0.0165230 0.0160557 0.0162442 0.0166882 0.0133328 0.0181597 0.0188186
2006 0.0017836 0.0133105 0.0126963 0.0121799 0.0056732 0.0128865 0.0128617 0.0192405 0.0085247 0.0194073 0.0214288 0.0178261 0.0218086 0.0146698 0.0133973 0.0165100 0.0224227 0.0185260 0.0171423 0.0219887 0.0103805 0.0141519 0.0170704 0.0172177 0.0107291 0.0210743 0.0314342 0.0170191 0.0120964 0.0122517 0.0197336 0.0117741 0.0214656 0.0172082 0.0168556 0.0149958 0.0125745 0.0203075 0.0137239 0.0156932 0.0160762 0.0227288 0.0109344 0.0110937 0.0157570 0.0146219 0.0133488 0.0233737 0.0139046 0.0160935 0.0103691 0.0292026 0.0226249 0.0198392 0.0202680 0.0160238 0.0198589 0.0236310 0.0206717 0.0137703 0.0169610 0.0182756 0.0169727 0.0189445 0.0128180 0.0198767 0.0183600 0.0210218 0.0292503 0.0187400 0.0235504 0.0141279 0.0147723 0.0152524 0.0158729 0.0159647 0.0194226 0.0165176 0.0204683 0.0161458 0.0139257 0.0226606 0.0206507 0.0262298 0.0107873 0.0109559 0.0139613 0.0143093 0.0159311 0.0149718 0.0173024 0.0270698 0.0163671 0.0152428 0.0139846 0.0228078 0.0200600 0.0179317 0.0182849 0.0157760 0.0144814 0.0130909 0.0204157 0.0194729 0.0174835 0.0197170 0.0233823 0.0206956 0.0187283 0.0133593 0.0141329 0.0138545 0.0139974 0.0106824 0.0196513 0.0142849 0.0113885 0.0162694 0.0165656 0.0185633 0.0117561 0.0126269 0.0149671 0.0210101
2007 0.0018176 0.0178110 0.0155539 0.0177216 0.0055292 0.0159703 0.0114532 0.0127887 0.0124701 0.0197992 0.0199178 0.0132664 0.0203481 0.0163025 0.0168781 0.0140200 0.0152750 0.0200049 0.0192564 0.0178255 0.0193554 0.0165889 0.0187292 0.0138014 0.0100102 0.0156124 0.0162982 0.0188478 0.0232742 0.0132711 0.0145751 0.0207499 0.0191592 0.0242813 0.0115969 0.0142268 0.0162113 0.0145708 0.0178919 0.0236182 0.0213679 0.0176726 0.0127846 0.0135358 0.0158653 0.0162975 0.0148817 0.0181833 0.0155489 0.0144510 0.0105490 0.0189432 0.0239475 0.0160823 0.0260911 0.0161244 0.0199805 0.0165847 0.0193257 0.0122254 0.0213440 0.0168714 0.0156959 0.0172282 0.0150172 0.0175416 0.0168529 0.0282194 0.0235131 0.0193753 0.0188225 0.0146215 0.0178351 0.0177767 0.0131599 0.0233453 0.0156154 0.0156223 0.0128967 0.0139008 0.0155677 0.0233429 0.0235193 0.0246965 0.0099134 0.0101872 0.0155945 0.0138229 0.0167098 0.0131638 0.0125928 0.0203625 0.0185416 0.0196394 0.0225693 0.0273695 0.0198507 0.0167037 0.0167708 0.0161851 0.0181746 0.0126937 0.0172015 0.0261073 0.0186278 0.0186976 0.0210426 0.0164886 0.0205648 0.0159769 0.0158601 0.0179710 0.0145248 0.0138645 0.0184385 0.0126255 0.0114967 0.0166584 0.0143382 0.0201939 0.0121111 0.0128132 0.0179762 0.0180677
2008 0.0018963 0.0145677 0.0122108 0.0200207 0.0059146 0.0388645 0.0170452 0.0180956 0.0102222 0.0213069 0.0168144 0.0158875 0.0232951 0.0170458 0.0145551 0.0133535 0.0177987 0.0172271 0.0177944 0.0192891 0.0098822 0.0169722 0.0162943 0.0213379 0.0098475 0.0227281 0.0130717 0.0176854 0.0144059 0.0126241 0.0163136 0.0148684 0.0174668 0.0266496 0.0100592 0.0130684 0.0143893 0.0186322 0.0159844 0.0177502 0.0215654 0.0178491 0.0120430 0.0154158 0.0169954 0.0163279 0.0140252 0.0219853 0.0149294 0.0142883 0.0098644 0.0209132 0.0205174 0.0151135 0.0172710 0.0249886 0.0190884 0.0177437 0.0187737 0.0143080 0.0196359 0.0193136 0.0173545 0.0194474 0.0112568 0.0161303 0.0166933 0.0210406 0.0164132 0.0192394 0.0285649 0.0140990 0.0161670 0.0141693 0.0160097 0.0219125 0.0167609 0.0162293 0.0138038 0.0175661 0.0175619 0.0241800 0.0288209 0.0326155 0.0103309 0.0116211 0.0132699 0.0135576 0.0192003 0.0136387 0.0139071 0.0159471 0.0136790 0.0209835 0.0192509 0.0189800 0.0240224 0.0202535 0.0184905 0.0172995 0.0243045 0.0151443 0.0231631 0.0166006 0.0144070 0.0181735 0.0171336 0.0180669 0.0155925 0.0128694 0.0184303 0.0185989 0.0206524 0.0153523 0.0197885 0.0115370 0.0126875 0.0175497 0.0224126 0.0192054 0.0134605 0.0118216 0.0176488 0.0184359
2009 0.0018881 0.0164704 0.0117798 0.0163658 0.0054818 0.0123273 0.0141152 0.0145098 0.0099637 0.0196881 0.0242188 0.0164914 0.0173866 0.0153258 0.0211108 0.0364109 0.0157895 0.0178148 0.0195899 0.0182115 0.0122914 0.0126675 0.0155173 0.0157439 0.0098048 0.0164661 0.0137172 0.0192834 0.0192904 0.0131084 0.0171653 0.0149943 0.0277484 0.0149983 0.0131673 0.0121487 0.0119900 0.0133989 0.0159186 0.0173019 0.0174420 0.0176439 0.0128212 0.0153025 0.0157236 0.0143817 0.0135622 0.0169026 0.0156604 0.0127228 0.0106239 0.0191757 0.0173287 0.0156854 0.0155559 0.0213106 0.0186876 0.0199278 0.0179663 0.0130527 0.0157394 0.0167455 0.0191595 0.0191889 0.0132255 0.0154090 0.0157848 0.0258662 0.0165854 0.0172138 0.0332560 0.0138671 0.0181332 0.0156890 0.0173253 0.0177152 0.0213270 0.0152334 0.0135155 0.0144681 0.0167954 0.0212390 0.0229635 0.0335094 0.0102402 0.0106336 0.0154183 0.0138263 0.0167722 0.0164421 0.0150383 0.0183256 0.0178026 0.0234656 0.0203709 0.0151538 0.0163195 0.0187075 0.0208504 0.0264067 0.0173580 0.0128906 0.0148653 0.0163681 0.0170934 0.0158339 0.0181031 0.0151026 0.0144242 0.0112160 0.0153647 0.0133758 0.0135501 0.0131050 0.0164199 0.0120369 0.0129608 0.0162940 0.0273469 0.0165940 0.0132888 0.0136242 0.0150656 0.0170491
2010 0.0017068 0.0298197 0.0129566 0.0157757 0.0050337 0.0154303 0.0130069 0.0217572 0.0102405 0.0158276 0.0146724 0.0121507 0.0197965 0.0192935 0.0209300 0.0167425 0.0209116 0.0156975 0.0207876 0.0154869 0.0133512 0.0146863 0.0141544 0.0168153 0.0121504 0.0164059 0.0132929 0.0172786 0.0158806 0.0138445 0.0157280 0.0130249 0.0158501 0.0166832 0.0134684 0.0127909 0.0111010 0.0191990 0.0195194 0.0189320 0.0138131 0.0176758 0.0107342 0.0133447 0.0164450 0.0156944 0.0125689 0.0138285 0.0134626 0.0126080 0.0101072 0.0170001 0.0184184 0.0222170 0.0208966 0.0181618 0.0163495 0.0183351 0.0187660 0.0141950 0.0170246 0.0225656 0.0172557 0.0176162 0.0133610 0.0190346 0.0176072 0.0208682 0.0160562 0.0162495 0.0188831 0.0147502 0.0176767 0.0159070 0.0136060 0.0226927 0.0140894 0.0176350 0.0151990 0.0209363 0.0179737 0.0194683 0.0193889 0.0233505 0.0101891 0.0113666 0.0123611 0.0124522 0.0200602 0.0131101 0.0211990 0.0165844 0.0157961 0.0127572 0.0156158 0.0159196 0.0171976 0.0199796 0.0173745 0.0217201 0.0285399 0.0150280 0.0143962 0.0173200 0.0234951 0.0162514 0.0176840 0.0141946 0.0166110 0.0188692 0.0166903 0.0122349 0.0185361 0.0133715 0.0151953 0.0156828 0.0117900 0.0294599 0.0261987 0.0195276 0.0141825 0.0129592 0.0163047 0.0185749
2011 0.0019164 0.0140134 0.0166227 0.0143363 0.0052844 0.0134029 0.0168974 0.0128880 0.0112419 0.0175372 0.0301080 0.0252235 0.0166095 0.0193399 0.0161668 0.0170327 0.0229013 0.0162390 0.0172850 0.0159129 0.0113900 0.0127554 0.0133912 0.0129677 0.0132941 0.0138306 0.0150158 0.0230066 0.0169656 0.0170627 0.0169432 0.0135413 0.0204161 0.0133614 0.0130327 0.0127057 0.0124763 0.0183687 0.0143040 0.0255233 0.0231400 0.0188326 0.0108112 0.0127323 0.0153385 0.0149905 0.0121570 0.0124830 0.0131338 0.0148853 0.0095979 0.0169239 0.0195261 0.0214915 0.0145235 0.0247242 0.0190026 0.0201698 0.0189198 0.0121877 0.0214295 0.0206310 0.0152745 0.0169683 0.0140381 0.0166458 0.0174349 0.0254926 0.0158453 0.0138040 0.0252312 0.0155575 0.0186988 0.0154025 0.0147257 0.0160486 0.0149973 0.0168870 0.0138392 0.0200359 0.0203156 0.0241101 0.0195894 0.0222592 0.0127379 0.0168409 0.0147087 0.0188096 0.0187140 0.0157815 0.0172956 0.0164608 0.0134741 0.0185631 0.0236864 0.0198231 0.0166819 0.0170651 0.0183828 0.0166776 0.0228612 0.0120438 0.0176515 0.0248079 0.0163310 0.0177293 0.0140606 0.0179787 0.0180421 0.0290263 0.0147911 0.0140810 0.0192727 0.0155962 0.0211441 0.0118280 0.0154857 0.0181382 0.0158270 0.0175595 0.0150592 0.0125159 0.0236032 0.0210650
2012 0.0018272 0.0194630 0.0136462 0.0139165 0.0058571 0.0124627 0.0170971 0.0130210 0.0107105 0.0206124 0.0180192 0.0207347 0.0148290 0.0160351 0.0138579 0.0225667 0.0181017 0.0214591 0.0267701 0.0263126 0.0096611 0.0132412 0.0148827 0.0122929 0.0108224 0.0201482 0.0174376 0.0235262 0.0170835 0.0147555 0.0176455 0.0153866 0.0214053 0.0176271 0.0105515 0.0238032 0.0163295 0.0173164 0.0185386 0.0160682 0.0194433 0.0191133 0.0108079 0.0123638 0.0150822 0.0168186 0.0134515 0.0148180 0.0126585 0.0150863 0.0102524 0.0171525 0.0166875 0.0183180 0.0140418 0.0177036 0.0190367 0.0169930 0.0171500 0.0122577 0.0177446 0.0185527 0.0159402 0.0225073 0.0133565 0.0180375 0.0160359 0.0207969 0.0159234 0.0150656 0.0213971 0.0143810 0.0194675 0.0172838 0.0152453 0.0152949 0.0164391 0.0187638 0.0151748 0.0162184 0.0160128 0.0284752 0.0225127 0.0217750 0.0145574 0.0159215 0.0154951 0.0197223 0.0202935 0.0134254 0.0151804 0.0184796 0.0232326 0.0146916 0.0147699 0.0167475 0.0151818 0.0183564 0.0200107 0.0254839 0.0150735 0.0115169 0.0132894 0.0176459 0.0191910 0.0142200 0.0169994 0.0205811 0.0165242 0.0127733 0.0178994 0.0136812 0.0140651 0.0121099 0.0149646 0.0146400 0.0109100 0.0177340 0.0175814 0.0189778 0.0123056 0.0141723 0.0153174 0.0232028
2013 0.0020184 0.0248648 0.0195886 0.0181225 0.0056264 0.0154207 0.0167807 0.0158676 0.0120778 0.0154135 0.0147087 0.0306826 0.0165830 0.0163506 0.0236167 0.0182007 0.0230355 0.0183740 0.0178472 0.0199312 0.0111390 0.0125017 0.0165098 0.0163435 0.0161022 0.0204975 0.0142237 0.0209686 0.0154148 0.0129757 0.0152467 0.0155131 0.0204856 0.0225808 0.0148066 0.0144075 0.0122518 0.0149855 0.0157919 0.0174821 0.0215020 0.0303917 0.0115877 0.0124316 0.0166217 0.0155339 0.0141578 0.0156298 0.0155135 0.0150010 0.0142320 0.0185694 0.0174141 0.0164452 0.0175378 0.0192773 0.0191671 0.0218088 0.0226314 0.0175352 0.0165059 0.0169429 0.0160859 0.0180336 0.0149077 0.0173369 0.0200937 0.0155508 0.0227826 0.0202657 0.0344428 0.0146928 0.0254509 0.0156585 0.0144125 0.0311540 0.0153980 0.0138382 0.0144787 0.0169963 0.0145966 0.0241504 0.0234971 0.0264924 0.0135106 0.0156685 0.0151734 0.0327888 0.0160960 0.0123988 0.0160450 0.0206741 0.0165973 0.0172905 0.0171626 0.0183649 0.0158383 0.0201835 0.0184031 0.0203090 0.0202561 0.0151428 0.0139412 0.0251585 0.0204326 0.0144804 0.0149199 0.0164365 0.0172767 0.0162550 0.0288167 0.0135497 0.0349291 0.0167164 0.0170091 0.0156208 0.0108784 0.0221193 0.0172276 0.0170259 0.0180402 0.0118343 0.0240334 0.0296208
2014 0.0018606 0.0174487 0.0126332 0.0368492 0.0066336 0.0187851 0.0133519 0.0162365 0.0109183 0.0179245 0.0384971 0.0148019 0.0190165 0.0163964 0.0164411 0.0165087 0.0201865 0.0211353 0.0191500 0.0169050 0.0208208 0.0130561 0.0201932 0.0158432 0.0137252 0.0251030 0.0183152 0.0200545 0.0171440 0.0229892 0.0189307 0.0199175 0.0206909 0.0173692 0.0194756 0.0185587 0.0218313 0.0143319 0.0165006 0.0176981 0.0191404 0.0206193 0.0129281 0.0136746 0.0144359 0.0168093 0.0145721 0.0144851 0.0137256 0.0123909 0.0110516 0.0192427 0.0218912 0.0181208 0.0169400 0.0237492 0.0201065 0.0231337 0.0194601 0.0119033 0.0162216 0.0172970 0.0173384 0.0206387 0.0146217 0.0164729 0.0169540 0.0196345 0.0187895 0.0162129 0.0246443 0.0150957 0.0204853 0.0143657 0.0153874 0.0180909 0.0153712 0.0154055 0.0142529 0.0177176 0.0191416 0.0243764 0.0181589 0.0224744 0.0150885 0.0154656 0.0162124 0.0197584 0.0184806 0.0143392 0.0188115 0.0199844 0.0171625 0.0134483 0.0164582 0.0142956 0.0185909 0.0165162 0.0161263 0.0160401 0.0150498 0.0124083 0.0175872 0.0272313 0.0172610 0.0146296 0.0150163 0.0200566 0.0143774 0.0162469 0.0181822 0.0155327 0.0174741 0.0115189 0.0172922 0.0128267 0.0107892 0.0206352 0.0206873 0.0205700 0.0166453 0.0104733 0.0332046 0.0274901
2015 0.0019800 0.0175567 0.0145814 0.0213266 0.0062891 0.0162082 0.0135997 0.0227305 0.0119545 0.0191317 0.0190811 0.0163183 0.0136947 0.0187347 0.0154204 0.0139237 0.0211995 0.0207269 0.0211158 0.0213190 0.0147078 0.0146155 0.0152098 0.0174367 0.0167097 0.0153003 0.0184557 0.0197580 0.0166978 0.0170033 0.0203306 0.0197151 0.0198764 0.0195997 0.0103109 0.0120018 0.0136846 0.0163070 0.0166184 0.0243140 0.0152637 0.0286901 0.0125310 0.0132557 0.0171474 0.0176867 0.0142638 0.0163306 0.0138370 0.0134588 0.0104171 0.0151932 0.0189526 0.0205249 0.0151083 0.0194099 0.0181278 0.0198761 0.0226958 0.0122132 0.0176790 0.0205079 0.0167418 0.0180501 0.0133549 0.0203829 0.0241475 0.0217316 0.0234107 0.0191052 0.0226521 0.0152086 0.0229007 0.0216332 0.0160847 0.0266478 0.0166366 0.0274327 0.0187867 0.0234830 0.0126816 0.0225901 0.0191573 0.0217177 0.0132401 0.0158182 0.0168694 0.0253595 0.0143062 0.0132667 0.0142541 0.0190045 0.0168220 0.0164356 0.0187590 0.0210565 0.0153516 0.0183897 0.0162744 0.0199352 0.0156917 0.0155980 0.0139153 0.0226772 0.0239589 0.0162546 0.0163307 0.0152695 0.0155162 0.0148457 0.0169921 0.0179790 0.0164487 0.0130553 0.0157326 0.0110936 0.0111049 0.0191489 0.0246577 0.0190065 0.0188051 0.0115969 0.0162089 0.0190055
2016 0.0018836 0.0196946 0.0167830 0.0142223 0.0064003 0.0160442 0.0152700 0.0204674 0.0102087 0.0167282 0.0262619 0.0115578 0.0191541 0.0167891 0.0153816 0.0171752 0.0195951 0.0150645 0.0200915 0.0212392 0.0115388 0.0136574 0.0206543 0.0150975 0.0099506 0.0210910 0.0150116 0.0179548 0.0180312 0.0140989 0.0205677 0.0139610 0.0169151 0.0157806 0.0114181 0.0114462 0.0127497 0.0165839 0.0165259 0.0169695 0.0234811 0.0163332 0.0111086 0.0125778 0.0138459 0.0132392 0.0133137 0.0177866 0.0135395 0.0137289 0.0093641 0.0157353 0.0186747 0.0162953 0.0179346 0.0192564 0.0177885 0.0187331 0.0190677 0.0138022 0.0166050 0.0223305 0.0194962 0.0184319 0.0152830 0.0180699 0.0258604 0.0188134 0.0200946 0.0216455 0.0217688 0.0169541 0.0176126 0.0169102 0.0133926 0.0239139 0.0153528 0.0185429 0.0141947 0.0227351 0.0155143 0.0257278 0.0247860 0.0272350 0.0140523 0.0126128 0.0171493 0.0176219 0.0196621 0.0130227 0.0168606 0.0214681 0.0167428 0.0143404 0.0177096 0.0193779 0.0173558 0.0152528 0.0225899 0.0316709 0.0184340 0.0119189 0.0214520 0.0198478 0.0165262 0.0135157 0.0184907 0.0146659 0.0142120 0.0137986 0.0142288 0.0153636 0.0166900 0.0119936 0.0213908 0.0118452 0.0128473 0.0214489 0.0169621 0.0163393 0.0111158 0.0122864 0.0219587 0.0172603
2017 0.0018453 0.0181880 0.0189387 0.0157781 0.0064242 0.0150502 0.0171453 0.0188392 0.0099350 0.0173480 0.0315282 0.0190025 0.0167713 0.0171310 0.0193409 0.0181427 0.0201384 0.0190069 0.0198419 0.0230713 0.0139650 0.0123042 0.0133420 0.0130474 0.0127354 0.0141872 0.0201948 0.0194365 0.0198306 0.0149871 0.0192901 0.0143214 0.0202948 0.0224990 0.0185243 0.0135326 0.0140307 0.0150572 0.0180517 0.0209387 0.0159886 0.0187857 0.0125648 0.0122986 0.0158986 0.0136498 0.0126339 0.0140243 0.0130785 0.0141034 0.0101701 0.0170798 0.0239673 0.0174539 0.0174689 0.0159316 0.0192221 0.0160346 0.0191978 0.0145635 0.0184420 0.0165089 0.0196015 0.0233686 0.0150138 0.0163335 0.0237822 0.0174225 0.0203458 0.0191222 0.0214854 0.0200497 0.0333082 0.0157768 0.0228031 0.0170078 0.0228939 0.0191427 0.0134849 0.0144512 0.0135383 0.0203602 0.0256104 0.0255129 0.0130561 0.0151010 0.0175019 0.0181728 0.0160692 0.0145602 0.0181656 0.0199084 0.0179320 0.0151744 0.0175430 0.0164211 0.0162343 0.0173190 0.0223001 0.0172437 0.0168982 0.0138989 0.0178868 0.0242438 0.0212696 0.0160260 0.0175847 0.0163205 0.0155250 0.0138907 0.0231183 0.0134335 0.0169795 0.0179295 0.0188716 0.0175076 0.0116513 0.0275630 0.0158968 0.0155638 0.0144154 0.0130608 0.0237875 0.0208151
2018 0.0018203 0.0138738 0.0153167 0.0198062 0.0060670 0.0147451 0.0160230 0.0141737 0.0108633 0.0166248 0.0176833 0.0165586 0.0178164 0.0145937 0.0205783 0.0258561 0.0238199 0.0188266 0.0225767 0.0158492 0.0164105 0.0135319 0.0126448 0.0182816 0.0115635 0.0313536 0.0142732 0.0168300 0.0286952 0.0138433 0.0262866 0.0137313 0.0185549 0.0289090 0.0117052 0.0157383 0.0124964 0.0181355 0.0143343 0.0179853 0.0167286 0.0177028 0.0129251 0.0115203 0.0180895 0.0147850 0.0132889 0.0140845 0.0148076 0.0132308 0.0106760 0.0188417 0.0197552 0.0213263 0.0176746 0.0175219 0.0196401 0.0199235 0.0203411 0.0129653 0.0229449 0.0179962 0.0184565 0.0160138 0.0146665 0.0170909 0.0215947 0.0300334 0.0169069 0.0202355 0.0206466 0.0226918 0.0184451 0.0155559 0.0234197 0.0207126 0.0146110 0.0170458 0.0235550 0.0151331 0.0150349 0.0234127 0.0207097 0.0186131 0.0122074 0.0152877 0.0143937 0.0188286 0.0230298 0.0136316 0.0194448 0.0162981 0.0174546 0.0183601 0.0190809 0.0187587 0.0156767 0.0182353 0.0159320 0.0223281 0.0174714 0.0116555 0.0264200 0.0257446 0.0217521 0.0149332 0.0170019 0.0173319 0.0160427 0.0108632 0.0160432 0.0123576 0.0167955 0.0142495 0.0146391 0.0149241 0.0107783 0.0173894 0.0181132 0.0160079 0.0206038 0.0119347 0.0162819 0.0200100
Gini standard errors for the five most populous states and their PUMAs with complete data (2005-2018)
YEAR Pennsylvania (42) 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908
2005 0.0020278 0.0157429 0.0146396 0.0118010 0.0161626 0.0138092 0.0212231 0.0213315 0.0138391 0.0099873 0.0101476 0.0134801 0.0188296 0.0172786 0.0154405 0.0180477 0.0132321 0.0138956 0.0091681 0.0106482 0.0119087 0.0134793 0.0171910 0.0168944 0.0181710 0.0127583 0.0158584 0.0186185 0.0141609 0.0194747 0.0347526 0.0175199 0.0213998 0.0095097 0.0297539 0.0089961 0.0067408 0.0176342 0.0114210 0.0192312 0.0184496 0.0277919 0.0215439 0.0182736 0.0236593 0.0243881 0.0174471 0.0110753 0.0081322 0.0121233 0.0102460 0.0197946 0.0138347 0.0184188 0.0133285 0.0126324
2006 0.0018820 0.0151151 0.0146525 0.0099576 0.0172773 0.0218894 0.0179906 0.0147508 0.0142456 0.0102616 0.0104806 0.0137445 0.0190590 0.0169507 0.0177913 0.0153269 0.0127817 0.0164675 0.0077126 0.0118116 0.0160004 0.0104843 0.0160457 0.0128722 0.0184293 0.0094885 0.0139500 0.0165512 0.0109706 0.0157062 0.0120666 0.0117331 0.0176610 0.0085295 0.0226002 0.0085449 0.0068962 0.0165945 0.0108637 0.0162224 0.0183565 0.0239265 0.0178424 0.0174499 0.0202002 0.0209555 0.0154807 0.0089388 0.0078558 0.0090860 0.0107972 0.0142009 0.0138852 0.0216980 0.0139000 0.0119798
2007 0.0020100 0.0148680 0.0132534 0.0108241 0.0145046 0.0145295 0.0220509 0.0176038 0.0137194 0.0098813 0.0099967 0.0238844 0.0184530 0.0159568 0.0144649 0.0162240 0.0138276 0.0203107 0.0092782 0.0114792 0.0202842 0.0116984 0.0175985 0.0140986 0.0207946 0.0091518 0.0119753 0.0202416 0.0160201 0.0160592 0.0154747 0.0106594 0.0148973 0.0092608 0.0267972 0.0083499 0.0073541 0.0200087 0.0124334 0.0195306 0.0183981 0.0184799 0.0175783 0.0168920 0.0227086 0.0184312 0.0176981 0.0102071 0.0088317 0.0097750 0.0123239 0.0174957 0.0158778 0.0215211 0.0122023 0.0144284
2008 0.0019164 0.0115301 0.0104312 0.0106408 0.0157079 0.0136711 0.0134906 0.0206226 0.0168218 0.0115922 0.0109296 0.0146815 0.0180331 0.0150613 0.0204716 0.0142830 0.0137911 0.0162604 0.0091837 0.0111154 0.0136794 0.0196608 0.0209549 0.0184584 0.0183687 0.0088704 0.0143103 0.0150820 0.0135282 0.0144528 0.0170820 0.0112470 0.0173044 0.0085375 0.0195190 0.0079152 0.0071638 0.0144562 0.0105320 0.0160048 0.0190478 0.0247033 0.0211077 0.0186200 0.0191685 0.0169750 0.0142688 0.0116203 0.0079621 0.0103364 0.0111786 0.0174376 0.0138240 0.0170703 0.0141141 0.0107179
2009 0.0019900 0.0113524 0.0166067 0.0109162 0.0112860 0.0133147 0.0224203 0.0188414 0.0168831 0.0125745 0.0117409 0.0222566 0.0182268 0.0156194 0.0135721 0.0132005 0.0135732 0.0145997 0.0086406 0.0114021 0.0127952 0.0146991 0.0185203 0.0139181 0.0153476 0.0116036 0.0119421 0.0155671 0.0131020 0.0182118 0.0154041 0.0094204 0.0155851 0.0090783 0.0304435 0.0087082 0.0081245 0.0146357 0.0104580 0.0170605 0.0234086 0.0234243 0.0184392 0.0180539 0.0203526 0.0215623 0.0135970 0.0094252 0.0080398 0.0098091 0.0106578 0.0224332 0.0204471 0.0156744 0.0159856 0.0104933
2010 0.0018823 0.0116734 0.0186489 0.0083721 0.0144671 0.0144403 0.0160859 0.0248337 0.0138514 0.0102187 0.0108052 0.0142147 0.0144067 0.0146852 0.0133720 0.0136381 0.0102211 0.0169657 0.0084406 0.0114682 0.0139908 0.0150469 0.0189612 0.0133604 0.0162694 0.0103660 0.0134174 0.0143057 0.0124806 0.0167102 0.0142172 0.0111780 0.0165444 0.0096557 0.0188550 0.0088462 0.0066434 0.0153805 0.0115956 0.0230502 0.0178121 0.0195032 0.0192792 0.0163842 0.0212690 0.0192608 0.0136478 0.0089319 0.0086671 0.0088277 0.0110001 0.0145680 0.0126010 0.0150791 0.0188018 0.0131431
2011 0.0019788 0.0201408 0.0158940 0.0091413 0.0148027 0.0135266 0.0261986 0.0157071 0.0168287 0.0097557 0.0127182 0.0168651 0.0184394 0.0279146 0.0253394 0.0201307 0.0152804 0.0148104 0.0072261 0.0106307 0.0115923 0.0131565 0.0216129 0.0134868 0.0169572 0.0089247 0.0134669 0.0189276 0.0149649 0.0215619 0.0145529 0.0123813 0.0210071 0.0107844 0.0149761 0.0080311 0.0067499 0.0177142 0.0165945 0.0218727 0.0167365 0.0254566 0.0188833 0.0192812 0.0181803 0.0229721 0.0153788 0.0113615 0.0084066 0.0093753 0.0118165 0.0202505 0.0153967 0.0172162 0.0111489 0.0123902
2012 0.0019612 0.0124200 0.0218714 0.0080891 0.0135130 0.0145342 0.0164698 0.0156357 0.0183171 0.0100713 0.0122155 0.0185390 0.0194318 0.0135965 0.0199271 0.0160274 0.0138429 0.0143036 0.0079759 0.0110971 0.0121072 0.0147637 0.0204446 0.0148635 0.0145853 0.0093422 0.0152724 0.0184880 0.0158514 0.0239999 0.0123706 0.0107353 0.0156545 0.0104763 0.0225963 0.0083562 0.0068475 0.0160692 0.0105906 0.0168434 0.0171811 0.0368749 0.0208107 0.0158311 0.0264159 0.0151272 0.0157186 0.0109250 0.0088490 0.0092934 0.0141710 0.0189056 0.0147983 0.0152603 0.0145468 0.0112604
2013 0.0021158 0.0134312 0.0170268 0.0099019 0.0141762 0.0126431 0.0158094 0.0242581 0.0129520 0.0119970 0.0145765 0.0168709 0.0188145 0.0161374 0.0173422 0.0149895 0.0134071 0.0156368 0.0087988 0.0127161 0.0145100 0.0175595 0.0220842 0.0186220 0.0261745 0.0097470 0.0167463 0.0173033 0.0137858 0.0211676 0.0205566 0.0099301 0.0153956 0.0106774 0.0187435 0.0086222 0.0076192 0.0160561 0.0100967 0.0165314 0.0194758 0.0277417 0.0190210 0.0213620 0.0206956 0.0258304 0.0147022 0.0158797 0.0090418 0.0087573 0.0150554 0.0223667 0.0134104 0.0218583 0.0190613 0.0129412
2014 0.0019970 0.0127841 0.0150666 0.0080836 0.0145165 0.0144486 0.0175259 0.0202143 0.0150395 0.0087945 0.0114606 0.0142979 0.0219006 0.0211051 0.0282299 0.0165564 0.0138714 0.0146489 0.0094006 0.0136680 0.0121802 0.0130538 0.0213866 0.0165348 0.0188437 0.0120731 0.0169673 0.0159317 0.0144649 0.0152390 0.0132727 0.0091570 0.0145863 0.0113590 0.0198347 0.0093055 0.0068128 0.0224735 0.0131951 0.0190765 0.0155219 0.0177691 0.0285289 0.0148529 0.0201407 0.0210606 0.0151298 0.0109758 0.0079021 0.0110974 0.0131492 0.0166364 0.0180357 0.0199555 0.0162949 0.0146627
2015 0.0020098 0.0124533 0.0119957 0.0084030 0.0185829 0.0149304 0.0157382 0.0226489 0.0168362 0.0123734 0.0127006 0.0194141 0.0185563 0.0238157 0.0221629 0.0145712 0.0140402 0.0173449 0.0090167 0.0121547 0.0154192 0.0147460 0.0168488 0.0161741 0.0203235 0.0107421 0.0175482 0.0159302 0.0124820 0.0186652 0.0190640 0.0175891 0.0185395 0.0096046 0.0206961 0.0082000 0.0068298 0.0190325 0.0114593 0.0177944 0.0170896 0.0216219 0.0172824 0.0136782 0.0211832 0.0171110 0.0144895 0.0103173 0.0088221 0.0101917 0.0117689 0.0151396 0.0153600 0.0227139 0.0169312 0.0131888
2016 0.0019317 0.0121980 0.0136299 0.0105733 0.0163216 0.0149522 0.0162534 0.0184094 0.0161183 0.0096348 0.0095014 0.0171077 0.0181961 0.0154498 0.0189239 0.0160371 0.0135765 0.0150515 0.0076443 0.0113720 0.0127374 0.0173264 0.0176280 0.0126222 0.0206385 0.0083447 0.0116494 0.0145201 0.0131667 0.0176358 0.0212086 0.0108631 0.0174313 0.0102133 0.0280780 0.0081621 0.0068026 0.0166146 0.0141060 0.0177284 0.0163189 0.0262309 0.0199709 0.0160967 0.0179857 0.0226385 0.0178275 0.0107107 0.0083993 0.0114294 0.0117242 0.0136765 0.0144567 0.0204240 0.0154462 0.0145777
2017 0.0020404 0.0139593 0.0177000 0.0104082 0.0158942 0.0138857 0.0200571 0.0218064 0.0188213 0.0143370 0.0104810 0.0171493 0.0206081 0.0157075 0.0189583 0.0144899 0.0143773 0.0161624 0.0086783 0.0133651 0.0123236 0.0121786 0.0233778 0.0127144 0.0205101 0.0084439 0.0145754 0.0157251 0.0147515 0.0156487 0.0178068 0.0135716 0.0152640 0.0102205 0.0265270 0.0078299 0.0068819 0.0158424 0.0142955 0.0258777 0.0178202 0.0216572 0.0216940 0.0145377 0.0238273 0.0256963 0.0150999 0.0124422 0.0089167 0.0091058 0.0129534 0.0147546 0.0165428 0.0188256 0.0155836 0.0121100
2018 0.0020143 0.0120300 0.0160317 0.0082054 0.0122086 0.0147205 0.0178912 0.0224363 0.0137918 0.0090610 0.0099489 0.0225144 0.0189156 0.0195042 0.0158621 0.0150777 0.0154213 0.0154052 0.0083251 0.0107456 0.0122023 0.0138171 0.0228161 0.0143027 0.0205737 0.0071637 0.0178663 0.0181526 0.0139005 0.0145928 0.0172943 0.0106215 0.0186467 0.0117724 0.0207088 0.0075857 0.0071347 0.0161435 0.0133022 0.0238794 0.0189292 0.0331732 0.0245874 0.0153301 0.0198918 0.0244149 0.0142390 0.0112380 0.0081114 0.0106139 0.0131728 0.0217622 0.0178725 0.0222147 0.0245573 0.0120737
Gini standard errors for the five most populous states and their PUMAs with complete data (2005-2018)
YEAR Texas (48) 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002
2005 0.0015008 0.0130181 0.0216024 0.0194417 0.0208567 0.0210725 0.0151848 0.0055732 0.0149642 0.0116450 0.0178136 0.0234439 0.0128621 0.0151749 0.0212791 0.0180179 0.0071509 0.0086073 0.0138724 0.0139025 0.0047349 0.0052329 0.0141966 0.0157266 0.0187451 0.0172376 0.0094320 0.0214237 0.0055801 0.0167569 0.0289070 0.0139343 0.0155557 0.0227446 0.0160476 0.0234050 0.0128727 0.0039757 0.0113345 0.0155011 0.0089477 0.0095722 0.0064191 0.0138884 0.0059808 0.0166039 0.0154101 0.0096262 0.0144957 0.0108119
2006 0.0014567 0.0154006 0.0170302 0.0183612 0.0161472 0.0189335 0.0153143 0.0063328 0.0245756 0.0100192 0.0158136 0.0194358 0.0092780 0.0170154 0.0219949 0.0202652 0.0075697 0.0078879 0.0153342 0.0199309 0.0048353 0.0049073 0.0133225 0.0183961 0.0183872 0.0230454 0.0098716 0.0267623 0.0061371 0.0162160 0.0211166 0.0184756 0.0174221 0.0151967 0.0202267 0.0155520 0.0166709 0.0036627 0.0109745 0.0143166 0.0087646 0.0083497 0.0063780 0.0172591 0.0050773 0.0153136 0.0138626 0.0082572 0.0113397 0.0094095
2007 0.0013992 0.0128402 0.0190389 0.0198377 0.0142198 0.0217661 0.0219899 0.0053914 0.0205104 0.0092130 0.0138506 0.0288940 0.0092893 0.0166808 0.0189671 0.0183505 0.0066061 0.0074506 0.0198708 0.0177844 0.0046292 0.0048451 0.0287355 0.0183864 0.0195722 0.0154727 0.0092631 0.0166740 0.0056751 0.0192067 0.0262901 0.0154345 0.0178517 0.0161878 0.0170176 0.0126887 0.0123341 0.0034753 0.0112823 0.0112623 0.0083652 0.0092911 0.0057631 0.0139424 0.0052649 0.0369728 0.0139244 0.0089464 0.0134966 0.0094914
2008 0.0014089 0.0116679 0.0192104 0.0217886 0.0198459 0.0277485 0.0172638 0.0057387 0.0194779 0.0090004 0.0149923 0.0209398 0.0124255 0.0126012 0.0200631 0.0154583 0.0073401 0.0081470 0.0139220 0.0178582 0.0045948 0.0048912 0.0189037 0.0160780 0.0330773 0.0188607 0.0093453 0.0229270 0.0053051 0.0163818 0.0292525 0.0136752 0.0142250 0.0168338 0.0209811 0.0177906 0.0115569 0.0035169 0.0119603 0.0102306 0.0084523 0.0095266 0.0058247 0.0130819 0.0056248 0.0222364 0.0141704 0.0102543 0.0106541 0.0095364
2009 0.0013785 0.0133569 0.0176819 0.0174843 0.0143787 0.0215424 0.0151111 0.0051749 0.0198772 0.0090293 0.0162262 0.0158425 0.0110842 0.0171611 0.0205459 0.0205918 0.0068233 0.0074931 0.0185989 0.0271957 0.0044775 0.0046387 0.0174632 0.0194839 0.0197473 0.0181299 0.0085804 0.0237811 0.0051994 0.0144217 0.0162084 0.0200975 0.0190610 0.0144864 0.0135143 0.0170941 0.0120765 0.0034678 0.0107012 0.0113547 0.0080273 0.0080360 0.0063464 0.0133044 0.0055821 0.0182329 0.0144515 0.0076345 0.0116112 0.0097536
2010 0.0012696 0.0145009 0.0138128 0.0166727 0.0163014 0.0214333 0.0124761 0.0051716 0.0194701 0.0079011 0.0144381 0.0173782 0.0100721 0.0148521 0.0201934 0.0137052 0.0062211 0.0066441 0.0178622 0.0203321 0.0041777 0.0044603 0.0226578 0.0192572 0.0210219 0.0235262 0.0083850 0.0259119 0.0048705 0.0153433 0.0199758 0.0117986 0.0187855 0.0159152 0.0183480 0.0145715 0.0110912 0.0031699 0.0097562 0.0118737 0.0079436 0.0089231 0.0052474 0.0128304 0.0048345 0.0154414 0.0137453 0.0082804 0.0117172 0.0099591
2011 0.0015192 0.0121274 0.0169213 0.0194535 0.0227573 0.0252106 0.0186569 0.0057611 0.0148485 0.0109244 0.0175972 0.0182217 0.0125838 0.0206684 0.0173599 0.0169734 0.0082726 0.0095332 0.0156138 0.0186464 0.0050251 0.0049855 0.0223706 0.0156213 0.0162682 0.0147529 0.0102789 0.0217328 0.0068724 0.0183021 0.0237133 0.0165825 0.0155752 0.0192233 0.0163365 0.0164990 0.0169744 0.0036775 0.0109142 0.0138692 0.0107517 0.0122185 0.0061582 0.0128175 0.0066170 0.0151294 0.0140857 0.0096721 0.0119108 0.0097749
2012 0.0014644 0.0145570 0.0153812 0.0175874 0.0156852 0.0275934 0.0153317 0.0058402 0.0165238 0.0119185 0.0151311 0.0162201 0.0100413 0.0178312 0.0252698 0.0167777 0.0073493 0.0066551 0.0162296 0.0145126 0.0041781 0.0051849 0.0276377 0.0236791 0.0156026 0.0291143 0.0115161 0.0325273 0.0071601 0.0151961 0.0171313 0.0212471 0.0162732 0.0154593 0.0173229 0.0152833 0.0143389 0.0036594 0.0107088 0.0134787 0.0089884 0.0081199 0.0063073 0.0114126 0.0056752 0.0167474 0.0124808 0.0088077 0.0136392 0.0128734
2013 0.0014298 0.0106193 0.0386299 0.0257420 0.0185482 0.0292785 0.0156891 0.0068308 0.0175957 0.0099999 0.0172874 0.0301749 0.0116590 0.0132559 0.0243884 0.0188841 0.0068492 0.0071527 0.0150504 0.0158068 0.0045859 0.0055246 0.0169300 0.0190390 0.0178338 0.0191117 0.0104641 0.0237564 0.0061698 0.0159511 0.0296264 0.0145392 0.0153382 0.0182096 0.0177721 0.0179681 0.0143912 0.0035624 0.0113914 0.0101708 0.0089195 0.0084002 0.0059399 0.0110365 0.0050889 0.0147689 0.0132441 0.0082152 0.0128398 0.0109203
2014 0.0013878 0.0114431 0.0215077 0.0171926 0.0162604 0.0228401 0.0166212 0.0057678 0.0201234 0.0086615 0.0130843 0.0182563 0.0113108 0.0170458 0.0174322 0.0156341 0.0061246 0.0071286 0.0110505 0.0165844 0.0042803 0.0049758 0.0210649 0.0174427 0.0198973 0.0193783 0.0085074 0.0216754 0.0062463 0.0192857 0.0183494 0.0156457 0.0142487 0.0212735 0.0117566 0.0242999 0.0122847 0.0034199 0.0114798 0.0147966 0.0084261 0.0088163 0.0057337 0.0120256 0.0050560 0.0221956 0.0177155 0.0081546 0.0099824 0.0127966
2015 0.0014195 0.0138962 0.0248409 0.0172062 0.0180804 0.0220693 0.0148409 0.0059715 0.0163218 0.0096937 0.0247526 0.0290293 0.0105912 0.0164827 0.0177916 0.0145718 0.0063400 0.0072104 0.0154441 0.0163392 0.0044822 0.0047645 0.0178314 0.0192880 0.0163005 0.0222218 0.0084866 0.0177235 0.0063423 0.0151061 0.0215511 0.0177094 0.0174852 0.0187185 0.0195159 0.0155208 0.0140939 0.0034952 0.0145371 0.0141307 0.0097720 0.0087267 0.0057975 0.0105734 0.0051271 0.0203825 0.0163949 0.0093213 0.0104193 0.0106938
2016 0.0013751 0.0122569 0.0195212 0.0177811 0.0124275 0.0249904 0.0174059 0.0059059 0.0174278 0.0081472 0.0133033 0.0195601 0.0138072 0.0138440 0.0171712 0.0209978 0.0061440 0.0061148 0.0149875 0.0221473 0.0041713 0.0043782 0.0175745 0.0178921 0.0239211 0.0181282 0.0095689 0.0217203 0.0062252 0.0149788 0.0274829 0.0164621 0.0172709 0.0164289 0.0187888 0.0158950 0.0121707 0.0037068 0.0105414 0.0130128 0.0092859 0.0083697 0.0054524 0.0110847 0.0050642 0.0206551 0.0129173 0.0081195 0.0148543 0.0103190
2017 0.0014595 0.0137816 0.0191269 0.0153215 0.0127835 0.0196347 0.0146773 0.0054313 0.0193253 0.0085625 0.0141382 0.0209425 0.0135676 0.0135235 0.0169704 0.0193611 0.0063753 0.0066689 0.0128177 0.0131301 0.0041248 0.0047791 0.0154362 0.0188559 0.0219323 0.0206066 0.0086471 0.0227805 0.0080200 0.0154701 0.0260892 0.0143811 0.0158094 0.0151774 0.0300836 0.0159936 0.0138044 0.0037650 0.0116878 0.0207059 0.0086046 0.0079726 0.0062051 0.0096606 0.0050704 0.0175729 0.0131801 0.0076152 0.0117344 0.0092472
2018 0.0013717 0.0126889 0.0227757 0.0158462 0.0141717 0.0218022 0.0176731 0.0059067 0.0186168 0.0082955 0.0157490 0.0224363 0.0107703 0.0158906 0.0198848 0.0168863 0.0061962 0.0064950 0.0128197 0.0141373 0.0042549 0.0046873 0.0151315 0.0203640 0.0178960 0.0183556 0.0082023 0.0235131 0.0059382 0.0142449 0.0207271 0.0149810 0.0168553 0.0180359 0.0215796 0.0191574 0.0141291 0.0033791 0.0139766 0.0138984 0.0091028 0.0074358 0.0057566 0.0111427 0.0051520 0.0173337 0.0174833 0.0105738 0.0110294 0.0096787

Next, we observe the gini coefficients for the five most populous states (and all PUMAs within).

# and a third loop to output ginis
for(i in c("06", "12", "36", "42", "48")){
df.state.puma.wide <- puma_state_gini %>%
  filter(STATEFIP == i & YEAR > 2004) %>%
  dplyr::select(YEAR, hh_inc, PUMA, LEVEL) %>%
  mutate(PUMA = replace(as.character(PUMA), LEVEL == "State", 
                       first(acs_data$State[acs_data$STATEFIP == i]))) %>%
  dplyr::select(YEAR, hh_inc, PUMA) %>%
  group_by(YEAR) %>%
  pivot_wider(names_from = PUMA, values_from = hh_inc) 

print(kable(df.state.puma.wide, caption = "Gini values for the five most populous states and their PUMAs with complete data (2005-2018)") %>%
  kable_styling() %>%
  scroll_box(width = "900px", height = "500px"))

}
Gini values for the five most populous states and their PUMAs with complete data (2005-2018)
YEAR California (6) 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158
2005 0.4688495 0.5382906 0.4766929 0.4748733 0.4559046 0.4533413 0.4382343 0.4133599 0.3674899 0.4047332 0.3801963 0.4181875 0.4693296 0.4603503 0.4518209 0.4453265 0.4495673 0.4629754 0.4981256 0.4444868 0.4563183 0.4388620 0.4455386 0.4377086 0.5056018 0.4287486 0.4620559 0.4480872 0.4255917 0.4848808 0.5164812 0.4406674 0.5001545 0.5328114 0.5156287 0.4620248 0.3948598 0.3834128 0.4140076 0.4604133 0.4827415 0.4339230 0.4807396 0.4167590 0.4044055 0.4163912 0.4285448 0.4593660 0.4965925 0.3878230 0.4396474 0.4301526 0.4319333 0.4374672 0.4988913 0.4310586 0.4137134 0.4742795 0.4547648 0.4008387 0.4287550 0.4959407 0.4145645 0.3573928 0.4340925 0.4274422 0.4127769 0.4270382 0.4415439 0.4943560 0.4076464 0.4617215 0.4371822 0.3768604 0.5224333 0.5540146 0.5680120 0.4606051 0.4679772 0.4549207 0.4196049 0.4405353 0.4487155 0.4087287 0.4147963 0.4985726 0.4244134 0.4758692 0.5016358 0.4856736 0.4733551 0.4402842 0.3991567 0.3631902 0.4253971 0.4726158 0.4459789 0.4642151 0.4652230 0.4251799 0.4130810 0.3841864 0.4476734 0.3861104 0.4506652 0.4417380 0.4256814 0.4781597 0.4404950 0.4256463 0.4690752
2006 0.4659449 0.5024780 0.4762638 0.4709483 0.4463294 0.4243363 0.4047789 0.4503861 0.3777059 0.3943177 0.3971703 0.4433649 0.4593564 0.4256838 0.4556336 0.4466362 0.4302382 0.4613499 0.4285828 0.4472958 0.4595947 0.4194478 0.4259776 0.4299976 0.5015031 0.4305924 0.4570134 0.4262303 0.3933047 0.4788342 0.4839047 0.4517823 0.4460167 0.5258468 0.5482332 0.4096221 0.4272296 0.3890777 0.3939625 0.3858100 0.4331678 0.5176937 0.4677591 0.4097422 0.3794231 0.4245166 0.4360509 0.4554205 0.4920036 0.3785601 0.4237953 0.4251834 0.4628110 0.4386810 0.5072111 0.4383358 0.4467101 0.4559186 0.4553763 0.4341231 0.4302342 0.4731267 0.4144181 0.3835550 0.4349210 0.4227400 0.3960573 0.4225762 0.4501918 0.4850214 0.4264433 0.4385243 0.4174179 0.3937396 0.4909743 0.5315506 0.5751061 0.4536344 0.4455785 0.4363044 0.4461943 0.4266412 0.4779285 0.3789476 0.3994845 0.5061368 0.4270043 0.4389055 0.5133456 0.4728641 0.4811062 0.4240678 0.3762808 0.4014061 0.4399294 0.4750508 0.4598343 0.4772181 0.4536273 0.4428075 0.3845291 0.4106936 0.4434283 0.4171307 0.4433519 0.4495515 0.4482303 0.4318200 0.4513408 0.4259701 0.4527010
2007 0.4684264 0.5127010 0.5125310 0.4830646 0.4409544 0.4348997 0.4474454 0.4164188 0.3789145 0.4029753 0.3743069 0.4177506 0.4646881 0.4579287 0.4553901 0.4359702 0.4415693 0.4509070 0.4728978 0.4860553 0.4546270 0.3975831 0.4310732 0.4265613 0.5110806 0.4234804 0.4551776 0.4542163 0.4079427 0.5032268 0.4678523 0.4501143 0.5006991 0.5273581 0.5260034 0.4535334 0.4305110 0.3985651 0.3963193 0.4591671 0.4468711 0.5114261 0.4579294 0.4140935 0.3931920 0.3970937 0.4398885 0.4636648 0.5116767 0.4076312 0.4200217 0.4174079 0.4558215 0.4407719 0.4993226 0.4719788 0.4414711 0.4531368 0.4559056 0.3946877 0.4165609 0.5073382 0.4211554 0.3741718 0.4294892 0.4102361 0.3784625 0.4244602 0.4329047 0.4756269 0.4160076 0.4485863 0.4243787 0.4235872 0.5071600 0.5336522 0.5503481 0.5017825 0.4552521 0.4810437 0.4508337 0.4367534 0.4825721 0.3867823 0.4043287 0.5047680 0.4357523 0.4754426 0.5237410 0.4730037 0.4842826 0.4337162 0.3817785 0.3921526 0.4327505 0.5107975 0.4641233 0.4807360 0.4637627 0.4215211 0.3864321 0.3776781 0.4561701 0.4221657 0.4507314 0.4261103 0.4391940 0.4580921 0.4438275 0.4344685 0.4476707
2008 0.4719104 0.5178572 0.4871353 0.4761460 0.4246737 0.4270344 0.4309532 0.4244535 0.3632221 0.4057901 0.4122668 0.4339825 0.4567151 0.4600616 0.4571811 0.4249319 0.4097060 0.4651972 0.4942224 0.4756133 0.4546875 0.3836865 0.4712100 0.4278058 0.5122741 0.4265614 0.4485227 0.4477599 0.4297724 0.5057985 0.4987516 0.4756374 0.4943605 0.5314865 0.5289990 0.4331644 0.4109406 0.3883718 0.4255064 0.4256190 0.4559666 0.4567127 0.4656068 0.4320379 0.3989984 0.4133270 0.4200920 0.4789804 0.4989959 0.3715785 0.4786115 0.4286895 0.4584449 0.4358820 0.4948706 0.4599873 0.4355797 0.4621941 0.4601403 0.4228040 0.4168339 0.4966110 0.4105102 0.3791442 0.4266570 0.4390925 0.3999479 0.4280666 0.4336210 0.4872671 0.4271290 0.4805462 0.4162392 0.4300929 0.5181321 0.5438344 0.5748773 0.4827406 0.4462076 0.4947493 0.4403935 0.4455326 0.4347309 0.3802424 0.4066006 0.5102468 0.4268987 0.4581223 0.5515438 0.4695368 0.4666604 0.4236609 0.3671904 0.3712178 0.4454760 0.4996920 0.4701178 0.4772635 0.4657044 0.3984966 0.3753660 0.3990327 0.4678507 0.4563574 0.4384403 0.4311376 0.4510522 0.4212747 0.4358931 0.4341208 0.4641305
2009 0.4657316 0.4917386 0.4699830 0.4544804 0.4522978 0.4486588 0.4123642 0.3974676 0.3560107 0.3762886 0.4249861 0.4238238 0.4455267 0.4309073 0.4532257 0.4526308 0.4064962 0.4680826 0.4710221 0.4857174 0.4508781 0.4526668 0.4666199 0.4296532 0.5009974 0.4363090 0.4620828 0.4022688 0.4107844 0.5038899 0.4905071 0.4336083 0.4596178 0.5222921 0.5340984 0.4058260 0.3999235 0.4307200 0.4011404 0.4181383 0.4444266 0.4841022 0.4467166 0.4160546 0.3882738 0.4097118 0.4416290 0.4584832 0.4876546 0.3886713 0.4674994 0.4041045 0.4445564 0.4424138 0.4952161 0.4497864 0.4452628 0.4525777 0.4490998 0.3983839 0.4214892 0.4929083 0.4098581 0.3794890 0.4433788 0.4374532 0.4079163 0.4195624 0.4311665 0.4777594 0.4247120 0.4568251 0.4295085 0.4163968 0.5140029 0.5479127 0.5741927 0.4839692 0.4336920 0.4514535 0.4384842 0.4310043 0.4418058 0.3735090 0.3753131 0.4885419 0.4433901 0.4410824 0.5408875 0.4618327 0.4758136 0.4252489 0.3744353 0.4258779 0.4211221 0.4806959 0.4201882 0.4654919 0.4737649 0.4299912 0.3962054 0.4005511 0.4404865 0.4226257 0.4403154 0.4280590 0.4252449 0.4509927 0.4451943 0.4385137 0.4423270
2010 0.4705484 0.5164803 0.5039970 0.4769115 0.4674210 0.4504359 0.4190169 0.4344219 0.3861525 0.4179268 0.4094692 0.4368901 0.4591436 0.4386723 0.4511407 0.4565799 0.4433789 0.4639072 0.4564071 0.4504561 0.4511596 0.4332999 0.4508907 0.4295508 0.5077251 0.4644099 0.4626961 0.4400158 0.4159195 0.4835147 0.4893338 0.4537721 0.4777178 0.5249328 0.5254461 0.4059659 0.4192434 0.3772525 0.3915574 0.3880655 0.4419325 0.4665054 0.4639373 0.4388149 0.4158844 0.4118838 0.4505928 0.4545429 0.4865538 0.4366221 0.4329411 0.4186010 0.4591518 0.4850218 0.4862122 0.4912981 0.4576568 0.4539576 0.4550732 0.3984034 0.4402182 0.4935586 0.4224307 0.3759372 0.4412107 0.4354965 0.4067642 0.4327095 0.4405189 0.5043733 0.4252924 0.4706266 0.4150509 0.4139956 0.5095907 0.5130475 0.5621215 0.4559965 0.4460055 0.4398181 0.4892256 0.4386488 0.4546229 0.3783311 0.3991822 0.4794920 0.4270712 0.4654297 0.4859239 0.4773393 0.4809047 0.4341963 0.3836086 0.3966221 0.4375165 0.4755669 0.4493729 0.4521191 0.4493004 0.4068706 0.3973287 0.3932572 0.4660075 0.4198558 0.4368299 0.4530750 0.4335334 0.4387650 0.4418435 0.4414674 0.4695190
2011 0.4800512 0.5271742 0.4807143 0.4834444 0.4560216 0.4383469 0.4487144 0.4326605 0.3934638 0.4094767 0.3959132 0.4567120 0.4597217 0.4583086 0.4791514 0.4878788 0.4605256 0.4590935 0.4746391 0.4921737 0.4614225 0.4453428 0.4486452 0.4389759 0.5170353 0.4714479 0.4656628 0.4343566 0.4561308 0.4886981 0.4874499 0.4731119 0.4708116 0.5397012 0.5324819 0.4306357 0.4038562 0.4362410 0.4025968 0.3964887 0.4450247 0.4919507 0.4648667 0.4621689 0.4184737 0.4078008 0.4597138 0.4659449 0.5030654 0.3916852 0.4632526 0.4166431 0.4173822 0.4839121 0.5301893 0.4760158 0.4465415 0.4645022 0.4637085 0.4089746 0.4306433 0.4735765 0.4319833 0.4112431 0.4511349 0.4437164 0.4287804 0.4462601 0.4628745 0.4818222 0.4326815 0.4663926 0.4290025 0.3951874 0.5043207 0.5285863 0.5680855 0.4836901 0.4394839 0.4669014 0.4798263 0.4390346 0.4704978 0.4142029 0.4057474 0.5045879 0.4300526 0.4592725 0.5471902 0.4740696 0.4945145 0.4490480 0.4049928 0.4220191 0.4547782 0.4904527 0.4776088 0.4610086 0.4490039 0.4460120 0.4123312 0.3924655 0.4748931 0.4311435 0.4390630 0.4571071 0.4136484 0.4230539 0.4616878 0.4449035 0.4955278
2012 0.4804002 0.5288426 0.4773737 0.4761821 0.4615024 0.4199195 0.4351420 0.4593328 0.4000153 0.4082851 0.4275050 0.4412383 0.4756729 0.4303692 0.4641999 0.4511093 0.4412887 0.4831318 0.4744519 0.4717316 0.4528761 0.4708766 0.4462859 0.4328935 0.4941285 0.4385798 0.4719444 0.4510177 0.4140050 0.4763257 0.4991243 0.4928583 0.4769645 0.5267978 0.5482871 0.4424797 0.4393492 0.4253344 0.4013404 0.3993473 0.4673357 0.5106323 0.4803980 0.4575734 0.4139110 0.4428161 0.4476114 0.4536615 0.5080066 0.3761029 0.4704209 0.4162004 0.4724416 0.4670576 0.5085163 0.4588808 0.4319770 0.4531631 0.4659389 0.4166234 0.4170828 0.4968767 0.4303594 0.3984887 0.4654036 0.4381863 0.4253872 0.4513607 0.4502826 0.4798499 0.4429475 0.4548946 0.4221140 0.4048533 0.5552824 0.5460536 0.5798605 0.4584204 0.4724073 0.4469876 0.4495501 0.4591991 0.4590554 0.4243503 0.4234851 0.5114932 0.4285160 0.4693705 0.5414259 0.4646906 0.5079021 0.4356636 0.4034356 0.4094155 0.4398163 0.5028644 0.4612855 0.4766844 0.4254869 0.4285947 0.4304592 0.4373061 0.4874487 0.4219898 0.4464155 0.4499491 0.4363533 0.4499537 0.4633028 0.4435256 0.4744565
2013 0.4885798 0.5461569 0.5023862 0.4724089 0.4637307 0.4669023 0.4186065 0.4559387 0.4212392 0.4256180 0.4043552 0.4455967 0.4772018 0.4634402 0.4754520 0.4572600 0.4891480 0.4848690 0.4441967 0.4536215 0.4615567 0.4464091 0.4766398 0.4573176 0.5201733 0.4430889 0.4866606 0.4415122 0.4258253 0.5246187 0.5176884 0.4617016 0.4788718 0.5240325 0.5500254 0.4373728 0.4258158 0.4367124 0.4152827 0.4075182 0.4494525 0.4936363 0.5029201 0.4503751 0.4063534 0.4443833 0.4629141 0.4503123 0.5124511 0.4082464 0.4516517 0.4234207 0.4626037 0.5051346 0.4881722 0.4414143 0.4532306 0.4398917 0.4647221 0.4330604 0.4418931 0.5147123 0.4344706 0.4092340 0.4634580 0.4466222 0.4292513 0.4699863 0.4491869 0.5008633 0.4424522 0.4306773 0.4427183 0.3957250 0.4902155 0.5227046 0.5999364 0.5110839 0.4603742 0.4854865 0.4864755 0.4432229 0.4705539 0.4150934 0.3802653 0.5339017 0.4383076 0.4630606 0.5179099 0.4976733 0.4878924 0.4638122 0.4136242 0.4345901 0.4546744 0.5082255 0.4444135 0.4744308 0.4593596 0.4539981 0.4145324 0.4225490 0.4771335 0.4361960 0.4446748 0.4546013 0.4287360 0.4690575 0.4602571 0.4438588 0.4863766
2014 0.4877625 0.5190406 0.4925944 0.4939678 0.4545248 0.4354117 0.4247756 0.4312696 0.3953796 0.3954383 0.4087546 0.4414871 0.4949561 0.5098418 0.4741282 0.4732370 0.4616339 0.4807483 0.4683069 0.4840842 0.4694628 0.4496374 0.4902416 0.4503564 0.5158959 0.4851665 0.4682532 0.4586949 0.4710850 0.4975141 0.5076763 0.4978207 0.4905737 0.5463203 0.5518567 0.4298816 0.4261104 0.4363037 0.4036922 0.4532828 0.4353148 0.4883634 0.4778290 0.4053216 0.3970667 0.4047213 0.4808399 0.4452826 0.5012321 0.3812036 0.4469719 0.4218843 0.4336232 0.4902950 0.5169381 0.4556814 0.4677964 0.4921048 0.4738944 0.4134625 0.4498825 0.5121928 0.4265316 0.4044227 0.4709500 0.4524498 0.4420348 0.4424570 0.4413683 0.4807892 0.4434173 0.4681948 0.4218865 0.4184377 0.5071252 0.5214957 0.5580970 0.4929856 0.4625012 0.4521710 0.4433475 0.4711884 0.4548195 0.4259533 0.4267084 0.4910180 0.4323133 0.4746020 0.5042194 0.4887694 0.4870716 0.4383694 0.3698823 0.4210953 0.4525559 0.4506283 0.4674207 0.4892337 0.4562048 0.4273792 0.4043559 0.4055766 0.4730024 0.4493376 0.4550893 0.4513712 0.4462423 0.4912603 0.4571457 0.4491391 0.5109478
2015 0.4862039 0.5211972 0.4842743 0.4962817 0.4522937 0.4521339 0.4216732 0.4214113 0.3779193 0.3860591 0.4224072 0.4632126 0.4715713 0.4780460 0.4701867 0.4721488 0.4592513 0.4775042 0.4831385 0.4648692 0.4698077 0.4383556 0.4993528 0.4428009 0.5113318 0.4397572 0.4672118 0.4774338 0.4351285 0.5043312 0.5165461 0.4820522 0.4899127 0.5254730 0.5414805 0.4232180 0.4198607 0.4376780 0.3922352 0.4447882 0.4586799 0.4490524 0.4788583 0.4439037 0.4177477 0.4096355 0.4497200 0.4620873 0.5019586 0.4012880 0.4439369 0.4242965 0.4678372 0.4687027 0.5331781 0.4842635 0.4606205 0.4969411 0.4696832 0.4405399 0.4378657 0.5113919 0.4229676 0.4030391 0.4668963 0.4470832 0.4190814 0.4261977 0.4464743 0.4765880 0.4166728 0.4819775 0.4158201 0.4067934 0.4942167 0.5153718 0.5770736 0.4953208 0.4721824 0.4738864 0.5275571 0.4456284 0.4712116 0.3875958 0.4017490 0.4965008 0.4402891 0.4916530 0.5617200 0.4915679 0.4874737 0.4482329 0.3956363 0.4114610 0.4451267 0.4806661 0.4602158 0.4864693 0.4397831 0.4385365 0.4460359 0.4217205 0.4878316 0.4225495 0.4466099 0.4447374 0.4550087 0.4588134 0.4604506 0.4328674 0.4857553
2016 0.4890393 0.5221456 0.5012125 0.4545402 0.4817370 0.4354323 0.4135857 0.4271800 0.3908262 0.3987201 0.4212798 0.4770144 0.5021184 0.4451625 0.4570690 0.4852808 0.4537938 0.4962796 0.5038995 0.4955330 0.4676224 0.4106691 0.4985517 0.4673578 0.5136363 0.4635304 0.4806330 0.4434204 0.4687102 0.4991191 0.5116535 0.4905474 0.5053202 0.5372850 0.5359538 0.4192495 0.4241871 0.4361599 0.4099191 0.4173338 0.4640350 0.5144403 0.5001040 0.4474351 0.4148836 0.4175054 0.4608650 0.4887338 0.4958780 0.3925587 0.4319201 0.4468439 0.4426404 0.4709996 0.5091200 0.4701227 0.4505078 0.4687144 0.4659365 0.4391103 0.4644696 0.4987652 0.4325008 0.3735555 0.4662494 0.4449327 0.4279078 0.4251223 0.4630136 0.4862381 0.4151884 0.4802268 0.4275170 0.4042281 0.5083930 0.5058813 0.5819460 0.4750688 0.4424794 0.4871177 0.4401490 0.4548405 0.4528657 0.4222125 0.4028828 0.5006737 0.4552527 0.4668376 0.5452160 0.4755092 0.5167679 0.4431688 0.3892509 0.4106877 0.4493540 0.5017225 0.4499550 0.5026869 0.4799965 0.4410355 0.4332710 0.4190814 0.4581603 0.4432603 0.4220258 0.4448533 0.4486022 0.4730109 0.4477203 0.4421315 0.5179207
2017 0.4849602 0.4969596 0.4832672 0.4574683 0.4608106 0.4759010 0.4125056 0.4092330 0.3775396 0.3972512 0.4276666 0.4450538 0.4988417 0.4614873 0.4696810 0.4851225 0.4372622 0.4776046 0.4969116 0.4861718 0.4561064 0.4005768 0.4766726 0.4459473 0.5012724 0.4422792 0.4629124 0.4506532 0.4274738 0.5381309 0.4946195 0.5023966 0.4841537 0.5265513 0.5309976 0.4344881 0.4223199 0.4122222 0.4055755 0.4113635 0.4477907 0.5433762 0.5275695 0.4377418 0.4188182 0.4120912 0.4614880 0.4805507 0.5005590 0.4142929 0.4584147 0.4123892 0.4185932 0.4352063 0.5125700 0.4741676 0.4259869 0.4474976 0.4639925 0.4275084 0.4544735 0.5408225 0.4300371 0.4154549 0.4552909 0.4352644 0.4201558 0.4342754 0.4507298 0.4772663 0.4423946 0.4563206 0.4466890 0.3949395 0.5007113 0.5080682 0.5306470 0.4421334 0.4743162 0.4405274 0.4877245 0.4648797 0.4474982 0.3870036 0.4206628 0.4768209 0.4718723 0.4719030 0.5167931 0.4778446 0.4799429 0.4439129 0.4172876 0.3919162 0.4499013 0.4824005 0.4555333 0.4883994 0.4841743 0.4568907 0.3851282 0.4051083 0.4648280 0.4310958 0.4441399 0.4248864 0.4176949 0.4629315 0.4691484 0.4661657 0.4767718
2018 0.4902577 0.5124568 0.5036585 0.4956395 0.4554494 0.4279695 0.4423500 0.4211587 0.3449550 0.4160002 0.4026104 0.4635947 0.4885888 0.4833044 0.4689529 0.4842307 0.4473146 0.4678053 0.4529017 0.4503910 0.4721899 0.4181179 0.4606496 0.4582208 0.5089469 0.4906529 0.4806830 0.4486958 0.4612524 0.5094776 0.5010727 0.5192042 0.4770013 0.5272480 0.5325559 0.4533731 0.4285954 0.4109222 0.4035154 0.4205211 0.4568530 0.5214903 0.5147804 0.4135945 0.4043503 0.4488610 0.4494913 0.4693905 0.4912017 0.4260553 0.4418344 0.4191827 0.4421622 0.4631956 0.4989362 0.4565699 0.4587451 0.4501693 0.4729797 0.4267017 0.4465541 0.5453066 0.4366096 0.4383289 0.4543437 0.4535212 0.4021348 0.4457377 0.4548846 0.4905098 0.4397023 0.4730013 0.4156706 0.4166122 0.5012344 0.5166769 0.5630605 0.4829012 0.4745388 0.5199821 0.4756156 0.4506438 0.4629655 0.4322303 0.4354013 0.4880541 0.4355806 0.4722177 0.5240354 0.4758001 0.5147248 0.4593065 0.4105485 0.3991330 0.4514799 0.4922980 0.4749474 0.4800673 0.4533743 0.4220004 0.3968762 0.3841409 0.4870239 0.4306369 0.4407305 0.4578979 0.4235966 0.4793131 0.5062563 0.4456106 0.4882056
Gini values for the five most populous states and their PUMAs with complete data (2005-2018)
YEAR Florida (12) 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261
2005 0.4662982 0.5118875 0.4514759 0.4282348 0.4894384 0.4325604 0.3785366 0.4254361 0.4680706 0.4548030 0.4193052 0.4212947 0.4064510 0.4780006 0.4741002 0.4049987 0.4250991 0.4546681 0.4748180 0.4288754 0.4277216 0.5189965 0.4126498 0.4567316 0.4633219 0.4215589 0.3981312 0.4529658 0.4659485 0.4555791 0.4300104 0.4932174 0.4883645 0.5765357 0.4868750 0.4255207 0.4059534 0.4492931 0.4765317 0.4224587 0.4818143 0.4993786 0.3882408 0.4317156 0.4587354 0.5279896 0.5295079 0.4770627 0.4487328 0.4366771 0.4747827 0.4713996 0.4428316 0.4187104 0.4130220 0.4340583 0.4330576 0.4089550 0.4830163 0.4341829
2006 0.4651495 0.5297658 0.4577234 0.4276766 0.4750660 0.4244788 0.4180093 0.4378395 0.4688790 0.4657260 0.4298009 0.4298010 0.3525047 0.4919565 0.4582462 0.4155515 0.4290729 0.4815624 0.4751054 0.4120513 0.4508529 0.5579509 0.3816084 0.4605803 0.5228006 0.4539976 0.3591188 0.4171689 0.4473049 0.4374858 0.4222783 0.4950365 0.4909094 0.5515841 0.4769275 0.4300566 0.4236413 0.4359846 0.5270178 0.4074065 0.4722882 0.5212449 0.4255699 0.4138356 0.4563135 0.4672517 0.5050207 0.4865582 0.4362645 0.4318036 0.4556315 0.4787629 0.4412737 0.4162511 0.4147108 0.4300664 0.4237316 0.3995126 0.4745248 0.4471659
2007 0.4664357 0.5335617 0.4445842 0.4027889 0.4752259 0.4577273 0.4307194 0.4524560 0.4751720 0.4513712 0.4210614 0.4208502 0.4070258 0.5014004 0.4693853 0.4058669 0.4211098 0.4842554 0.4638252 0.4256266 0.4213541 0.5343054 0.4550483 0.4653852 0.5118401 0.4121122 0.3765862 0.4441466 0.4614034 0.4449979 0.4548023 0.4851095 0.4769779 0.5631462 0.4642312 0.4444262 0.3995710 0.4554661 0.5274959 0.3989338 0.5004371 0.5554821 0.4309305 0.4635089 0.4534428 0.5144685 0.5226694 0.4628076 0.4670670 0.4217494 0.4630553 0.4591726 0.4431496 0.4265053 0.4031586 0.4214821 0.4052052 0.4281749 0.4716421 0.4583441
2008 0.4696204 0.4954869 0.4550838 0.4144978 0.4782931 0.4293104 0.4154426 0.4461211 0.4704989 0.4560302 0.4449406 0.4281215 0.3875304 0.4954754 0.4882560 0.4256074 0.4213666 0.4516913 0.4554795 0.4117354 0.4229518 0.5208422 0.4618670 0.4704757 0.5185424 0.4285292 0.3665475 0.4301618 0.4661025 0.4711161 0.4478555 0.5061096 0.4898782 0.5815055 0.4884116 0.4002439 0.4466740 0.4434705 0.5037173 0.4000853 0.5240095 0.5479124 0.4180555 0.4815319 0.4592449 0.5310046 0.5366801 0.4920428 0.4280979 0.4382511 0.4604100 0.4637033 0.4393014 0.4046902 0.4670077 0.4314493 0.4096626 0.3893347 0.4797557 0.4509655
2009 0.4678980 0.5381474 0.4545625 0.4152826 0.4922038 0.4533821 0.4098997 0.4200509 0.4765212 0.4613178 0.4301714 0.4238701 0.3978394 0.4925176 0.4520905 0.4349562 0.4448555 0.4514155 0.4656516 0.4226020 0.4256663 0.5271385 0.4387758 0.4680018 0.4993989 0.4180341 0.3915534 0.4226312 0.4650002 0.4571315 0.4360363 0.5099350 0.4917219 0.5519290 0.4688044 0.4168002 0.4408537 0.4501593 0.5166483 0.4111763 0.5000114 0.5103101 0.3985992 0.4428502 0.4453646 0.5255993 0.5229896 0.5005745 0.4609589 0.4351994 0.4725931 0.4618604 0.4447327 0.4179863 0.4409198 0.4189223 0.4300592 0.4172970 0.4825694 0.4465162
2010 0.4719196 0.5230838 0.4619693 0.4137481 0.4726539 0.4696436 0.4256946 0.4748190 0.4811422 0.4611268 0.4388931 0.4196267 0.3887171 0.4964112 0.4525090 0.4232452 0.4203261 0.4997324 0.4752854 0.4283456 0.4550263 0.5288806 0.4590950 0.4712344 0.5127205 0.4312597 0.4013058 0.4453207 0.4710665 0.4635521 0.4267678 0.4885177 0.4979359 0.5612860 0.4877612 0.4206561 0.3816767 0.4586065 0.5229874 0.4093595 0.5065411 0.5210351 0.4154258 0.4708719 0.4540357 0.4839290 0.5184663 0.4639497 0.4492386 0.4338339 0.4636057 0.4760276 0.4201460 0.4362414 0.4219194 0.4353704 0.4465407 0.4367728 0.4644141 0.4391657
2011 0.4797610 0.5133897 0.4686481 0.4459715 0.4606192 0.4695424 0.4069161 0.4591718 0.4864044 0.4769496 0.4445324 0.4226341 0.4533889 0.5182499 0.4931902 0.4401134 0.4297122 0.4751692 0.4828415 0.4001654 0.4659185 0.5360114 0.4591922 0.4754222 0.5186070 0.4819699 0.4083632 0.3992520 0.4722599 0.4695442 0.4435865 0.5107082 0.5009736 0.5726520 0.4872460 0.4488407 0.4417997 0.4758980 0.5145244 0.4114087 0.5033619 0.5026340 0.4298442 0.4540799 0.4641789 0.5468161 0.5268629 0.4678970 0.4614149 0.4530900 0.4624743 0.4801272 0.4435656 0.4283871 0.4248880 0.4554285 0.4551199 0.4500045 0.4693793 0.4625188
2012 0.4802428 0.5398041 0.4617553 0.4426957 0.4909967 0.4467905 0.4378157 0.4521737 0.4777536 0.4704755 0.4185451 0.4429822 0.4149425 0.5137893 0.5068270 0.4645247 0.4250677 0.4369913 0.4797181 0.4139429 0.4847097 0.5487101 0.4754161 0.4726614 0.5387492 0.4506923 0.4206659 0.4251003 0.4699815 0.4790968 0.4451282 0.5345721 0.5025733 0.5769590 0.4911824 0.4394125 0.4559432 0.4686143 0.5428026 0.4249581 0.4929708 0.5620540 0.4164651 0.4678045 0.4748518 0.4765370 0.5299903 0.5157941 0.4457042 0.4460516 0.4563368 0.4825439 0.4316239 0.4213164 0.4282145 0.4455349 0.4521745 0.4327965 0.4703218 0.4393185
2013 0.4835584 0.5234050 0.4683951 0.4255659 0.4744708 0.4117512 0.4235945 0.4704983 0.4845484 0.4879359 0.4362170 0.4300179 0.4328662 0.5199323 0.5086692 0.4836370 0.4015998 0.4753278 0.4776261 0.4259529 0.4617518 0.5222326 0.4747473 0.4986530 0.5204217 0.4563826 0.4112796 0.4282750 0.4876955 0.4842869 0.4481891 0.5090109 0.5019399 0.5692979 0.4926062 0.4395406 0.4047603 0.4671229 0.5150850 0.4451439 0.5056646 0.5332677 0.4382350 0.4694274 0.4733619 0.5242035 0.5282950 0.5186380 0.4745637 0.4480650 0.4952765 0.4921799 0.4369753 0.4151691 0.4354673 0.4335158 0.4771952 0.4302915 0.4754400 0.4394893
2014 0.4820291 0.5197681 0.4756787 0.4360364 0.4762153 0.4646138 0.3940309 0.4679499 0.4853747 0.4496855 0.4569967 0.4693953 0.4187183 0.4978832 0.4813318 0.4460717 0.4074823 0.4308165 0.4740294 0.4314295 0.4590172 0.5144232 0.4442462 0.4666511 0.5030041 0.4551175 0.3945286 0.4565711 0.4687247 0.4600415 0.4358303 0.4994569 0.5214670 0.5675210 0.4894522 0.4310935 0.4818949 0.4767393 0.5568770 0.4257339 0.5172529 0.5136362 0.4550183 0.4576530 0.4636344 0.5246301 0.5213405 0.4639097 0.4653533 0.4396105 0.4899489 0.4910454 0.4330304 0.4576885 0.4285161 0.4148572 0.4330425 0.4479159 0.4882027 0.4685085
2015 0.4862335 0.5158704 0.4761264 0.4474197 0.4432741 0.4354812 0.4067424 0.4739327 0.4707918 0.4832002 0.4829386 0.4357726 0.4250703 0.5033790 0.4988289 0.4612579 0.4270309 0.4386275 0.4957159 0.4352802 0.4850002 0.5450526 0.4380447 0.4576773 0.5297950 0.4331191 0.3902429 0.4297338 0.4765975 0.4700296 0.4415679 0.4978626 0.5398014 0.5837829 0.4956334 0.4304847 0.4360005 0.4835759 0.5361411 0.4307450 0.4981937 0.5439760 0.4132042 0.4786314 0.4743715 0.5267191 0.5443468 0.4719732 0.4781665 0.4492091 0.4906046 0.4925038 0.4394033 0.4240575 0.4540492 0.4156889 0.4500169 0.4290336 0.4723233 0.4632752
2016 0.4827579 0.5047321 0.4686737 0.4272204 0.4854683 0.4466478 0.4438069 0.4650260 0.4855618 0.4864275 0.4711624 0.4357596 0.4241541 0.5101128 0.4900919 0.4373593 0.4226800 0.4640724 0.4800022 0.4216912 0.4770455 0.5447265 0.4743050 0.4827612 0.5053770 0.4314976 0.4007499 0.4374500 0.4714211 0.4774691 0.4445985 0.5201246 0.5112713 0.5737734 0.4888895 0.4384778 0.4274878 0.4737520 0.5364956 0.4015372 0.4899554 0.5388548 0.4285289 0.4666892 0.4698172 0.5358152 0.5434194 0.4837301 0.4608246 0.4705489 0.4819007 0.4675945 0.4588558 0.4691938 0.4315084 0.4054789 0.4330731 0.4092837 0.4912003 0.4627877
2017 0.4845617 0.5359481 0.4692387 0.4437243 0.4929206 0.4659474 0.4026137 0.4767516 0.4994322 0.4841466 0.4371400 0.4304005 0.4024221 0.5014019 0.4710632 0.4644486 0.4275155 0.4566145 0.4770459 0.4239931 0.4403345 0.5565258 0.4787219 0.4839048 0.5175983 0.4499921 0.4213370 0.4179059 0.4770907 0.4680441 0.4458051 0.5278597 0.5031280 0.5631588 0.4832527 0.4288672 0.4153733 0.4939132 0.5350650 0.4131637 0.5189418 0.5229012 0.4345920 0.4469081 0.4874779 0.5312186 0.5440585 0.4972694 0.4740183 0.4495531 0.4787442 0.4834909 0.4626974 0.4705671 0.4410584 0.4143502 0.4283044 0.4120416 0.4950851 0.4817699
2018 0.4866674 0.5316082 0.4770944 0.4221813 0.4313656 0.4498047 0.4317168 0.4467004 0.4943577 0.4824876 0.4644393 0.4510877 0.4094468 0.5151415 0.5084916 0.4782617 0.4270541 0.4788416 0.4747079 0.4564340 0.4958883 0.5344946 0.4728455 0.5020379 0.5017750 0.4501999 0.4035863 0.4421250 0.4877690 0.4726277 0.4673543 0.5281894 0.4972525 0.5682782 0.4881271 0.4544147 0.4212684 0.4722627 0.5679563 0.4296255 0.5181917 0.5472286 0.4320879 0.4409297 0.4892682 0.5135692 0.5585094 0.5392783 0.4788425 0.4501136 0.4949604 0.4802686 0.4245432 0.4128950 0.4680644 0.4427666 0.4452851 0.4509827 0.4826020 0.4512123
Gini values for the five most populous states and their PUMAs with complete data (2005-2018)
YEAR New York (36) 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755
2005 0.4952089 0.4296849 0.4234534 0.4196040 0.4253070 0.4373155 0.4015011 0.4850670 0.4264568 0.4627578 0.4556753 0.3893441 0.4437278 0.4596898 0.3814271 0.4016218 0.4521845 0.4013731 0.4941250 0.4325949 0.3799051 0.4787786 0.3929753 0.3983432 0.4092384 0.3910450 0.4371087 0.4191151 0.4162372 0.4203839 0.4916512 0.4384409 0.4734992 0.4636587 0.4127699 0.4394284 0.4286899 0.3767135 0.4172041 0.3983328 0.4529588 0.3894431 0.4312992 0.4727071 0.4488750 0.5705221 0.5415854 0.4883291 0.5093420 0.4963239 0.4399799 0.3920639 0.4491557 0.4328322 0.3541473 0.3820045 0.4255199 0.3643586 0.4874242 0.4528772 0.3839930 0.4147169 0.4928185 0.3895931 0.3916076 0.3736555 0.3650304 0.3953644 0.3933185 0.3846764 0.4707617 0.4243271 0.4710366 0.4385635 0.4997522 0.4459303 0.5144044 0.4740504 0.4829864 0.5289931 0.4909224 0.6345562 0.5085310 0.5481393 0.5432595 0.5722471 0.5324091 0.4839005 0.5239079 0.5275379 0.4520421 0.4529186 0.4397109 0.4741401 0.5103224 0.4740973 0.5141660 0.4869426 0.5307001 0.5336075 0.4699516 0.3699758 0.4134096 0.4695859 0.4996056 0.5454255 0.4904444 0.5114828 0.4924999 0.4732283 0.5395002 0.4346831 0.4042503 0.4293836 0.3961070 0.3559010 0.4352880 0.3957619 0.4512877 0.4252568 0.4201784 0.3988617 0.4185470 0.4702081
2006 0.4933160 0.3909200 0.4313751 0.4005823 0.4239106 0.4163032 0.4336323 0.5045483 0.4221858 0.4738159 0.4859731 0.3906166 0.3790050 0.4570383 0.3854703 0.4207231 0.4048016 0.4119689 0.4318408 0.4061133 0.3708648 0.5028654 0.4542806 0.4110717 0.4433228 0.4449267 0.4502688 0.4145217 0.3772595 0.4035475 0.4255293 0.4012785 0.4431784 0.4413387 0.4098556 0.4456231 0.4409238 0.4322297 0.3923819 0.3943157 0.3742987 0.4062724 0.4361046 0.4579030 0.4380952 0.5345126 0.5117994 0.4577339 0.5472483 0.5000217 0.4541025 0.4449853 0.4460899 0.4224895 0.3737151 0.3820177 0.4314897 0.4238463 0.4652092 0.4451531 0.3809689 0.4375835 0.4964719 0.4038808 0.3878975 0.3696567 0.3519090 0.4050344 0.4088134 0.3856542 0.4780829 0.4207461 0.4033761 0.4233376 0.4831680 0.4505563 0.4887486 0.4606513 0.4461869 0.4917161 0.4644057 0.5933168 0.5257885 0.5569462 0.5331292 0.5530778 0.5342204 0.5021477 0.5274927 0.5479564 0.3930308 0.4383945 0.4525282 0.5174834 0.4740447 0.5297255 0.5322284 0.4723770 0.4998947 0.5034838 0.4752757 0.3997227 0.4505059 0.4813179 0.4624948 0.4770151 0.4846985 0.4898364 0.5094972 0.4606992 0.5113123 0.4385221 0.4017412 0.4209656 0.4477264 0.3768072 0.4121138 0.4322401 0.4510778 0.4271324 0.4168745 0.3936131 0.3902730 0.4808110
2007 0.4990642 0.4264760 0.4284401 0.4220671 0.4251265 0.4164332 0.3974609 0.4591826 0.4359051 0.4934946 0.4444408 0.3828699 0.3914894 0.4608526 0.4144438 0.4489727 0.4089958 0.3997847 0.4796581 0.4228816 0.4050550 0.5147862 0.4361535 0.3633709 0.4464465 0.4145663 0.4455534 0.4148569 0.4255893 0.4142575 0.4431226 0.4437846 0.4373342 0.4926550 0.4102538 0.4128414 0.4445080 0.3959399 0.4402180 0.4443414 0.4435666 0.3874074 0.4445376 0.4728072 0.4833414 0.5559643 0.4934873 0.4874741 0.5274146 0.5249122 0.4574016 0.4334363 0.4555791 0.4069188 0.3905641 0.3703666 0.4343406 0.3788072 0.4873787 0.4385006 0.3996760 0.4175626 0.4564439 0.3578427 0.3937934 0.3687078 0.3501851 0.4071483 0.4158306 0.4014458 0.4880037 0.4036954 0.4300055 0.4520797 0.4695726 0.4733895 0.4645551 0.4863243 0.4516044 0.4961696 0.4547581 0.5987820 0.5358961 0.5725448 0.5324908 0.5716333 0.5522384 0.5117342 0.5558495 0.5366076 0.3804697 0.4401886 0.4538456 0.4716324 0.4783340 0.5229091 0.5613599 0.5290181 0.5121709 0.4792965 0.4695005 0.4030414 0.4302042 0.4450260 0.4770260 0.4915210 0.4755711 0.4813747 0.4727148 0.4696156 0.5149486 0.4640499 0.4173836 0.4401145 0.4137481 0.3516797 0.4299594 0.3841978 0.4388548 0.4119368 0.4009375 0.3957646 0.4082116 0.4979631
2008 0.5015716 0.4206390 0.4294087 0.4140624 0.4326668 0.4337247 0.4427094 0.4780058 0.4240413 0.5042909 0.4706019 0.3764954 0.3786995 0.4515896 0.3822850 0.4241324 0.4128836 0.4051479 0.4545910 0.3966003 0.3691604 0.5074660 0.4122074 0.4192275 0.4362287 0.4286044 0.4177031 0.4030280 0.3768875 0.4056611 0.4602487 0.4163671 0.4225173 0.4985240 0.3872422 0.4262885 0.4441931 0.4151348 0.4413352 0.4315179 0.4262156 0.4081745 0.4535464 0.4772243 0.4786233 0.5532856 0.5142639 0.4773163 0.5339145 0.4921749 0.4491278 0.4305785 0.4175517 0.4337778 0.3673945 0.4087105 0.4230777 0.3928593 0.4877786 0.4381973 0.4095867 0.4315765 0.5131781 0.3816056 0.3747743 0.3703294 0.3576556 0.4036118 0.3674562 0.3923592 0.4996321 0.4137042 0.4016609 0.4395491 0.4862622 0.4680367 0.4486179 0.4583977 0.4548264 0.4902684 0.4775763 0.5785711 0.5608164 0.5896508 0.5264689 0.5587205 0.5683370 0.5078039 0.5818543 0.5720701 0.3464428 0.4158546 0.4322429 0.5018787 0.4729871 0.4688373 0.5627036 0.5024855 0.5054738 0.5279906 0.5043609 0.4421804 0.4575635 0.4742014 0.4773862 0.4831174 0.5021865 0.5228010 0.4749315 0.4482282 0.4773739 0.4360558 0.4450215 0.4599476 0.4387728 0.3680641 0.4262656 0.4283089 0.4589823 0.4466118 0.4293712 0.4071907 0.4187534 0.4736569
2009 0.5017188 0.4103796 0.4212505 0.4316133 0.4217329 0.4006294 0.4221579 0.4759523 0.4343967 0.4964961 0.4778444 0.3990740 0.3842760 0.4433243 0.4139905 0.4761704 0.4259657 0.4082716 0.4727570 0.4221482 0.4062486 0.5220490 0.4523369 0.4062558 0.4235356 0.4448935 0.4073381 0.4086653 0.4252534 0.4176237 0.4629433 0.4335456 0.4880364 0.4712100 0.4419989 0.4306107 0.4437346 0.3968582 0.4326472 0.4055223 0.4318071 0.4044221 0.4604542 0.4941945 0.4746535 0.5638294 0.4997831 0.4758860 0.5351025 0.5190589 0.4483326 0.4235804 0.4335678 0.4105930 0.3783850 0.4071186 0.3945423 0.4044430 0.4428369 0.4375628 0.4189526 0.4351032 0.4786225 0.4086631 0.3910585 0.3671195 0.3675600 0.4256881 0.3684220 0.3897618 0.5230427 0.4370520 0.4450138 0.4212560 0.4767424 0.4632580 0.4794450 0.4303108 0.4566395 0.4847438 0.5199972 0.5732752 0.5488516 0.5930450 0.5414452 0.5524411 0.5583546 0.5232911 0.5420489 0.5556719 0.4005458 0.4443961 0.4881942 0.5183365 0.4757301 0.4971478 0.5844702 0.4771384 0.5344774 0.5669940 0.4832882 0.4007279 0.4292060 0.4617452 0.5118828 0.4639018 0.4807283 0.4942314 0.4484131 0.4273331 0.4802015 0.4700980 0.3928352 0.4628638 0.4150781 0.3811107 0.4249434 0.4166959 0.5208651 0.4216324 0.4227612 0.4120584 0.3724815 0.4800644
2010 0.4994055 0.4857305 0.4352844 0.3959422 0.4214368 0.4295313 0.4192820 0.5633561 0.4324216 0.4748831 0.4494559 0.3784638 0.3727261 0.4781533 0.4183748 0.4657619 0.4360475 0.4028162 0.4654319 0.3967135 0.3866878 0.5194102 0.4062439 0.4092962 0.4559047 0.4095028 0.4337462 0.4373041 0.3859476 0.4293731 0.4848287 0.4283965 0.4343962 0.4676553 0.4232175 0.4237741 0.4564168 0.4242404 0.4581175 0.4272467 0.3957616 0.4130071 0.4423916 0.4902268 0.4942600 0.5235094 0.5162195 0.4283873 0.5344081 0.5356195 0.4382663 0.4312406 0.4322562 0.4581058 0.3792431 0.3685253 0.4250470 0.3932680 0.5021168 0.4656881 0.4088511 0.4004870 0.4799502 0.3877371 0.3930950 0.4197177 0.3953537 0.4204016 0.3640872 0.3958102 0.4885072 0.4266259 0.4236219 0.4530345 0.4976461 0.4659929 0.4312842 0.4647836 0.4470907 0.4982366 0.4783739 0.6205779 0.5730280 0.5773299 0.5397612 0.5663339 0.5749428 0.5179825 0.5848686 0.5206047 0.4189697 0.4383743 0.4638175 0.4780127 0.4328878 0.5007398 0.5408424 0.5171858 0.5162864 0.5247081 0.5425132 0.4245485 0.4476556 0.4721166 0.4919788 0.4712263 0.4965139 0.4754883 0.4858457 0.4747517 0.4932917 0.4426146 0.4258321 0.4557290 0.4254955 0.3903270 0.4292967 0.4661011 0.4965061 0.4522391 0.4391539 0.4273985 0.4207980 0.5048695
2011 0.5004082 0.4291160 0.4310988 0.4215114 0.4328126 0.3960187 0.4284948 0.4937591 0.4273497 0.4906114 0.5143529 0.4262321 0.3805340 0.4901943 0.3987548 0.4583281 0.4205558 0.4083810 0.4737799 0.4199804 0.3855355 0.4960954 0.4240622 0.3822752 0.4543205 0.4274522 0.4379106 0.4153162 0.4167189 0.3975459 0.4297448 0.4133727 0.4397983 0.4651821 0.4265146 0.4210563 0.4680271 0.4395049 0.4297145 0.4744507 0.4480252 0.4266783 0.4189251 0.4911225 0.4797206 0.5299911 0.4944494 0.4566875 0.5080378 0.5185398 0.4550968 0.4246711 0.4271191 0.4454236 0.3673279 0.4222355 0.4453008 0.3869581 0.4630065 0.4549506 0.4239239 0.4181527 0.4328546 0.3778421 0.3906644 0.3577549 0.3970356 0.4106198 0.3658218 0.3917237 0.4940223 0.4662498 0.4315945 0.4768050 0.4836068 0.4553573 0.4468388 0.4744896 0.4502902 0.4687361 0.4772729 0.5533536 0.5217563 0.5693208 0.5363737 0.5549900 0.5750975 0.5192093 0.5478011 0.5137203 0.4051511 0.4301985 0.4566710 0.4983316 0.4969818 0.5316630 0.5193165 0.4959752 0.5131648 0.5179010 0.5289326 0.4189731 0.4585254 0.4804525 0.4718493 0.4748890 0.4998485 0.5025525 0.5079154 0.5018736 0.5440179 0.4757738 0.4536894 0.4791394 0.4405162 0.3762740 0.4586263 0.4315308 0.4064101 0.4330451 0.4612359 0.4418354 0.4273676 0.5029002
2012 0.4986531 0.4645344 0.4466056 0.4139117 0.4363880 0.4105991 0.4285933 0.4866393 0.4509964 0.4888380 0.5155609 0.4142822 0.3732641 0.4423440 0.4018374 0.4561703 0.4203499 0.4081671 0.4677940 0.4294761 0.3957814 0.5011181 0.4154382 0.3721154 0.4368218 0.4472043 0.4551437 0.4420760 0.4204231 0.4138516 0.4563808 0.4354285 0.4580606 0.4594902 0.3921727 0.4708753 0.4706260 0.4321564 0.4456938 0.4439275 0.4548264 0.4653024 0.4408787 0.4769072 0.5042293 0.5409991 0.5062301 0.4933706 0.5127121 0.5018166 0.4408682 0.4350511 0.4154354 0.4446267 0.3571620 0.4044523 0.4127463 0.4281002 0.4389875 0.4728800 0.4106516 0.4092803 0.4878663 0.4378642 0.4153035 0.3991970 0.3956950 0.4112467 0.3775262 0.4096873 0.5389550 0.4541415 0.4500838 0.4541157 0.4962908 0.4409718 0.4791233 0.4582100 0.4702610 0.4832763 0.4918546 0.5898752 0.5750488 0.5428116 0.5348091 0.5375080 0.5668506 0.5145303 0.5719925 0.5440571 0.4011463 0.4271310 0.4871057 0.5152409 0.4629503 0.4860320 0.5130508 0.4784439 0.5303232 0.4960131 0.4843251 0.4292069 0.4005639 0.4446233 0.5061271 0.4624683 0.5022083 0.5196973 0.4828718 0.4686056 0.4999488 0.4581461 0.4439122 0.4492291 0.4179807 0.4011092 0.4190365 0.4579326 0.4489516 0.4711734 0.4276332 0.4316381 0.4300729 0.4994783
2013 0.5095780 0.4471993 0.4647152 0.4534980 0.4403504 0.4376444 0.4309710 0.5010409 0.4455815 0.4866191 0.4614786 0.4292146 0.3856762 0.4814883 0.4475514 0.4385728 0.4242983 0.3842121 0.4711232 0.4276395 0.3892838 0.4848943 0.4438187 0.4037689 0.4740926 0.4458670 0.4421989 0.4484899 0.4074267 0.4263501 0.4486824 0.4679826 0.4890348 0.5078228 0.4164163 0.4207484 0.4512400 0.4120856 0.4329797 0.4394862 0.4800690 0.4419485 0.4704478 0.4767361 0.4912696 0.5639930 0.4910412 0.4628849 0.5523804 0.5114480 0.4633899 0.4427544 0.4366764 0.4676477 0.3855756 0.4075929 0.4622129 0.4249974 0.4993348 0.4911168 0.4034474 0.4239017 0.4952059 0.4235096 0.4116925 0.4044011 0.3981215 0.3756461 0.4246673 0.4217046 0.4649172 0.4436091 0.4569983 0.4543897 0.4831554 0.5136463 0.4741481 0.4300345 0.4729653 0.4674178 0.5130196 0.5614659 0.5308145 0.6088289 0.5387603 0.5270110 0.5593845 0.5483904 0.5631613 0.5091582 0.4273327 0.4743301 0.4893279 0.5105311 0.4723428 0.5343108 0.5579088 0.4951134 0.5475982 0.5258525 0.4947932 0.4377367 0.4278316 0.5025641 0.4833318 0.4840842 0.4845348 0.5115826 0.5013375 0.4698411 0.5938068 0.4728476 0.4775058 0.4844337 0.4559060 0.3970533 0.4368216 0.4483014 0.4510954 0.4665250 0.4647641 0.4103847 0.4490724 0.5225834
2014 0.5092288 0.4438501 0.4163214 0.4565896 0.4355897 0.4339795 0.4176862 0.5012850 0.4469904 0.4779637 0.4845685 0.3836325 0.3793097 0.4964622 0.4045974 0.4558349 0.4281103 0.4145908 0.4744507 0.4010830 0.4329497 0.5073672 0.4356477 0.4133371 0.4502590 0.4479814 0.4291102 0.4324557 0.3918503 0.4663811 0.4813087 0.4498816 0.4655690 0.4745563 0.4277345 0.4564552 0.4925916 0.4226944 0.4757822 0.4449075 0.4415598 0.4169454 0.4666231 0.4892725 0.5076159 0.5229852 0.5108220 0.4785901 0.5543923 0.5112782 0.4794213 0.4279396 0.4325234 0.4378101 0.3854171 0.4239036 0.4485016 0.4138592 0.4926503 0.4477264 0.4264719 0.4476034 0.4848493 0.4197478 0.4078201 0.3793951 0.3782909 0.3830459 0.3718993 0.4142945 0.5232402 0.4632330 0.4205773 0.4567180 0.4959612 0.4464442 0.4752379 0.4610356 0.4597135 0.4972633 0.4648996 0.5804045 0.5725868 0.5733284 0.5244109 0.5446472 0.5225995 0.5292831 0.5775254 0.5382320 0.4411939 0.4337151 0.4891125 0.4931640 0.4785862 0.5054708 0.5281703 0.4996015 0.4971331 0.4979141 0.4871775 0.4376552 0.4828397 0.4754000 0.4875121 0.5114512 0.4891244 0.4942723 0.4997978 0.4763490 0.5464522 0.4776159 0.4374162 0.4606241 0.4238851 0.3845968 0.4297728 0.4354361 0.5105836 0.4568809 0.4269852 0.4157866 0.4736179 0.5322698
2015 0.5131678 0.4527831 0.4303597 0.4520123 0.4419347 0.4355668 0.3986265 0.5133251 0.4526792 0.4783507 0.4817730 0.4068685 0.3776451 0.4657488 0.4021297 0.4616305 0.4450020 0.4136711 0.5045954 0.4202888 0.3994491 0.4977911 0.4090156 0.4145684 0.4762949 0.4355049 0.4550019 0.4163570 0.3868924 0.4464598 0.4889103 0.4563566 0.4963021 0.5007606 0.4171838 0.4260036 0.4597049 0.4213088 0.4498347 0.4566611 0.4221716 0.4371655 0.4736764 0.4851675 0.5054792 0.5643796 0.5318733 0.5137717 0.5288158 0.5289730 0.4725274 0.4376504 0.4422222 0.4523454 0.3833969 0.3906743 0.4522285 0.4389971 0.4858087 0.4763691 0.4173608 0.4406101 0.5162340 0.4161529 0.4217414 0.3952683 0.3792200 0.4494368 0.4600279 0.4292204 0.4783525 0.4549630 0.4723818 0.4872040 0.4961574 0.4880771 0.4769648 0.5232267 0.4754302 0.5515936 0.4588020 0.5825683 0.5406388 0.5857399 0.5580744 0.5817475 0.5538227 0.5336821 0.5727502 0.5460266 0.3915315 0.4512981 0.4998786 0.5262382 0.5026086 0.5629947 0.5530791 0.4834380 0.5050872 0.5259590 0.5062430 0.4593360 0.4271773 0.4689741 0.5368920 0.4743905 0.4889079 0.5238418 0.4884952 0.4767098 0.4940866 0.4601819 0.4268592 0.4763803 0.4218989 0.3842554 0.4543809 0.4311148 0.5007492 0.4727564 0.4712206 0.4060398 0.4189644 0.4887229
2016 0.5109897 0.4458786 0.4586450 0.4193621 0.4455175 0.4378957 0.4224121 0.5274996 0.4409318 0.5038330 0.5173618 0.3867343 0.4144427 0.4756429 0.4052159 0.4531720 0.3956472 0.3970928 0.4792445 0.4256882 0.4057902 0.5239445 0.4295668 0.3836667 0.4458003 0.4604684 0.4577582 0.4422277 0.4174876 0.4342771 0.5034398 0.4495004 0.4789545 0.4727331 0.4172330 0.4219298 0.4774248 0.4371871 0.4577934 0.4443175 0.5015752 0.4012026 0.4593544 0.4857991 0.4970281 0.5144370 0.5082986 0.4984660 0.5360742 0.5125871 0.4635564 0.4402138 0.4192686 0.4467570 0.3854831 0.3882253 0.4408799 0.3867065 0.4885458 0.4508174 0.4123681 0.4446394 0.4813661 0.4171789 0.4301252 0.4083214 0.4427176 0.4184438 0.4056692 0.4290782 0.4966768 0.4613319 0.4128804 0.4525013 0.4766593 0.4627742 0.4554418 0.4742836 0.4528960 0.5346745 0.4781940 0.5909154 0.5791525 0.5916248 0.5457979 0.5732935 0.5727750 0.5176563 0.5903714 0.5276183 0.4455050 0.4926880 0.4662306 0.5103189 0.5237364 0.5074461 0.5481582 0.5146400 0.5681435 0.5864901 0.4968016 0.4279298 0.4651755 0.4498324 0.4934502 0.4695791 0.5160827 0.4821630 0.4641504 0.4864931 0.5020401 0.4739477 0.4611183 0.4681341 0.4506624 0.3984560 0.4557944 0.4583296 0.4775947 0.4522857 0.3875402 0.4223863 0.4279462 0.5193675
2017 0.5133048 0.4390952 0.4361612 0.4283718 0.4465300 0.4307420 0.4096262 0.4922844 0.4525515 0.4965161 0.5523922 0.4057880 0.3838844 0.4908541 0.4171472 0.4499472 0.4149301 0.3969495 0.4641672 0.4348386 0.4052074 0.4993991 0.4250625 0.4073825 0.4477052 0.4185024 0.4357497 0.4227102 0.4291757 0.4410922 0.4813280 0.4404897 0.4606338 0.4774978 0.4310697 0.4420961 0.4552506 0.4277668 0.4765340 0.4136780 0.4254961 0.4132597 0.4690448 0.5006799 0.5129393 0.5277206 0.5066388 0.4863264 0.5420323 0.5375896 0.4792384 0.4585591 0.4400228 0.4455545 0.3826577 0.3799938 0.4383157 0.3639176 0.4927064 0.4773364 0.4448784 0.4449447 0.4985532 0.4434179 0.4037248 0.4110094 0.4225553 0.3899918 0.3963004 0.4237362 0.5287787 0.4684995 0.4999871 0.4586739 0.5200127 0.4348322 0.5139430 0.4874222 0.4687188 0.5003840 0.4525503 0.5694888 0.5962892 0.5773970 0.5200095 0.5551674 0.5469160 0.5344376 0.5754172 0.5293937 0.4324759 0.4650699 0.5077884 0.5099377 0.4965811 0.5278703 0.5263335 0.4905645 0.5498917 0.5888529 0.5159336 0.4281502 0.4679347 0.4976109 0.5523986 0.4935866 0.5026908 0.5061892 0.4792024 0.4766244 0.5490759 0.4555136 0.4046167 0.5044982 0.4621766 0.4016909 0.4244965 0.4386508 0.4582579 0.4562146 0.4190306 0.4384276 0.4492962 0.5058020
2018 0.5115166 0.4465775 0.4404974 0.4437568 0.4404350 0.4109288 0.4691333 0.4822936 0.4553043 0.4899222 0.4374544 0.4181261 0.4263630 0.4478830 0.4345759 0.4872286 0.4292767 0.4268098 0.4806964 0.4237530 0.4071723 0.4786518 0.4245593 0.4127674 0.4508224 0.4794792 0.4376227 0.3893372 0.4565165 0.3891778 0.4798524 0.4299220 0.4735731 0.5323586 0.4297557 0.4624724 0.4676479 0.4722793 0.4517702 0.4591106 0.4441298 0.4611734 0.4802547 0.4835061 0.4875880 0.5362213 0.5294755 0.4938092 0.5571595 0.4980371 0.4672930 0.4469478 0.4402268 0.4467854 0.3604831 0.3960967 0.4588610 0.3943049 0.4696316 0.4535228 0.4175180 0.4127273 0.5034513 0.4292052 0.4177738 0.3959029 0.4242637 0.4274277 0.3766613 0.4301894 0.5659401 0.5030548 0.4532270 0.4405562 0.5558824 0.4905231 0.4656438 0.4607815 0.5138325 0.5139763 0.4602157 0.5233104 0.5966623 0.5991165 0.5250664 0.5615444 0.5726407 0.5108074 0.6026699 0.5267678 0.4639832 0.4113586 0.4847897 0.5476135 0.4910666 0.5399749 0.5380511 0.5173028 0.5008578 0.5380046 0.5154136 0.4317321 0.4614888 0.4947131 0.5035460 0.4928378 0.4987961 0.4706030 0.5341554 0.4549878 0.5235632 0.4564120 0.4301223 0.5022522 0.3968588 0.4137497 0.4345763 0.4089329 0.4644733 0.4417204 0.4330516 0.4134835 0.4288816 0.4953064
Gini values for the five most populous states and their PUMAs with complete data (2005-2018)
YEAR Pennsylvania (42) 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908
2005 0.4514464 0.4518754 0.4105195 0.4340597 0.4218782 0.4343543 0.4095989 0.4516546 0.4602622 0.4419068 0.4121957 0.4011782 0.4544228 0.4168608 0.4047550 0.4279356 0.4137252 0.5388295 0.4423161 0.4594864 0.4203174 0.4295951 0.4196115 0.4350987 0.4216297 0.4343333 0.3807796 0.4071944 0.4300545 0.4095328 0.4623623 0.4285088 0.4223065 0.4253051 0.4556743 0.4327977 0.4299582 0.4443976 0.4194991 0.4693852 0.4920873 0.5367711 0.4966358 0.4969065 0.4883476 0.4761150 0.4596752 0.4424145 0.4331186 0.3994990 0.3896568 0.3861208 0.3676468 0.3881004 0.4193246 0.4212848
2006 0.4531325 0.4437106 0.4159953 0.4195481 0.4078173 0.4166520 0.4142729 0.4170530 0.4337637 0.4330871 0.4210409 0.4311491 0.4809039 0.4608257 0.4400770 0.4061394 0.4140132 0.5307886 0.4493365 0.4713394 0.4418520 0.4070154 0.4403526 0.3889217 0.4367706 0.4284426 0.3888651 0.3966053 0.4163000 0.3931261 0.3931045 0.3940760 0.4164967 0.4217099 0.4358772 0.4260700 0.4418055 0.4073264 0.4628241 0.4252602 0.4941389 0.5536027 0.4884425 0.5209570 0.4857811 0.5030071 0.4220369 0.4350363 0.4448440 0.4194715 0.4039778 0.3412000 0.3828897 0.4153350 0.4363508 0.4387759
2007 0.4604500 0.4338297 0.4238315 0.4275515 0.4397648 0.4321521 0.4157561 0.4404642 0.4288031 0.4451989 0.4121879 0.4544414 0.4700314 0.4114385 0.4248695 0.4290286 0.4340146 0.5639337 0.4620345 0.5007892 0.4750233 0.4217486 0.4625753 0.4306008 0.4446787 0.4229489 0.3805260 0.4135743 0.4296467 0.3951102 0.4203635 0.4248860 0.4097759 0.4023153 0.4622326 0.4244625 0.4636975 0.4520046 0.4678210 0.4465967 0.4848100 0.5201745 0.4444240 0.5286915 0.4564993 0.4470414 0.4578299 0.4409872 0.4319025 0.4057346 0.4341652 0.3843938 0.3895090 0.4481659 0.4214888 0.4269181
2008 0.4540986 0.4449142 0.4026597 0.4155730 0.4146807 0.4078440 0.3667500 0.4308317 0.4663000 0.4412282 0.4249367 0.4085490 0.4675304 0.3937538 0.4378414 0.4254341 0.4233507 0.5635322 0.4486516 0.4558690 0.4261892 0.4122573 0.4520446 0.4348664 0.4515449 0.4265375 0.3945765 0.3899591 0.4421634 0.3724373 0.4340895 0.4150942 0.4072927 0.4110116 0.4318435 0.4209481 0.4465885 0.3758777 0.4333621 0.4256836 0.4749636 0.5334710 0.5038462 0.5203348 0.4721034 0.4441217 0.4726373 0.4452619 0.4387859 0.4106734 0.4251581 0.3658746 0.3803774 0.3763413 0.4400236 0.4293506
2009 0.4596238 0.4421446 0.4404503 0.4296248 0.4151231 0.3903813 0.4305190 0.4396118 0.4404769 0.4569567 0.4139908 0.4463934 0.4605155 0.4171907 0.3996303 0.4162498 0.4216736 0.5350856 0.4624659 0.4864677 0.4225608 0.4082828 0.4438775 0.4373047 0.3861634 0.4435472 0.3724950 0.4089513 0.4451061 0.4317204 0.4081408 0.4116216 0.4091840 0.4155697 0.4749071 0.4203136 0.4549003 0.4052592 0.4619170 0.4698924 0.4990038 0.5065005 0.5011296 0.5134836 0.5073160 0.4737963 0.4344758 0.4480968 0.4478815 0.4087904 0.4020211 0.4092546 0.4134216 0.4131122 0.4454199 0.4321950
2010 0.4592992 0.4491782 0.4276906 0.4132352 0.4253879 0.4089536 0.4142345 0.4690507 0.4265644 0.4594123 0.4260560 0.4352130 0.4485894 0.4294203 0.4255441 0.4366010 0.3962830 0.5538135 0.4475432 0.4846945 0.4398644 0.4354075 0.4515385 0.4179210 0.4300519 0.4316500 0.3762492 0.4240564 0.4461767 0.4181372 0.4258525 0.4341072 0.4215451 0.4254067 0.4579607 0.4373435 0.4410932 0.4006939 0.4575080 0.4606132 0.5276875 0.5371584 0.5426905 0.4962773 0.5100597 0.4924143 0.4424935 0.4480715 0.4335900 0.4158130 0.4227763 0.3710612 0.3820708 0.3913741 0.4419600 0.4461246
2011 0.4604582 0.4567905 0.4233157 0.4277035 0.4391240 0.4164306 0.4236228 0.4330279 0.4344843 0.4541241 0.4278767 0.4338000 0.4821385 0.4526434 0.4561753 0.4373369 0.4589037 0.5751964 0.4393442 0.4560367 0.4322162 0.4428243 0.4728350 0.4216092 0.4171320 0.4243352 0.4056957 0.4037711 0.4457863 0.4217361 0.4037125 0.4282337 0.4297925 0.4426228 0.4275476 0.4240741 0.4515387 0.4598477 0.4781112 0.4311650 0.4653417 0.5114699 0.5368260 0.5359368 0.4663005 0.4942462 0.4637768 0.4502152 0.4417718 0.3963351 0.4336319 0.3926916 0.3911759 0.3944963 0.3987022 0.4419189
2012 0.4641501 0.4526331 0.4474486 0.4146019 0.4270108 0.4230013 0.4110049 0.4500496 0.4437058 0.4652436 0.4359134 0.4492412 0.4648492 0.4118916 0.4528031 0.4299983 0.4375898 0.5524824 0.4364225 0.4597876 0.4392268 0.4409367 0.4426218 0.4432843 0.4273051 0.4315318 0.4071846 0.4514929 0.4497650 0.4159925 0.4048453 0.4521879 0.3928335 0.4191322 0.4495601 0.4391943 0.4615522 0.4403354 0.4641279 0.4570713 0.5067003 0.5203910 0.5052652 0.5311640 0.5356967 0.4278744 0.4772347 0.4652622 0.4558402 0.4090785 0.4366496 0.3923175 0.4139209 0.3948811 0.4493364 0.4394099
2013 0.4691303 0.4671471 0.4289154 0.4226842 0.4292208 0.4078714 0.4270553 0.4524710 0.4411145 0.4594942 0.4327002 0.4248457 0.4564970 0.4360970 0.4125202 0.4367745 0.4621339 0.5630183 0.4584435 0.4626259 0.4436329 0.4406571 0.4506777 0.4703844 0.4418484 0.4320336 0.4106078 0.4330029 0.4381780 0.4355367 0.4435501 0.4306564 0.4335592 0.4512973 0.4280374 0.4481702 0.4762000 0.4218729 0.4596209 0.4455983 0.5400159 0.5251556 0.5002794 0.5202801 0.4870670 0.4923599 0.4616881 0.4768101 0.4569951 0.4100169 0.4448159 0.4027670 0.3913153 0.3948121 0.4429662 0.4481396
2014 0.4673423 0.4602237 0.4424092 0.4114791 0.4299251 0.4365128 0.4042321 0.4630208 0.4516336 0.4390370 0.4394884 0.4260018 0.4952571 0.4257576 0.4713568 0.4472158 0.4547086 0.5477010 0.4612662 0.4811775 0.4324533 0.4352536 0.4700530 0.4400940 0.4559144 0.4465258 0.4186741 0.4111820 0.4624897 0.3843187 0.4175845 0.4296596 0.3827888 0.4535706 0.4387311 0.4399624 0.4615897 0.4564734 0.4725628 0.4699336 0.4951532 0.4862053 0.5311282 0.4934864 0.5071316 0.4432337 0.4504550 0.4738594 0.4484033 0.4251287 0.4261075 0.3993244 0.4293832 0.4123128 0.4519943 0.4609872
2015 0.4689562 0.4454850 0.4019913 0.4178917 0.4527258 0.4329694 0.4157166 0.4885285 0.4507825 0.4499422 0.4364496 0.4235569 0.4628520 0.4324267 0.4836645 0.4311667 0.4284430 0.5815820 0.4608338 0.4831646 0.4561076 0.4416517 0.4501111 0.4663028 0.4516450 0.4359940 0.4201947 0.4129488 0.4294688 0.4273085 0.4510916 0.4583533 0.4241289 0.4319089 0.4474020 0.4498328 0.4694425 0.4484461 0.4474892 0.4652685 0.5027606 0.4912344 0.5066521 0.4868207 0.4875121 0.4709370 0.4616100 0.4498000 0.4503531 0.4493136 0.4033064 0.3610583 0.3980815 0.4003971 0.4760602 0.4515638
2016 0.4672412 0.4483663 0.4303250 0.4443662 0.4141024 0.4454951 0.3915314 0.4808261 0.4430726 0.4556075 0.4271300 0.4391887 0.4933007 0.4301787 0.4477059 0.4518635 0.4339385 0.5514850 0.4461694 0.4789680 0.4323450 0.4548018 0.4428080 0.4233572 0.4727377 0.4293791 0.3834814 0.3987461 0.4357886 0.4100033 0.4260180 0.4383395 0.4634143 0.4254372 0.4803817 0.4444848 0.4589420 0.4313636 0.4774547 0.4654511 0.5082667 0.6178672 0.5108107 0.5061559 0.4567333 0.4879923 0.4565086 0.4677670 0.4531290 0.4295932 0.4064189 0.3685830 0.4222802 0.4189433 0.4342475 0.4715876
2017 0.4763948 0.4708133 0.4199580 0.4391895 0.4492314 0.4135338 0.4353773 0.4565934 0.4295896 0.4531584 0.4188145 0.4404254 0.4755407 0.4324168 0.4612925 0.4410875 0.4479544 0.5677820 0.4579042 0.4881157 0.4359799 0.4312461 0.4653328 0.4254184 0.4665330 0.4249912 0.4052534 0.4258291 0.4438332 0.4173470 0.4131257 0.4569721 0.4175655 0.4670049 0.4839672 0.4554054 0.4599064 0.4362515 0.5503529 0.5817560 0.5253293 0.7072820 0.5352602 0.5165204 0.5297366 0.4944536 0.4629739 0.4719234 0.4426880 0.4083636 0.4245329 0.3803648 0.4020527 0.3999538 0.4258338 0.4659360
2018 0.4716892 0.4614758 0.4160487 0.4277211 0.4284202 0.4489026 0.4231629 0.4312509 0.4214666 0.4258350 0.4108551 0.4919149 0.4789302 0.4494706 0.4172891 0.4310448 0.4685284 0.5640185 0.4635742 0.4827203 0.4122642 0.4252723 0.4748336 0.4378529 0.4189633 0.4182725 0.4240940 0.4305393 0.4679649 0.3971601 0.4544152 0.4377843 0.4399330 0.4423950 0.4450450 0.4437190 0.4583198 0.4515403 0.4759971 0.4594160 0.4918972 0.5473916 0.5215608 0.5239640 0.5325182 0.5153283 0.4942462 0.4737346 0.4483197 0.4132480 0.4499488 0.4116445 0.4088786 0.4076987 0.4502859 0.4546902
Gini values for the five most populous states and their PUMAs with complete data (2005-2018)
YEAR Texas (48) 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002
2005 0.4725611 0.4308579 0.4835068 0.4410594 0.4645173 0.4754570 0.4609106 0.4397255 0.4173852 0.4175006 0.4546943 0.4794858 0.4800996 0.4850489 0.4438711 0.4548568 0.4273553 0.4276161 0.3786066 0.4173098 0.4821843 0.4432620 0.4279504 0.4725233 0.4633725 0.4595085 0.4619744 0.5208588 0.4661917 0.5457543 0.5370137 0.3925145 0.4557327 0.5018573 0.4049998 0.4392567 0.4548247 0.4807418 0.4376957 0.4455973 0.4134774 0.3781202 0.4857575 0.4509518 0.4668552 0.4802758 0.4732561 0.4781441 0.5289508 0.4933219
2006 0.4721527 0.4467988 0.4546914 0.4428624 0.4565853 0.4776448 0.4453025 0.4564705 0.5280957 0.4346987 0.4490427 0.4608312 0.4476608 0.4634870 0.4339325 0.4658555 0.4293302 0.4259405 0.4060170 0.4042981 0.4824618 0.4473427 0.4040034 0.5204884 0.4261447 0.4563277 0.4738979 0.5042810 0.4616582 0.5201798 0.4851311 0.4230556 0.4729913 0.4500014 0.4742881 0.4254583 0.5105756 0.4812090 0.4429886 0.4270380 0.4295194 0.3764637 0.4817026 0.4271318 0.4506900 0.4331479 0.4620501 0.4779125 0.4902813 0.4913083
2007 0.4717420 0.4466280 0.4626271 0.4616135 0.4438659 0.4833261 0.4519450 0.4384165 0.4497759 0.4326938 0.4247551 0.4991428 0.4306168 0.4789234 0.4509017 0.4478901 0.4032676 0.4150282 0.4214058 0.4124913 0.4885453 0.4470588 0.4417783 0.5126624 0.4631576 0.4610760 0.4798866 0.4851801 0.4659498 0.5409961 0.5243157 0.4149131 0.4480999 0.4668066 0.4491692 0.3897808 0.4709261 0.4876971 0.4643575 0.4199462 0.4273357 0.3675089 0.4741435 0.4271752 0.4614371 0.4997610 0.4566852 0.4744275 0.4916346 0.4810195
2008 0.4736132 0.4418011 0.4918107 0.4655813 0.4632755 0.5123214 0.4510523 0.4452980 0.4314318 0.4318065 0.4508531 0.4859059 0.4544304 0.4432575 0.4564419 0.4240082 0.4240830 0.4255441 0.4000137 0.4206920 0.4949218 0.4449223 0.4716392 0.4594670 0.4777250 0.4447462 0.4588360 0.5122711 0.4543704 0.5175674 0.5411455 0.4143119 0.4518105 0.4848395 0.4898373 0.4268458 0.4450274 0.4848931 0.4514079 0.4155321 0.4115354 0.3799043 0.4856581 0.4286441 0.4740120 0.4964138 0.4593149 0.4892704 0.4805732 0.5014416
2009 0.4741431 0.4380456 0.4515148 0.4259194 0.4381517 0.4795730 0.4622356 0.4465344 0.4530798 0.4302052 0.4602598 0.4626231 0.4508380 0.4992373 0.4692483 0.4608867 0.4339767 0.4220795 0.4117835 0.4437399 0.4932366 0.4535970 0.4326879 0.4890287 0.4507466 0.4630259 0.4521182 0.4931121 0.4672824 0.5380215 0.4790727 0.4506156 0.4836209 0.4553646 0.4304950 0.4697316 0.4751278 0.4841383 0.4602440 0.4057488 0.4183167 0.3563806 0.4807336 0.4255310 0.4667609 0.4945885 0.4451838 0.4752785 0.5058073 0.4959036
2010 0.4680554 0.4388502 0.4241250 0.4122847 0.4512666 0.4988942 0.4460455 0.4411661 0.4518809 0.4346038 0.4316689 0.4587889 0.4504926 0.4783565 0.4557157 0.4494634 0.4282632 0.4246320 0.4460716 0.4056721 0.4814577 0.4468049 0.4733599 0.4812277 0.4933587 0.4758675 0.4624208 0.5226951 0.4586467 0.5357907 0.4826018 0.3966229 0.4845726 0.4269446 0.4717126 0.4351943 0.4579122 0.4787774 0.4496821 0.4226734 0.4383064 0.3864428 0.4837764 0.4182631 0.4551341 0.4645724 0.4750433 0.4659826 0.4825427 0.4853911
2011 0.4753711 0.4384498 0.4708515 0.4750636 0.4862440 0.5158949 0.4881130 0.4567340 0.4258286 0.4415611 0.4726964 0.4657527 0.4681772 0.4999504 0.4624844 0.4549869 0.4251361 0.4172678 0.3996370 0.3906052 0.4871131 0.4571098 0.4706051 0.4617506 0.4292024 0.4400409 0.4590880 0.5187869 0.4677161 0.5449617 0.5067472 0.4349701 0.4786527 0.4699253 0.4499221 0.4496627 0.4836815 0.4928330 0.4457565 0.4313966 0.4185794 0.4002154 0.4904672 0.4154608 0.4647944 0.4728030 0.4399121 0.4857871 0.4902389 0.4911304
2012 0.4747593 0.4394835 0.4752309 0.4175149 0.4769290 0.5223824 0.4431794 0.4517069 0.4399136 0.4577715 0.4768717 0.4553420 0.4414471 0.4698103 0.4881871 0.4709294 0.4294362 0.4187528 0.4034737 0.3820759 0.4841582 0.4503709 0.5090438 0.4800470 0.4236378 0.4862952 0.4742821 0.5740410 0.4703045 0.5413956 0.4798930 0.4354223 0.4558159 0.4532929 0.4706390 0.4109510 0.4899535 0.4939168 0.4402665 0.4295296 0.4161513 0.3792216 0.4909889 0.4257938 0.4662686 0.4563911 0.4715271 0.4697746 0.4961252 0.5027146
2013 0.4791761 0.4351143 0.5198347 0.4382044 0.4599066 0.5348343 0.4450929 0.4585726 0.4642417 0.4448070 0.4519728 0.5285233 0.4638031 0.4552086 0.4822268 0.4529608 0.4339272 0.4280273 0.4201986 0.4141874 0.5050793 0.4629536 0.4420492 0.4730999 0.4539033 0.4947959 0.4603408 0.5169941 0.4611306 0.5284422 0.5293096 0.4245807 0.4679580 0.4815435 0.4780397 0.4459001 0.4965527 0.4949934 0.4683650 0.3995000 0.4414313 0.4095375 0.4796141 0.4234278 0.4617014 0.4521708 0.4901281 0.4656343 0.5001173 0.4905918
2014 0.4817846 0.4389181 0.4694182 0.4387824 0.4638818 0.4777342 0.4714870 0.4523368 0.4822031 0.4451089 0.4319831 0.4681408 0.4478050 0.4728045 0.4743452 0.4458383 0.4249475 0.4477435 0.4008264 0.4400655 0.4985013 0.4650672 0.4781956 0.4732104 0.4507571 0.4467435 0.4508187 0.5213257 0.4811474 0.5159521 0.5014883 0.4269430 0.4579149 0.4690991 0.4356681 0.4627084 0.4964343 0.4974609 0.4775474 0.4210351 0.4293864 0.4034516 0.4866068 0.4256989 0.4708446 0.4930683 0.4968717 0.4756869 0.4843177 0.5061090
2015 0.4818033 0.4427203 0.4759411 0.4375245 0.4363355 0.4748644 0.4554205 0.4650338 0.4456764 0.4621434 0.4977018 0.4873275 0.4403542 0.4736962 0.4710802 0.4365562 0.4293786 0.4374662 0.4190004 0.4318852 0.5009076 0.4685987 0.4761751 0.4658036 0.4406296 0.4772508 0.4372608 0.4367266 0.4834616 0.5167429 0.5017278 0.4374406 0.4824845 0.5005207 0.4526976 0.4507367 0.4639973 0.4957138 0.4823791 0.4456566 0.4410031 0.4035250 0.4902037 0.4086482 0.4624667 0.4549919 0.4843522 0.4850781 0.4882358 0.5057856
2016 0.4787102 0.4574667 0.4684209 0.4511856 0.4259632 0.5064289 0.4838305 0.4513803 0.4584048 0.4386035 0.4470067 0.4840580 0.4627582 0.4489944 0.4480368 0.4683204 0.4333782 0.4386493 0.4139604 0.4069081 0.4860618 0.4513199 0.4429837 0.4756049 0.4730189 0.4546565 0.4435591 0.5167262 0.4754138 0.5430912 0.5327594 0.4340684 0.4557421 0.4721144 0.4570209 0.4523314 0.4905771 0.4976812 0.4781799 0.4180531 0.4447485 0.4022360 0.4757437 0.4309105 0.4612435 0.4829057 0.5085376 0.4666465 0.4990150 0.4979721
2017 0.4763822 0.4405759 0.4663925 0.4258166 0.4172836 0.5327494 0.4870233 0.4512124 0.4906793 0.4371686 0.4530439 0.4578350 0.4517322 0.4671533 0.4356279 0.4502011 0.4298802 0.4321740 0.3974054 0.3733873 0.4840405 0.4511126 0.4573214 0.4313703 0.4140610 0.4701844 0.4501194 0.5371913 0.4817076 0.5066398 0.5050169 0.4221685 0.4615420 0.4817389 0.5100251 0.4594455 0.4821566 0.4964634 0.4586038 0.4351159 0.4361629 0.4054708 0.4722888 0.4253694 0.4651620 0.4838655 0.4610366 0.4825208 0.4898126 0.4910716
2018 0.4799454 0.4587995 0.5014638 0.4132385 0.4804489 0.5042699 0.4545657 0.4447247 0.4719481 0.4354140 0.4459333 0.4980920 0.4666510 0.4802739 0.4627629 0.4788045 0.4388741 0.4349756 0.3802584 0.4086477 0.4886928 0.4584392 0.4459782 0.4596877 0.4387302 0.4383721 0.4626203 0.5340457 0.4745312 0.5238015 0.4993978 0.4165781 0.4884989 0.4514755 0.4764067 0.4457362 0.5007063 0.4950004 0.4835502 0.4332044 0.4361040 0.3914909 0.4876535 0.4396216 0.4728957 0.4670150 0.4720010 0.4798062 0.4743696 0.4935517

Finally, we want to get a sense of trends at the state and local levels. Considering the restricted sample of the five most populous states (CA, FL, NY, PA, and TX), the following analysis describes the trends for the “average” state and county. The Hodrick-Prescott filter models the trend by obtaining filter weights \(\hat{\beta_{j}} = argmin E[(y_t - \hat{y_t}^2]\), where the filter, \(B(L)\), is a function of weights and a lag operator \(L\): \(B(L) = \sum_{j=-\infty}^{\infty}B_jL^j\), and \(L^kx_t = x_{t-k}\). The filter is used in the model \(y_t = B(L)x_t\) to predict time series outcomes.

### sort pumas by increase in gini
df.deltas <- puma_state_gini %>% 
  dplyr::select(YEAR, hh_inc, PUMA, STATEFIP, LEVEL) %>% 
  pivot_wider(names_from = YEAR, values_from = hh_inc) %>%
  na.omit() %>%
  mutate(delta = `2018` - `2005`,
         quint = ntile(delta, 5))

# mean income deltas as well
df.inc.deltas <- puma_state_gini %>%
  dplyr::select(YEAR, hh_inc_mn, PUMA, STATEFIP, LEVEL) %>%
  pivot_wider(names_from = YEAR, values_from = hh_inc_mn) %>%
  na.omit() %>%
  mutate(delta_inc = `2018` - `2005`)

ggplot(df.deltas, aes(x = delta, col = LEVEL))+
  geom_density(lwd = 2)+
  geom_vline(xintercept = 0)+
  theme_minimal()+
  labs(title = "Distribution of change in inequality (2018 Gini - 2005 Gini)",
       caption = "States were excluded from this analysis, as there were only 6 values.")

ggplot(df.inc.deltas, aes(x = delta_inc, col = LEVEL))+
  geom_density(lwd = 2)+
  geom_vline(xintercept = 0)+
  theme_minimal()+
  labs(title = "Distribution of change in income (2018 Mean - 2005 Mean)",
       caption = "Incomes are standardized to 1999 dollars (using the CPI adjustment factor). States excluded.")

puma_state_gini <- puma_state_gini %>% # check that this is working
  left_join(dplyr::select(df.deltas, PUMA, delta, quint)) %>%
  left_join(dplyr::select(df.inc.deltas, PUMA, delta_inc))
## Joining, by = "PUMA"
## Joining, by = "PUMA"
####### join county and state estimates

ggplot(puma_state_gini, aes(x = YEAR, y = hh_inc, color = LEVEL)) + 
  geom_point() + 
  facet_wrap(~LEVEL)  + 
  labs(title = "Gini estimates at the state and PUMA levels, (2005-2018)")

state_ts <- puma_state_gini %>%
  filter(LEVEL == "State") %>%
  group_by(YEAR, STATEFIP) %>%
  summarise(gini = mean(hh_inc))

`California (6)` <- ts(state_ts$gini[state_ts$STATEFIP == "06"],  # need to assign to name of state
               start = 2005, end = 2018)
`Florida (12)` <- ts(state_ts$gini[state_ts$STATEFIP == "12"],  # need to assign to name of state
               start = 2005, end = 2018)
`New York (36)` <- ts(state_ts$gini[state_ts$STATEFIP == "36"],  # need to assign to name of state
               start = 2005, end = 2018)
`Pennsylvania (42)` <- ts(state_ts$gini[state_ts$STATEFIP == "42"],  # need to assign to name of state
               start = 2005, end = 2018)
`Texas (48)` <- ts(state_ts$gini[state_ts$STATEFIP == "48"],  # need to assign to name of state
               start = 2005, end = 2018)

# looping wouldn't work with the plot names
state.hp.6 <- hpfilter(`California (6)`)
plot(state.hp.6)

state.hp.12 <- hpfilter(`Florida (12)`)
plot(state.hp.12)

state.hp.36 <- hpfilter(`New York (36)`)
plot(state.hp.36)

state.hp.42 <- hpfilter(`Pennsylvania (42)`)
plot(state.hp.42)

state.hp.48 <- hpfilter(`Texas (48)`)
plot(state.hp.48)

For the five most populous states, we notice a rise in inequality from close to 2008 through 2018. The total increase is roughly 0.02 points for each of these states, although the starting points are different (for example, PA is at 0.45 in 2005 while NY is at 0.495). Texas shows the least increase in Gini, rising only about 0.01 points.

puma_ts <- puma_state_gini %>%
  filter(LEVEL == "PUMA") %>%
  group_by(YEAR, quint) %>%
  summarise(gini = mean(hh_inc))

`1st Quintile` <- ts(puma_ts$gini[puma_ts$quint == "1"],  # need to assign to name of state
               start = 2005, end = 2018)
`2nd Quintile` <- ts(puma_ts$gini[puma_ts$quint == "2"],  # need to assign to name of state
               start = 2005, end = 2018)
`3rd Quintile` <- ts(puma_ts$gini[puma_ts$quint == "3"],  # need to assign to name of state
               start = 2005, end = 2018)
`4th Quintile` <- ts(puma_ts$gini[puma_ts$quint == "4"],  # need to assign to name of state
               start = 2005, end = 2018)
`5th Quintile` <- ts(puma_ts$gini[puma_ts$quint == "5"],  # need to assign to name of state
               start = 2005, end = 2018)

# looping wouldn't work with the plot names
puma.hp.1 <- hpfilter(`1st Quintile`)
plot(puma.hp.1)

puma.hp.2 <- hpfilter(`2nd Quintile`)
plot(puma.hp.2)

puma.hp.3 <- hpfilter(`3rd Quintile`)
plot(puma.hp.3)

puma.hp.4 <- hpfilter(`4th Quintile`)
plot(puma.hp.4)

puma.hp.5 <- hpfilter(`5th Quintile`)
plot(puma.hp.5)

At the PUMA level, the 3rd and 4th quintiles (measured by absolute Gini difference from 2005-2018) show increases in Gini that mirror the state-level results (roughly a 0.02 point increase). However, the first quintile shows stable or slightly declining Gini values, while the second quintile shows only a very slight increase. The fifth quintile, on the other hand, shows an increase of nearly 0.05 points.

Now, we compare PUMA level trends in gini coefficients to trends in mean household income. For this analysis, I classified PUMAs into nine groups: increasing, stable, and decreasing, based on their Gini Coefficient and mean income values in 2005 and 2018.

To classify substantial change over time, I converted the mean PUMA standard errors to a margin of error by multiplying by \(MOE_{\delta} = 1.96 \cdot \sqrt{2\bar{SE}_{PUMA}^2}\). Any PUMAs where the Gini rose by more than 0.0417 points, or where the mean income rose by more than $6,769 were classified as increasing (the same threshold was used for decreasing Gini Coefficients and mean income levels). Of the 397 PUMAs in the five largest U.S. states, six are classified as having decreasing Gini coefficients, 326 are classified as stable, and 62 are classified as increasing. For mean income, only one PUMA is classified as decreasing, 248 are classified as stable, and 147 are classified as increasing. Because incomes are standardized at 1999 dollars, this means that a large number of localities saw increases in average earnings during the time period examined. However, only some of these areas experienced substantial rises in inequality (and another group experienced a rise in inequality with no major increase in mean earnings). Further analyses is needed to ajudicate between residential sorting/migration as opposed to changes in local economies.

gini_change <- puma_state_gini %>% filter(LEVEL == "PUMA") %>% dplyr::select(se) %>% summarise(moe = 1.96*mean(se)*sqrt(2)) %>% unlist()

hh_inc_change <- puma_state_gini %>% filter(LEVEL == "PUMA") %>% dplyr::select(hh_inc_se) %>% summarise(moe = 1.96*mean(hh_inc_se)*sqrt(2)) %>% unlist()


df.change.puma <- puma_state_gini %>% filter(LEVEL == "PUMA") %>%
  mutate(gini_change = recode(cut(delta, breaks = c(-Inf,-gini_change, gini_change, Inf), 
                           labels = FALSE), "1" = "decreasing gini",
                           "2" = "stable gini", "3" = "increasing gini"),
         inc_change = recode(cut(delta_inc, breaks = 
                                   c(-Inf, -hh_inc_change, hh_inc_change, Inf),
                          labels = FALSE), "1" = "decreasing mean income",
                          "2" = "stable mean income", "3" = "increasing mean income"))
  

df.change.table <- table(df.change.puma$gini_change, df.change.puma$inc_change)/14



print(kable(df.change.table[c(1,3,2),c(1,3,2)], caption = "Gini and mean income trends for PUMAs in the five most populous states (2005-2018)") %>%
  kable_styling())
Gini and mean income trends for PUMAs in the five most populous states (2005-2018)
decreasing mean income stable mean income increasing mean income
decreasing gini 0 6 1
stable gini 1 208 118
increasing gini 0 34 28