## 1.7 Real World Examples

In 2006, the Financial Times reported on a team of researchers finding that “Personal wealth is distributed so unevenly across the world that the richest two per cent of adults own more than 50 per cent of the world’s assets while the poorest half hold only 1 per cent of wealth.” Although the original publication presented a global estimate, we haven chosen to reproduce this calculation using nationally-representative surveys from both the United States and Brazil. We reproduce this inequality statistic with a variety of surveys and levels of analysis to highlight how this software can be used not only to estimate a number but also to understand the uncertainty around that number.

To understand the construction of each survey design object and respective variables of interest, please refer to section 1.4 for CPS-ASEC, section 1.5 for PNAD-Contínua, and section 1.6 for SCF.

### 1.7.1 CPS-ASEC Household Income

result <-
svylorenz( ~ htotval ,
cps_household_design ,
quantile = c(0.5 , 0.98) ,
plot = FALSE)

The richest two percent:

1 - coef(result)[2]
##   L(0.98)
## 0.1362526
1 - confint(result)[2, ]
##     2.5 %    97.5 %
## 0.1405340 0.1319713

The poorest half:

coef(result)[1]
##    L(0.5)
## 0.1743857
confint(result)[1, ]
##     2.5 %    97.5 %
## 0.1724502 0.1763213

### 1.7.2 CPS-ASEC Family Income

result <-
svylorenz( ~ ftotval ,
cps_family_design ,
quantile = c(0.5 , 0.98) ,
plot = FALSE)

The richest two percent:

1 - coef(result)[2]
##   L(0.98)
## 0.1285084
1 - confint(result)[2, ]
##     2.5 %    97.5 %
## 0.1332705 0.1237463

The poorest half:

coef(result)[1]
##    L(0.5)
## 0.1952713
confint(result)[1, ]
##     2.5 %    97.5 %
## 0.1929511 0.1975914

### 1.7.3 CPS-ASEC Worker Earnings

result <-
svylorenz(~ pearnval ,
cps_ftfy_worker_design ,
quantile = c(0.5 , 0.98) ,
plot = FALSE)

The richest two percent:

1 - coef(result)[2]
##   L(0.98)
## 0.1382385
1 - confint(result)[2, ]
##     2.5 %    97.5 %
## 0.1435179 0.1329591

The poorest half:

coef(result)[1]
##    L(0.5)
## 0.2335371
confint(result)[1, ]
##     2.5 %    97.5 %
## 0.2309755 0.2360987

### 1.7.4 PNAD-Contínua Per Capita Income

result <- svylorenz(
~ deflated_per_capita_income ,
na.rm = TRUE ,
quantile = c(0.5 , 0.98) ,
plot = FALSE
)

The richest two percent:

1 - coef(result)[2]
##   L(0.98)
## 0.1682959
1 - confint(result)[2, ]
##     2.5 %    97.5 %
## 0.1740323 0.1625595

The poorest half:

coef(result)[1]
##    L(0.5)
## 0.1690023
confint(result)[1, ]
##     2.5 %    97.5 %
## 0.1660912 0.1719135

result <- svylorenz(
~ deflated_labor_income ,
na.rm = TRUE ,
quantile = c(0.5 , 0.98) ,
plot = FALSE
)

The richest two percent:

1 - coef(result)[2]
##   L(0.98)
## 0.1681662
1 - confint(result)[2, ]
##     2.5 %    97.5 %
## 0.1745635 0.1617688

The poorest half:

coef(result)[1]
##    L(0.5)
## 0.1957089
confint(result)[1, ]
##     2.5 %    97.5 %
## 0.1922068 0.1992109

### 1.7.6 SCF Family Net Worth

result <-
scf_MIcombine(with(scf_design , svylorenz(
~ networth , quantile = c(0.5 , 0.98) , plot = FALSE
)))

The richest two percent:

1 - coef(result)[2]
##   L(0.98)
## 0.4518496
1 - confint(result)[2, ]
##     2.5 %    97.5 %
## 0.4720704 0.4316288

The poorest half:

coef(result)[1]
##     L(0.5)
## 0.02199973
confint(result)[1, ]
##      2.5 %     97.5 %
## 0.02018196 0.02381751

### 1.7.7 SCF Family Income

result <-
scf_MIcombine(with(scf_design , svylorenz(
~ income , quantile = c(0.5 , 0.98) , plot = FALSE
)))

The richest two percent:

1 - coef(result)[2]
##   L(0.98)
## 0.2915461
1 - confint(result)[2, ]
##     2.5 %    97.5 %
## 0.3254621 0.2576302

The poorest half:

coef(result)[1]
##    L(0.5)
## 0.1319798
confint(result)[1, ]
##     2.5 %    97.5 %
## 0.1238655 0.1400942