Summary Statistics
Table 9.26
t1<- xtabs(~ hhi + lfp); insx= round(prop.table(t1,1)*100,2)
t1<- xtabs(~ edu2 + lfp); edux= round(prop.table(t1,1)*100,2)
t1<- xtabs(~ race2 + lfp); racex= round(prop.table(t1,1)*100,2)
exper.years<- round(tapply(experience, lfp,mean),2)
kids.under.6<- round(tapply(kidslt6, lfp,mean),2)
kids.6.to.18<- round(tapply(kids618, lfp,mean),2)
husb.inc<- round(tapply(husby, lfp,mean),2)
t1<- xtabs(~ region + lfp); regionx= round(prop.table(t1,1)*100,2)
tab<- rbind(insx, edux, racex, exper.years, kids.under.6, kids.6.to.18, husb.inc, regionx)
tab1<-xtable(tab)
print(tab1, type="html")
|
unemployed
|
part-time
|
full-time
|
no
|
26.17
|
13.82
|
60.01
|
yes
|
33.62
|
22.25
|
44.13
|
LT 9 years
|
64.80
|
9.00
|
26.20
|
9-11years
|
52.00
|
14.06
|
33.94
|
12years
|
31.88
|
18.57
|
49.56
|
13-15years
|
23.94
|
20.55
|
55.51
|
16years
|
19.50
|
18.38
|
62.13
|
GT 16 years
|
12.15
|
15.28
|
72.57
|
Whites
|
30.13
|
18.50
|
51.36
|
African-Americans
|
24.09
|
10.64
|
65.27
|
Other race
|
39.18
|
9.94
|
50.88
|
exper.years
|
26.92
|
22.07
|
20.97
|
kids.under.6
|
0.47
|
0.37
|
0.27
|
kids.6.to.18
|
0.67
|
0.85
|
0.65
|
husb.inc
|
25.66
|
29.76
|
27.00
|
other
|
28.86
|
20.75
|
50.39
|
northcentral
|
26.86
|
21.18
|
51.96
|
south
|
31.75
|
13.03
|
55.22
|
west
|
31.72
|
18.42
|
49.87
|
htmlTable(txtRound(tab1,0, excl.rows = c(13,14)),
rgroup=c("Husband's insurance covers wife (%)",
"Education status (%)",
"Race (%)",
"Experience in years",
"Children less than 6 years old",
"Children between 6 and 18 years old",
"Husband's income",
"Region of origin (%)"),
n.rgroup = c(2,6,3,1,1,1,1,4),
cgroup = c("Wives' Work Status"),
n.cgroup = c(3),
rowlabel="Demographic Attributes")
|
Wives’ Work Status
|
Demographic Attributes
|
unemployed
|
part-time
|
full-time
|
Husband’s insurance covers wife (%)
|
no
|
26
|
14
|
60
|
yes
|
34
|
22
|
44
|
Education status (%)
|
LT 9 years
|
65
|
9
|
26
|
9-11years
|
52
|
14
|
34
|
12years
|
32
|
19
|
50
|
13-15years
|
24
|
21
|
56
|
16years
|
20
|
18
|
62
|
GT 16 years
|
12
|
15
|
73
|
Race (%)
|
Whites
|
30
|
18
|
51
|
African-Americans
|
24
|
11
|
65
|
Other race
|
39
|
10
|
51
|
Experience in years
|
exper.years
|
27
|
22
|
21
|
Children less than 6 years old
|
kids.under.6
|
0.47
|
0.37
|
0.27
|
Children between 6 and 18 years old
|
kids.6.to.18
|
0.67
|
0.85
|
0.65
|
Husband’s income
|
husb.inc
|
26
|
30
|
27
|
Region of origin (%)
|
other
|
29
|
21
|
50
|
northcentral
|
27
|
21
|
52
|
south
|
32
|
13
|
55
|
west
|
32
|
18
|
50
|
Binary Model
library(stargazer)
##
## Please cite as:
##
## Hlavac, Marek (2014). stargazer: LaTeX code and ASCII text for well-formatted regression and summary statistics tables.
## R package version 5.1. http://CRAN.R-project.org/package=stargazer
table(HI$lfp_yn)
unemployed employed 6652 15620
rm(mod.1)
## Warning in rm(mod.1): object 'mod.1' not found
mod.1<-glm(formula = lfp_yn ~ hhi + factor(edu2) +race2 +
factor(hispanic)+ experience + exp2 +exp3 +kidslt6 +
kids618 + husby +factor(region), weight=mean_wt,
family = binomial(link = "probit"),
data=HI)
## Warning: non-integer #successes in a binomial glm!
stargazer(mod.1, type="html", no.space=TRUE,
covariate.labels = c("Wife covered by husband's insurance", "9-11 years education",
"12 years education", "13-15 years education", "16 years education",
"GT 16 years education", "African-American", "Other race", "Hispanic",
"Years of potential work experience", "Potential LF exp2/100",
"Potential LF exp3/100" ,"No. of children < 6 years old",
"No. of children 6±18 years old", "Husband's income in thousands",
"North Central Region", "South Region", "West Region"))
|
|
Dependent variable:
|
|
|
|
lfp_yn
|
|
Wife covered by husband’s insurance
|
-0.283***
|
|
(0.021)
|
9-11 years education
|
0.093*
|
|
(0.056)
|
12 years education
|
0.529***
|
|
(0.050)
|
13-15 years education
|
0.682***
|
|
(0.052)
|
16 years education
|
0.774***
|
|
(0.056)
|
GT 16 years education
|
1.026***
|
|
(0.066)
|
African-American
|
0.220***
|
|
(0.040)
|
Other race
|
-0.152
|
|
(0.133)
|
Hispanic
|
-0.227***
|
|
(0.045)
|
Years of potential work experience
|
0.044***
|
|
(0.010)
|
Potential LF exp2/100
|
-0.200***
|
|
(0.046)
|
Potential LF exp3/100
|
0.001
|
|
(0.001)
|
No. of children < 6 years old
|
-0.566***
|
|
(0.017)
|
No. of children 6±18 years old
|
-0.165***
|
|
(0.011)
|
Husband’s income in thousands
|
-0.003***
|
|
(0.0005)
|
North Central Region
|
0.055*
|
|
(0.029)
|
South Region
|
-0.120***
|
|
(0.027)
|
West Region
|
-0.114***
|
|
(0.030)
|
Constant
|
0.749***
|
|
(0.088)
|
|
Observations
|
22,272
|
Log Likelihood
|
-11,794.590
|
Akaike Inf. Crit.
|
23,627.190
|
|
Note:
|
p<0.1; p<0.05; p<0.01
|
library(nnet)
rm(mod.2)
## Warning in rm(mod.2): object 'mod.2' not found
mod.2<- multinom(lfp ~ hhi + factor(edu2) + race2 +
factor(hispanic)+ experience + exp2 +exp3 +kidslt6 +
kids618 + husby +factor(region), weight=mean_wt, data=HI)
## # weights: 60 (38 variable)
## initial value 24468.292893
## iter 10 value 20539.051691
## iter 20 value 20257.930245
## iter 30 value 19851.086965
## iter 40 value 19745.014947
## final value 19734.064405
## converged
Table 9.27
stargazer(mod.2, type="html", no.space=TRUE,
covariate.labels = c("Wife covered by husband's insurance", "9-11 years education",
"12 years education", "13-15 years education", "16 years education",
"GT 16 years education", "African-American", "Other race", "Hispanic",
"Years of potential work experience", "Potential LF exp2/100",
"Potential LF exp3/100" ,"No. of children < 6 years old",
"No. of children 6±18 years old", "Husband's income in thousands",
"North Central Region", "South Region", "West Region"))
|
|
Dependent variable:
|
|
|
|
part-time
|
full-time
|
|
(1)
|
(2)
|
|
Wife covered by husband’s insurance
|
0.064
|
-0.701***
|
|
(0.047)
|
(0.038)
|
9-11 years education
|
0.219
|
0.166
|
|
(0.140)
|
(0.105)
|
12 years education
|
0.839***
|
0.928***
|
|
(0.124)
|
(0.093)
|
13-15 years education
|
1.119***
|
1.164***
|
|
(0.129)
|
(0.097)
|
16 years education
|
1.121***
|
1.388***
|
|
(0.136)
|
(0.103)
|
GT 16 years education
|
1.370***
|
1.897***
|
|
(0.160)
|
(0.125)
|
African-American
|
-0.172*
|
0.542***
|
|
(0.101)
|
(0.072)
|
Other race
|
-0.534***
|
-0.179
|
|
(0.081)
|
(0.190)
|
Hispanic
|
-0.456***
|
-0.336***
|
|
(0.108)
|
(0.082)
|
Years of potential work experience
|
0.007
|
0.106***
|
|
(0.023)
|
(0.019)
|
Potential LF exp2/100
|
-0.058
|
-0.472***
|
|
(0.103)
|
(0.086)
|
Potential LF exp3/100
|
-0.001
|
0.002**
|
|
(0.001)
|
(0.001)
|
No. of children < 6 years old
|
-0.594***
|
-1.114***
|
|
(0.038)
|
(0.033)
|
No. of children 6±18 years old
|
-0.049**
|
-0.390***
|
|
(0.024)
|
(0.021)
|
Husband’s income in thousands
|
-0.004***
|
-0.005***
|
|
(0.001)
|
(0.001)
|
North Central Region
|
0.032
|
0.115**
|
|
(0.061)
|
(0.053)
|
South Region
|
-0.510***
|
-0.081*
|
|
(0.059)
|
(0.049)
|
West Region
|
-0.235***
|
-0.164***
|
|
(0.064)
|
(0.055)
|
Constant
|
-0.252
|
0.952***
|
|
(0.203)
|
(0.163)
|
|
Akaike Inf. Crit.
|
39,544.130
|
39,544.130
|
|
Note:
|
p<0.1; p<0.05; p<0.01
|
Table 9.28 and Table 9.29
exponentiate <- function(x) exp(x)
stargazer(mod.2, type="html", no.space=TRUE, apply.coef= exponentiate, se= list(NA),
covariate.labels = c("Wife covered by husband's insurance", "9-11 years education",
"12 years education", "13-15 years education", "16 years education",
"GT 16 years education", "African-American", "Other race", "Hispanic",
"Years of potential work experience", "Potential LF exp2/100",
"Potential LF exp3/100" ,"No. of children < 6 years old",
"No. of children 6±18 years old", "Husband's income in thousands",
"North Central Region", "South Region", "West Region"))
|
|
Dependent variable:
|
|
|
|
part-time
|
full-time
|
|
(1)
|
(2)
|
|
Wife covered by husband’s insurance
|
1.067
|
0.496
|
|
|
|
9-11 years education
|
1.244
|
1.180
|
|
|
|
12 years education
|
2.314
|
2.531
|
|
|
|
13-15 years education
|
3.063
|
3.202
|
|
|
|
16 years education
|
3.067
|
4.006
|
|
|
|
GT 16 years education
|
3.934
|
6.669
|
|
|
|
African-American
|
0.842
|
1.719
|
|
|
|
Other race
|
0.586
|
0.836
|
|
|
|
Hispanic
|
0.634
|
0.715
|
|
|
|
Years of potential work experience
|
1.007
|
1.112
|
|
|
|
Potential LF exp2/100
|
0.943
|
0.624
|
|
|
|
Potential LF exp3/100
|
0.999
|
1.002
|
|
|
|
No. of children < 6 years old
|
0.552
|
0.328
|
|
|
|
No. of children 6±18 years old
|
0.953
|
0.677
|
|
|
|
Husband’s income in thousands
|
0.996
|
0.995
|
|
|
|
North Central Region
|
1.033
|
1.122
|
|
|
|
South Region
|
0.601
|
0.923
|
|
|
|
West Region
|
0.791
|
0.848
|
|
|
|
Constant
|
0.778
|
2.591
|
|
|
|
|
Akaike Inf. Crit.
|
39,544.130
|
39,544.130
|
|
Note:
|
p<0.1; p<0.05; p<0.01
|
percentx <- function(x) (exp(x)-1)*100
stargazer(mod.2, type="html", no.space=TRUE, apply.coef= percentx, se= list(NA),
covariate.labels = c("Wife covered by husband's insurance", "9-11 years education",
"12 years education", "13-15 years education", "16 years education",
"GT 16 years education", "African-American", "Other race", "Hispanic",
"Years of potential work experience", "Potential LF exp2/100",
"Potential LF exp3/100" ,"No. of children < 6 years old",
"No. of children 6±18 years old", "Husband's income in thousands",
"North Central Region", "South Region", "West Region"))
|
|
Dependent variable:
|
|
|
|
part-time
|
full-time
|
|
(1)
|
(2)
|
|
Wife covered by husband’s insurance
|
6.660
|
-50.385
|
|
|
|
9-11 years education
|
24.430
|
18.001
|
|
|
|
12 years education
|
131.402
|
153.065
|
|
|
|
13-15 years education
|
206.293
|
220.190
|
|
|
|
16 years education
|
206.689
|
300.579
|
|
|
|
GT 16 years education
|
293.446
|
566.864
|
|
|
|
African-American
|
-15.761
|
71.947
|
|
|
|
Other race
|
-41.391
|
-16.390
|
|
|
|
Hispanic
|
-36.646
|
-28.508
|
|
|
|
Years of potential work experience
|
0.737
|
11.228
|
|
|
|
Potential LF exp2/100
|
-5.679
|
-37.613
|
|
|
|
Potential LF exp3/100
|
-0.110
|
0.245
|
|
|
|
No. of children < 6 years old
|
-44.762
|
-67.172
|
|
|
|
No. of children 6±18 years old
|
-4.739
|
-32.300
|
|
|
|
Husband’s income in thousands
|
-0.442
|
-0.505
|
|
|
|
North Central Region
|
3.293
|
12.193
|
|
|
|
South Region
|
-39.939
|
-7.735
|
|
|
|
West Region
|
-20.937
|
-15.161
|
|
|
|
Constant
|
-22.245
|
159.071
|
|
|
|
|
Akaike Inf. Crit.
|
39,544.130
|
39,544.130
|
|
Note:
|
p<0.1; p<0.05; p<0.01
|