test_precarity_indice
2025-02-12
Multilevel models
m0 <- lmer(indice~1+(1|country), data=alldata3)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## unable to evaluate scaled gradient## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge: degenerate Hessian with 1 negative eigenvaluesprint(icc(m0, by_group = TRUE))## # ICC by Group
##
## Group | ICC
## ---------------
## country | 0.152fm0 <-plm(indice~ relevel(country, ref = "DE"), model="within", data=alldata3)## Warning in pdata.frame(data, index = index, ...): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")###fm0 <-lmer(indice~ relevel(country, ref = "DE")+(1|country), data=alldata3)
fm1 <- plm(indice~ relevel(country, ref = "DE") + factor(year)+sex+ relevel(age, ref="55-65")+countrybirth +education +relevel(yearsar, ref="native") + relevel(compo,ref = "conf_adults"), model="within", effect = "individual", data=alldata3)## Warning in pdata.frame(data, index = index, ...): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")fm2 <- plm(indice~ relevel(country, ref = "DE") + factor(year)+sex+ relevel(age, ref="55-65")+countrybirth +education + relevel(compo,ref = "conf_adults"), model="within", data=alldata3)## Warning in pdata.frame(data, index = index, ...): duplicate couples (id-time) in resulting pdata.frame
## to find out which, use, e.g., table(index(your_pdataframe), useNA = "ifany")htmlreg(list("Multilevel 0"=m0, "Multilevel 1"=fm0, "Multilevel Fixe-effect 2"=fm1, "Multilevel Fixe-effect 3"=fm2))| Multilevel 0 | Multilevel 1 | Multilevel Fixe-effect 2 | Multilevel Fixe-effect 3 | |
|---|---|---|---|---|
| (Intercept) | 2.39*** | |||
| (0.06) | ||||
| relevel(country, ref = “DE”)AT | -0.01*** | -0.00 | -0.00 | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)BG | 0.37*** | 0.36*** | 0.36*** | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)CY | 0.88*** | 0.80*** | 0.82*** | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)CZ | 0.63*** | 0.65*** | 0.65*** | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)DK | 0.18*** | 0.29*** | 0.29*** | |
| (0.00) | (0.01) | (0.01) | ||
| relevel(country, ref = “DE”)EE | 0.13*** | 0.17*** | 0.17*** | |
| (0.01) | (0.01) | (0.01) | ||
| relevel(country, ref = “DE”)EL | 0.82*** | 0.80*** | 0.80*** | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)FI | 0.52*** | 0.59*** | 0.59*** | |
| (0.01) | (0.01) | (0.01) | ||
| relevel(country, ref = “DE”)FR | 0.49*** | 0.53*** | 0.53*** | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)HR | 0.68*** | 0.71*** | 0.71*** | |
| (0.01) | (0.01) | (0.01) | ||
| relevel(country, ref = “DE”)HU | 0.80*** | 0.79*** | 0.79*** | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)IE | 0.35*** | 0.34*** | 0.34*** | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)IT | 0.72*** | 0.70*** | 0.70*** | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)LT | 0.51*** | 0.50*** | 0.50*** | |
| (0.01) | (0.01) | (0.01) | ||
| relevel(country, ref = “DE”)LU | 0.17*** | 0.17*** | 0.17*** | |
| (0.01) | (0.01) | (0.01) | ||
| relevel(country, ref = “DE”)LV | 0.60*** | 0.60*** | 0.60*** | |
| (0.01) | (0.01) | (0.01) | ||
| relevel(country, ref = “DE”)NL | 0.18*** | 0.23*** | 0.23*** | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)PL | 0.55*** | 0.58*** | 0.58*** | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)PT | 0.87*** | 0.89*** | 0.89*** | |
| (0.00) | (0.00) | (0.00) | ||
| relevel(country, ref = “DE”)UK | 0.21*** | 0.23*** | 0.23*** | |
| (0.00) | (0.00) | (0.00) | ||
| factor(year)2010 | 0.03*** | 0.03*** | ||
| (0.00) | (0.00) | |||
| factor(year)2011 | 0.03*** | 0.03*** | ||
| (0.00) | (0.00) | |||
| factor(year)2012 | 0.06*** | 0.06*** | ||
| (0.00) | (0.00) | |||
| factor(year)2013 | 0.08*** | 0.08*** | ||
| (0.00) | (0.00) | |||
| factor(year)2014 | 0.07*** | 0.07*** | ||
| (0.00) | (0.00) | |||
| factor(year)2015 | 0.07*** | 0.07*** | ||
| (0.00) | (0.00) | |||
| factor(year)2016 | 0.07*** | 0.07*** | ||
| (0.00) | (0.00) | |||
| factor(year)2017 | 0.05*** | 0.05*** | ||
| (0.00) | (0.00) | |||
| factor(year)2018 | 0.05*** | 0.05*** | ||
| (0.00) | (0.00) | |||
| factor(year)2019 | 0.04*** | 0.04*** | ||
| (0.00) | (0.00) | |||
| sexfemale | -0.00** | -0.00** | ||
| (0.00) | (0.00) | |||
| relevel(age, ref = “55-65”)15-25 | -0.29*** | -0.29*** | ||
| (0.00) | (0.00) | |||
| relevel(age, ref = “55-65”)26-34 | 0.03*** | 0.04*** | ||
| (0.00) | (0.00) | |||
| relevel(age, ref = “55-65”)35-44 | 0.08*** | 0.08*** | ||
| (0.00) | (0.00) | |||
| relevel(age, ref = “55-65”)45-54 | 0.08*** | 0.08*** | ||
| (0.00) | (0.00) | |||
| countrybirthEU/EFTA | 0.27* | 0.03*** | ||
| (0.10) | (0.00) | |||
| countrybirthNew_Member | 0.37*** | 0.14*** | ||
| (0.10) | (0.00) | |||
| countrybirthEurope_nEU/nEFTA | 0.37*** | 0.12*** | ||
| (0.10) | (0.00) | |||
| countrybirthNon_Europe | 0.37*** | 0.13*** | ||
| (0.10) | (0.00) | |||
| educationISCED3/4 | 0.00 | 0.00 | ||
| (0.00) | (0.00) | |||
| educationISCED5+ | -0.06*** | -0.06*** | ||
| (0.00) | (0.00) | |||
| relevel(yearsar, ref = “native”)<5years | -0.19 | |||
| (0.10) | ||||
| relevel(yearsar, ref = “native”)5-9years | -0.22* | |||
| (0.10) | ||||
| relevel(yearsar, ref = “native”)>10years | -0.25* | |||
| (0.10) | ||||
| relevel(compo, ref = “conf_adults”)one_adult | 0.04*** | 0.04*** | ||
| (0.00) | (0.00) | |||
| relevel(compo, ref = “conf_adults”)adult_ch | -0.04*** | -0.04*** | ||
| (0.00) | (0.00) | |||
| relevel(compo, ref = “conf_adults”)couple | 0.00 | 0.00 | ||
| (0.00) | (0.00) | |||
| relevel(compo, ref = “conf_adults”)couple_ch | -0.08*** | -0.08*** | ||
| (0.00) | (0.00) | |||
| relevel(compo, ref = “conf_adults”)conf_adults_ch | -0.04*** | -0.04*** | ||
| (0.00) | (0.00) | |||
| AIC | 5150075.24 | |||
| BIC | 5150113.43 | |||
| Log Likelihood | -2575034.62 | |||
| Num. obs. | 2494857 | 2494857 | 2261970 | 2264162 |
| Num. groups: country | 21 | |||
| Var: country (Intercept) | 0.08 | |||
| Var: Residual | 0.46 | |||
| R2 | 0.18 | 0.22 | 0.22 | |
| Adj. R2 | 0.05 | 0.09 | 0.09 | |
| ***p < 0.001; **p < 0.01; *p < 0.05 | ||||
summary(fm2)Oneway (individual) effect Within Model
Call: plm(formula = indice ~ relevel(country, ref = “DE”) + factor(year) + sex + relevel(age, ref = “55-65”) + countrybirth + education + relevel(compo, ref = “conf_adults”), data = alldata3, model = “within”)
Unbalanced Panel: n = 330246, T = 1-51, N = 2264162
Residuals: Min. 1st Qu. Median 3rd Qu. Max. -2.5199006 -0.3330309 0.0067116 0.3453325 2.7046481
Coefficients: Estimate Std. Error relevel(country, ref = “DE”)AT
-0.00371075 0.00209793 relevel(country, ref = “DE”)BG 0.35945489
0.00280971 relevel(country, ref = “DE”)CY 0.81820892 0.00455080
relevel(country, ref = “DE”)CZ 0.65027441 0.00471478 relevel(country,
ref = “DE”)DK 0.29321809 0.00504445 relevel(country, ref = “DE”)EE
0.17004141 0.00700518 relevel(country, ref = “DE”)EL 0.79814927
0.00301316 relevel(country, ref = “DE”)FI 0.59101091 0.00536592
relevel(country, ref = “DE”)FR 0.53109050 0.00270513 relevel(country,
ref = “DE”)HR 0.71387319 0.00673265 relevel(country, ref = “DE”)HU
0.79443704 0.00248110 relevel(country, ref = “DE”)IE 0.34094305
0.00310661 relevel(country, ref = “DE”)IT 0.69692488 0.00171085
relevel(country, ref = “DE”)LT 0.50393191 0.00564004 relevel(country,
ref = “DE”)LU 0.16783359 0.00697776 relevel(country, ref = “DE”)LV
0.59714510 0.00719890 relevel(country, ref = “DE”)NL 0.22701702
0.00235756 relevel(country, ref = “DE”)PL 0.58113888 0.00236807
relevel(country, ref = “DE”)PT 0.88740403 0.00288654 relevel(country,
ref = “DE”)UK 0.22688647 0.00342532 factor(year)2010 0.03268822
0.00244166 factor(year)2011 0.03096527 0.00245331 factor(year)2012
0.05626161 0.00238658 factor(year)2013 0.07576328 0.00239639
factor(year)2014 0.07092806 0.00242350 factor(year)2015 0.07204335
0.00243064 factor(year)2016 0.06908648 0.00242804 factor(year)2017
0.05353920 0.00243557 factor(year)2018 0.05152352 0.00245010
factor(year)2019 0.03757566 0.00245759 sexfemale -0.00304253 0.00110944
relevel(age, ref = “55-65”)15-25 -0.28602906 0.00180138 relevel(age, ref
= “55-65”)26-34 0.03806331 0.00183917 relevel(age, ref = “55-65”)35-44
0.07733947 0.00186680 relevel(age, ref = “55-65”)45-54 0.07853969
0.00170113 countrybirthEU/EFTA 0.02630480 0.00348245
countrybirthNew_Member 0.14432651 0.00314325
countrybirthEurope_nEU/nEFTA 0.12401135 0.00285778
countrybirthNon_Europe 0.13481067 0.00238034 educationISCED3/4
0.00074357 0.00115698 educationISCED5+ -0.05890693 0.00157936
relevel(compo, ref = “conf_adults”)one_adult 0.03659588 0.00179136
relevel(compo, ref = “conf_adults”)adult_ch -0.03796181 0.00269222
relevel(compo, ref = “conf_adults”)couple 0.00230708 0.00161757
relevel(compo, ref = “conf_adults”)couple_ch -0.07666926 0.00148833
relevel(compo, ref = “conf_adults”)conf_adults_ch -0.03914579 0.00158650
t-value Pr(>|t|)
relevel(country, ref = “DE”)AT -1.7688 0.076933 .
relevel(country, ref = “DE”)BG 127.9329 < 2.2e-16
relevel(country, ref = “DE”)CY 179.7946 < 2.2e-16
relevel(country, ref = “DE”)CZ 137.9224 < 2.2e-16
relevel(country, ref = “DE”)DK 58.1268 < 2.2e-16
relevel(country, ref = “DE”)EE 24.2737 < 2.2e-16
relevel(country, ref = “DE”)EL 264.8880 < 2.2e-16
relevel(country, ref = “DE”)FI 110.1415 < 2.2e-16
relevel(country, ref = “DE”)FR 196.3268 < 2.2e-16
relevel(country, ref = “DE”)HR 106.0316 < 2.2e-16
relevel(country, ref = “DE”)HU 320.1955 < 2.2e-16
relevel(country, ref = “DE”)IE 109.7476 < 2.2e-16
relevel(country, ref = “DE”)IT 407.3564 < 2.2e-16
relevel(country, ref = “DE”)LT 89.3490 < 2.2e-16
relevel(country, ref = “DE”)LU 24.0526 < 2.2e-16
relevel(country, ref = “DE”)LV 82.9495 < 2.2e-16
relevel(country, ref = “DE”)NL 96.2934 < 2.2e-16
relevel(country, ref = “DE”)PL 245.4060 < 2.2e-16
relevel(country, ref = “DE”)PT 307.4282 < 2.2e-16
relevel(country, ref = “DE”)UK 66.2381 < 2.2e-16
factor(year)2010 13.3877 < 2.2e-16 factor(year)2011
12.6218 < 2.2e-16 factor(year)2012 23.5742 < 2.2e-16
factor(year)2013 31.6156 < 2.2e-16
factor(year)2014 29.2668 < 2.2e-16 factor(year)2015
29.6397 < 2.2e-16 factor(year)2016 28.4536 < 2.2e-16
factor(year)2017 21.9822 < 2.2e-16
factor(year)2018 21.0292 < 2.2e-16 factor(year)2019
15.2896 < 2.2e-16 sexfemale -2.7424 0.006099
relevel(age, ref = “55-65”)15-25 -158.7829 < 2.2e-16
relevel(age, ref = “55-65”)26-34 20.6959 < 2.2e-16
relevel(age, ref = “55-65”)35-44 41.4289 < 2.2e-16
relevel(age, ref = “55-65”)45-54 46.1692 < 2.2e-16
countrybirthEU/EFTA 7.5535 4.238e-14
countrybirthNew_Member 45.9164 < 2.2e-16
countrybirthEurope_nEU/nEFTA 43.3943 < 2.2e-16
countrybirthNon_Europe 56.6350 < 2.2e-16
educationISCED3/4 0.6427 0.520427
educationISCED5+ -37.2980 < 2.2e-16 relevel(compo, ref
= “conf_adults”)one_adult 20.4291 < 2.2e-16
relevel(compo, ref = “conf_adults”)adult_ch -14.1006 < 2.2e-16
relevel(compo, ref = “conf_adults”)couple 1.4263
0.153792
relevel(compo, ref = “conf_adults”)couple_ch -51.5136 < 2.2e-16
relevel(compo, ref = “conf_adults”)conf_adults_ch -24.6742
< 2.2e-16 ** — Signif. codes: 0 ‘’ 0.001 ’’
0.01 ’’ 0.05 ‘.’ 0.1 ’ ’ 1
Total Sum of Squares: 1106700 Residual Sum of Squares: 864770 R-Squared: 0.2186 Adj. R-Squared: 0.08514 F-statistic: 11760.9 on 46 and 1933870 DF, p-value: < 2.22e-16
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