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Appendix 1

Stata do-file codes

*Importing the dataset

use "D:\Рабочий стол\RP 2020\Working files\KOUZHI18.dta", clear

*Excluding economically inactive population

drop if ZAN == 2

label define ZAN 1 "занятые в экономике (работающие)" 3 "указавшие себя занятыми" 4 "находящиеся в отпуске по уходу за ребенком от 0 до 3 лет", replace

lab values ZAN ZAN

codebook ZAN

*Keeping only age group 20-34

keep if R_3_1 >= 9 & R_3_1 <= 11

label define R_3_1 9 "20 - 24" 10 "25 - 29" 11 "30 - 34", replace

lab values R_3_1 R_3_1

*Making a dummy variable out of categorical for Self-employment

recode NAIM (1=0)

recode NAIM (2=1)

label define NAIM 1 "работающие не по найму" 0 "работающие по найму", replace

lab values NAIM NAIM

*Setting the reference group - working as self-employed

fvset base 1 NAIM

*Dropping the values of individuals working in agriculture

drop if NAIM == 1 & I05_04 == 3

*Renaming the variable to more understandable names

rename H01_02 VOZ

rename H01_04 BRAK

rename R_1 MESTO

rename I07_01 OBRAZ

Appendix 1 (Continued)

rename I07_04 OBRAZ_LET

rename H00_02 REGION

*Combining values of `Marriage' into 2 groups of `Married' and `Not married'

replace BRAK = 1 if BRAK == 2

replace BRAK = 3 if BRAK == 5

replace BRAK = 3 if BRAK == 3

replace BRAK = 3 if BRAK == 4

replace BRAK = 3 if BRAK == 6

replace BRAK = 2 if BRAK == 3

label define BRAK 1 "Состоит в браке (зарег/незарег)" 2 "Не состоит в браке", replace

lab values BRAK BRAK

*Making a dummy variable on the presence of children under the age of 9

recode CH_0_8 (6=5)

recode CH_0_8 (5=4)

recode CH_0_8 (4=3)

recode CH_0_8 (3=2)

recode CH_0_8 (2=1)

lab define CH_0_8 1 "Да" 0 "Нет", replace

lab values CH_0_8 CH_0_8

*Dropping the response with `not sure' category

drop if OBRAZ_LET == -7

*Transforming the variable for Region into type float

destring REGION, replace float

*Making two categories of education - `Higher education' and `Other education'

recode OBRAZ (3=2)

recode OBRAZ (2=1)

recode OBRAZ (9=8)

recode OBRAZ (8=7)

recode OBRAZ (7=6)

Appendix 1 (Continued)

recode OBRAZ (6=5)

recode OBRAZ (5=4)

recode OBRAZ (4=2)

lab define OBRAZ 1 "Высшая квалификация" 2 "Средняя, основная квал.", replace

lab values OBRAZ OBRAZ

*Making two categories of qualification - `Higher qualification' and `Other qualification'

recode GR_ZAN (2=1)

recode GR_ZAN (8=7)

recode GR_ZAN (7=6)

recode GR_ZAN (6=5)

recode GR_ZAN (5=4)

recode GR_ZAN (4=3)

recode GR_ZAN (3=2)

lab define GR_ZAN 1 "Спец. высшей квалификации" 2 "Специалисты сред. остальные", replace

lab values GR_ZAN GR_ZAN

*Cross tabulating variables of Education and Qualification with two categories

egen OVERQ1 = group(OBRAZ GR_ZAN)

lab define OVERQ1 1 "MATCHED_HIGH" 2 "OVERQUALIFIED" 3 "UNDERQUALIFIED" 4 "MATCHED_MIDDLE", replace

lab values OVERQ1 OVERQ1

recode OVERQ1 (4=1)

lab define OVERQ1 1 "MATCHED" 2 "OVERQUALIFIED" 3 "UNDERQUALIFIED" , replace

lab values OVERQ1 OVERQ1

lab var OVERQ1 "Наличие чрезмерной квалификации (образование и группа занятости)"

drop if OVERQ1 == .

*Exporting Descriptive statistics for the whole sample

tab OVERQ1, gen(OVERQ1x)

tab POL, gen(POLx)

tab BRAK, gen(BRAKx)

tab MESTO, gen(MESTOx)

Appendix 1 (Continued)

tab CH_0_8, gen(CH_0_8x)

eststo: estpost ttest OVERQ1x* POLx* VOZ BRAKx* MESTOx* CH_0_8x* OBRAZ_LET, by(NAIM) unequal

esttab using sumstat1.rtf, replace cells((mu_1(fmt(3)) mu_2 se sig(star pvalue(p))))

*Exporting probit regression models and estimating ROC curves

asdoc probit NAIM i.OVERQ1 i.POL c.VOZ#c.VOZ i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 29 & VOZ >= 20, replace nest drop(i.REGION) add(Dummy for Regions, YES)

lroc, nograph

asdoc probit NAIM i.OVERQ1 i.POL VOZ c.VOZ#c.VOZ i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 30 & VOZ >= 20, nest drop(i.REGION) add(Dummy for Regions, YES)

lroc, nograph

asdoc probit NAIM i.OVERQ1 i.POL VOZ c.VOZ#c.VOZ i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 34 & VOZ >= 24, nest drop(i.REGION) add(Dummy for Regions, YES)

lroc, nograph

asdoc probit NAIM i.OVERQ1 i.POL VOZ c.VOZ#c.VOZ i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 29 & VOZ >= 20 & REGION != 77 & REGION != 78 & REGION != 50, nest drop(i.REGION) add(Dummy for Regions, YES)

lroc, nograph

asdoc probit NAIM i.OVERQ1 i.POL VOZ c.VOZ#c.VOZ i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 30 & VOZ >= 20 & REGION != 77 & REGION != 78 & REGION != 50, nest drop(i.REGION) add(Dummy for Regions, YES)

lroc, nograph

asdoc probit NAIM i.OVERQ1 i.POL VOZ c.VOZ#c.VOZ i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 34 & VOZ >= 24 & REGION != 77 & REGION != 78 & REGION != 50, nest drop(i.REGION) add(Dummy for Regions, YES)

lroc, nograph

*Exporting marginal effects

gen VOZ2 = VOZ^2

probit NAIM i.OVERQ1 i.POL VOZ VOZ2 i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 29 & VOZ >= 20, nolog

Appendix 1 (Continued)

quietly margins, dydx(*) post

estimates store marg1

quietly probit NAIM i.OVERQ1 i.POL VOZ VOZ2 i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 30 & VOZ >= 20, nolog

margins, dydx(*) post

estimates store marg2

quietly probit NAIM i.OVERQ1 i.POL VOZ VOZ2 i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 34 & VOZ >= 24, nolog

margins, dydx(*) post

estimates store marg3

quietly probit NAIM i.OVERQ1 i.POL VOZ VOZ2 i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 29 & VOZ >= 20 & REGION != 77 & REGION != 78 & REGION != 50, nolog

margins, dydx(*) post

estimates store marg4

quietly probit NAIM i.OVERQ1 i.POL VOZ VOZ2 i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 30 & VOZ >= 20 & REGION != 77 & REGION != 78 & REGION != 50, nolog

margins, dydx(*) post

estimates store marg5

quietly probit NAIM i.OVERQ1 i.POL VOZ VOZ2 i.BRAK c.OBRAZ_LET i.MESTO i.CH_0_8 i.REGION if VOZ <= 34 & VOZ >= 24 & REGION != 77 & REGION != 78 & REGION != 50, nolog

margins, dydx(*) post

estimates store marg6

esttab marg1 marg2 marg3 marg4 marg5 marg6 using "Marginal effects.rtf", replace

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