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CMGPD-LN Methodological Lecture

CMGPD-LN Methodological Lecture. Day 6 Marriage and Reproduction. Marriage Event history. Outcome: marriage (or remarriage) in the next three years Logistic regression Restrict to people not currently married Useful for considering the effects of time-varying characteristics

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CMGPD-LN Methodological Lecture

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  1. CMGPD-LNMethodological Lecture Day 6 Marriage and Reproduction

  2. MarriageEvent history • Outcome: marriage (or remarriage) in the next three years • Logistic regression • Restrict to people not currently married • Useful for considering the effects of time-varying characteristics • Current characteristics of kin, etc. • Can be carried out for daughters, subject to caveats related to omission of records • Discrete-time event-history via logit or complementary log-log • AT_RISK_MARRY and NEXT_MARRY • AT_RISK_REMARRY and NEXT_REMARRY

  3. MarriageCurrent marital status • Alternatively, can look at current marital status as an outcome • Fine if right-hand side of variables of interest are fixed • Childhood characteristics etc. • Can construct flag variables for outcomes from MARITAL_STATUS • Ever married (MARITAL_STATUS != 2 & MARITAL_STATUS >= 1) • Currently married (MARITAL_STATUS == 1) • Currently remarried (MARITAL_STATUS==4) • Would want to restrict to observations of people who were MARITAL_STATUS == 3 | MARITAL_STATUS == 4

  4. MarriageVariables for parents’ characteristics • For the study of marriage, and social mobility, parental characteristics are important • In STATA, it is easy to extract information from records of parents, and add it as a variable to an individual’s observation • Basic principle is to merge based on FATHER_ID, MOTHER_ID and so forth • Can also extract information from other kin

  5. Preparing a file with father’s information to be merged in use "C:\Users\Cameron Campbe\Documents\Baqi\CMGPD-LN from ICPSR\ICPSR_27063\DS0001\27063-0001-Data.dta", clear keep PERSON_ID YEAR HAS_POSITION rename PERSON_ID FATHER_ID rename HAS_POSITION FATHER_HAS_POSITION bysort FATHER_ID YEAR: keep if _n == 1 save father_information, replace

  6. Merging the file and carrying out a tabulation use "C:\Users\Cameron Campbe\Documents\Baqi\CMGPD-LN from ICPSR\ICPSR_27063\DS0001\27063-0001-Data.dta", clear merge m:1 FATHER_ID YEAR using father_information drop if _merge == 2 label variable FATHER_HAS_POSITION "Father has position" tab HAS_POSITION FATHER_HAS_POSITION if SEX == 2 & AGE_IN_SUI > 16 & AGE_IN_SUI <= 55 & PRESENT & FATHER_HAS_POSITION >= 0, col generate byte IS_MARRIED = MARITAL_STATUS != 2 tab IS_MARRIED FATHER_HAS_POSITION if SEX == 2 & AGE_IN_SUI > 16 & AGE_IN_SUI <= 35 & PRESENT & FATHER_HAS_POSITION >= 0 & MARITAL_STATUS >= 1, col

  7. tab HAS_POSITION FATHER_HAS_POSITION if SEX == 2 & AGE_IN_SUI > 16 & AGE_IN_SUI <= 55 & PRESENT & FATHER_HAS_POSITION >= 0, col +-------------------+ | Key | |-------------------| | frequency | | column percentage | +-------------------+ Has Official | Father has position Position | No Yes | Total ---------------+----------------------+---------- No | 218,254 9,256 | 227,510 | 98.84 86.88 | 98.29 ---------------+----------------------+---------- Yes | 2,561 1,398 | 3,959 | 1.16 13.12 | 1.71 ---------------+----------------------+---------- Total | 220,815 10,654 | 231,469 | 100.00 100.00 | 100.00

  8. . tab IS_MARRIED FATHER_HAS_POSITION if SEX == 2 & AGE_IN_SUI > 16 & AGE_IN_SUI <= 35 & PRESENT & FATHER_HAS_POSITION >= 0 & MARITAL > _STATUS >= 1, col +-------------------+ | Key | |-------------------| | frequency | | column percentage | +-------------------+ | Father has position IS_MARRIED | No Yes | Total -----------+----------------------+---------- 0 | 68,210 2,452 | 70,662 | 40.20 30.27 | 39.75 -----------+----------------------+---------- 1 | 101,447 5,648 | 107,095 | 59.80 69.73 | 60.25 -----------+----------------------+---------- Total | 169,657 8,100 | 177,757 | 100.00 100.00 | 100.00

  9. Creating one record per father and using it as the basis for the merge use "C:\Users\Cameron Campbe\Documents\Baqi\CMGPD-LN from ICPSR\ICPSR_27063\DS0001\27063-0001-Data.dta", clear bysort PERSON_ID (HAS_POSITION): generate father_ever_position = HAS_POSITION[_N] bysort PERSON_ID: keep if _n == 1 keep PERSON_ID father_ever_position rename PERSON_ID FATHER_ID save father_ever_position use "C:\Users\Cameron Campbe\Documents\Baqi\CMGPD-LN from ICPSR\ICPSR_27063\DS0001\27063-0001-Data.dta", clear keep if SEX == 2 merge m:1 FATHER_ID using father_ever_position, keep(match master) label variable father_ever_position "Father ever held position" tab HAS_POSITION father_ever_position if PRESENT & HAS_POSITION >= 0 & father_ever_position >= 0 & AGE_IN_SUI >= 16 & AGE_IN_SUI <= 55, column

  10. Results +-------------------+ | Key | |-------------------| | frequency | | column percentage | +-------------------+ | Father ever held Has Official | position Position | 0 1 | Total ---------------+----------------------+---------- No | 429,455 22,841 | 452,296 | 98.76 86.02 | 98.03 ---------------+----------------------+---------- Yes | 5,390 3,711 | 9,101 | 1.24 13.98 | 1.97 ---------------+----------------------+---------- Total | 434,845 26,552 | 461,397 | 100.00 100.00 | 100.00

  11. Moving information about a husband into a wife’s record use "C:\Users\Cameron Campbe\Documents\Baqi\CMGPD-LN from ICPSR\ICPSR_27063\DS0001\27063-0001-Data.dta", clear keep if SEX == 2 keep PERSON_ID YEAR AGE_IN_SUI rename PERSON_ID HUSBAND_ID rename AGE_IN_SUI HUSBAND_AGE bysort HUSBAND_ID YEAR: keep if _n == 1 save husband_information use "C:\Users\Cameron Campbe\Documents\Baqi\CMGPD-LN from ICPSR\ICPSR_27063\DS0001\27063-0001-Data.dta", clear keep if SEX == 1 merge m:1 HUSBAND_ID YEAR using husband_information, keep(match master) generate AGE_DIFFERENCE = HUSBAND_AGE - AGE_IN_SUI if HUSBAND_AGE > 0 & AGE_IN_SUI > 0 recode AGE_DIFFERENCE min/-10=-10 10/max=10 bysortPERSON_ID:keep if _n == 1& MARITAL_STATUS > 0 & MARITAL_STATUS != 2 histogram AGE_DIFFERENCE, width(1) discrete scheme(s1mono) xtitle("Husband's age - wife's age") fraction

  12. Age differences in newly married couples

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