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CMGPD-LN Methodological Lecture Day 5

CMGPD-LN Methodological Lecture Day 5. Households (Continued) Variables for Position. Outline. Houshold Use of the RELATIONSHIP variable Indicators for relationship to head Counts of various relatives of head Position Introduction Relationship of flag variables to original variables

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CMGPD-LN Methodological Lecture Day 5

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  1. CMGPD-LNMethodological LectureDay 5 Households (Continued) Variables for Position

  2. Outline • Houshold • Use of the RELATIONSHIP variable • Indicators for relationship to head • Counts of various relatives of head • Position • Introduction • Relationship of flag variables to original variables • Creation of variables for attainment by next register

  3. RELATIONSHIP • String describes relationship of individual to the head of the household • Before 1789, describes relationship to head of yihu • This is the basis of our kinship linkage • Automated linkage of children to their parents • Automated linkage of wives to their husband’s • All based on processing of strings describing relationship

  4. RELATIONSHIPCore • e is household head • wis a household head’s wife • m is household head’s mother • f is household head’s father (usually dead) • 1yb, 2yb, 2ob etc. are head’s brothers • Older brothers of the head are unusual • 1yz, 2yz, 2oz etc. are head’s unmarried sisters • 1s, 2s, etc. are head’s sons • 1d, 2d, etc. are the head’s unmarried daughters

  5. RELATIONSHIPCombining codes • More distant relationships are built up from these core relationships by combining them • Examples • ff is grandfather of head • fm is grandmother of head • f2yb is an uncle: father’s second younger brother • f2ybw is his wife • f2yb1s is a cousin: father’s 2nd younger brother’s 1st son • 3yb2s is a nephew: 3rd younger brother’s 2nd son • 3s2s is a grandson: 3rd son’s 2nd son • 3s2sw is his wife

  6. RELATIONSHIPLinking wives to husbands • Strip the w off of a married woman’s relationship and search the household for the remaining string. • f2yb1sw -> search for f2yb1s • Exceptions • For w, search for e • For f, search for m • For fm, search for ff • Etc. • Basically prepare a target string, and then make use of merge on HOUSEHOLD_ID and the target

  7. RELATIONSHIPLinking children to fathers • In most cases, strip off the last relationship code and look for the remainder. • 1s1s -> look for 1s • ff2yb3s2s -> look for ff2yb3s • Exceptions • e look for f • 2yb look for f • f2yb look for ff • To link married women to their fathers-in-law, strip off w first, then convert to father’s relationship

  8. RELATIONSHIPIndicators of specify basic relationships to head generate head = RELATIONSHIP == “e” generate head_wife = RELATIONSHIP == “w” generate mother = RELATIONSHIP == “m” generate father = RELATIONSHIP == “f” . tab head SEX if PRESENT & SEX >= 1, row col +-------------------+ | Key | |-------------------| | frequency | | row percentage | | column percentage | +-------------------+ | Sex head | Female Male | Total -----------+----------------------+---------- 0 | 539,935 671,972 | 1,211,907 | 44.55 55.45 | 100.00 | 98.69 78.90 | 86.64 -----------+----------------------+---------- 1 | 7,148 179,658 | 186,806 | 3.83 96.17 | 100.00 | 1.31 21.10 | 13.36 -----------+----------------------+---------- Total | 547,083 851,630 | 1,398,713 | 39.11 60.89 | 100.00 | 100.00 100.00 | 100.00

  9. RELATIONSHIPProcessing for distant relationships • Strip out numbers, seniority modifiers y and b, etc. • In a .do file, this will create a new variable with a stripped relationship generate new_RELATIONSHIP = RELATIONSHIP local for_removal "1 2 3 4 5 6 7 8 9 o y w" foreach x of local for_removal { replace new_RELATIONSHIP = subinstr(new_RELATIONSHIP,"`x'","",.) }

  10. Examples

  11. generate brother = new_RELATIONSHIP = “b” & SEX == 2 generate brothers_wife = “b” & SEX == 1 & MARITAL_STATUS !=2 & MARITAL_STATUS > 0 generate sister = new_RELATIONSHIP = “z” & SEX == 1 generate male_cousin = new_RELATIONSHIP = “fbs” & SEX == 2 generate nephew = new_RELATIONSHIP = “bs” & SEX == 2

  12. Proportions of different relationships by age generate brother = new_RELATIONSHIP == "b" bysort AGE_IN_SUI: egen males = total(SEX == 2 & PRESENT) bysort AGE_IN_SUI: egen brothers = total(SEX == 2 & brother & PRESENT) generate proportion_brothers = brothers/males by AGE_IN_SUI: generate first_in_age = _n == 1 twoway line proportion_brothers AGE_IN_SUI if AGE_IN_SUI >= 1 & AGE_IN_SUI <= 80 & first_in_age, ytitle("Proportion of males who are brother of a head") scheme(s1mono) bysort AGE_IN_SUI: egen heads = total(SEX == 2 & RELATIONSHIP == "e" & PRESENT) generate proportion_heads = heads/males twoway line proportion_heads AGE_IN_SUI if AGE_IN_SUI >= 1 & AGE_IN_SUI <= 80 & first_in_age, ytitle("Proportion of males who are household head") scheme(s1mono) bysort AGE_IN_SUI: egen sons = total(SEX == 2 & new_RELATIONSHIP == "s" & PRESENT) generate proportion_sons = sons/males twoway line proportion_sons AGE_IN_SUI if AGE_IN_SUI >= 1 & AGE_IN_SUI <= 80 & first_in_age, ytitle("Proportion of males who are son of a head") scheme(s1mono)

  13. Relationship at first appearance bysort PERSON_ID (YEAR): generate fa_nephew = new_RELATIONSHIP[1] == "bs" & AGE[1] <= 10 & SEX == 2 & PRESENT bysort PERSON_ID (YEAR): generate fa_son = new_RELATIONSHIP[1] == "s" & AGE[1] <= 10 & SEX == 2 & PRESENT generate fa_nephew_head = fa_nephew & head generate fa_son_head = fa_son & head bysort AGE_IN_SUI: egenfa_sons = total(fa_son) bysort AGE_IN_SUI: egenfa_nephews = total(fa_nephew) bysort AGE_IN_SUI: egenfa_sons_head = total(fa_son_head) bysort AGE_IN_SUI: egenfa_nephews_head = total(fa_nephew_head) generate p_fa_sons_head = fa_sons_head/fa_sons generate p_fa_nephews_head = fa_nephews_head/fa_nephews twoway line p_fa_sons_headp_fa_nephews_head AGE_IN_SUI if AGE_IN_SUI >= 1 & AGE_IN_SUI <= 80 & first_in_age, ytitle("Proportion") scheme(s1mono) twoway line p_fa_sons_headp_fa_nephews_head AGE_IN_SUI if AGE_IN_SUI >= 1 & AGE_IN_SUI <= 80 & first_in_age, ytitle("Proportion now head") scheme(s1mono) legend(order(1 "Appeared as sons of head" 2 "Appeared as nephews of head"))

  14. Variables for position • The basic and analytic files include a variety of indicator variables for whether a male holds title • These are based on the raw occupations • Files with hanyu pinyin for raw occupations will be released soon • Occupations with original Chinese characters are being released as a PDF • Turned out to be difficult to include Chinese characters in the released data

  15. Variables for position • In the original data, entries included the official positions held by males. • Coders assigned a numeric code to each new position, and entered the code into the dataset. • Codes started again for each new dataset • Transcribed the original Chinese into a codebook • Can use DATASET and POSITION_CODE to look up original Chinese in the appendix to the Analytic release codebook • File available for download soon will allow merging of hanyu pinyin for code.

  16. Variables for position • We have provided a variable of flag variables identifying different kinds of position • HAS_POSITION • Any salaried official position or purchased title • Doesn’t include miding, piding, etc. Those were statuses, not salaried official positions • ESTIMATED_INCOME • Imputed income based on stipends associated with the position(s) held by an individual • RANK • Bureaucratic rank, based on specification of pin in the position • BI_TIE_SHI, ZHI_SHI_REN, and flags for specific positions • JUAN, DING_DAI etc. for presence of modifiers • EXAMINATION for any examination-related title • NO_STATUS indicates that no status at all was recorded for a male, even though we would have expected one.

  17. Studying attainment • We have mainly used event-history • Determinants of chances of attaining position by next register • Allows for consideration of time-varying characteristics • Characteristics of kin • An alternative would be to look at determinants of attaining a position by a specific age, with one observation per person

  18. Creating variables to identify attainment of position by next register generate at_risk_position = SEX == 2 & PRESENT & NEXT_3 & HAS_POSITION == 0 bysort PERSON_ID (YEAR): generate next_position = at_risk_position & HAS_POSITION[_n+1] bysort AGE_IN_SUI: egentotal_at_risk_position = total(at_risk_position) bysort AGE_IN_SUI: egentotal_next_position = total(next_position) generate p_next_position = total_next_position/total_at_risk_position twoway line p_next_position AGE_IN_SUI if AGE_IN_SUI >= 1 & AGE_IN_SUI <= 80 & first_in_age, ytitle("Proportion attaining position by next register") scheme(s1mono)

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