Transcript
Page 1: CMGPD-LN Methodological Lecture Day 5

CMGPD-LNMethodological Lecture

Day 5

Households (Continued)Variables for Position

Page 2: CMGPD-LN Methodological Lecture Day 5

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

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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

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RELATIONSHIPCore

• e is household head• w is 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

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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

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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

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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

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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

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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 = RELATIONSHIPlocal 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'","",.)

}

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ExamplesRELATIONSHIP new_RELATIONSHIPe ewf fm m1ob b1obw b1ob1s bs3yb b3ybw b3yb1s bs3yb1d bd4yb b4ybw bf2yb fbf2ybw fb

RELATIONSHIP new_RELATIONSHIPf2yb1d fbdf3yb fbf3ybw fbf3yb1s fbsf3yb1sw fbsf3yb1s1s fbssf3yb1s1d fbsdf3yb2s fbsf3yb2sw fbsf3yb2s1d fbsdf4ybw fbf4yb1sw fbsf4yb1s1d fbsdf4yb1d fbdf4yb2d fbd

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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

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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/malesby AGE_IN_SUI: generate first_in_age = _n == 1twoway 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/malestwoway 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/malestwoway 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)

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Relationship at first appearancebysort PERSON_ID (YEAR): generate fa_nephew = new_RELATIONSHIP[1] == "bs" & AGE[1] <= 10 &

SEX == 2 & PRESENTbysort PERSON_ID (YEAR): generate fa_son = new_RELATIONSHIP[1] == "s" & AGE[1] <= 10 & SEX

== 2 & PRESENTgenerate fa_nephew_head = fa_nephew & headgenerate fa_son_head = fa_son & headbysort AGE_IN_SUI: egen fa_sons = total(fa_son)bysort AGE_IN_SUI: egen fa_nephews = total(fa_nephew)bysort AGE_IN_SUI: egen fa_sons_head = total(fa_son_head)bysort AGE_IN_SUI: egen fa_nephews_head = total(fa_nephew_head)generate p_fa_sons_head = fa_sons_head/fa_sonsgenerate p_fa_nephews_head = fa_nephews_head/fa_nephewstwoway line p_fa_sons_head p_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_head p_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"))

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Appeared as sons of head Appeared as nephews of head

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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

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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.

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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.

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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

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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: egen total_at_risk_position = total(at_risk_position)

bysort AGE_IN_SUI: egen total_next_position = total(next_position)generate p_next_position =

total_next_position/total_at_risk_positiontwoway 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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