cmgpd-ln methodological lecture day 5
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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 - PowerPoint PPT PresentationTRANSCRIPT
CMGPD-LNMethodological 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– Creation of variables for attainment by next
register
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
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
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
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
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
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
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'","",.)
}
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
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
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
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
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.
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.
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
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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