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Variations of wealth resemblance by relationship types in modern Chinese

C. Y. Cyrus Chua,1, Kamhon Kana, and Jou Chun Linb

aInstitute of Economics, Academia Sinica, Taipei 11529, Taiwan; and bDepartment of Economics, University of California, Davis, CA 95616

This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected in 2017.

Contributed by C. Y. Cyrus Chu, February 4, 2019 (sent for review July 31, 2018; reviewed by Josh Goldstein and Yu Xie)

For a long time, social scientists have used correlations in social from the ego up to the first common then down to the status, measured by such characteristics as schooling, income, or corresponding relative, and the sum of counts is the degree of occupation, across family members to capture family resemblance relationship. in social status. In this study, we use millions of records from The advantage of the correlation measure, compared with the a public registry to estimate the wealth correlations among Tai- genetic relatedness or the Roman law measure, is that it captures wanese members, from the closest – pairing to the dynamics of complicated social institutions and forces. The the farthest kinship ties, with only 1/32 genetic relatedness. Based disadvantage, however, as noted by Mare (4), is that the data on this wealth correlation, we present a complete picture of eco- beyond are rarely available. In this paper, we try nomic similarity among kin members. These correlations give us to analyze what are perhaps the best family network data in the a better grasp of the hitherto obscure Chinese family structure world to study what are arguably among the closest family rela- than that of mechanical genetic relatedness. We obtain statistical tionships in the world—Chinese families in Taiwan. Relations evidence to support the following hypotheses: Family members’ among members of Chinese families are known to be strong, and wealth resemblance to male egos is stronger than to female egos, their interactions are frequent and affectionate. Their interac- wealth correlations are larger along patrilineal lines than along tions often involve provision of emotional and material support matrilineal counterparts, wealthy families have larger correlations to each other. [Evidence in previous studies (11, 14) shows that within the members but smaller correlations out- the intensity of interaction among family members in Taiwan is side it, and adopted children have weaker wealth resemblance higher than in their Western counterparts. For example, while with close relatives. 72.4% of individuals in Taiwan gave cash to (14), only 44.2% of black individuals and 28.5% of white individuals in the family network | kinship | intergenerational wealth correlation United States gave financial support to a family member (15).] Our empirical analysis, along the lines of Solon (16, 17) and Mare (3, 4), sets out to calculate the correlation of family ocial scientists often use the correlation coefficient of fam- members’ wealth while controlling their personal characteris- Sily members’ socioeconomic status to characterize the status tics. Because of the huge number of observations available to resemblance between them using survey data; a larger correla- us from the registry observations available to us from the reg- tion often reveals a closer family relationship in the background. istry records and our efforts in identifying the relatives from Both the achievement indexes and the family members being the records, we are able to trace an ego’s family members, studied are usually limited by the coverage of survey question- according to the Roman law criteria, from the most direct line, naires (e.g., availability of measures of socioeconomic status and which is parents–children, to /, great aunts/uncles, information on kin network members). These limitations may first , second cousins, etc. (Fig. 1), and the farthest point have constricted our understanding of the family structure in of kinship in our observation can have only a 1/32 genetic question. Studies on family members’ resemblance in economic out- Significance comes focus on the parents–children correlation in early ones and correlations between in later ones (1, 2) and This study uses millions of records from a public registry in Tai- on correlations between multigenerational or extended fam- wan to estimate wealth correlations among kinship members. ily members in more recent ones (3–5). The reasons why This wealth correlation as a measure of kinship resemblance is such correlation measures capture the idea of family mem- shown to capture much more information about the modern bers’ connection may be due to material and affective support Chinese family than that of mechanical genetic relatedness (6), cognitive and emotional interactions (7), experience and or the correlations among immediate family members. We information sharing, or the of intelligence or other are able to see from our proposed measure the variations of traits. The general conceptual idea of the correlation analy- family members’ resemblance between males and females, sis is similar both to that of Sahlins (8), which involves cap- between paternal and maternal lines of relatives, between turing the nature of kinship as “mutuality of being,” and to rich and ordinary families, and between adoptees and other measuring the resemblance in performance among kinship mem- children. bers (9, 10). Because the family structure is time variant and has dynamic social contexts, it is important to see how such Author contributions: C.Y.C.C., K.K., and J.C.L. designed research; K.K. and J.C.L. per- dynamic correlations change as modern Chinese family structure formed research; C.Y.C.C., K.K., and J.C.L. analyzed data; and C.Y.C.C., K.K., and J.C.L. evolves (11). wrote the paper.y The standard way of measuring genetic relatedness between Reviewers: J.G., University of California, Berkeley; and Y.X., Princeton University. y any two family members was first proposed by Wright (12) and The authors declare no conflict of interest.y has been broadly used by evolutionary anthropologists. Another This open access article is distributed under Creative Commons Attribution-NonCommercial- time-invariant measure of relatedness is the degree of relation- NoDerivatives License 4.0 (CC BY-NC-ND).y ships defined by the Roman civil law. It is now adopted by most See QnAs on page 6517.y countries, including France, Germany, Japan, Switzerland, and 1 To whom correspondence should be addressed. Email: [email protected] Taiwan (13). The Roman law approach consists of counting Published online March 18, 2019.

6548–6553 | PNAS | April 2, 2019 | vol. 116 | no. 14 www.pnas.org/cgi/doi/10.1073/pnas.1813136116 Downloaded by guest on September 26, 2021 Downloaded by guest on September 26, 2021 al .Wat correlations Wealth 1. Table h tal. et Chu Eq. for are measures. 7 law column Roman in the Results of 3–6. those and aunts/uncles follow 1 Great columns in controlled are cousins 1st Aunts/uncles 0.125 Grandparents 0.125 Siblings 0.25 Parents 0.25 4 0.5 4 0.5 3 2 2 1 overlap Genetic degree Relative recorded “interest originally on FIA The based records. also deposits tax income savings We the of land. in amount income” and total housing, all the shares, derive to records—stock be wealth available to ual and have center. data public data the on-site the FIA’s involving the in to operations undertaken Taiwan. any open Finance, but are of researchers, Ministry Finan- records the (FIA), by These Agency provided Taiwan Information in wealth cial and income of records Data. Method Estimation and Data can really data. traditional patterns the some family by whether supported Chinese be test on hypotheses to science etc., correlation maternal social females, and the and paternal Moreover, males for status. lines, separately estimated economic are in to coefficients resem- other us members helps family each remotely which how ble network, or closely family how coef- whole just identify correlation the obtain almost therefore for We ficients ego. the with relatedness the and to changing by relatives. lines corresponding maternal paternal to to grandfather and paternal grandmother changing by line paternal–maternal the to 1. Fig. .651tcuisoc eoe .45* 65652005**002**008**007**0.0178*** 0.0470*** 0.0485*** 0.0429*** 0.0551*** 26,556,522 0.0495*** cousins 2nd removed once cousins 1st 0.0313 0.0625 6 5 ,* n * eoesaitclsgicnea h 0,5,ad1 ees xetfrprnsadsbig,teptra/aenllnaefie effects fixed paternal/maternal the siblings, and parents for Except levels. 1% and 5%, 10%, the at significance statistical denote *** and *,**, individ- of sets three use we wealth, individual calculate To u nlssaebsdo eietfidadministrative de-identified on based are analyses Our arlna ecnscvrdi hssuy hscudas eapplied be also could This study. this in covered descents Patrilineal i type Kin orlto ieeo gseo gsmaternal egos egos egos egos size correlation )Wat )Sml )Ml )Fml )Ml )Fml )Ptra vs. Paternal 7) Female 6) Male 5) Female 4) Male 3) Sample 2) Wealth 1) .57* ,0,0 .67* .53* .54* .45* 0.00958*** 0.0118*** — 0.0230*** 0.0485*** 0.107*** 0.0875*** 0.0504*** 0.0938*** 0.0553*** 0.113*** 0.300*** 0.0804*** 0.0627*** 0.106*** — 0.275*** 0.105*** 7,604,802 0.135*** 0.242*** 52,878,902 0.0547*** 886,056 — 38,480,347 0.0931*** 0.403*** 0.117*** 13,667,901 0.131*** 5,147,035 0.305*** 0.304*** .31* 11415005**009**006**003**0.0150*** 0.0334*** 0.0369*** 0.0299*** 0.0351*** 31,174,165 0.0341*** All hr h ru um sfrptra/aenlptra ieg.Rltv degrees Relative lineage. paternal/paternal–paternal for is dummy group the where 2, samaueo iettasiso fwat rmprnsto parents from wealth of interpreted transmission direct often of is measure the It a in mobility. as wealth intergenerational used commonly father’s of most the of indicator is wealth coefficient children’s of the model regression or correlation wealth Resemblance. of Measurement only simplicity. descendants, of sake patrilineal the taking for dataset, mem- our kinship by the paternal–maternal of covered structure as bers the shows them 1 paternal to Fig. the aunts/uncles. refer great for example, we for siblings, first; the lineage grandmother’s from closer clar- start the we put To separate lineages, and lineage. different a ego to each estimate referring first for notations then the relative we ify a and estimation with effects the coefficient fixed in correlation system, lineage kinship the Chinese control the in roles Their grandmothers. average. than grandfathers on older and y , old 2.64 their y about than older were 81 y and 3.5 average respec- old on grandparents, were y and 61.42 parents or Their were (paternal 2015. tively, in both sample old ego y had the 35.27 of 886,056 age was average and The 2015, alive. grandparents in maternal) alive parents both had them 2015. of of most as away because passed included not Here, are once aunts/uncles). great-grandparents cousins (great siblings (first grandparents’ cousins and removed), parents’ first cousins, relatives: parents’ second the influ- collateral (aunts/uncles), cousins, from of siblings first the siblings, possible, generations to parents, then three ego’s susceptible is identify the more It to egos are background.] tree, these family lineal and of their larger of variations be ence wealth to 1980). the likely (after equal, are deteriorate being y to things 9 when began Other to period inequality the exposed experienced income have were affecting Taiwan’s They 1968, and 1956. after in after War, launched long born was people World 1970, which Second after education, compulsory born the of all of the were end from egos the [These great-grandparents records. and FIA grandparents, parents, their 2013–2015. period 3-y the the the for take by level we wealth value fluctuations, average by short-term land assessed avoid the To as authorities. undervaluation adjust the of We percentage value. county-level market yearly com- 40–60% the by with understated for is pared authorities value value registration assessed The the The by unavailable. purposes. assessed tax are is values land net and their housing net of if their use value we question, face stocks, in unlisted or For companies value 31. the July for on date price closing ex-right or, their price an dates market of ex-right absence respective their the stocks’ measure the in at we prices value; closing the face using their at shares stock steptra n aenllnso eaie aedifferent have relatives of lines maternal and paternal the As had 5,147,035 them among egos; 7,682,140 of total a have We trace we egos, as 2015 in old y 25–45 were who those Taking aerelatives Male — — PNAS | pi ,2019 2, April nteltrtr,tefather–child the literature, the In eaerltvsDifference relatives Female — — | o.116 vol. 0.0160*** — — | o 14 no. — | 6549

SOCIAL SCIENCES INAUGURAL ARTICLE Fig. 2. Wealth correlation and genetic relatedness.

their children, plus the indirect passage of other advantages, such coefficient βk is not exactly equal to the correlation coefficient of as investment in their children’s human capital (17) and pro- wealth, but is close to it. It is identical to the correlation coeffi- vision of opportunities. Here we do not want to overinterpret cient if the standard deviations of the ego’s and his/her relatives’ the meaning of the correlation to imply any causality of kinship wealth ranks are the same after controlling for age and other fac- behavior toward the ego. Just as the correlation is seen as tors in the regression model, which is likely to be the case.) The the embodiment of family factors shared among siblings (1, 2), following is the regression model, one could imagine such correlations with his/her kinship mem- bers as being forged over time by a variety of different factors 4 4 X m a X f a and through multiple channels. Thus, a static, contemporaneous Ri = α + βk Rikj + γa AikjMikj + γa Aikj(1 − Mikj) wealth correlation could be seen as a useful way of capturing the a=1 a=1 pattern of egocentric similarity among kin members (4). 4 a X a X a Following Chetty et al. (18) and Boserup et al. (19), we mea- + δa (Ai − 40) + θa Rikj(Ai − 40) + λPikj + ikj, sure an individual’s wealth using his/her relative position (i.e., a=1 a=1 his/her rank, in the range 0–1) in the sample instead of its level. [1] To estimate wealth correlation βk between an ego and his/her relatives belonging to kinship relationship k, we regress his/her where Ri is ego i’s wealth rank, Rikj is the wealth rank of member wealth rank on that of his/her relatives while controlling for age j of i’s kinship relationship k, Aikj and Ai denote the age, Mikj is a (using a fourth-order polynomial) and whether the relative is binary variable indicating j is male, Pikj is a binary variable indi- a matrilineal or patrilineal one. (It is noted that the regression cating that j is a patrilineal relative, and ikj is an error term.

Fig. 3. Paternal and maternal lineages.

6550 | www.pnas.org/cgi/doi/10.1073/pnas.1813136116 Chu et al. Downloaded by guest on September 26, 2021 Downloaded by guest on September 26, 2021 .2 aenlptra ra ut/nls000**106180.0103*** 1,066,118 0.0701*** aunts/uncles great Paternal–paternal 0.125 4 .33Mtra–aenl2dcuis003**704860009 0.000260 0.00576*** 0.000996 10,375,945 0.0000877 7,004,836 0.0325*** 0.0105*** 8,368,383 0.0330*** 5,425,001 0.0296*** 0.0471*** 0.000337 cousins 2nd 8,968,386 Maternal–maternal 0.00276*** cousins 6,282,853 2nd 0.0313 Maternal–paternal 0.0465*** 0.0151*** cousins 6,710,593 2nd 0.0313 0.0531*** Paternal–maternal 4,594,690 cousins 2nd 0.0415*** 0.0313 Paternal–paternal o/r cousins 0.0634*** 1st 0.0313 Maternal–maternal 6 o/r cousins 1st 0.0625 Maternal–paternal 6 2,904,250 o/r cousins 0.00274* 1st 0.0625 1,513,377 Paternal–maternal 6 o/r 0.0528*** cousins 1st 0.0625 2,121,057 Paternal–paternal 6 aunts/uncles 0.0559*** great Maternal–maternal 0.0625 5 0.0511*** aunts/uncles great Maternal–paternal 0.125 5 aunts/uncles great Paternal–maternal 0.125 5 0.125 5 4 4 4 .2 aenl1tcousins 1st Maternal cousins 1st Paternal 0.125 aunts/uncles Maternal 0.125 0.25 4 4 3 .5Ptra aunts/uncles Paternal grandparents Maternal 0.25 grandparents Paternal 0.25 0.25 3 2 2 ereoverlap degree Genetic Relative h tal. of et peer Chu are and background cousins their and his/her and 1 ego, and the (Table siblings as increases generation ego’s law same an the Roman However, in of 2). variation kinship Fig. as the in declines is correlation distance larger wealth the the the why higher is, explains the degree This Thus, correlation. kinship correlation. cousins law smaller the a Roman then have general, the to in tend close siblings. not question own are in their siblings with parents’ interact the parents If ego’s the An be how may relatives. instance, to for their related cousins, with his/her with closeness correlation cor- parents’ individual’s correlations, the on that wealth implies depends For parents relation through parents. going relationship through kinship counted estab- and is relationship lished kinship of degree the approach, relatedness correlation relationship. the of same-sex general, distance In egos, with siblings. female declines for For only ones. higher female relatives is col- with male correlation in with that those correlation than wealth to higher the similar is egos, patterns male show For dis- 1. the and umn of further ego gender the not the for and are control relatives 3–6 and columns similar in correlation Results are of here. cussed relatives patterns The distant cousins. more first with but with grandparents those with correlations those than than Wealth higher lower are nontrivial. uncles and is multigenera- aunts square wealth with direct the of that than transmission suggests larger tional correlation similar is ego–parent correlation for the this next of that come fact The influence Grandparents mutual reasons. have accumulation. to likely wealth most fac- the socioeconomic on are and and ego genetic the most with the tors share closest they the as are relatives, correlation siblings wealth and the Parents . that with show decreases 1 column in Results Correlation. results. tion Wealth the of ego’s Features an normalizing by for (20) females y. paths Solon 40 and life-cycle and to age males Lee distinct follow for have We may effects wealth. women different and have men to because adoptees. age were egos allow of 1% We About alive. parents both have egos of 67% About 2015. in alive parents both had who egos Siblings Parents 0.5 0.5 2 1 family biological and wealth, parental gender, lineage: paternal/maternal by differences Group 2. Table oeta o ohteRmnlwapoc n h genetic the and approach law Roman the both for that Note only include we 5 and 4 columns in results estimating In removed.” “once o/r, levels. 1% and 5%, 10%, the at significance statistical denote *** and **, *, i type Kin al rsnsteestima- the presents 1 Table orlto ieegos size correlation .80* 765090027* 0.00166*** 0.0150*** 0.00247*** 0.0223*** 27,655,029 0.00445*** 25,223,873 0.0820*** 21,103,991 0.105*** 0.114*** .4**3397003**0.00974** 0.0192*** 0.0137*** 522,139 17,376,356 363,917 0.121*** 0.126*** 0.142*** .0**1,6,0 .66* .2**0.160*** 8.686*** 0.125*** 0.645*** 0.0616*** 0.0170*** 13,667,901 5,147,035 0.305*** 0.304*** )Wat )Sml )Ml aetlprna )Adoptee 6) parental parental Male 3) Sample 2) Wealth 1) Eq. 1 Tbe1 oun7.Ti eutsilsad vnatrw control we after even counterparts stands still maternal result the This 7). with column 1, score those (Table relatives than cor- paternal–paternal) higher the (and consistently that shows paternal test with The between relations lineages. differences maternal the and on paternal shortly, the illustrated is which test, tical Differences. Matrilineal and Patrilineal Networks Family Chinese of Resemblance ordinal Wealth the than pre- rather member. kinship relatedness distances, each genetic numeric of intricate rankings, and the more system provides far law It is dict. Roman correlation the wealth what the than by 1/32 depicted blance of kins his/her remarkably is 1/32. and which to 0.0341, the close ego is instance, cousins) an (second For similarity though. genetic between level, genetic correlation low the as very wealth level a near-zero consanguinity. reaches similar by a relatedness simply Tai- reach work indexes the two not and These family, does nuclear network the top-to-bottom family of the wanese outside capture relatedness cannot of the relatedness mode highlights This genetic results. that our fact in the aunts/uncles great for first the as and account well cousins in as to aunts/uncles, and rate fails grandparents grand- between overlapping similar difference and genetic siblings, a However, parents, at parents. categories: decrease relationship three measures first two The overlap. relatedness genetic of terms law. in Roman are ego the aunts/uncles the and great to relationship the in though tighter that even to aunts/uncles, close very great is removed with once wealth first ego’s the the also with fact, correlation are In relatives). who fourth-degree aunts/uncles, different-generation and great second- of the and generally grandparents relatives as degree) (such than fourth ones the correlations the in larger in cousins siblings have first as and This (such degree correlation. relatives second their same-generation increase why which explains similar, likely are groups vrl,orrslssgetta h aiymmes resem- members’ family the that suggest results our Overall, genetic and correlation wealth of patterns the compares 2 Fig. −0.000593 −0.000231 −0.00235* −0.00137 .01 0.00792** −0.00412 PNAS Eq. −0.0160*** −0.00159* −0.00594*** −0.00474*** −0.00272 −0.000704 −0.00369*** −0.00359* −0.00533*** −0.0187*** −0.0100*** −0.0133*** )Tp2%5 o 1% Top 5) 25% Top 4) | ru ifrne(β difference group 2: elhwat egos wealth wealth pi ,2019 2, April ecnutasml statis- simple a conduct We −0.0502*** .51* 0.0273 −0.0501*** −0.0207*** −0.0185*** −0.0393*** −0.0480*** 0.0110 0.00189 −0.0349*** −0.0441*** −0.0691*** −0.0838*** .40* 0.0143** −0.0440*** 0.00558 −0.0528*** 0.00609 −0.0480*** −0.0407*** −0.0892*** −0.109*** .69* 0.0171 −0.0609*** −0.101*** | o.116 vol. k D ) | o 14 no. −0.00728*** −0.00567 −0.00777 −0.00286 −0.00312 −0.000124 −0.0100 −0.0276*** −0.0119*** −0.000727 −0.168*** −0.0154 −0.0586*** | 6551

SOCIAL SCIENCES INAUGURAL ARTICLE for the gender of ego and that of his/her relatives. (The test is Now we conduct some subgroup analyses to investigate fur- conducted using Eq. 2, where Di is replaced with the paternal ther the characteristics of wealth resemblance of members of the or paternal–paternal lineage dummy, conditional on the genders Chinese family. We use an interaction term for a group dummy of ego and the corresponding relative.) In Fig. 3 we separate and the wealth rank of the kinship member to test for subgroup the two lineages from parents, demonstrating the stronger rela- differences in wealth correlation. We let Di be a group dummy tions with the paternal (and paternal–paternal) side. The exact and run the following regression:

numbers can be found in Table 2, column 1. One may won- D der whether the male/female difference is intertwined with the Ri = α + δDi + βk Rikj + Di · βk Rikj + age controls + ikj. [2] paternal/maternal difference. To disentangle these two factors For group dummies, we consider gender, parental wealth we separate the groups and do a refined analysis. In Fig. 4, we (whether in the top 25% and whether in the top 1%), and observe the particular characteristic of a patrilineal society in whether the ego is an adoptee or not. (We rely on income tax that males are more resembled to their paternal relatives and records to find gender, and therefore some observations are that there is little gender difference in relations with maternal lost if they have never reported income taxes. Over 95% of relatives. observations have the gender information.) In rural societies, according to the literature, the existence of a distinctively patrilineal system is due to efficiency Gender Difference. The results of estimating Eq. 2 are reported concerns. For instance, if males are more efficient in a hunting in Table 2, columns 3–6. Column 3 contains the coefficient society, then a patrilineal system secures more returns and thus estimates of the male dummy. They are mostly positive and facilitates more family collaboration (9, 21). It is interesting to statistically significant for the paternal lineage relatives, while see that in a developed industrial society like Taiwan, where peo- mostly smaller or insignificant for the maternal lineage rela- ple are not reliant upon family cooperation for their living, the tives, which is consistent with the discussion in Patrilineal and patrilineal tendency is still present. Matrilineal Differences.

Fig. 4. Paternal and maternal lineages by gender.

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Available 6, of Copenhagen). March records Accessed Copenhagen, papers/WealthAcrossGen.pdf. wealth of Danish (Univ from ations Evidence formation: wealth erational States. United the in 1623. mobility intergenerational of geography generations. 82:393–408. organization. out. crowding of evidence New transfers: o oilRsac,Ui fMcia,AnAbr I,PCRsac eot15-845. Report Research PSC MI), Arbor, Ann Michigan, of Institute Center, Univ Research, Studies Social (Population for wealth family in associations multigenerational Stud Asian Anthropol 91:766–772. 57:S118–S130. 5:275–333. e o taicto Mobility Stratification Soc Res mSco Rev Sociol Am PNAS 69:812–837. | pi ,2019 2, April Economica 35:13–18. | u Nat Hum 81:721–746. o.116 vol. 22:156–176. Econ J Q | o 14 no. e cnStat Econ Rev mEo Rev Econ Am 129:1553– u East J Eur | 6553 Curr

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