Bargaining for the American Dream

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Bargaining for the American Dream

What Unions do for Mobility

By Richard Freeman, Eunice Han, David Madland, and Brendan V. Duke September 2015


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Bargaining for theAmerican DreamWhat Unions do for Mobility

By Richard Freeman, Eunice Han, David Madland, and Brendan V. Duke

September 2015


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1 Introduction and summary

4 Unions and intergenerational mobility by area

10 Mobility in union and nonunion households

14 Unions and stagnant intergenerational mobility

16 Conclusion

17 Appendix A: Area-level data

20 Appendix B: Area-level analysis

24 Appendix C: Individual household data and analysis

31 Endnotes

Contents


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1 Center for American Progress | Bargaining for the American Dream

Introduction and summary

One o he cenral challenges acing he Unied Saes on which boh progressives

and conservaives can agree is he need o increase economic mobiliy. Upward

mobiliy and opporuniy are he definiion o he American dream. Bu oday,

he naion has less mobiliy and ewer opporuniies when compared o oher

advanced economies. A U.S. child born in he botom 20 percen o he income

disribuion, or example, has a 7.5 percen probabiliy o reaching he op 20

percen as an adul, compared o 11.7 percen in Denmark and 13.4 percen in

Canada.1 Increasing mobiliy, however, requires undersanding why i is low.

Research by economiss Raj Chety o Sanord Universiy, Nahaniel Hendren

o Harvard Universiy and Parick Kline and Emmanuel Saez o he Universiy o

Caliornia, Berkeley, shows ha some regions o he Unied Saes have levels o

mobiliyha is o say, he abiliy o improve upon he siuaion o one’s birh

similar o Denmark and Canada. However, ha same research reveals ha oher

U.S. areas have mobiliy levels ha are lower han any oher advanced economy

or which daa are available. Te research o Chety and his ellow auhors also

show ha five acors have he sronges geographical relaionshipposiive or

negaivewih mobiliy: single moherhood raes, income inequaliy, high school

dropou raes, social capial, and segregaion.2

Tis repor examines he relaionship beween mobiliy and anoher variable ha

Chety and his co-auhors did no consider: union membership. Te analysis in

his repor begins on he area level using he same mehodological approach as

Chety and his co-auhors or heir five acors. Bu he analysis hen goes beyond

his area-level analysis, using anoher daase ha maches parens wih children

ha allows or he comparison o oucomes or children who grew up in oherwise

similar union and nonunion households. Tis individual-level analysis is moreappropriae han he area-level analysis or examining wheher parens’ union

membership acually influences mobiliy.


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*All reference to “we,” “us,” and “our” refer to the authors of this report.

Based on he research or his repor, i is clear ha here is a srong relaionship

beween union membership and inergeneraional mobiliy. More specifically:

• Areas with higher union membership demonstrate more mobility for low-

income children. Using Chety and ohers’ daa, we* find ha low-income

children rise higher in he income rankings when hey grow up in areas wihhigh-union membership. A 10 percenage poin increase in a geographic area’s

union membership is associaed wih low-income children ranking 1.3 per-

cenile poins higher in he naional income disribuion. Tis relaionship

beween unions and he mobiliy o low-income children is a leas as srong

as he relaionship beween mobiliy and high school dropou raesa acor

ha is generally recognized as one o he mos imporan correlaes o eco-

nomic mobiliy. Indeed, union densiy is one o he sronges predicors o an

area’s mobiliy. Furhermore, unions remain a significan predicor o economic

mobiliy even afer one conrols or several variables including race, ypes o

indusries, inequaliy, and more.

• Areas with higher union membership have more mobility as measured by

all children’s incomes. We also measure he geographic relaionship beween

union membership and anoher measure o mobiliy: he income o all children

who grew up in an area afer conrolling or heir parens’ incomes. According

o our findings, a 10 percenage poin increase in union densiy is associaed

wih a 4.5 percen increase in he income o an area’s children. Here again, union

densiy compares quie avorable wih oher common predicors o an area’s

mobiliy. In addiion, he relaionship beween unions and he mobiliy o all

children remains srong afer adoping several addiional conrols.

• Children who grow up in union households have better outcomes. Using a differ-

en daase, we mach parens and children o compare he oucomes o children

who grew up in oherwise similar union and nonunion households. Te findings

show ha children growing up in union households end o have beter oucomes

han children who grew up in nonunion households, especially when he parens

are low skilled. For example, children o non-college-educaed ahers earn 28

percen more i heir aher was in a labor union. Tis analysis helps provide evi-

dence suggesing a link beween unions and economic mobiliy.

Tese findings are new and illusrae a previously ignored acor ha could be

essenial or promoing economic mobiliy. However, hey are no surprising, par-

icularly given he exensive research ha has been done on unions and middle-


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class incomes. Previous research by he CAP Acion Fund has ound a srong

geographical relaionship beween union membership and inrageneraional

mobiliyhe relaionship beween someone’s earnings when hey are 35 o 39

years old and when hey are 45 o 49 years old.3 Our findings also coincide wih

he findings o several sudies showing ha alling union membership has been a

key driver in he rise o income inequaliy.4

Mos recenly, Bruce Wesern and JakeRoseneld o Harvard and he Washingon Universiy a S. Louis, respecively,

ound ha he decline o labor unions explains up o one-hird o he increase in

male wage inequaliy beween 1973 and 2007.5

Tere are srong reasons o believe ha unions may increase opporuniy. Firs,

here are he direc effecs ha a paren’s union membership may have on heir

children. Union workers make more money han comparable nonunion work-

erswha economiss call he union premiumand when parens make more

money, heir children end o make more moneywhich economiss reer o as

he inergeneraional earnings elasiciy. In heory, unionized parens should passon a porion o he union premium o heir children. Tere may be oher chan-

nels hrough which children whose parens were in a union have beter oucomes

han oher children: union jobs may be more sable and predicable, which could

produce a more sable living environmen or children, and union jobs are more

likely o provide amily healh insurance.

Bu here are also a series o oher ways ha unions could boos inergeneraional

mobiliy or nonunion workers. I has been shown ha unions push up wages or

nonunion workers, or example, and hese wage gains or nonunion members

could be passed on o heir children.6 Children who grow up in nonunion house-

holds may also display more mobiliy in highly unionized areas, or example,

because hey may be able o join a union when hey ener he labor marke. Finally,

unions generally advocae or policies ha benefi all working peoplesuch as

minimum wage increases and increased expendiures on schools and public ser-

vicesha may especially benefi low-income parens and heir children. A recen

sudy on ineres groups and poliical influence ound ha mos o he naional

groups ha suppored middle-class prioriies were unions.7 Anoher sudy ound

ha saes wih higher union densiy also have higher minimum wages.8

In shor, here are many heoreical reasons o expec unions o go hand in hand

wih economic mobiliy, and his paper provides empirical evidence ha his is

indeed he case.


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Unions and intergenerational

mobility by area

In 2013, Chety, Hendren, Kline, and Saez made headlines wih heir paper

“Where is he Land o Opporuniy? Te Geography o Inergeneraional

Mobiliy in he Unied Saes.” Using ederal ax records, hey were able o

esimae he relaionship beween paren and child incomesinergeneraional

mobiliywih more precision han previous daases. Measuring he variaion in

mobiliy in areaswha hey call commuing zones, or CZsacross he counry,

hey ound ha some areas such as Pitsburgh, Pennsylvania, and Minneapolis,

Minnesoa, had much higher mobiliy han oher areas such as Charlote, NorhCarolina, and Alana, Georgia.

Te main limiaion o using ax records, however, is he lack o deailed individual

demographic and socioeconomic daa ha would allow scholars o examine par-

ens’ and children’s characerisics ha have he closes associaions wih inergen-

eraional mobiliy. Insead, Chety and his co-auhors combined he geographical

mobiliy esimaes wih rich demographic and social saisics on commuing

zones rom public daa sources o examine he geographical correlaion. Tey

ound ha five acors had he sronges relaionship wih mobiliy across com-

muing zones: he percen o children wih single mohers, social capial, income

inequaliy, high school dropou raes, and a measure o residenial segregaion

he percenage o workers wih less han 15 minue commues o heir jobs.

Chety and his co-auhors righly emphasize ha he geographical correlaions

hey find are no necessarily causal, bu raher serve as “a se o sylized acs o

guide he search or causal deerminans and he developmen o new models o

inergeneraional mobiliy.”9 Wha our geographical analysis does esablish is he

sylized ac ha regions wih higher union membership exhibi higher inergener-

aional mobiliy. Our analysis in he nex secion invesigaes his relaionship moreclosely, using survey daa o examine he relaionship beween individual parens’

union saus and heir children’s mobiliy while conrolling or more acors.


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Using wo geographic measures o mobiliy, we ollow he same approach as

Chety and his co-auhors o examine heir relaionship wih unions: We calcu-

lae he percen o workers in a commuing zone who are members o a union

reerred o as union densiyand measure is correlaion wih mobiliy across

commuing zones. o see how we consruced he union variable and he com-

muing zones, see Appendix A.

Mobility for low-income children

Te main variable Chety and his co-auhors use o measure geographical mobil-

iy is wha hey call absolue upward mobiliyhe expeced rank in he naional

income disribuion o a 29- o 32-year-old whose parens were in he 25h

percenile o he naional income disribuion. We use he same variable in heir

analysis, bu call i “mobiliy or low-income children” o avoid conusion wih our

oher mobiliy measure.

In our sample’s average commuing zone, he average 29- o 32-year old whose

parens were in he 25h percenile o he naional income disribuion ends up in

he 40.7h percenile as an adul. We find a very srong correlaion beween unions

and mobiliy across commuing zones: A 10 percenage poin increase in he

share o workers in a union is associaed wih a 1.3 percenile increase in children’s

rank. As a poin o comparison, he difference in mobiliy beween San Francisco,

Caliornia and Alana, Georgiarespecively, one o he mos and one o he

leas mobile o he 25 larges CZsis 7.1 percenile poins.

Figure 2 compares he size o he correlaion beween areas’ union membership

raes wih he five oher acors Chety and his co-auhors idenified as having he

sronges correlaion wih mobiliy.10 Te relaionship beween unionizaion and

mobiliy is abou he same as he relaionship beween residenial segregaion and

high school dropou raes, wo commonly cied drivers o mobiliy. Even when

one conrols or several variablesa commuing zone’s racial makeup, indusry

makeup, Chety’s five acors, he number o children per amily, he child pov-

ery rae, he median house value, he progressiviy o he ax code, and he share

o amilies covered by a sae’s Earned Income ax Credi, or EIChe shareo workers in a union remains a significan correlae o mobiliy or low-income

children. For deails on he analysis, see Appendix B.


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FIGURE 1

Union membership goes with economic mobility for low-income

kids across regions

Note: Dots represent union membership and mobility for low-income children by commuting zone. Labeled dots represent 15 mostpopulous commuting zones.

Source: Authors' analysis using data from Raj Chetty and others, "Where is the Land of Opportunity? The Geography of Intergenerational

Mobility in the United States," Quarterly Journal of Economics 129 (4) (2014): 1553–1623, available at http://www.equality-of-opportuni-ty.org; Data from Barry T. Hirsch and David A. Macpherson, "Union Membership and Coverage Database from the Current Population

Survey: Note," Industrial and Labor Relations Review 56 (2) (2003): 349–54, available at http://www.unionstats.com.

Expected income rank of low-income children by region

0 10 20 30 40

33

37

41

45

49

Union membership, 1986

Houston

Dallas

Atlanta

Miami

Boston

Washington, D.C.Los Angeles

Bridgeport

Newark San Francisco

Detroit

New York Seattle

Chicago

Philadelphia


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Mobility for all children

How unions affec he mobiliy o children who grew up in he 25h percenile is

imporan, bu perhaps even more imporan is how union membership affecs

he income rajecories o all children in a geographic area. Using Chety and his

co-auhors’ daa, we explore his quesion wih a variable ha we call mobiliy or

all childrenhe average income o aduls who grew up in an area conrolling or

he average income o heir parens.

Imporanly, his measure avoids he issue o wha he opimal-level o social

mobiliy is since higher incomes or all children in an area is unambiguously posi-

ive. For he rank-based measure used or low-income children, on he oher hand,

he opimal-level o mobiliy is unclear oher han he ac ha having i higherhan i is oday is preerable. Some associaion beween paren and children’s eco-

nomic saus may be desirable or sociey as i provides an incenive or parens o

inves in he human capial o heir children.

FIGURE 2

Union membership is strongly correlated with economic mobility

for low-income children

Absolute value of correlation between economic mobility for low-income children

and union membership compared to Chetty and others' "five factors"

Note: Correlation is estimate from regression, normalizing both dependent and independent variables so that univariate regressioncoefficients equal correlation coefficients. Unlike Chetty and his coauthors’ analysis, inequality is for the entire income distributioninstead of the bottom 99 percent resulting from issues in merging union and mobility data.

Source: Authors' analysis using data from Raj Chetty and others, "Where is the Land of Opportunity? The Geography of IntergenerationalMobility in the United States," Quarterly Journal of Economics 129 (4) (2014): 1553–1623, available at http://www.equality-of-opportuni-

ty.org; Data from Barry T. Hirsch and David A. Macpherson, "Union Membership and Coverage Database from the Current PopulationSurvey: Note," Industrial and Labor Relations Review 56 (2) (2003): 349–54, available at http://www.unionstats.com.

0.0

0.2

0.4

0.6

Segregation Social capital Dropout rates

Singlemotherhood

Unionmembership

0.255 0.270 0.274 0.333 0.367 0.626

Inequality


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Again, we find a srong relaionship beween mobiliy or all children and union

membershipa 10 percenage poin increase in union densiy is associaed wih a

4.5 percen increase in children’s incomesconrolling or heir parens’ incomes.

Even afer inroducing he several conrols menioned above, a 10 percenage

poin increase in an area’s union membership is sill associaed wih a 3 percen

increase in children’s laer incomes.

FIGURE 3

Union membership goes with economic mobility for all kids

across regions

Note: Dots represent union membership and mobility for all children by commuting zone. Mobility for all children is displayed using theresidual from a regression of the log of the commuting zone's average children's income on the log of the commuting zone's averageparent's income. Labeled dots represent 15 most populous commuting zones.

Source: Authors' analysis using data from Raj Chetty and others, "Where is the Land of Opportunity? The Geography of Intergenerational

Mobility in the United States," Quarterly Journal of Economics 129 (4) (2014): 1553–1623, available at http://www.equality-of-opportuni-ty.org; Data from Barry T. Hirsch and David A. Macpherson, "Union Membership and Coverage Database from the Current Population

Survey: Note," Industrial and Labor Relations Review 56 (2) (2003): 349–54, available at http://www.unionstats.com.

0 10 20 30 40

-0.2

-0.1

0.0

0.1

0.2

Union membership, 1986

Mobility for all children, 1980–1982 cohort

Houston

Dallas

Atlanta

Miami

Boston

Washington, D.C.

Los Angeles

Newark

San Francisco

Detroit

New York

Seattle

Chicago

Philadelphia

Bridgeport


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Discussion

Tis analysis reveals ha areas wih higher union membership have higher mobil-

iy no jus or low- income children, bu or all children. Tis relaionship holds

even afer conrolling or several oher acors, some o which may serve as a chan-

nel or how unions increase mobiliy. Our analysis, or example, conrols or ax

progressiviy, which Chety and his co-auhors find has a posiive correlaion wih

mobiliy. Unions, o course, are possibly he mos imporan advocaes in saes

or progressive ax codes and ha may be one o he key ways ha unions increase

mobiliy. By conrolling or ax progressiviy and oher variables such as social

capial ha a region’s union membership likely influences, we have subjeced he

union-mobiliy relaionship o a sringen es ha i appears o have passed.

Neverheless, Chety and his co-auhors cauion ha he correlaions hey find

such as he srongly negaive relaionship beween single moherhood raes and

mobiliyshould be inerpreed as a se o correlaions and sylized acs raherhan a causal finding. Te same cavea applies o our findings abou he spaial

relaionship beween unions and inergeneraional mobiliy. Wha is clear, how-

ever, is ha mobiliy hrives in areas where unions hrive.

Note: Correlation is estimate from regression, normalizing both dependent and independent variables so that univariate regression

coefficients equal correlation coefficients

Source: Authors' analysis using data from Raj Chetty and others, "Where is the Land of Opportunity? The Geography of IntergenerationalMobility in the United States," Quarterly Journal of Economics 129 (4) (2014): 1553–1623, available at http://www.equality-of-opportuni-

ty.org; Data from Barry T. Hirsch and David A. Macpherson, "Union Membership and Coverage Database from the Current PopulationSurvey: Note," Industrial and Labor Relations Review 56 (2) (2003): 349–54, available at http://www.unionstats.com.

FIGURE 4

Union membership is strongly correlated with mobility for all children

Absolute value of correlation between mobility for all children and union

membership compared to Chetty and others' "five factors"

0.00

0.10

0.20

0.30

Dropout rates

Singlemotherhood

Social capital SegregationUnion

membership

Inequality

0.219 0.247 0.260 0.270 0.271 0.310


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Mobility in union and

nonunion households

More confidence can be developed ha here is a srong relaionship beween

unions and upward mobiliy by using household-level daa o compare he

rajecories o children rom union and similar nonunion households. Ideally,

randomized conrols could be perormed or a naural experimen could be ideni-

fied where he assignmen o union membership is random and mobiliy could

be measured. Unorunaely, ha is no plausible. Insead, we use survey daa and

conrol or several observable characerisics o he parens, including race, educa-

ion, indusry, occupaion, age, work saus, and urban saus.

Te Panel Sudy o Income Dynamics, or PSID, is he bes daase or his work

because i no only racks households, bu when children rom he original house-

hold orm heir own household, i coninues o collec inormaion abou hem.

Tereore, i is possible o combine he characerisics o 26- o 37-year olds in

2011 wih he characerisics o heir parens in 1985 and compare he rajecories

o children whose parens were oherwise similar excep or heir union saus. See

Appendix C or more deails.

Similar o he geographic analysis, we examine wheher parens’ union saus

booss earnings or children overall and wheher i raises he earnings o he chil-

dren o low-skilled parens relaive o he children o high-skilled parens. Unlike

he previous analysis, which ocused on children whose parens’ incomes were

he samein he 25h percenilewe ocus on measures o skilleducaion and

blue- or whie-collar saussince one o he ways ha unions may boos relaive

mobiliy is by increasing he incomes o low-skilled aduls via he union premium,

which hese workers can hen pass on o heir children.

Neverheless, when one conrols or income, here is sill a saisically significanposiive relaionship beween union membership and children’s mobiliy, sugges-

ing channels or how parens’ union saus influences mobiliy independen o

one year o income. We also examine wheher parens’ union saus affecs oher

measures o well-being ouside o income, more specifically healh and educa-

ionwhich can also lead o higher incomes laer in lie.


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Effect of unions on children’s incomes

o provide a firs look a he effec o unions on children’s income, we do a simple

comparison o he labor incomes o ull-ime workers by he union saus o heir

parens. Tis par o he analysis does no conrol or any o he many possible

differences beween union and nonunion parens; insead, i does he comparisonseparaely or children wih a paren who graduaed college and children whose

parens did no. Tis is o ensure ha any posiive effec o unions on children’s

incomes acually increases opporuniy or hose who need i mos. Figure 5 pres-

ens he average incomes o children in he sample differeniaed by heir parens’

union saus and educaional saus.

Among children whose parens did no graduae college, he average income o

children wih a union paren exceeds he average income o children wih non-

union parens by $6,300, or 16 percen, a difference ha is significan a he 1 per-

cen level. For children who did have a paren who graduaed college, union saushad essenially no effec. Te resul or children whose parens graduaed college

indicaes ha unions could increase inergeneraional mobiliy. Bu he resuls do

no provide any insigh ino wheher hese differences reflec he direc impac o

paren’s union saus on children’s incomes.

*Difference is not statistically significant

Note: Calculations are for 26- to 37-year-olds who work full time and who had at least one parent who worked full time in 1985.

Source: Authors' analysis of the Panel Study of Income Dynamics 1985 and 2011 files, available at https://psidonline.isr.umich.edu/.

FIGURE 5

Children whose parents were in a union have higher earnings

Average labor income of children by parents’ union and education status

Parents did not graduate college At least one parent graduated college*

Union parent

Nonunion parents

$0

$20,000

$40,000

$60,000

$46,000

$39,000

$53,000 $54,000


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For his repor, we perorm a regression analysis ha conrols or several char-

acerisics o he parens ha affec heir income o allow or an apples-o-apples

comparison beween union and nonunion parens: race, ehniciy, marial saus,

educaion, age, urbanizaion, occupaion, ull-ime saus, and indusry. We find

ha he effec o having a aher in a union is an 18.7 percen increase in a child’s

earnings, an effec ha is significan a he 1 percen level. Nex, we conrol or heincome o he parens o examine i here are oher ways ha parens’ union saus

affecs mobiliy ouside o higher parenal incomes. Based on he findings, a union

aher sill increases an offspring’s income by a saisically significan 16.4 percen.

When he sample is divided ino sons and daughers, one finds ha union ahers

have posiive effecs on boh sons and daughers. Union mohers, on he oher

hand, have a posiive effec on daughers’ earnings bu have no effec on sons. We

also find ha union membership o he parens raises he incomes o children

independen o he child’s own union saus.

Te ac ha unions increase he earnings o children does no necessarily meanhey boos inergeneraional mobiliy in relaive erms; he quesion is wheher

unions boos he earnings o he children o higher-skilled or lower-skilled

parens. We do his by dividing our sample ino approximaely equally sized skill

groups based on he skill saus o he aher. Te firs comparison is or ahers

who atended college and ahers who did no. Te second comparison is or

ahers in blue-collar jobs and ahers in whie-collar jobs.

We find ha he effecs o ahers’ union saus are concenraed among he chil-

dren o lower-skilled ahers. For sons wih a aher who did no atend college,

unions boos earnings by 27.5 percen, and children o a aher wih a blue-collar

job see a 21.3 percen earnings increase. On he oher hand, unions do no have

saisically significan effecs on children wih college-educaed ahers or whie-

collar ahers. Te benefis o parens’ union saus are hus concenraed among

he children o lower-skilled parens, implying ha unions increase relaive iner-

generaional mobiliy.

We also examine wo oher measures o mobiliyhe healh and educaion o

he children. We measure educaion by years o school compleed and find ha a

aher in a union is associaed wih compleing an addiional hal year o educa-ion. We measure he effec o unions on healh using a five-poin scale or sel-

repored healh, 1 being lowes and 5 being highes. We find boh union ahers

and mohers are associaed wih saisically significan increases o 0.14 and 0.16

poins, respecively.11


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Discussion

Our findings among households ell a similar sory o he findings among com-

muing zones: union membership or parens has a posiive associaion wih

children’s uure earnings. Imporanly, hese effecs are concenraed among he

children o low-skill workers, which urns his inergeneraional union premium

ino a orce or inergeneraional mobiliy. Tese findings are especially noewor-

hy when combined wih he previous area-level analysis because he analyses

come rom wo compleely differen daases on wo differen levelshe regional

and household level.

Te household-level findings sugges a srong relaionship exiss beween unions

and mobiliy. Proving causaliy, however, is difficul wihou experimenal or quasi-

experimenal daa, which have become he gold sandard in modern empirical eco-

nomics. Bu he hope is ha hese findings will rigger urher research ino wheher

a causal relaionship beween unions and inergeneraional mobiliy exiss.

0%

10%

20%

30%

*Not statistically significant

Note: Calculations are for 26- to 37-year-olds who work full time and lived with a father in 1985 who worked full time. Calculationscontrol for father’s age, race, marital status, industry, occupation, and the urban status of the household.

Source: Authors' analysis of the Panel Study of Income Dynamics 1985 and 2011 files, available at https://psidonline.isr.umich.edu/

FIGURE 6

Unions increase the earnings of children with lower-skilled fathers

Effect of father’s union status on labor incomes of children by father’s skill group

No college education

Blue collar

White collar*

At least somecollege education*

27.5% 10.7% 21.3% 6.7%


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Unions and stagnant

intergenerational mobility

I unions boos inergeneraional mobiliy and hey have declined so much over

he pas 40 years, should economic mobiliy have allen? Chety and his co-

auhors analyze he ime rend o anoher measure o mobiliyhe probabiliy

ha a child born in he botom quinile would reach he op quinileand hey

find ha i did no decline beween he 1973 and 1993 birh cohors, a period over

which income inequaliy grew and unionizaion ell.12 A firs glance, his presens

a puzzle or our finding ha unionizaion is associaed wih inergeneraional

mobiliy, as well as or Chety and ohers’ finding wih respec o income equaliy.

Bu his puzzle only exiss i one believes ha declining union membership and

growing income inequaliy were he only rends ha affeced mobiliy over he

pas 40 years. Chety and his co-auhors find ha high school dropou raes and

racial segregaion have declined, offseting he decline in mobiliy one would

predic based on rising inequaliy and single moherhood raes:

We predict the trend in the rank-rank slope [relative mobility] implied by

changes in the five key correlates over time … Te predicted changes are quite

small because the factors move in opposing directions. For example, the increase

in inequality and single parenthood rates in recent decades predict a small

decline in mobility in recent decades. In contrast, the decline in racial segregation

and high school dropout rates predict an increase in mobility of similar mag-

nitude. Overall, the cross-sectional correlations documented here are consistent

with the lack of a substantial time trend in mobility in recent decades.13

Chety has also noed elsewhere ha mobiliy should have grown in a period

o alling racial discriminaion and he War on Povery.14 Mobiliy did no rise

beween he early 1970s and early 1990s despie rends ha Chety and his co-auhors’ daa sugges should have increased mobiliyincreasing educaional

atainmen, declining segregaion, and ederal programs argeed a reducing pov-

ery. I hese rends had no occurred, alling union membership along wih rising

inequaliy and single moherhood raes would likely have pushed down mobiliy.


18/36


I is also imporan o examine he rend in mobiliy over a longer ime period

since 20 years is a relaively shor span. In a recen Naional Bureau o Economic

Research, or NBER, working paper, Brown Universiy economis Nahaniel

Hilger examines educaional mobiliy using U.S. Census Bureau daa going all he

way back o 1940.15 He also finds ha mobiliy as measured by child educaional

atainmen did no change among 22- o 25-year olds beween 1980 and 2000, bu his comes afer 40 years o growing mobiliy beween 1940 and 1980.16 In

oher words, he ailure o inergeneraional mobiliy o grow beween 1980 and

2000 represens a change rom rising mobiliy in he decades beore. Moreover,

as Harvard poliical scienis Rober Punam has argued, i may ake ime or he

ull effecs o growing inequaliy o be refleced in mobiliy saisics i a causal

relaionship exiss.17 Te same could be rue or unions.

Our findings rom boh he area and household levels sugges ha he decline o

union densiy over he pas 40 years along wih he increase in inequaliy and rise o

single mohers played a role in prevening mobiliy rom rising. Wha his impliesabou he uure rend or economic mobiliy is discouraging unless one expecs

a coninued decline in high school dropou raes and urher reducion in racial

segregaion o offse he effecs o rising inequaliy and alling union membership.


19/36


Conclusion

In his repor, we have shown ha parens’ union membership has a significan

and posiive relaionship wih heir children’s well-being. Te adul offspring

o unionized parens earn higher labor incomes compared o he offspring o

nonunionized parens. Tey also atain higher levels o educaion, which can help

hem achieve beter economic sandings. Tis inergeneraional union effec is

sronger or less-educaed and less-skilled parens, making i a posiive orce or

inergeneraional mobiliy. An associaion also appears on he area level: Localiies

wih higher union membership are also areas where children o poor parens endup higher in he naional income disribuion and children hroughou he income

disribuion earn more in hese areas.

Te research in his repor is he firs o examine he relaionship beween unions

and inergeneraional mobiliy, bu hopeully i will no be he las sudy on his

opic. Researchers have produced a plehora o sudies on how alling union

membership has increased income inequaliy, and his repor will hopeully inspire

ohers o examine he relaionship beween unions and mobiliy in greaer deail.

Tis repor also provides lessons or policymakers who have, a leas rheorically,

embraced he concep o inergeneraional mobiliy. A serious policy agenda

aimed a boosing inergeneraional mobiliy mus include policies ha will

increase he bargaining power o workers. Te resuls rom his repor show ha

unions are a powerul orce or improving he economic lives no jus o organized

workers, bu o heir offspring as well. I is possible ha a srong union movemen

is no simply sufficien or high levels o inergeneraional mobiliy, bu i may be

necessary. I ha is he case, i will be difficul o meaningully increase inergen-

eraional mobiliy wihou also rebuilding unions or some comparable worker-

based organizaions.


20/36


Appendix A: Area-level data

o perorm he analysis o unions and commuing zones, we linked wo area-

level daases. Te firs comes rom he “Inergeneraional Mobiliy Saisics and

Seleced Covariaes by Couny,” developed by Chety and his co-auhors rom

which mobiliy or low-income and all children daa were obained (available a

www.Equaliy-o-Opporuniy.org). Te second daase is Barry Hirsch and David

McPherson’s Curren Populaion Survey-based esimaes o union densiy or

meropolian saisical areas (available a www.UnionSas.com).

Maching he wo daases involved some echnical complicaions. Te mobil-

iy and income daa relae o counies and commuing zones, or CZs, which are

hemselves collecions o counies. Te union daa are available on he meropoli-

an saisical area, or MSA, level, which are also collecions o couniesexcep

in New England, as described below. Te geographic analysis akes place on he

CZ level. Te primary advanage o CZs over MSAs is ha he CZ file comes

wih sae idenificaion, which allows or he use o sandard errors clusered a

he sae level o accoun or spaial and sae-specific correlaions. Boh CZ and

MSAs ofen cross sae boundariesor example, he Washingon, D.C., MSA

and CZ cover counies in he Disric o Columbia, Virginia, and Maryland. Bu

he MSAs do no have sae IDs, and hus we canno use sae clusered sandard

errors wih hem. We assign o each couny he union densiy o he MSA o

which i belongs and hen combines he counies ino CZs, dropping counies

ha are no par o MSAs since here are no union daa or hem. Tis removes

rural counies rom CZs and creaes some sligh differences in he covariaes rom

he original daa eaured in Chety’s paper. Bu we do no believe his is a serious

problem: he correlaion beween mobiliy or low-income children esimaes

o our limied CZs and he whole CZs is 0.946. Addiionally, we reconsruc he

covariaes on he CZ-level only or counies or which here are also union daa.Te correlaion beween he five acors in our limied CZs and he whole CZs

ranges beween 0.937 and 0.980.

http://www.equality-of-opportunity.org/http://www.unionstats.com/http://www.unionstats.com/http://www.equality-of-opportunity.org/


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Anoher problem in orming he mobiliy/unionizaion area daase is ha he

unionizaion daa or he New England saes differ rom hose o he res o

he counry. Insead o MSAswhich are collecions o whole counieshey

are really New England Ciy and own Areas, or NECAs, which are collec-

ions o owns. Counies can hus belong o muliple NECAs. Fairfield Couny,

Connecicu, or example, belongs o he Danbury, Samord-Norwalk, andBridgepor NECAs. o deal wih his problem, we ake he average o he union

densiies o he NECAs o which each couny belongs rom UnionSas.com,

weighed by he porion o heir 2000 populaion ha lived in each NECA. For

Fairfield Couny, or example, we averaged he union densiies o he NECAs o

Danbury (13.2 percen), Samord-Norwalk (12.9 percen), and Bridgepor (22.8

percen) MSAs, weighed by heir 2000 populaions residing in Fairfield Couny

(183,303, 353,556, and 345,708, respecively).

Once we successully combined heir mobiliy and union daa a he couny level,

he nex sep was linking hem o several oher couny-level covariaes beoreurning hem ino CZs. Mos covariaes come rom Chety’s publicly available

older on www.Equaliy-o-Opporuniy.org: populaion; percen o children wih

a single moher; commue ime; high school dropou raes; he Gini coefficien;

social capial; a sae’s EIC coverage; and he progressiviy o he sae’s ax code.

Te SAA code in he older was used o produce couny-level esimaes o

hese variables, mached hem o he couny-level esimaes o mobiliy and union

densiy, and hen ransormed hem ino CZs. Chety and his co-auhors ound

ha he mos significan acors in heir analysis were single moherhood raes,

dropou raes, commue imes, social capial, and inequaliy among he botom

99 percen. We do no include he las covariaea Gini coefficien o he botom

99 percen o he couny’s income disribuionbecause i is based on nonpublic

ax daa and is no provided a he couny level. We use he overall Gini coefficien

insead. We hen added oher covariaes: indusry since some indusries are more

unionized han ohers, wih daa on indusries in Chety ’s raw daa older rom

he 2000 Census: ”Sex by Indusry or he Employed Civilian Populaion 16 Years

and Over.” We place he indusries ino five caegories.18 Muliple race variables

were also creaed. Using race daa rom he 2000 Census in he Naional Hisorical

Geographic Inormaion Sysem in Chety’s public daa older, variables or he

percenage o he commuing zone ha is non-Hispanic whie, non-Hispanic black, non-Hispanic Asian, non-Hispanic “oher,” and Hispanic were creaed.

Finally, we added U.S. Census daa rom 2000 on he child povery rae, average

number o children per amily, and he median value o owner-occupied housing.

http://www.equality-of-opportunity.org/http://www.equality-of-opportunity.org/


22/36


Once we combined union, mobiliy, and oher covariae daa on he couny level,

we urned hem ino CZs. Lacking union daa ouside o MSAs, his analysis does

no apply o rural areas. Te oal populaion o our CZs in 2000 was 207 million

people compared o a U.S. populaion o 281 million in 2000.19 Tere is no way o

obain unionizaion raes or rural areas o see wheher he resuls o his repor do

or do no hold or hese areas.


23/36


Appendix B: Area-level analysis

Tis repor uses he area-level daa or wo ypes o analysis.

Firs, he repor uses Chety’s preerred “absolue upward mobiliy” variable,

which measures he expeced rank in he 2011–2012 income disribuion o per-

sons rom he 1980–1982 birh cohor whose parens’ 1996–2000 income placed

hem in he 25h percenile o he naional income disribuion. Tis is reerred o

as mobiliy or low-income children.

Te ollowing model was used:

(1) R25 iO = β0 + β1U i

P + ∑ di X i + εi

In his model, i indexes commuing zone (CZ), o indexes offspring, and p indexes

heir parens. R25 iO measures he expeced rank o a 25h percenile child in 2011

and 2012. U i P measures he CZ’s union densiy in 1986, which is when he young

persons would have been 4 o 6 years old. Because union densiy by area is a sable

saisic across areas in relaive erms, he resuls are similar or union densiy over

oher ime periods. o reduce he poenial ha he effec o unionism will be con-

ounded wih ha o oher area variables, he X i vecor in he regression conrols

or a large se o covariaes, including many ha could be channels or unionism o

increase mobiliy: a commuing zone’s racial makeup, indusry makeup, Chety’s

and his co-auhor’s five acors, he number o children per amily, he child

povery rae, he median house value, he progressiviy o he ax code, and sae

Earned Income ax Credi, or EIC, coverage.

We firs perorm he univariae correlaion beween union densiy and mobiliy

or low-income children displayed in column 1. o assess he relaive srengh ohis correlaion beween mobiliy or low-income children and union densiy, we

compare i o he correlaion beween mobiliy or low-income children and he

five acors ha Chety ound o have he sronges relaionship wih mobiliy or

low-income children: he percen o children wih single mohers as parens; he


24/36


income-adjused dropou rae; he level o social capial; he percen o work-

ers wih less han 15 minues commues, which is a measure o segregaion; and

inequaliy as measured by he Gini coefficien. As menioned in Appendix A and

endnoe 10, we use he overall Gini coefficien while Chety and ohers use he

Gini or he botom 99 percen. As done by Chety and his co-auhors, we normal-

ize all covariaes and mobiliy or low-income children so ha hey have a meano zero and sandard deviaion o one or beter comparison. Columns 2 hrough

7 show ha he correlaion beween mobiliy and union densiy is a leas as large

as he correlaion beween mobiliy and dropou raes, social capial, or segrega-

ion. Columns 8 and 9 repor he coefficiens rom he mulilevel regression o he

mobiliy or low-income children on union densiy and he oher covariaes. In

column 8, even afer conrolling or all five acors, union densiy sill shows a sig-

nificanly posiive associaion wih mobiliy or low-income children. In column 9,

we conrol or he five acors and several oher covariaes: race; indusry; median

housing value; he number o children per amily; ax progressiviy; he sae’s

EIC coverage; and he share o children living below he povery line. In hisspecificaion, union densiy sill remains significan.

Nex, we esimae he effec o union densiy in a commuing zone on he 2011–

2012 income o persons rom he 1980–1982 birh cohor who had resided in ha

zone by he ollowing model:

(2) LogȲ iO = β0 + β1U i

P + β2 LogȲ i P + ∑ di X i + εi

In his model, i indexes commuing zone (CZ), o indexes offspring, and p indexes

heir parens. Ȳ i P measures he average income o parens in he ih CZ rom 1996

o 2000, and Ȳ iO measures he average income o offspring who grew up in he same

CZ. As beore, he X i vecor in he regression conrols or a large se o covariaes.

As above, column 1 shows he relaionship beween union membership and

mobiliy or all children. A 10 percenage poin increase in union densiy is associ-

aed wih a 4.5 percen increase in children’s incomes. Columns 2 hrough 7 com-

pare he correlaions beween mobiliy or all children, union densiy, and he five

acors. Union densiy has a leas as large o a correlaion as he oher variables

wih he excepion o inequaliy. I also mainains a srong correlaion in each ohe mulivariae analyses in columns 8 and 9.


25/36


TABLE A1

Unions, the five factors, and mobility for low-income children

Mobility for

low-income

children

Mobility for

low-income

children,

normalized

Mobility for

low-income

children,

normalized

Mobility for

low-income

children,

normalized

Mobility for

low-income

children,

normalized

Mobility for

low-income

children,

normalized

Mobility for

low-income

children,

normalized

Mobility for

low-income

children,

normalized

Mobi

low-i

chil

norm

(1) (2) (3) (4) (5) (6) (7) (8) (

Union density12.90***

(4.579)

Union density,

normalized

0.333*** 0.386*** 0.2

(0.118) (0.131) (0.0

Percentage of

workers with a

commute under

15 minutes,

normalized

0.255*** 0.214** 0.1

(0.090) (0.090) (0.0

Overall Gini

coefficient,normalized

-0.367*** 0.123 -0.1

(0.112) (0.113) (0.0

Dropout rate,

income adjusted

and normalized

-0.274** -0.047 -0.1

(0.110) (0.088) (0.0

Social capital,

normalized

0.270** 0.044 -0.0

(0.132) (0.084) (0.0

Percentage of kids

with single mother,

normalized

-0.626*** -0.576*** -0.

(0.061) (0.078) (0.1

Other covariates No No No No No No No No Y

State clusteredstandard errors

Yes Yes Yes Yes Yes Yes Yes Yes Y

Observations 203 203 203 203 163 201 203 161 1

R-squared 0.111 0.111 0.065 0.135 0.070 0.073 0.392 0.540 0.7

Note: Cluster robust standard errors in parentheses. *** p


26/36


TABLE A2

Unions, the five factors, and mobility for all children

Log child

income

Log child

income,

normalized

Log child

income,

normalized

Log child

income,

normalized

Log child

income,

normalized

Log child

income,

normalized

Log child

income,

normalized

Log child

income

Log

inc

(1) (2) (3) (4) (5) (6) (7) (8)

Log parent income0.442*** 3.424*** 3.921*** 3.392*** 3.647*** 3.120*** 3.232*** 0.422*** 0.

(0.033) (0.258) (0.285) (0.272) (0.313) (0.254) (0.269) (0.050) (0.0

Union density0.449*** 0.451*** 0.

(0.107) (0.124) (0.

Union density,

normalized

0.271***

(0.065)

Percentage of

workers with

commute under 15

minutes, normalized

0.270*** 0.021** 0.

(0.051) (0.009) (0.

Overall Ginicoefficient,

normalized

-0.310*** -0.011 -0.

(0.059) (0.011) (0.

Dropout rate,

normalized

-0.219*** -0.010 -0.

(0.078) (0.009) (0.

Social Capital,

normalized

0.260*** 0.002 -0.

(0.085) (0.012) (0.

Percentage of kids

with single mother,

normalized

-0.247*** -0.019* 0.

(0.053) (0.010) (0.

Other covariates No No No No No No No No

State clustered

standard errors Yes Yes Yes Yes Yes Yes Yes Yes

Observations 203 203 203 203 163 201 203 161

R-squared 0.687 0.687 0.687 0.709 0.656 0.668 0.668 0.803 0.



27/36


Appendix C: Individual household

data and analysis

Te Panel Sudy o Income Dynamics, or PSID, provides deail on he characeris-

ics o amilies, including he labor income and union saus o he head o house-

hold and o he head’s spouse and he comparable characerisics o heir adul

offspring when hey orm heir own households. o obain a sample o parens

and heir adul offspring, we mached he 1985 and 2011 PSID files by individual

and creaed a new file limied o individuals who were children or sepchildren o

he head o a household in 1985 and were hemselves heads o household or he

spouses o household heads in 2011. We also resric he sample o hose youngerhan 38 years old in 2011younger han 12 years old in 1985so ha hey are

young enough o be direcly influenced by parens’ economic saus. We creaed a

new se o 2011 offspring variables o characerize his group: characerisics o he

household heads i he individual was he head o household and characerisics o

he wives i he individual was he married or unmarried parner o he household

head. Tese offspring variables are designed o ocus on he relaionships beween

parens and heir children raher han beween parens and he spouses o heir

children. Because we limi heir analysis o heads o household and spouses, he

daa exclude children who were no heads o household or spouses, which consis

primarily o hose living wih heir parens in 2011.

We regress he log o offspring income on he log o heir parenal income and

oher parenal characerisics using he ollowing orm:

(3) LogY jk = β0 + β1U k P + β2 LogY k

P + ∑ dk X k P + ε jk

In his model, j indexes offspring and k indexes heir parens. Y is offspring’s labor

income.20 UP is heir parens’ union saus, where 1 means he parens are union-

ized and 0 ha hey are no in a union. Y P

is parens’ amily income and X P

rep-resens oher parenal atribues: parens’ age; race and ehniciy; heir ull-ime

saus; educaion; marial saus; indusry and occupaions; and he urban saus

o he household. I UP is significanly posiive, hen on average, he offspring o

union parens earn higher incomes han he offspring o nonunion parens.


28/36


able 3 gives he resuls o he regressions o he log o offspring income on par-

ens’ atribues, including parens’ amily income.21 Te coefficien on he log o

amily income in column 1 is he inergeneraional income elasiciy, or IGE, ha

measures he associaion beween parens’ income and heir offspring’s income.22

Te esimaed coefficien o 0.326 indicaes ha i parens’ income increases by

10 percen, offspring’s labor income increases by 3.3 percen or all persons in hesample.23 Te addiion o he covariaes or parenal atribues reduces he coe-

ficien o 0.239 in column 2.

Column 3 examines he effec o having union parens on offspring income

absen amily income bu wih inclusion o oher parenal covariaes and deliv-

ers our main finding rom he individual-level daa: he aher’s union saus has a

significan effec on child income wih a magniude o 0.187, which implies ha

he adul offspring o unionized ahers earn 18.7 percen higher income han he

adul offspring o nonunionized ahers. Te addiion o parenal amily income in

column 4 reduces he coefficien on he union saus o parenal-household heado 0.164. Tis implies ha he effec o parens’ unionism goes beyond heir higher

income due o he union premium.

Finally, in columns 5 and 6, we add a dummy variable indicaing wheher he

offspring are unionized. Te esimaed coefficiens on parenal union saus and

parenal income do no change much afer we include offspring’s union saus,

which suggess ha parens’ union saus has an independenly posiive impac on

heir children’s income beyond wheher heir children join a union. Te esimaed

coefficien on children’s union saus shows ha hey earn a subsanial union pre-

mium. Compared o children whose parens and hemselves have no connecion

o unionism, children whose parens are unionized and hemselves are also union-

ized earn abou 37 percen (18.5 percen + 18.6 percen) higher labor incomes.

We also analyzed he effec o parens’ unionism conrolling or separae labor

incomes o household heads and heir spouses raher han conrolling or paren’s

amily income, and we find an even higher efficien coefficien on union ahers.24

We also examine he effecs o mohers’ and ahers’ union saus on daughers and

sons separaely in ables 4 and 5. Te relaionship is less precisely esimaed han

he above regressions since he sample size is abou hal. Te poin esimaes or heeffec o ahers’ union saus on sons are slighly smaller han in he pooled samples

while, mohers’ union saus appears o have no effec on sons’ labor incomes. For

daughers, we find he effecs o ahers’ union saus are larger han hose or sons,

and he effec o mohers’ union saus is also posiive bu no quie significan.


29/36


Given he many pahways ha educaed and skilled workers are likely o have o

pass on heir economic advanages o heir children, i is imporan o deermine

wheher he union parens’ effec on heir offspring’s income is sronger among

less-educaed and less-skilled workers han among more-educaed and more-

skilled workers. In he ormer case, he union effec would reduce relaive social

mobiliy while in he later case he union effec would increase relaive mobiliy.

o examine his issue, we divided heir sample by level o educaionahers

wih no college educaion and hose wih a leas some college educaionand

by naure o workahers in blue-collar occupaions compared o ahers in

whie-collar occupaionsand esimaed equaion 3 and 4 or hese groups. We

only examine ahers in order o avoid he complicaions o marriages where one

parner has a college educaion or a whie-collar job while he oher has no college

educaion or a blue-collar job. We used a leas some college as he cuoff because

roughly hal o ahers had some college educaion, and he cuoff hus maximizes

sample size or boh groups. Te resuls, summarized in able 6 show ha heunion effec in raising he income o offspring is concenraed among ahers wih

less educaion and among ahers in blue-collar jobs. While one poenial explana-

ion is he large union wage premium or low-skilled workers, he inclusion o he

parenal household income variable, which should reflec he wage premium, sill

leaves a sizable independen union effec.

Our final research quesion in he individual-level daa is wha exen does he

effec o parens’ unionism show up in oher measures o socioeconomic well-

being? We examine his quesion by esimaing varians o equaions 3 and 4 ha

replace children’s labor income wih measures o educaional progresshighes

grade compleedand healh, as repored by individuals on a 1 o 5 scale wih 5

as he bes healh and 1 as he wors healh saus.

For he healh and educaion regressions, we condiion on a head o household

who works ull ime raher han a head o household or wie ha works ull ime

as in he oher regressions. Tis is in order o capure unions’ poenial role on

moher’s well-being hrough beter maerniy leave since a moher on maerniy

leave would no be couned as working ull ime. Unlike all he oher resuls

including he educaion resulshe healh resuls are sensiive o his adjusmenand do no display significan effecs i we condiion on eiher he household head

or wie working ull ime. We also drop he requiremen or he healh regressions

ha he children work ull ime since he beneficial effecs o unions on children’s

healh should no depend on heir labor marke saus. Te healh resuls are posi-


30/36


ive bu no significan when we condiion on he child working ull ime and/or

condiion on a head o household or wie working ull ime. Columns 1 and 2 o

able 7 give he resuls or he educaion measure. Tey show ha having a union

aher increases highes grade compleed even or persons wih he same amily

income.25 Columns 3 and 4 o able 7 give he resuls or he healh measure o

offspring. Te healh saus o offspring is associaed wih boh heir moher’s andaher’s union saus. And, as in he calculaions or he highes grade compleed,

he resul or union ahers holds wih he addiion o amily income, implying

ha unionism improves offspring’s healh hrough mechanisms beyond parens’

income. Tis may reflec he beter healh care benefis ha unions provide mem-

bers and heir amilies.

TABLE A3

Unions and children’s earnings

Log childlabor income





Log chlabor in

(1) (2) (3) (4) (5) (6)

Log of family income, 19850.326*** 0.239*** 0.224*** 0.23

(0.074) (0.068) (0.070) (0.07

Union Father, 19850.187*** 0.164** 0.185*** 0.16

(0.062) (0.064) (0.060) (0.06

Union Mother, 19850.073 0.023 0.060 0.00

(0.087) (0.085) (0.085) (0.08

Union child

0.186*** 0.20

(0.059) (0.05

Other covariates No Yes Yes Yes Yes Ye

State clustered standard errors Yes Yes Yes Yes Yes Ye

Observations 1,068 1,068 1,068 1,068 1,068 1,06

R-squared 0.066 0.188 0.179 0.193 0.186 0.20



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TABLE A4

Effect of parents’ union status on sons’ earnings

Log child

labor income

Log child

labor income

Log child

labor income

Log child

labor income

Log child

labor income

Log ch

labor in

(1) (2) (3) (4) (5) (6)

Log parent income

0.313*** 0.205 0.201 0.212

(0.098) (0.125) (0.129) (0.126

Union father0.142 0.125 0.133 0.115

(0.087) (0.087) (0.083) (0.083

Union mother-0.017 -0.054 -0.014 -0.053

(0.137) (0.137) (0.133) (0.132

Union child0.247** 0.260

(0.073) (0.07

Other covariates No Yes Yes Yes Yes Ye

State clustered standard errors Yes Yes Yes Yes Yes Ye

Observations 566 566 566 566 566 56R-squared 0.060 0.238 0.231 0.241 0.242 0.25



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TABLE A6

Unions and mobility by fathers’ educational and occupational group

Noncollege-

educated

father

Noncollege-

educated

father

College-

educated

father

College-

educated

father

Blue collar

father

Blue collar

father

White collar

father

White

fat

Log child

labor income

Log child

labor income

Log child

labor income

Log child

labor income

Log child

labor income

Log child

labor income

Log child

labor income

Log

labor i

(1) (2) (3) (4) (5) (6) (7) (8

Union father0.275*** 0.195** 0.107 0.104 0.213*** 0.146** 0.067 0.

(0.083) (0.088) (0.086) (0.085) (0.075) (0.069) (0.100) (0.

Log father labor

income

0.284*** 0.059 0.293*** 0.

(0.066) (0.097) (0.069) (0.

Other covariates Yes Yes Yes Yes Yes Yes Yes

State clustered

standard errors Yes Yes Yes Yes Yes Yes Yes

Observations 435 435 479 478 498 497 416

R-squared 0.234 0.263 0.059 0.060 0.194 0.230 0.047 0.



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About the authors

Richard Freeman holds he Herber Ascherman chair in economics a Harvard

Universiy and is a research associae a he Naional Bureau o Economic

Research in Cambridge, Massachusets.

Eunice Han is a proessor o economics a Wellesley College and a research ellow

a he Naional Bureau o Economic Research. Her research covers opics in labor

economics and he economics o educaion wih an emphasis on insiuions and

legal sysems. She currenly ocuses on he impac o unionism on he local labor

marke, especially wih regards o income inequaliy and economic mobiliy. She

received her Ph.D. in economics rom Harvard Universiy in 2013.

David Madland is he Managing Direcor o he Economic Policy eam and he

Direcor o he American Worker Projec a Cener or American Progress. He has

writen exensively abou he economy and American poliics on a range o opics,including he middle class, economic inequaliy, reiremen policy, labor unions,

and workplace sandards such as he minimum wage. His book, Hollowed Out:

Why the Economy Doesn’t Work without a Strong Middle Class , was published by he

Universiy o Caliornia Press in June 2015. Madland has a docorae in govern-

men rom Georgeown Universiy and received his bachelor’s degree rom he

Universiy o Caliornia, Berkeley.

Brendan V. Duke is a Policy Analys or he Cener or American Progress’ Middle-

Ou Economics projec. His research ocuses on economic inequaliy and eco-

nomic growh. He holds a maser’s degree in economics and public policy rom

Princeon Universiy’s Woodrow Wilson School o Public and Inernaional Affairs.


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Endnotes

1 Raj Chetty, Nathaniel Hendren, Patrick Kline, and Em-manuel Saez, “Where is the Land of Opportunit y? TheGeography of Intergenerational Mobility in the UnitedStates,” Quarterly Journal of Economics 129 (4) (2014):1553–1623.

2 Ibid.

3 David Madland and Nick Bunker, “Unions BoostEconomic Mobility in U.S. States” (Washington: Centerfor American Progress Action Fund, 2012), available athttps://www.americanprogressaction.org/issues/labor/report/2012/09/20/38624/unions-boost-economic-mobility-in-u-s-states/.

4 Bruce Western and Jake Rosenfeld, “How Much HasDe-Unionisation Contributed to the Rise in Male Earn-ings Inequality,” The American Sociological Review 4 (76)(2011): 513–537; David Card, Thomas Lemieux, and W.Craig Riddell, “Unions and Wage I nequality,” Journalof Labor Research 25 (2004); John DiNardo, Nicole M.Fortin, and Thomas Lemieux, “Labor Market Institu-tions and the Distribution of Wages, 1973–1992: ASemiparametric Approach,” Econometrica 5 (64) (1996):1001-1004; Richard B. Freeman, “How Much Has De-Unionisation Contributed to the Rise in Male EarningsInequality?” In Sheldon Danziger and Peter Gottschalk(eds.), Uneven Tides (New York: Sage Press, 1992), pp.133–163.

5 Western and Rosenfeld, “How Much Has De-Unionisa-tion Contributed to the Rise in Male Earnings Inequal-ity.”

6 Unions’ tendency to raise wages for nonunion workersbecause firms try to avoid unionization is called thethreat effect. Unions could also reduce wages fornonunion workers if union wages and benefits reducedemployment in the union sector, increasing the laborsupply in nonunion work; this is called the crowdingeffect. Evidence suggests that the threat effect domi-nates the crowding effect and that unions raise wagesfor nonunion workers. See Henry S. Farber, “NonunionWage Rates and the Threat of Unionization,” ILR Review 28 (3) (2005): 335–352.

7 Martin Gilens, Affluence and Influence: EconomicInequality and Political Power in America (Princeton, NJ:Princeton University Press, 2013), pp. 154–160.

8 James Cox and Ronald L. Oaxaca, “The Political Econo-my of Minimum Wage Legislation,” Economic Inquiry 20(4) (1982): 533–555.

9 Chetty, Hendren, Kline, and Saez, “Where is the Land ofOpportunity?”

10 Chetty and others, “Where is the Land of Opportunity?”finds a Gini coefficient of just the bottom 99 percent ofhouseholds has a stronger negative association withmobility than an overall Gini does and uses this bottom99 percent Gini as one of its five factors. We use theoverall Gini, however, because they do not provide abottom 99 percent Gini by county (which we need to

include it in our analysis because of the complicationsof combining with the union data), and it comes fromtheir federal tax data, so public data could not be used.See Appendix A for more details.

11 As described in the appendix, the health results aresensitive to the population analyzed. We find positiveand statistically significant results when we do not con-dition on the child working full time and only condition

on the head of household working full time (the latterto include union mothers on maternity leave). Thehealth results are positive but not sign ificant when wecondition on the child working full time and/or condi-tion on a head of household or wife working full time.

12 Raj Chetty and others, “Is the United States Still a Landof Opportunity? Recent Trends in IntergenerationalMobility,” American Economic Review Papers and Pro-ceedings 104 (5) (2014): 141–147.

13 Chetty, Hendren, Kline, and Saez, “Where is the Land ofOpportunity?”

14 Danny Vinik, “Is It Inequality or Mobility? Neither Econo-mists nor GOP Candidates Can Decide,” New Republic ,April 7, 2015, available at http://www.newrepublic.com/article/121465/2016-presidential-candidates-face-challenge-talking-about-inequality.

15 Nathaniel G. Hilger, “The Great Escape: Intergenera-tional Mobility Sin ce 1940.” Working Paper 21217 (Cam-bridge, MA: National Bureau of Economic Research,2015).

16 Ibid.

17 Robert D. Putnam, Our Kids (New York: Simon & Schus-ter, 2015), p. 228.

18 Sectors are based on Zoltan Kenessey, “The Primary,Secondary, Tertiary And Quaternary Sectors Of TheEconomy,” Review of Income and Wealth 33 (4) (1987):359–385. Analysis with major industry categories yieldssimilar results.

19 Marc J. Perry and Paul J. Mackun, “Population Changeand Distribution” (Washington: U.S. Bureau of theCensus, 2001), available at https://www.census.gov/prod/2001pubs/c2kbr01-2.pdf.

20 To measure the direct effect of parents’ unionism onoffspring income, the authors focus on offspring’slabor income rather than the combined family incomeof married couples. The use of labor income drops

children who are self-employed status or out of laborforce.

21 The full results for all of the authors’ regression analysesare available upon request.

22 It is commonly understood that the higher value ofIGE, the lower the intergenerational mobility is. In oneextreme case, the IGE would be equal to zero if thereexists no relationship between family background andthe adult offspring income. Children born into a poorfamily would have the same likelihood of earning ahigh income as children born into a rich family.

23 Although the authors used labor income rather thanfamily income of offspring, this estimate is consistentwith literature. See Chetty and others, “Where is theLand of Opportunity?”; Chul-In Lee and Gary Solon,“Trends in Intergenerational Income M obility,” Review

of Economics and Statistics 91 (4) (2009): 766-772;Bhashkar Mazumder, “Fortunate Sons: New Es timatesof Intergenerational Mobility in the United States UsingSocial Security Earnings Data,”The Review of Economicsand Statistics 87 (2) (2005): 235-255. This literaturestates that the estimated IGE could be subject to theattenuation bias if the data focus on short-term periodsdue to the long-lasting transitory shocks to income.

http://www.newrepublic.com/article/121465/2016-presidential-candidates-face-challenge-talking-about-inequalityhttp://www.newrepublic.com/article/121465/2016-presidential-candidates-face-challenge-talking-about-inequalityhttp://www.newrepublic.com/article/121465/2016-presidential-candidates-face-challenge-talking-about-inequalityhttp://www.newrepublic.com/article/121465/2016-presidential-candidates-face-challenge-talking-about-inequalityhttp://www.newrepublic.com/article/121465/2016-presidential-candidates-face-challenge-talking-about-inequalityhttp://www.newrepublic.com/article/121465/2016-presidential-candidates-face-challenge-talking-about-inequality


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24 If we control for separate labor incomes of bothparents, the coefficients on union father in Model 4, forexample, is 0.25 and is statistically significant at the 1percent of significance level. The coefficient on unionmothers remain insignificant.

25 In regressions with high school graduation as themeasure of schooling, the father’s unionism raises sons’high school graduation rate by a statistically significant4.4 percentage points.


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