asian development review: volume 30, number 2

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Asian Development Review

Demographic Dividends RevisitedJefrey G. Williamson

Princelings and Paupers? State Employment and the Distribution of Human

Capital Investments Among Households in Viet NamIan Coxhead and Diep Phan

Foreign Firms and Indigenous Technology Development in the

Peoples Republic of ChinaFredrik Sjholm and Nannan Lundin

Dynamics of Household Assets and Income Shocks in the Long-run Process

of Economic Development: The Case of Rural PakistanTakashi Kurosaki

Inequality of Human Opportunities in Developing AsiaHyun H. Son

Political Connection and Firm ValueJames S. Ang, David K. Ding, and Tiong Yang Thong

Volume 30 2013 Number 2


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EDITOR

Masahiro Kawai

EDITORIAL BOARD

Chair Changyong Rhee

Co-Managing Editors Maria Socorro G. Bautista

Mario Lamberte

KEIJIRO OTSUKA, National Graduate Institute

for Policy Studies

EUSTON QUAH, Nanyang Technological

UniversityHYUN SONG SHIN, Princeton UniversityKAR-YIU WONG, University of WashingtonWING THYE WOO, University of California,

Davis

CHARLES WYPLOSZ, Graduate Institute ofInternational and Development Studies

KYM ANDERSON, University of Adelaide

PREMACHANDRA ATHUKORALA,

Australian National University

IWAN AZIS, Cornell UniversityPRANAB K. BARDHAN, University of

California, Berkeley

SHIN-ICHI FUKUDA, The University of TokyoJONG-WHA LEE, Korea UniversityMARCUS NOLAND, Peterson Institute for

International Economics

The Asian Development Review is a professional journal for disseminating the results of economicand development research relevant to Asia. The journal seeks high-quality papers done in an empiricallyrigorous way. Articles are intended for readership among economists and social scientists in government,

private sector, academia, and international organizations.The views expressed in this publication are those of the authors and do not necessarily

reflect the views and policies of the Asian Development Bank (ADB), the Asian Development Bank Institute(ADBI), ADBs Board of Governors, or the governments they represent.

ADB and ADBI do not guarantee the accuracy of the data included in this publication and accept noresponsibility for any consequence of their use.

By making any designation of or reference to a particular territory or geographic area, or by usingthe term country in this document, ADB and ADBI do not intend to make any judgments as to the legalor other status of any territory or area.

Please direct all editorial correspondence to the Co-Managing Editors,Asian Development Review,Economics and Research Department, Asian Development Bank, 6 ADB Avenue, Mandaluyong City,1550 Metro Manila, Philippines. E-mail: [email protected]

Note: In this publication, $ refers to United States dollars.

For more information, please visit the website of the publication

at www.adb.org/data/publications/1125

HONORARY BOARD

Chair Takehiko Nakao

MONTEK SINGH AHLUWALIA, Government

of IndiaMASAHIKO AOKI, Stanford University

PETER DRYSDALE, Australian National University

JUSTIN LIN, Peking University

MARI ELKA PANGESTU, Republic of Indonesia

HAN SEUNG-SOO, Member, UN

Secretary-Generals Advisory Boardon Water and Sanitation

LAWRENCE SUMMERS, Harvard

University, John F. Kennedy School

of Government


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Asian Development ReviewVolume 30 2013 Number 2

September 2013


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Volume 30 2013 Number 2

Demographic Dividends Revisited 1

Jefrey G. Williamson

Princelings and Paupers? State Employment and 26

the Distribution of Human Capital Investments Among

Households in Viet Nam

Ian Coxhead and Diep Phan

Foreign Firms and Indigenous Technology Development 49

in the Peoples Republic of China

Fredrik Sjholm and Nannan Lundin

Dynamics of Household Assets and Income Shocks 76

in the Long-run Process of Economic Development:

The Case of Rural Pakistan

Takashi Kurosaki

Inequality of Human Opportunities in Developing Asia 110

Hyun H. Son

Political Connection and Firm Value 131

James S. Ang, David K. Ding, and Tiong Yang Thong

2013 List of Referees 167

Call for Papers 168

Instructions for Authors 169


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Demographic Dividends RevisitedJ EFFREY G. WILLIAMSON

Thispaperrevisitsdemographicdividendissuesafteralmost2decadesof debate.In 1998, David Bloomand I used a convergencemodel to estimatethe impactof demographic-transition-driven agestructure effects and calculated what theliterature has come to call the demographic dividend. Theseearly estimatesseem to be similar to those coming from more recent overlapping generationmodels, when properly estimated. Research has shown that the demographicdividend is not simply alabor participation rateeffect, but also agrowth effect.Life-cycle savings, investment deepening, foreign capital flows, and school-ing have all been greatly affected by the demographic transition. The paperdiscusses just how much of these positive growth effects are based on accel-erating human capital accumulation induced by demand-side qualityquantitytrade-offs versus a co-movement between demographic transitions and publicschooling supply-sideexpansions. Sinceemigration has been driven in part bydemography, it has wasted some of the demographic dividend by brain drain.In addition, within-country ruralurban migrations have also been driven inpart by demographic transitions with different spatial timing. Finally, thepapershows how lifetimenot just annualincome inequality has been influencedby demographic transitions.

Keywords:demographictransitions, demographicdividends,growth,inequality,AsiaJEL codes: J10, O11, O15, O40, O53

I. LookingBackwards: TheDemographic DividendConvergenceModel

Backinthe1950s,1960s,and1970s,pessimistsbelievedthatrapidpopulationgrowth in the Third World was immiserizing because it tended to overwhelm thecontributionsof technical changeandcapital accumulation(CoaleandHoover1958,Ehrlich1968). Optimists believed that rapid population growthhelped an economycapture economies of scale from market size and promoted both technologicalandinstitutional innovation (Kuznets1967, Boserup1981, Simon1981). Researchculminating in the late1980s defeated both viewspopulation growthwas shownto have no significant impact on economic growth, positive or negative (Kelley

JeffreyWilliamsonistheLairdBell Professor of Economics,emeritus,of HarvardUniversityandanHonoraryFellow

of theEconomics Departmentat theUniversity of Wisconsin. This paper drawsheavily onmy previouspublicationscited in the text, some of which havebeen withcollaborators who havemy thanks: David Bloom, Timothy Hatton,and Matthew Higgins. In addition, thecommentsof Noel deDios, John Nye, Xin Meng, Feng Wang, Andy Mason,participants at the Asian Development Review conference held in Manila on 2526 March 2013, and the journalsrefereesaregratefully appreciated.

Asian Development Review, vol. 30, no. 2, pp. 125 C 2013AsianDevelopmentBankandAsianDevelopmentBank Institute


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2 ASIAN DEVELOPMENT REVIEW

1988).Thesestudiesweretypically basedoncross-countryregressionsof per capitaincome growth on population growth, controlling for a variety of other influences.As Allen Kelley and Robert Schmidt(1995, p. 543) put it:

Possibly the most influential statistical finding that has shaped thepopulation debates in recent decades is the failure, in more thana dozen studies using cross-country data, to unearth a statisticallysignificant association between the growthrates of population and ofper capitaoutput.

This finding was surprising, but it was unclear then whether it arose be-cause population truly had no effect on economic growth or because the test hadbeen somehow misspecified. Work immediately followingdecomposed populationgrowthinto its fertility and mortality components and examined their independenteffects oneconomic growth (Coale1986, Bloomand Freeman 1986, Barlow 1994,Brander and Dowrick 1994, Kelley and Schmidt 1995). These studies found thatmeasures of fertility, specifically past birth rates, were negatively andsignificantlyassociatedwitheconomic growth, whereas theeffectof mortalitywasinsignificant.

These contributions were the direct precursors to the demographic dividend liter-

ature that followed in the wake of the Asian Development Banks Emerging Asiaconference (ADB 1997): This line of research justified the decomposition on thegrounds that changes in fertility and mortality could imply very different changesin theagedistribution.

Populationgrowthattributabletoafall ininfantmortalityandariseinfertilityboth had an immediatenegativeeffect on economic growth sincethis meant moremouths to feed. A fall in mortality everywhere across the age distribution couldraisetheadult labor force, giving an offsetting positiveimpact.

However, wenow understand that thenegativedemographic effect has ade-

layedpositiveimpactoneconomic growthsincetheeconomically activepopulationbooms 2 decades later, long after theaggregatepopulation growtheffect may havedisappeared. This positive effect on economic growth abates as the fertility ratedeclines, but withalong lag.

Figure 1 plots the stylized version of this demographic transition, showingthetransitionfromhigh fertility and highmortality whenthecountry ispoor to lowfertility and low mortality when the country is rich. Thetwo critical aspects of thetransition arefirst, that the initial mortality declineis driven primarily by a fall ininfant mortality, andsecond, that fertilityrates arevery slow todeclineinresponse.

The transition takes decades to complete. The population growth rate is implicitin the first panel of Figure 1 as the differencebetween fertility and mortality. Thesecond panel makes the population dynamics explicit: the demographic transitionis accompanied by a cycle in population growth and an even more dramatic cycle


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DEMOGRAPHIC DIVIDENDS REVISITED 3

Figure1. TheStylizedDemographic Transition

Share

working

Percent in

workforceGrowth

Time

Birth rate

minus

death

rate

Birth rateDeath rate

Time

Birth rateDeath rate

Population

growth rate

Demographic Transition

Population Growth and the Age Structure

Source: Bloomand Williamson (1998), Figure1.

in theagestructure. Figure1 treatsthedemographic systemas if it was closed, andthusitignoresexternal migration.Thisassumptionwill berelaxedlater inthepaper.

The East Asian demographic evidence certainly supports Figure 1 (BloomandWilliamson1997and1998; Feeney andMason2001;OshimaandMason2001;Lee2003; Mason2007aand2007b; BloomandCanning2008;Mason, Lee, andLee2010), but the question back in 1997 was just how big the demographic transitionimpactoneconomic growthwas. Indeed, how muchof theEast Asianmiraclecouldit explain?

DavidBloomandI (1997and1998) contributedtothisstageof thepopulation

debatein four ways.

1

First, likeAllen Kelley and Robert Schmidt (1995), we usedthe empirical convergence model (Barro 1991 and 1997) to isolate the effects of

1Theseresults werelater confirmed in moredetail by Bloom, Canning, and Malaney (2000).


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demography. Second, weexploredthepossibilityof reversecausalitybyusingatwo-stagespecificationwhereinstrumentsforpopulationgrowthwereusedtoaccountforpossible endogeneity. Third, weintroduced demography into the growth equationsin a theoretically more appealing way than simply by the ad hoc addition of birthand deathrates, specifically by adding the growth rates of the total population andtheeconomically activepopulation. By doingso, populationgrowthwas allowed toaffect economic growth by its overall rateand by its age structure. Thedistinctionmattered. Fourth, we used theseeconometric results to assess the extent to whichpopulation dynamics could help account for a significant portion of East Asiaseconomic miracle.

What did we find? Between 1965 and 1990, the working age population in

East Asia grew 2.4% per annum, dramatically faster than the 1.6% rate for theentire population, yielding a 0.8 percentage point differential. The working agepopulation also grew faster than the entire population in Southeast Asia, but thedifference was almost half that of East Asia, while in South Asia it was a quarterof the East Asian figure. Combining the coefficients from the estimated growthequations and the growth rates of the working age and total population, Table 1reports that population dynamics explained between 1.4 and 1.9 percentage pointsof per capita GDP growth in East Asia (6.11% per annum)the biggest regionaleffectworldwideorasmuchasathirdof thegrowthmiracle(1.9/6.11= 0.31).2 If

instead the miracle weredefined as the differencebetween current per capitaGDPgrowth (a transitional rate where population dynamics matter) and some steadystate of say 2% (when population is also in steady state and has no impact), thenpopulation dynamicsexplained almost half of themiracle (1.9/[6.112]= 0.46).

In Southeast Asia, where the fertility decline took place a little later andthe infant mortality decline was a little less dramatic, population dynamics stillaccountedfor0.9to1.8percentagepointsof economic growth, oragain, asmuchashalf of their lessimpressivemiracle(1.8/3.8=0.47).TheEastAsianeconomiesthatbenefitedmostfromthesedemographiceventswereHongKong,China;theRepublic

of Korea; Malaysia; Singapore; Taipei,China; andThailand. ItisnocoincidencethattheseAsian tigers attracted most of Paul Krugmansattention whenheasserted thatthe East Asian miracle was driven mainly by high rates of accumulation and laborforcegrowth (Krugman 1994).3

Based on the coefficients of the estimated convergence model and the UN2025demographic projections, BloomandI (1998) concludedthatthefuturewouldlook quitedifferent(Table2). InEastAsia, per capitagrossdomestic product(GDP)growthattributabletodemographic influenceswasprojectedtobenegativebetween1990and2025,decliningfromapositivegainof 1.4to1.9percentagepointsbetween

2Eight years later, Kelley andSchmidt (2005) also used the convergence model to estimatea figureof 28%for all Asia in 19601995, quiteclosetoour 31% for East Asia in 19651990.

3Krugman relied on the results of Alwyn Young (1994a and 1994b) and J ong-Il Kim and Lawrence Lau(1994), but theseresults weresubsequently challenged with muchhigher total factor productivity growthestimates.


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Table1

.ContributionofDemographicChangetoEconomicGrowth,1

965

1990

Regions

AverageGrowth:

RealGDPPer

Capita(%)

A

verageGrowth:

Population(%)

AverageGrowth:

Economically

Active

Population

(%)

AverageGrowth:

Dependent

Population(%)

EstimatedContribution,

1965

1990

(4modelspecifications)

(

1)

(2)

(3)

(4)

Asia

3.

33

2.

32

2.

76

1.

56

1.

04

1.

64

0.

86

0.

73

EastA

sia

6.

11

1.

58

2.

39

0.

25

1.

71

1.

87

1.

60

1.

37

Southe

astAsia

3.

80

2.

36

2.

90

1.

66

1.

25

1.

81

1.

07

0.

91

SouthAsia

1.

71

2.

27

2.

51

1.

95

0.

66

1.

34

0.

48

0.

41

Africa

0.

97

2.

64

2.

62

2.

92

0.

14

1.

10

0

.

07

0

.

06

Europe

2.

83

0.

53

0.

73

0.

15

0.

43

0.

52

0.

39

0.

33

SouthAmerica

0.

85

2.

06

2.

50

1.

71

1.

03

1.

54

0.

87

0.

74

NorthAmerica

1.

61

1.

72

2.

13

1.

11

0.

94

1.

34

0.

81

0.

69

Oceania

1.

97

1.

57

1.

89

1.

00

0.

74

1.

14

0.

62

0.

53

Source:BloomandWilliamson(1998),Table6

.


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Table2

.Contr

ibutionofDemographicChangetoFutureEconomicGrowth,1

9902025

Regions

ProjectedGrowth:

Population(%

)

ProjectedGrowth:

EconomicallyActive

Population(%)

ProjectedGrowth:

D

ependent

Population(%)

EstimatedContribution,

1990

2025

(4mo

delspecifications)

(1)

(2)

(3)

(4)

Asia

1.

36

1.

61

0.

99

0.

61

0.99

0.

50

0.

43

EastAsia

0.

43

0.

20

0.

87

0

.

40

0.14

0

.

44

0

.

38

SoutheastAsia

1.

29

1.

66

0.

63

0.

83

1.10

0.

73

0.

62

SouthAsia

1.

65

2.

11

0.

90

1.

02

1.38

0.

90

0.

77

Africa

2.

40

2.

78

1.

88

0.

98

1.63

0.

73

0.

68

Europe

0.

17

0

.

004

0.

48

0

.

32

0.16

0

.

34

0

.

29

SouthAmerica

1.

50

1.

87

0.

94

0.

82

1.15

0.

71

0.

60

NorthAmerica

1.

28

1.

33

1.

21

0.

21

0.645

0.

11

0.

10

Oceania

1.

08

0.

93

1.

37

0

.

22

0.24

0

.

31

0

.

26

Sour

ce:BloomandWilliamson(1998),Table7

.


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Figure2. Economic GrowthandtheDemographic Transition,East Asia

Youth

demographic

burden

Economic

miracle

Sutainable

growth

Demographic gift

Other transitional

forces Economic

miracle

Growth rate of real GDP per capita

c. 1945 c. 1960 c. 2010 c. 2025

Time

Source: Bloomand Williamson (1998), Figure6.

1965 and 1990 to a loss of 0.1 to 0.4 percentage points up to 2025, a projectedretardationof 1.5 to2.3 percentagepoints duesolely todemographic forces. SouthAsia was projected to see a 0.8 to 1.4 percentage point growth rate gain as it leftthe burden stage of the demographic transition entirely and entered the gift ordividend stage. Southeast Asia was predicted to register a smaller demographicdividend (0.61.1 percentage points): The biggest gainer was projected to be thePhilippines whilethebiggest loserswereprojected tobeMalaysiaand Thailand.

The macro evidence seemed to support the hypothesis that demographic

eventshelpedaccountfortheEastAsianeconomicmiracle.Figure2offersastylizedversionof thedemographicdividendhypothesis wherethesustainablegrowthrateistakentobeabout2%per annum. Theactual growthrateinGDP per capitafirstfalls,due to a large and rising child share; then rises, as that large child cohort reachesyoung adulthood; then reaches a peak, reinforced by a lagged decline in fertility;after whichagingandretirementlower theworkingageshareandslowgrowthrates.

The reader should note that the contribution of the demographic transition(labeled the demographic gift in Figure 2) to East Asian economic growth past,present, and futuredepends on how themiracleis defined. If it is defined as ashare

of per capitaGDP growth between 1960 and 2010 in Figure2, then it accountsforabout athird of themiracle. If it is defined as the surplus over thesustainable rate,then it accounts for almost half. But if it is defined as the increase in growth ratesfrom19451960 to 19602010, then it accounts for almost three-quarters. These


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are very big numbers. Could their size be attributable to the assumptions of theconvergencemodel?

II. DecomposingtheConvergenceModel: ParticipationRate

andProductivity Effects

The demographic dividend literature took a big empirical step forward withapaper by Allen Kelley and Robert Schmidt (2005) whichdecomposed thegrowtheffectsuncoveredby thenavedemographic dividendmodel into itstransitorylaborparticipation rate effects and its longer term productivity effects. The first part is

pure demographygiven labor productivity growth, any rise in activity or laborparticipation rate (LPR) will raise per capita income growth. Furthermore, theimpact is transitory, although it may last decades. What about thesecond part?

Kelley and Schmidt (2005) listed some possible channels of impact of de-mography onproductivitygrowthscaleeconomies,density, life-cyclesavingsandinvestment responses, and human capital accumulation, two of which will be dis-cussed at length below. But they only used the list to motivate a reduced-formestimationof thetwo effects. Their main finding was that demography had no longrun impactonproductivity growth. It turns out that they spoketoo soon.

III. HowBigtheDividend? ComputableOLG andConvergenceModels

Analysts weresuspiciousof the sizeof thedemographic dividend estimatedwith the reduced-form convergence model (taking accumulation as exogenous)since the underlying savings, capital accumulation, and schooling variables are allendogenous (Feyrer 2007, Sanchez-Romero 2012). Thus, a more recent literaturehasemergedusingcomputableoverlappinggenerations(OLG) modelswhichfocus

explicitly on the savings and accumulation response, and the demographic impactis typically estimated to be much smaller. For example, that literature finds onlya small demographic impact on Japans economic growth in the late 20th century(Braun, Ikeda, and Joines 2009). While the OLG estimated impacts are biggerfor Taipei,China (Lee, Mason, and Miller 2000, 2001, and 2003) and the PeoplesRepublic of China(PRC) (Curtis, Lugauer, and Mark 2011) than for Japan, all ofthe morerecentOLG models seemed to yield smaller demographic dividends thandid the original convergencemodels. But now it appears that they do so mainly byassumption.

A recent and impressive paper by Miguel Sanchez-Romero (2012) showsthat there is actually little difference between the computable OLG and the earlyconvergencemodel resultswhenappliedtoTaipei,Chinaslate20thcentury history.Sanchez-Romero finds that demography accounts for 22% of Taipei,Chinas per


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capitaoutput growth in 19652005. Why the differencebetween Sanchez-Romeroand Leeet al.? Bothareusing computableOLG models, but oneadds an importantreality missing from the other. Typically, the computable OLG models get theirresult by performing counterfactual experiments fixing birth and death rates atthoseprevailingat thestart of theperiodexamined. In contrast, and morecorrectly,Sanchez-Romero fixes birth and death rates at the levels prevailing a generationbefore. The former underestimates the demographic impact; the latter reports thatfor Taipei,Chinain 19651990, 25% of per capitaincomegrowth can beexplainedby demography, muchcloser tothe28% estimateof Kelley and Schmidt (2005) forAsiaand the31% estimateof Bloomand Williamson (1998) for East Asia.

Thus, it appears that the difference in the estimated growth impact of the

demographic transition on Taipei,Chinas performance is much the same whethertheconvergencemodel ortheOLG model isemployed.Whatremainsistodeterminewhether theresult for Taipei,Chinageneralizes toEastandSoutheast Asia.

IV. Channelsof DividendImpact: SavingsandPhysical Capital Accumulation

A. Savings, Investment, andAccumulation

Sincethekey totheKelleySchmidt productivityimpactof thedemographicdividendmust lielargely withaccumulationresponses, thelife-cyclesavingsmodeland related literaturehas pursued this connectionfor Asiaever sinceAnsley Coaleand Edgar Hoover (1958) wrote about dependency burdens a half century ago.An anecdotal fact illustrates the point. In the early 1970s, Korean authorities wereconcerned by their countrys heavy dependence on Japaneseinvestment financingand commissioned World Bank papers toexplorewhy theRepublic of Koreasavedsolittle (Williamson1979). By thelate1980s, theRepublic of Koreahaddoubleditssavingsrate, anditscurrent account balanceshareof GDP had swungfrom8%

(netcapital inflow)to+3.2%(netcapital outflow). Over thesameperiod, theKoreandependency ratefell by morethan 12 percentagepoints, ahugedecline.

Was the correlation spurious, or was demography driving some of the accu-mulation boomand its financing? The subsequent literature was thus motivated bythefollowingquestions:Howmuchof theimpressiveriseinEastAsiansavingsratesacrossthelate20thcentury couldbeexplainedby theequally impressivedeclineindependency burdens? How much of the fall in external capital dependency in EastAsiasincethe1970scould beexplained by thesamedemographic forces?

Over thepast 2 decades, theliteraturehas assigned alargeroletothedemo-

graphic transitionin explaining accumulation-driven productivity gains underlyingthe East Asian miracle. Saving and investment rates can both be driven by demog-raphy, each tracing out an inverted-U. The explanation for the saving rate trendwould be the famous life-cycle model with high saving rates in the middle of the


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demographic transitionwheremature adultsdominate.4Theexplanation for thein-vestmentratetrendwouldbetheimpactof bigworkingadultsharesgeneratinglargeinvestment shares, and thus accumulation rates, in the middle of the demographictransition. Thefollowing predictions logically follow:

(i) If thesavingrateinverted-U is moredramatic than that of investment, then netcapital import shares, or foreign capital dependency, would be big early andsmall in themiddleof thetransition.

(ii) If, incontrast,theinvestment inverted-U ismoredramatic thanthatfor savings,thennet capital import shareswould besmall early andbig in themiddleof thetransition.

Theory cannot discriminatebetween thetwo predictions, but empirical workcan. The earliest work to pursue the assessment for East Asia (Higgins andWilliamson 1997, Higgins 1998, Williamson and Higgins 2001) found the fol-lowing: rising fertility and falling infant mortality had a profound impact on EastAsian saving rates, investment rates, and foreign capital dependency over the halfcentury following 1950. Much of the impressive rise in East Asian saving ratesafter the late1960s could be explained by the equally impressive decline in youthdependency burdens.

Furthermore, the evidence supported the first prediction abovecountriesthat kicked the foreign capital dependency habit first and fastest were the coun-tries where the youthdependency burden fell first and most dramatically. Much ofthe contrasting foreign capital dependency between South and East Asia could beexplained by the size of the youth dependency burden and its persistence. All ofthis implied that demography could explain alargeshareof theEast Asian miraclethroughaccumulationandKelleySchmidtproductivity effects.

Theseearly studies mademany assumptions along theway: that moreabun-

dant world savings supplies did not alter capitals incentive to seek new Asianopportunities, although it certainly did; that world capital markets stayed equallyopen throughout thehalf century, although they certainly did not; that thelife-cyclemodel was an appropriate explanation for savings behavior; and that the demo-graphic transition was exogenous to accumulation performance. Subsequent workhas explored the importance of these assumptions at length, but never in a reallypersuasiveway.

UsinganOLG model withfixedhouseholdsizeandexogenousinterest rates,we are told that demography explains almost none of J apans national savings rate

4Life cycle trends in income and saving have been well documented in the literature, much of it for Asia(Mason, Lee, and Lee 2008, p. 12; M ason and Kinugasa 2008, p. 390). Recent work on the PRC since the 1990ssuggests thesame(Curtis, Lugauer, andMark 2011; Wei andZhang2011; Banerjee, Meng, andQuian 2010).


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(Hayashi and Prescott 2002; Chen, Imrohoroglu, Imrohoroglu 2006 and 2007), butusing an OLG model with endogenous interest rates and variable household size,we aretold that demography has a positiveeffect (Braun, Ikeda, and Joines 2009).Using an OLG model with fixed interest rates and youth dependency, we are toldthat demography matters for Taipei,Chinassavingrateexperiencesince1960(Lee,Mason, and Miller 2000, 2001, and 2003). Morerecently, andagain usingtheOLGmodel withfixed interest rates, wearetold that most of thePRCshigh savingratesare driven by demography (Curtis, Lugauer, and Mark 2011). These assumptionsmatter.

B. What About World Capital Markets?

Of all these assumptions invoked in the literature surveyed in the previoussection, the financial capital open economy assumption, or what the analysts calltheinterestrateassumption, is probably themost important, and themost poorlyunderstood. If the interest rate is taken as exogenous, then we are assuming aneconomy open to world capital markets, where financial capital is allowed to flowfreely across borders, the world interest rateprevails locally, and domestic savingoffers no constraint on domestic investment. We are also asked to assume that theworld borrowingratefacingEastandSoutheastAsiawasconstant over thelate20th

century although it certainly was not. Instead, their emerging market borrowingrates converged on the Organisation for Economic Co-operation and Development(OECD) rates (Obstfeld and Taylor 2004; Mauro, Sussman, and Yafeh 2006).

If, instead, the interest rate is taken to be endogenous, then we are askedto assume an economy completely closed off from world capital markets, wherecapital does not flow across borders at all, domestic savings constrains domesticinvestment, anddomestic savingandinvestmentjointly determinethelocal interestrate. Some of these papers make the open economy assumption, some make theclosed economy assumption, but noneas far as I knowexplorethewidereality

in between and how it changed over time.Indeed, it is rare that we are told how much the assumption matters.

Taipei,China is an exception. Between 1965 and 1990, Sanchez-Romero (2012)reports that when the economy is assumed to havebeen open to capital flows, de-mography accountsfor 25% of per capitaoutput growth, and when it is assumed tohavebeen closed, demography accounts for only 17.2%.5

Inopeneconomies,domesticsavingsisnotaconstraintonaccumulation, andthusbooming workingadult shares haveabigger impact oninvestment, accumula-tion, and growth. Whereis the literaturethat shows us that Asian economies open

toworldcapital marketshadbigger demographic effectsthanthoseclosed?Perhaps

5However, Sanchez-Romero does not explore an open economy assumption where Third World borrowingrates fall, acharacterization that comes closer toworld capital market integrationfromthe1970s onwards.


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moretothepoint, Asiancapital marketsweremostly closedbeforethe1970s, whilethey havebeen mostly open since. Thus, where is the literature that shows us thatAsianeconomieshadbigger demographic effectsbeforethe1970sthanafterwards?

Theempirical problemunderlyingthelastresearchquestionis, of course, thatstagesof worldcapital market integrationandstagesof demographic transitionshavebeencorrelated in Asiaover thepast half century.

C. A SecondDemographic Dividend?

TheearlyconvergenceandOLG modelsassumedthatolder andretiredwork-ers dissaved, and that the demographic dividend evaporated as the demographictransition moved into its last stages. Some now think that the dividend persists.Why? TheAsiandatashow that individualsconsumemuchmorethanthey producewell into old age (Mason, Lee, and Lee 2008; Mason and Kinugasa 2008, p. 390).Of course, this could be explained by massive intergenerational transfers withinfamilies, but it might also be explained by higher rates of saving for old age bymatureworkingadults.

Thereareat least threeplausiblereasons why current matureworking adultsmight havehigher saving rates than the previous generation thus raising aggregatesaving rates late in the demographic transition. First, greater expected longevity

would encouragethat result. Whilethenavedemographic transition models stresstheinitial declineinchildmortality, improvementsinhealthenvironmentsalsoraiselife expectancy at age 40 or 50, and those effects become increasingly importantas the transition evolves. Second, mortality becomes less uncertain as disease issuppressed in poor countries. Lower uncertainty about life expectancy would alsoencourage more saving by mature working adults. Third, as family size declines,thespatial mobility of children rises, andretirement years increase, parentsmay bemuchless certain about thesupport they can expect fromtheir children in their oldage, offeringanother incentiveformatureworkingadultstosaveevenmore. If these

forces do indeed raise the saving rates of mature working adults, then they couldcreateasecond demographic dividend.

All of this is certainly plausible, and it has been confirmed for Asia wheregreater longevityhasraisedsavingratesacrossall adultgroups(BloomandCanning2003). But the PRC, South Asia, and Southeast Asia are not far enough advancedwith their demographic transition to offer the required evidence for assessing themagnitudesof aseconddemographictransition.6 All theAsianevidencecomesfrom

6Between2000and2005, thepopulation growth ratewas 1.39% in ASEAN and 1.62% in India, whileit was

only 0.14% in J apan, 0.46% in the Republic of Korea, and 0.54% in Taipei,China. In 2000, the youth dependencyrates were: 41.8% in ASEAN and 45.1% in India versus 20.5% in J apan; 28.9% in theRepublic of Korea; 23.7% inHong Kong, China; and 29.7% in Taipei,China. In 2000, the population shares 65 and older were: 4.9% in ASEANand 4.6% in India versus 17.2% in J apan; 7.4% in the Republic of Korea; 11% in Hong Kong, China; and 8.1% inTaipei,China(Mason, Lee, and Lee2010, Tables 1.1, 1.2, and 1.4).


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theRepublicof Korea; Japan; andTaipei,China. RonaldLeeandAndrewMasonfindvery large second dividends for Taipei,China (Mason and Lee 2007; Mason, Lee,andLee2010) whichthey argueisconsistent withthemicrostudiesof Taipei,China(Deaton and Paxson 2000). For a sample of 25 European countries plus Australia,

Japan, the Republic of Korea, Malaysia, New Zealand, Thailand, and the UnitedStates (US), the estimates of second dividends are large. Indeed, the two (savingrate) dividends areestimated to havebeen aboutequal (Mason andKinugasa2008,p. 398): declining child dependency led to arisein saving rates by 6.9 percentagepoints (while) improvements in adult survival led to a rise in saving rates by 6.7percentagepoints.7

Whether thesesecond dividend magnitudes will hold up for thePRC, South

Asia, and Southeast Asiacannotyet beasserted, but that futurelooks likely.

V. Channelsof DividendImpact: HumanCapital Accumulation

andVintageEffects

We all agree that human capital accumulation is an important driver ofgrowth, so how might it beconnected tothedemographic transition? Therearetwopossibilities.

First, and following Gary Becker (1960 and 1981) and H. Gregg Lewis(Becker and Lewis 1973), there may be a qualityquantity trade-off working atthe family leveli.e., more children and lower investment per child versus fewerchildrenandhigherinvestmentperchild.Thiswouldclearlybeaforceendogenoustothedemographic transition: A low-quality child cohort (produced under conditionsofhighfertilityandbigfamilies)impliesweakvintageeffectswhenthatcohortentersthe labor forcea decade or two later, while a high-quality child cohort (producedunder conditions of low fertility and small families) implies a big vintage effectwhen the cohort enters the labor force a decade or two later. If those cohorts are

themselves big, thevintageeffect is even bigger.Second, there is the possibility of an independent co-movement between

public spending ontheseinvestmentsand thesizeof theyouthcohorts. If apublic-schoolinghealth revolution coincides with the demographic transition, and if thatrevolution impacts on the quality of the new children, we have what might becalled a quasi-endogenous effect. Without the public-schoolinghealth revolution,the vintage effects of the demographic transition would be weak and limited tothe demand-side Becker effects, but with it, they would be strong and pushed bythe supply side. In any case, both of these forces imply vintage effectsaverage

human capital per worker rises as the well-schooled young workers replace thepoorly-schooledolder workers.

7For an elegantandimpressiveextension of their views, seeLeeandMason (2011).


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A. EndogenousSchoolingfromtheDemandSide: QualityversusQuantity

Someof thebestwork documentingtheendogenousqualityquantity humancapital effectscomingfromfertilitydeclinesinthesecondstageof thedemographictransition, atleastfor Asia, havebeenproducedby AndrewMason, RonaldLee, andtheir collaborators. The cross-section correlation between total public and privatehuman capital investment per child and the total fertility rate is striking (Mason,Lee, andLee2010, Figure1.8). Intheir research, Japan, theRepublic of Korea, and

Taipei,Chinaarelater in thedemographic transition with high investment per childand low fertility rates. India, Indonesia, and thePhilippines, meanwhile, areearlierin the demographic transition with low investment per child and higher fertility

rates. Thailand is in themiddle.Lee and Mason (2009) haveshown how these qualityquantity correlations

couldhaveapowerful impactonhumancapital accumulationandgrowth.AlthoughindependentEastAsianevidencecertainlyseemstosupporttheBecker demand-sideconnection (Montgomery, Arends-Kuenning, and Mete 2000; Jun 2013), Lee andMasonnever identify thesourceof thecorrelationthey observeacross Asia. Was itqualityquantityfamilyeffectsthatwouldbesoclearlyassociatedwithdemographictransitions, or was it somethingelse?

Inaddition,theirmeasuresof investmentperchilddonotcontrol forschooling

qualitywhen parents demand more schooling for their children, it may generatecrowding and rising teacher (and other schooling) costs and thus more spending,butmaybenotmorequality-adjustedschooling. Thisisexactly what T. Paul Schultz(1987) found for a large sample of countries for the period 19601981, and whatI found for a smaller sample (but which included Hong Kong, China; Japan; theRepublic of Korea; Malaysia; the Philippines; and Thailand). Controlling for otherrelevant variables, we found the relative price of teachers had a strong negativeimpact onschooling (Williamson1993, p. 154).

Whyshouldwecare?Becausepositivepublicsupply-sideforcesshouldlower

the relativeschooling pricewhile demand side forces should raise it. The behaviorof the relativecost of schooling (and health) might help untangle the demand andsupply sideforces. Whereis theliteraturethat explores this important issue?

In short, whileother studies haveconfirmed thequalityquantity trade-off inmicro data, Lee and Mason (2009) are dealing with macro data (and magnitudesacrosscountriesandover time) andwearenotyet surehow muchof thecorrelationtheyobserveisdrivenbyprivatefamily schoolingdemands, andhowmuchbypublicschooling supplies. Thedifferences will influenceinterpretation and thus policy.

B. SupplySide: DemographicTransitionsandPublicSchoolingRevolutions

Taipei,Chinawasaschoolingleader inAsia, anditsexperienceillustratesthesupply-sidepoint. In it was established 6 years of compulsory education, and this


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period was extended to 9 years in 1968. As a result, the proportion of illiterate. . .changed from 40% in 1940 to almost [zero] in 1970 (S

anchez-Romero 2012,

footnote2; citingHuang 2001).Obviously, whenTaipei,Chinapassedfromtheyouthdependencyphaseof the

demographictransitiontotheyoungadultworkerandthematureadultworkerphasesduring19502000(Mason,Lee,andLee2010, Tables1.2and1.3), theco-movementof theearly public schoolingrevolutionlater raisedaverageworker schoolingduetothesepowerful vintageeffects. TheAsianpublic schoolingrevolutionexamplescanbe easily multiplied (Williamson 1993, Duflo 2011).8 Indeed, the evidence showsthat since1950East Asiahas madeabigger commitment toschoolingand withasteeper riseinthatcommitmentthananywhereelseintheThirdWorld.Whyisthat

so,andwhyisitcorrelatedwithamoredramatic demographictransition?Isitpublicsupply-sidepolitical economy at work, orisit privatedemand-sidequalityquantitytrade-offs?Therecentneo-institutional contributionsof DaronAcemogluandJamesRobinson (e.g., 2006) and Stanley Engerman and Kenneth Sokoloff (e.g., 2012)would suggest low inequalityand broad political participationmight explainit. Butweneed far moreresearchonthis question.

VI. Emigration: MutingtheDividendsImpact by Brain Drain

A. EmigrationLifeCycles

Countries typically pass through a migration transition, or what might becalledanemigrationlifecycle, drivenby incomedifferencesbetweenthelow-wagesendingcountryandhigh-wagehostcountries,modernization, andeconomicgrowthat home, and of course, the sending countrys experience with its demographictransition. These emigration life cycles have been used by economic historians todescribeEuropeanemigrationfromthe1840stoWorld War I, whereeachcountrys

emigrationraterosesteeply fromvery low levels, after whichtherisebegantoslowdownastheemigrationratesreachedapeakandsubsequentlyfell againtolowlevels.

Thesehistorical emigration lifecycles can beseen in aggregatecountry emigrationrates, regional emigration rates within countries, and ruralurban emigration rateswithin countries (Hattonand Williamson2005b, Chapter 4).

Since these emigration life cycles are so pervasive in the historical data,it is hardly surprising that we also have seen them in the Third World since the1950s(HattonandWilliamson2005aand2011, Williamson[Forthcoming]). Whilesimilar to 19thcentury European emigration patterns, themorerecent Third World

8Thebest paper coveringthe19thandearly 20thcentury(primary) schoolingrevolutionin thenow-advancedcountriesis by RichardEasterlin(1981). Thereferencetothepost-World War II Asianschoolingrevolutionis mainlysecondary education.


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country emigration life cycles cover shorter time periods. One oft-cited exampleis the Republic of Korea where emigration rose steeply to a peak in 1982 andsubsequently declinedjust asquickly. Similar patternshavebeenobservedfor otherAsian countries and it is tempting to associatethese more compressed emigrationlife cycleswith economic miraclesand accelerated demographic transitions.

While emigration life cycles have been examined for individual countries,they have also been explored at more aggregative continental levels, although theexpectationis that theaggregatelife cycles should beless dramatic. After all, somecountriesstart andcompletetheir emigrationlifecyclesearly,whileothersstart andfinish later, tending topartially smoothout theaggregateregional experience. Still,Asia reached peak emigration rates in 19801984, even though some economies

reachedpeaksearly, liketheRepublic of KoreaandTaipei,China, whileothersmuchlater, likeIndonesiaand thePhilippines (Hattonand Williamson2011, Table1).9

This brief survey raises three questions. First, are emigration life cyclescountry-specific special cases or do they reflect some common laws of motion?Second, if they do reflect some common laws of motion, what are the shared eco-nomicanddemographicfundamentalsdrivingthem?Inparticular,whilewecertainlyseethecorrelationemigration life cycles following adecadeor two after thefirststageof thedemographic transitionexactly what roledoes thedemographic tran-sition play? Third, are the demographic forces powerful enough to account for at

least someof theobserved brain drain, and if so, arethedrainsbig enough to mutesomeof thedemographic dividends?

Modern economic analysis of international migration uses the frameworkfirstsetoutby Larry Sjaastad(1962) andrefinedby GeorgeBorjas(1987and1994),BarryChiswick (2000), andothers. Thus, theemigrationdecisionischaracterizedasdependingontheeconomic gainfrommigrationnet of itscosts, thelatter includingwaitingtime(influencedby short-runlabor marketconditionsinhostcountries) andqueuesrelatedtohostcountry admissioncriteria(andillegal migrationcosts). Sinceyoungadultshavethemost togainfromlongdistancemoves, they recordby farthe

highest emigrationrates. Thus, whenyoungadult cohortsarebig duringthesecondstage of the demographic transition, aggregate emigration rates should be big aswell, other things being equal.

Since capital markets facing most poor households are imperfect or evenabsent, thedemand to emigrateis constrained by poverty. But thoseconstraintsarereleased over time as growth miracles at home createmore good jobs and thus theincomes necessary to finance moreemigrants, andas remittances and in-kind helpfromprevious (and increasing) emigrants living abroad rises.10

9Asia is defined here very broadly to include East Asia, Southeast Asia, South Asia, the Middle East, andNorth Africa.

10Uninformed observers often think that successful development at home will keep young adults fromemigrating. On thecontrary, thebig incomegapsbetween sending andhostcountries arestill big, andnow familieshavemoreresources tofinancethenext emigrant.


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As growth miracles unfold, they generate two competing forces on the up-swing of the emigration life cycle: poverty rates fall making it easier for familiestofinancethemoves of their children and helping releasethepoverty constraint onemigration; but miracle growth implies catching up with theleaders, thus reducingthe gains fromthe move. The first dominates early in the emigration cycle, whilethesecond dominates later in thecycle.

Schooling matters as well. As the educational attainment of young cohortsrise, their abilitytoexploit labor market opportunitiesabroadrisesaswell. Emigra-tion may also be constrained by host country immigration policy and perturbed bycivil strifeat home, buttheseevents aremorerandom.

So goes thetheory, but theeconometric facts support thetheory.

B. EmigrationLifeCycleFundamentals

Recent research has identified the main drivers of Third World emigrationrates after the 1960s, the start of the great boom in world migration (Martin and

Taylor 1996). Thebestevidenceisfor sending-countryemigrationtotheUS (Hattonand Williamson 2011). While changing immigration policy, civil strife at home,and other exogenous events have mattered, it is the underlying demographic andeconomic fundamentals that explain the common emigration life-cycle experience

acrosssendingcountries.First, the US migrant stock effect made the most important contribution to

the boom up to the 1990s, reflecting both the importance of family reunificationin US immigration policy and the previous impact of economic and demographicfundamentals on migration flows which then got embedded in the current migrantstock, thus raising current flows. Indeed, were it not for the migrant stock effect,Asian emigration rates would havefallen steeply after 19901994 rather than onlyslightly dropping. Second, the birth cohort effect played an important role in thedownturn after 19901994 in Asia.11 Third, education catch-up also played an

important role everywhere in the Third World, augmentingemigration rates, but itwasespecially powerful inAsia, wheretheschoolingrevolutionwasmost dramatic.Fourth, while there was certainly per capita income growth catch-up in Asia, thegrowthmiracleswerenotfastenoughtoreducesignificantlytheincomegapwiththeUS, thus they contributed little to the emigration boom. Finally, while statisticallysignificant, the diminished poverty trap did not contribute as much to either theemigration boomin 19901994, or thedeclinethereafter.

C. BrainDrainandWastedDemographic Dividends?

Perhapsitisobviousthatemigrationof well-schooledyoungadultsdiminishesthedemographic dividend. True, somehaveshownthatemigrationof well-schooled

11Thesamewas trueof Latin Americabut not Africawherethedemographic transition is lagging behind.


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young adults raises the expected rate of return to schooling for the next youngercohort left behind.12 Since this raises schooling rates, it offers a partial offset tothe drain (Cervantes and Guellec 2002, Williamson 2007, Docquier and Rapoport2012). Others haveargued that remittances offset thebrain drain losses (Fajnzylberand Lopez 2007, Yang 2008 and 2011, Guiliano and Ruiz-Arranz 2009), but theassessment ignores potential damage created by Dutch disease on manufacturing

jobsorhouseholdsuseof thoseremittancestofinanceyetanotherchildsemigration.Any assessment of the brain drain and demographic transition connection is madeeven more complicated by the powerful role of emigrant migration stocks abroadpulling even more young well-schooled adults abroad long after demography haditsfirst-order effectonemigration. Asfar asI know, theconnectionhasnotyet been

assessed empirically.

VII. BeneaththeMacro: RuralUrbanMigrationandIncomeGaps

Oddly enough, it is hardtofindasinglepaper in theliteraturethat breaksthedemographic transition down into rural andurban component parts. We know thatthericher, better educated, moreprogressive, andfemale-jobfriendly citiesleadthepoorer, less educated, moreconservative, andlessfemale-jobfriendly rural areas inthedemographictransition. Postwar childmortalityinAsiafell firstinthecities, andwith a lag, fertility rates fell therefirst as well. Wherethe rural lag (behindurban)has been big, we should see three things (ceteris paribus): (i) big migrations to thecities pushed by a young adult glut in the countryside; (ii) rising rural inequalitydrivenbythesameglut;and(iii) risingwagegapsalsodrivenby thesameglut.If theanalyst just compares the size of youth cohort age shares in urban and rural areas,shewill downplay theseforces sinceruralurban migrationtends, at least partly, toequilibrate. Therefore, onehastolook attheruralurbanfertilityandchildmortalitydifferentials acoupleof decades earlier toproperly assessimpact.

I havesaidthattheseruralurbandifferencesintimingandmagnitudesshouldhave countrywide inequality implications (within regions, between regions, andcountrywide). These will be explored in the next section, but here I will simplyrepeat the prediction that a glut of young adults who stay in rural areas will lowerwages andincomes andraiseruralurban wageandincomegaps.

Anyone interested in ruralurban migrations in Asia and their distributionalimplicationsshouldpay attentiontoruralurbandifferenceswiththeir demographictransition experiencesespecially for the PRC, Indonesia, the Philippines, and

Thailand. As far as I know, nobody has yet doneso.

12That is, expected rates of return to schooling are raised by the possibility of emigration to high-wagecountries (confirmed by theexperienceof older emigratingsiblings).


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VIII. TheDemographicTransitionandInequalityConnection

Thecohortsizehypothesisissimpleenough: fatagecohortstendtogetlowerrewardsduetoasupply glutandthinagecohortsget higher rewardsduetoscarcity.When the fat cohorts lie in the middle of the ageearnings curve where life-cycleincomeishighest, thislabormarketglutlowersincomeinthemiddle, thustendingtoflatten theageearnings curve, andearnings inequality is moderated. When insteadthe fat cohorts are either young or old, these kinds of labor market gluts lowerincomesatthetwotailsof theageearningscurve, thustendingtoaugmentearningsinequality.

This demographic hypothesis has along tradition in theUS starting with the

entry of the baby boomers into the labor market when their big numbers createdpoorer job prospects (Easterlin 1980), and the impact was surveyed not too longago (Lam1997, pp. 102324andpp. 104452; Macunovich1998). All suchstudieshave shown that relative cohort size has had an adverse supply-side effect on therelativewages of thefat cohort in theUS sincethe1950s.

What about the world more generally, and Asia in particular? If the cohortsizehypothesis helps explain US (and European) postwar experiencewith earningsinequality, it might do even better elsewhere. After all, thereis far greater variancein the age distribution of populations between countries than there has been over

time in the US. More to the point, the post-World War II (WWII) demographictransitioninAsiaandtherestof theThirdWorld hasgeneratedmuchmoredramaticchanges in relative cohort size than did the baby boom in the US and the OECD.In addition, thepostwar OECD countries werealready urbanized, so thepostulatedruralurbaninequalityeffectsdiscussedintheprevioussectionwouldhavebeenfarweaker therethanshouldhavebeentrueof Asia andtherest of theThird World. Asfar as I know, nobody has yet explored this last hypothesis in theliterature.

One study (Williamson 2001, Higgins and Williamson 2002) used a worldpanel database of 92 countries to explain the DeiningerSquire (1996) income

inequality Gini coefficients fromthe1960stothe1990s. Theexplanatory variableswere: older labor forcecohortsizedefinedas theproportionof theadult population(taken to be persons 1569) who are ages 4059; a measure of openness; andGDP per capitaentered nonlinearly to capture Kuznets Curve effects. The resultswerestatistically significant androbust. Moreimportantly, theanalysis assignedthebiggestinfluenceto demographic-transition-induced cohort size effects.

Indeed, compared with the East and Southeast Asian economies, inequalityin Africaand Latin Americain the1990s was muchhigher, bigger by 7.2points inAfricaand by 10.8 points in Latin America.13 If Africahad thesamedemographic

mix as East and Southeast Asia, inequality would have been lower by 3.6 points:

13Asian economies here include the PRC; Hong Kong, China; Indonesia; Japan; the Republic of Korea;Malaysia; thePhilippines; Taipei,China; andThailand.


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cohort size accounting for about half of the differencebetween the two regions. IfLatinAmericahadthesamedemographicmixasEastandSoutheastAsia,inequalitywould have been lower by 3.1 points: cohort size accounting for almost a third ofthe difference between the two regions. The study also showed that cohort sizeeffects (rising mature labor forceshares) should serveto lower inequality by morethan 8 percentagepoints between the early 1990s and 2025, suggesting that thesedemographic changescouldbeapowerful forcepromotingreducedinequalitytheGini coefficient for East and Southeast Asia was projected to fall froma relativelylow 39.2to astill lower 31.5by 2025, after which it should stabilize.

Harry Oshima and Andrew Mason also explored some of these issues forAsia, but their most novel contribution, at least in my opinion, was their stress on

inequality of years of life (Oshima and Mason 2001, pp. 4045). Some time ago,Simon Kuznets (1976) stressed that it was inequality of lifetime earnings that weshould be measuring. Sincechild and adult mortality arepowerfully influenced bypoverty in very poor countries, low incomesand low life expectancyarecorrelated.

Thus, lifetimeincomes must havebeenmuchmoreunequal than annual incomesinmost of Asia during the 1950s and 1960s. But if a fall in child mortality early inthe demographic transition favors the poor (perhaps because it is driven mainly bypublic intervention), thenit shouldoffer another sourceof moreegalitarianlifetimeincomes. If a fall in adult mortality later in the demographic transition also favors

the poor, it should be a source of more egalitarian lifetime incomes. Oshima andMason (2001) report a very steep decline in the inequality of years lived by EastAsians during the post-WWII era (something we also see across countries in the20thcentury), contributingtomuchmoreegalitarianlifetimeincomes.Thesetrendsarelikely tocontinuein thenear future, and they need moreof our attention.

IX. Agenda

Itseemstomethattherearemanyunansweredquestionsinvolvingtheimpact

of the demographic transition on country economic performance. Estimates of thefirst and second demographic dividendsseemonly to scratch the surface. We needto learn muchmoreabout theschooling, emigration, and inequality connections aswell as ruralurban dynamics.

Thedemographic transition matters!

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Princelings and Paupers?

StateEmployment and theDistributionof Human Capital Investments Among

Households in Viet NamIAN COXHEAD AND DIEP PHAN

Inequalityinaccesstoeducationisknowntobeakeydriverof incomeinequality

in developing countries. Viet Nam, a transitional economy, exhibits significantsegmentation in the market for skilled labor based on moreremunerativeem-ployment in government and state firms. We ask whether this segmentation isalsoreflected in human capital investments at thehousehold level. Wefind thathouseholds whose heads hold state jobs keep their children in school longer,spend more on education, and are more likely to enroll their children in ter-tiary institutions relative to households whose heads hold nonstate jobs. Theestimates arerobusttoawiderangeof household andindividual controls. Overtime, disparitiesin educational investmentsbased ondifferential access to jobsthat reward skills and/or credentials help widen existing income and earningsgaps between well-connected princelings and the rest of the labor market.

Capital market policies that create segmentation in the market for skills alsocrowd out investment in private sector firms, further reducing incentives forhuman capital deepening.

Keywords: humancapital, state-owned, education, connections, inequality, VietNamJEL codes: J24, J45, O15, P23

I. PolicyDistortions, Connections,andInequalityin TransitionEconomies

Inequality in Viet Namis low by the standards of Asian economies but has

risen during that countrys transition to market-led socialism. Part of the rise

can be explained by referenceto the weakening of many socialist-era policies that

repressedreturnstoskills, ability, andentrepreneurial activity, inwhichcasegreater

incomedisparitiesmightberegardedasnecessary andevenbeneficial consequences

of liberalization.Butdespitehugestridestowardamarketeconomy, thestateretains

significantpoweroversomeproductmarkets,notablythoseinwhichthereispotential

Ian Coxhead is Professor, Department of Agricultural and Applied Economics at the University of Wisconsin-Madison. Diep Phan is Assistant Professor of Economics at Beloit College. We thank Bernard Thiam Hee Ng,seminar participantsat theAsianDevelopmentBank andtheUniversity of Wisconsin-Madison, andtwo anonymousreferees for helpful commentsonearlier drafts. Remainingerrorsareoursalone.

Asian Development Review, vol. 30, no. 2, pp. 2648 C 2013AsianDevelopmentBankandAsianDevelopmentBank Institute


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PRINCELINGS AND PAUPERS? 27

formonopolistic behavior,andfactormarkets,especially thoseforcapital andland.It

followsthatpartof theobservedriseininequalitymay beduetolesspositivetrends,

includingrentcaptureby thosewithaccesstohigh-level government positionsor to

employment in firms that arein someway protected by policy or market structure.

As in thePeoples Republic of China(PRC), another economy undergoing a

broadly similar transition, thereiswidespreadconcerninViet Namover thealleged

capture of state-owned or partially privatized firms and influential public service

positions by princelingsthat is, members of theformer nomenklaturaandtheir

closerelativesandassociates.1Thesameconcernsextendto many other developing

economies in which privileges extended to well-connected owners of capital and

land haveled to diminished earnings and opportunities for owners of labor (Berg

and Ostry 2011). Paradoxically, in some economies, the structure of product andlabor markets (and especially that for skilled labor) is such that the rewards to

skillsaresignificantly higher inpublic sectoremployment thanintheprivatesector,

leading toqueuing and competition for suchjobs.2

In Viet Nam, income inequality across the state/nonstate divide is clearly

visible in household survey data. Thedataalso reveal that this inequality is caused

by just afew householdsat thevery topof thepolitical hierarchy. Figure1, whichis

basedonrepresentativenational householddata, showsthatthepercapitaincomesof

state households(thosecontainingatleastonemember workingforastatefirmor

inpublic administration) areappreciably higher thanthosefor nonstatehouseholds,whether inurbanorrural areas.3Thegapwidenedbetween2004and2008, aperiod

of very rapid growth in Viet Namduringwhichaveragereal incomeper capitarose

by almost 50%.

Why should the labor market connections of households be important, and

why should returns to skills be higher for state employees than those in the pri-

vatesector? A default model would predict equal returns to labor of equal skills in

equilibrium. Moreover, the experience of the transition from socialism in Eastern

Europe and the former Soviet Unionwas overwhelmingly one in which movement

of white-collar workers to the private sector was strongly positively selected, re-flecting moreproductiveemployment opportunities with higher earnings to match

(Adamchik and Bedi 2000, Munich, Svejnar, and Terrell 2005). Viet Nam, likethe

PRC, showstheoppositetrend (Phan andCoxhead 2013).

Our answer,whilespeculative, fitswiththestylizedfactsof aneconomy inan

as yet incompletetransition fromcommand to market economy. Theskill intensity

of civil serviceemploymentishigh, butthedemandfor workersislimitedby budget

1Princelings in [the Peoples Republic of] China Use Family Ties to Gain Riches, New York Times,17 May 2012. See also, In Viet Nam, Message of Equality is Challenged by Widening Wealth Gap, New York

Times, 1September 2012.2Young Feel Hungrier for Golden RiceBowl Jobs: RecordNumbersEyePublic Sector, Financial Times,25October 2012.

3Simple t-tests also show statistically significant difference in the mean per capitaincome between the twogroups of households, for bothrural andurban areas (at significancelevels 7%or lower).


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Figure1. DistributionofPer CapitaIncomefor StateandNonstateHouseholds(D million, J anuary 1998prices)

0

.00002

.00004

.00006

Density

0 20000 40000 60000 80000 100000

pcinc

state urban

nonstate urban

kernel = epanechnikov, bandwidth = 2089.57

0

pcinc

kernel = epanechnikov, bandwidth = 1501.76

Kernel Density Estimate

0

.00002

.00004

.00006

.00008

.0001

Density

20000 40000 60000 80000 100000

state rural

nonstate rural

Kernel Density Estimate

Note: State households are those with at least one member working for the state(in either a statefirm or for thegovernmentinpublic administration).

Source: Viet NamHousehold Living Standards Survey 2004, 2006, and2008.

constraints on government agencies. State-owned enterprises (SOEs), on the other

hand, benefit from capital market interventions that lower their borrowing costs;they therefore adopt relatively capital-intensive techniques. Because capital and

skills are complementary inputs, morehighly educated workers are drawn to these

firmsand competetobehired by them. ButsinceSOEs primarily supply goods and


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PRINCELINGS AND PAUPERS? 29

services to (often highly-regulated) domestic markets, their expansionand thus

their demand for laboris bounded in ways that do not apply to privately-owned

andtrade-orientedfirms. WhatbothSOEsandcivil administrationhaveincommon,

however, is access to rents, which when distributed among their workers, generate

potential for incomes that are higher than the earnings of equivalent workers in

competitiveindustries.4

Nonstatefirms,meanwhile,sufferfromcrowdingoutincapital marketsandso

adoptlesscapital-intensivetechniques.Inthesefirms,capital-skillscomplementarity

means they will hirefewer skilled workers, and will offer to compensate themat a

lower rate, commensuratewiththeir lower valuemarginal product.5

Inthissystem, segmentationintheskilledlabor marketarisesindirectly, from

capital market distortions, market structure, and budget constraints limiting hiringby stateentities. Thissegmentationisvisibleasqueuingby applicantsanddemands

for up-front payments fromprospective employers. The difference in earnings for

equivalent workers at each type of firm will persist so long as the favored firms

face market or regulatory conditions that generaterents and so encourage themto

restrict hiring. Thus capital market policieswill leadto jobrationing and incentives

for corrupt behavior across a broad spectrumof the white-collar labor market, not

merely amongthefew thathavedirectaccesstothehighestlevelsof political power.

In earlier work (Phan andCoxhead 2013), weuncovered evidencein support

of an important part of the above narrative. Viet Nam displays a high degree ofindustrial policy distortion, with a clear bias in favor of state-owned enterprises in

the markets for banking sector credit, equity capital, and land (World Bank 2005,

Sjoholm 2008, Hakkala and Kokko 2008, Leung 2009, Nixson and Walters 2010,

IMF 2012) and in trade and pricing policies (Athukorala 2006). We discovered a

highly significant statesector premiumin earnings and in returns toeducationas

of 2008, this premiumhad persisted despitetwo decades of economic reforms. We

also foundthat family connectionstostatesector employersincreaseanindividuals

own probability of having a state sector job. Together, these results indicate that

connections to the statesector increase individual earnings and returns on humancapital investments,andthattheseeffectsoperateatleastinpart throughhousehold-

level connections.

Theconcernsraisedbythesefindingsarenotlimitedtoinequality.A countrys

long-term economic growth depends on its ability to accumulate and efficiently

deploy human capital, and theacquisition of human capital is akey determinant of

improvements in individual earning power. The preceding narrative suggests that

4For an equivalent account usingChineselabor market data, seeXin Meng(2000).5A recentstudy usinglabor forcedatacoveringfivebroad industrial sectorsconfirms this prediction, finding

that in manufacturing, post-secondary qualifications earn a premium of only 40%50% over primary education,andconcluding that thereis currently not a strong demandfor workers with either professional training or tertiaryeducationin either low-valueor medium-valueindustries. . . workers withpost-secondaryqualificationsarethereforelikely togravitatetowardsbetter-remuneratedjobsingovernmentandadministrationandtheservices (Baulch,Dat,andThang2012, p. 2223).


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in the presence of certain policies and capital market distortions, household-level

incentives for educational investments will depend, in part, on the likelihood that

their childrenwill beabletosecurejobs inwhichskills or credentialsarerewarded.

If this probability is viewed as small, then returns to additional years of education

are perceived as low, and capital-constrained parents will spend less on education

and/or withdraw children from school earlier; those children will enter the labor

forceat ayounger ageand withless formal training.

That perceived returns matter for educational investments is well established

in empirical studies. In astudy fromtheDominican Republic, for example, Jensen

(2010) finds that when children are given information on higher measured returns

toeducation, they completeonaverage0.200.35moreyears of schooling over the

next 4 years. Similarly, J ensen (2012) finds that young rural women in India aresignificantly morelikely toenter thelabor market or obtain moreschooling instead

of getting married and having children if they have access to recruiting services,

whichincreasetheir awareness of jobopportunities.

Lower perceived returns to schooling reduce educational investments and

the schooling achievementsof children. As a result their lifetime earnings profiles

will be flatter and their capacity to invest in the education of their own children

will be diminished. In this way, initial household-level disparities in opportunity

may become persistent over more than one generation. Moreover, the potential

productivityof less-educatedworkerswill also belower, so theeconomy asawholewill faceadiminishedgrowthrateand lower steady-stateincomeper capitarelative

tothecounterfactual of onein whichperceived returns arehigher.

In this paper, we test the hypothesis that households with close connections

toVietNamsstatesectorinvestmoreintheir childrenshumancapital. Specifically,

we ask whether children from households headed by state employees are more

likely toattendhighschool or university, andwhether thosehouseholdsspendmore

on their childrens education. The first of these questions explores the extensive

margin of educational attainment in an economy where only a small minority of

school-leavers continue on to higher education. The second question investigatesthe intensive margin of educational investments in a system in which household

spending on discretionary educational items, such as tutors and privateschools, is

an importantcomponentof total educational expenditures.

After controlling for characteristics of the potential student, the household

head, and the household, we fin

asian development review: volume 30, number 2

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