Transmissão Intergeracional

Universidade da Madeira 1

Transmissão Intergeracional

Pedro Telhado Pereira


Existe uma vasta literatura, da qual destacamos: Bauer P.C., Riphahn, R.T. (2009) Age at School Entry and Intergenerational Educational Mobility, CESIFO WORKING PAPER NO. 2541 Bauer, P., Regina, R.T. (2006) Timing of school tracking as a determinant of intergenerational transmission of education, Economics Letters, 91(1), 90-97 Bertrand, M., Hanna R., Mullainathan, S. (2010) Affirmative action in education: Evidence from engineering college admissions in India, , Journal of Public

Economics 94 16–29 Black, S.E,Devereux, P. J. (2010) Recent Developments in Intergenerational Mobility. WP 15889, National Bureau of Economic Research, MA Booth, A. L., Coles, M. G. (2010) Tax policy and returns to education, , Labour Economics 17, 291–301 Carneiro, P. (2008) Equality of opportunity and educational achievement in Portugal. Portuguese Economic Journal 7, 17–41 Carneiro, P., Heckman, J. J. (2002) The Evidence on Credit Constraints in Post-Secondary Schooling,The Economic Journal, 112, 705-734 Caucutt, E. M, Kumar, K.B. (2003) Higher education subsidies and heterogeneity: a dynamic analysis, Journal of Economic Dynamics & Control 27 (2003) 1459

– 1502. Christofides, L. N., Hoy, M., Yang, L, (2010) Participation in Canadian Universities: The gender imbalance (1977–2005), , Economics of Education Review 29,

400–410 Daouli,J., Demoussis, M., Giannakopoulos N.(2010) Mothers, fathers and daughters: Intergenerational transmission of education in Greece, Economics of

Education Review 29, 83–93 Ewijk, R. V., Sleegers, P. (2010) The effect of peer socioeconomic status on student achievement: A meta-analysis, Educational Research Review 5 (2), 134-

150. Fershtman, Chaim (2010) Social Animal and Social Interaction, Iinbergen Institute Magazine, 21, 4 Gilman, R., Anderman, E. M. (2006) The relationship between relative levels of motivation and intrapersonal, interpersonal, and academic functioning among

older adolescents, Journal of School Psychology , 44 (5), 375-391 Haegeland, T., Kirkebøen, L. J., Raaum, O., Salvanes K. G. (2010), Why Children of College Graduates Outperform their Schoolmates: A Study of Cousins and

Adoptees, IZA D.P. 5369. Heckman, J.J., Moon, S. H., Pinto, R., Savelyev, P. A., Yavitz A. (2010),The rate of return to the HighScope Perry Preschool Program, Journal of Public

Economics 94 114–128. Heineck, G, Riphahn, R. T. (2009) Intergenerational Transmission of Educational Attainment in Germany - The Last Five Decades. Journal of Economics and

Statistics (Jahr Nationalökon Statist) 229(1), 36-60. Hoy, W. K., Tarter, C. J., Woolfolk Hoy, A. (2006). Academic optimism of schools: A force for student achievement, American Educational Research Journal, 43,

425-446. Kane, T. J. (1994) College Entry by Blacks since 1970: The Role of College Costs, Family Background, and the Returns to Education The Journal of Political

Economy, 102 (5), 878-911 Kao, G, , Tienda, M. (2005) Optimism and Achievement: The Educational Performance of Immigrant Youth, in The new immigration: an interdisciplinary reader,

ed. Marcelo M. Suárez-Orozco,Carola Suárez-Orozco; Taylor and Frances Group. Kleinjans, K. J. (2010) Family background and gender differences in educational expectations, Kristin J. , Economics Letters 107, 125–127


Mahoney, J. L., Cairns, B. D., Farmer, T. W. (2003) Promoting Interpersonal Competence and Educational Success Through Extracurricular Activity Participation, , Journal of Educational Psychology, 95 (2), 409–418

Martin, P. Y., Jackson, S., (2002) Educational success for children in public care: advice from a group of high achievers, Child & Family Social Work, 7 (2), 121–130

Martins, P. (2010), Can Targeted, Non-Cognitive Skills Programs Improve Achievement? Evidence from EPIS, IZA DP No. 5266

OECD (2010a) Education at a Glance 2010 - OECD indicators. OECD (2010b) PISA 2009 Results: Overcoming Social Background – Equity in

Learning Opportunities and Outcomes (Volume II) Pascual, M. (2009) Intergenerational income mobility: The transmission of socio-

economic status in Spain. Economics of Education Review 31, 835–846. Pereira, P. T. (2010) Higher Education Attainment: The Case of

Intergenerational T Transmission of Education in Portugal, IZA DP No. 4813 Ribeyre, F., (2003) Pour une écologie familiale. Fondements et finalités -

Towards a family ecology. Fundaments and aims, Nature Sciences Sociétés 11 (2), 169-173

Rivkin, S. G, Hanushek, E. A, Kain, J. E. (2005) Teachers, Schools, and Academic Achievement Econometrica, 73 (2), 417-458

Rumberger, R. W. (2010) Education and the reproduction of economic inequality in the United States: An empirical investigation. Economics of Education Review 29(2), 146-254.


Alguns resultados There is a ongoing debate about the causality of parents education as surveyed in Black

and Devereux, 2010, and new evidence is being produced (Haegeland, Kirkebøen, Raaum and Salvanes 2010, Daouli, Demoussis and Giannakopoulos, 2010, Kleinjans, 2010, where there seems to be some causality but not as strong as some previous studies pointed.The literature points other aspects influence the educational success of a individual:Peers or neighborhood effects as in Ewijk and Peter Sleegers, 2010 where they show that peers’ socioeconomic status is important in explaining academic achievement.Kindergarten Enrolment and Early Child Intervention as in Bauer and Riphahn, 2009, Heckman, Moon. Pinto, Savelyev and Yavitz, 2010, where they show that early entry at kindergarten or early child intervention have a positive effect in success, particularly if the intervention is before the school age.School tracking as in Bauer and Riphahn 2006 where they show that “late tracking significantly affects mobility and reduces the relative advantage of children of better educated parents”.Affirmative Action as in Bertrand, Hanna and Mullainathan, 2010, show that in India this type of programs increase the probability of individuals from lower castes to have success in engineering.Tax Policy and Subsidies as in Booth and Coles, 2010, where they show that different tax systems can affect female education, Caucutt and Kumar 2003 “… conclude that the case for further increases in higher education subsidies might have been overstated” and Kane, 1994, show that the increase of college costs decreased black attendance.Societal norms as in Christofides, Hoy and Yang, 2010 that help to explain the evolution of the participation of females in higher education.


School Resources and Teachers as in Carneiro 2008 show that family and peers influence success more than school resources and Rivkin, Hanushek and Kain, 2005 showed that quality of teachers matters more than decrease in class size.Credit constraints as in Carneiro and Heckman 2002, where they showed that the existence of support programs helped to overcome the credit constraints in USA.Optimism and motivation as in Kao and Tienda, 2005, Hoy, Tarter, and Woolfolk Hoy, 2006, where they show that immigrants or academic optimism helps to explain the success of the children and Gilman and Anderman, 2006, showed academic benefits that are associated with incremental levels of motivation.Extracurricular Activity Participation as in Mahoney, Cairns and Farmer, 2003, as they develop interpersonal competences and lead to sucess.Support and encouragement for academic achievement as in Martin and Jackson, 2002, where they showed its importance for sucess.Non-Cognitive Skills Programs as in Martins, 2010, shows that this type of programs can increase the success.In a different perspective “the family represents a fundamental ecological unit: genetic and affective links between family members, shared cultural background, social structure, a place where decisions are taken, a place for handing down knowledge and helping young family members to grow... characterised by shifting structures and functions of varying complexity” (Ribeyre, 2003).


Higher Education Attainment - The Case of Intergenerational Transmission of Education in

Portugal

Pedro Telhado Pereira Universidade da Madeira

IZA DP N. 4813/2010CEEAplA W.P. 2/2010

.


Schooling in Portugal – OCDE data and IEFA data

Sorting in the marriage and schooling of the parents

From the schooling of the parents to the schooling of the individuals

Reasons to leave school Conclusions


The lack of formal education and competences of the Portuguese workers is one of the biggest problems of the country


Portugal is one of the countries that presents lower percentage of people aged 25-64 with at least upper secondary education. The increase between the oldest cohort and the youngest (31 p. p.) is lower than the one verified in other southern European countries

Italy – 34 p.p., Spain – 37 p. p. and Greece – 38 p.p..


Table A1.3a. Population with tertiary education (2007)

Percentage of the population that has attained tertiary-type B education or tertiary-type A and advanced research programmes, by age group

Total tertiary25-64 25-34 35-44 45-54 55-64 (11) (12) (13) (14) (15) (15)-(12)

Australia 34 41 34 32 27 14Austria 18 19 19 17 14 5Belgium 32 41 36 28 22 19Canada 48 56 53 45 39 17Czech Republic 14 15 14 14 11 5Denmark 32 40 34 30 24 16Finland 36 39 43 36 28 11France 27 41 29 20 17 25Germany 24 23 26 25 23 0Greece 23 28 26 21 14 14Hungary 18 22 17 16 16 6Iceland 30 31 35 28 23 8Ireland 32 44 34 25 17 26Italy 14 19 14 11 9 10Japan 41 54 46 41 24 30Korea 35 56 40 21 11 45Luxembourg 27 36 27 22 19 17Mexico 16 19 16 15 9 10Netherlands 31 37 31 30 26 11New Zealand 41 47 41 39 35 13Norway 34 43 36 31 26 16Poland 19 30 18 13 12 18Portugal 14 21 14 10 7 14Slovak Republic 14 17 13 14 11 7Spain 29 39 32 23 16 23Sweden 31 40 31 29 26 14Switzerland 31 35 34 30 26 9Turkey 11 14 10 9 8 6United Kingdom 32 37 32 31 25 12United States 40 40 42 40 39 2

OECD average 28 34 29 25 20 14EU19 average 24 31 26 22 18 13


In terms of higher education Portugal still lags behind the majority of other OECD countries even for the younger cohort.


In IEFA (Adult education and training survey – 2007)

From the 11 289 individuals we have information of parents education and labour market conditions for 10 433 individuals. Parents’ situation when the children were 12 to 16 years old (or 14 years old if the individual asked for a specific date)

The education levels are NONE – no formal education degree (appears only for the individuals) BAS –corresponding to less than or equal to 9 years of education SEC – degree corresponding to 11 or 12 years of education HIG – Higher education degree


Table IV. Individual’s education

N. %

NONE 514 4.93

BAS 7,098 68.03

SEC 1,675 16.05

HIG 1,146 10.98

Total 10,433 100.00


Very similar with the OECD data (green)

Individual’s Education

18-24 % 25-34 % 35-44 % 45-54 % 55-64 %

NONE 13 0.95 38 2.22 73 3.20 129 5.04 261 10.37

BAS 700 51.28 916 53.54 1,622 71.11 1,931 75.46 1,929 76.64

SEC 556 40.73 398 23.26 316 13.85 251 9.81 154 6.12

HIG 96 7.03 359 20.98(21)

270 11.84(14)

248 9.69(10)

173 6.87(7)

Total 1,365 100 1,711 100 2,281 100 2,559 100 2,517 100


Table V. Individual’s education by gender

Individual’s Education Female(FEM)

% Male %

NONE 324 5.92 190 3.83

BAS 3,557 64.96 3,541 71.43

SEC 884 16.14 791 15.96

HIG 711 12.98 435 8.78

Total 5,476 100.00 4,957 100.00


Parents’ marriage market

Saint-Paul, Gilles (2009), Genes, Legitimacy and Hypergamy: Another Look at the Economics of Marriage, IZA DP No. 4456, September.

Abstract: “…As a consequence, it is shown that the equilibrium can only be of two types. In the “Victorian” type, all agents marry somebody of the same rank in the distribution of income. In the “Sex and the City” (SATC) type, women marry men who are better ranked than themselves. There is a mass of unmarried men at the bottom of the distribution of human capital, and a mass of single women at the top of that distribution. It is shown that the economy switches from a Victorian to an SATC equilibrium as inequality goes up.”


Random marriage M_BAS M_SEC M_HIG FATHER

F_BAS 87,73% 2,90% 2,54% 93,2%F_SEC 3,24% 0,11% 0,09% 3,4%F_HIG 3,20% 0,11% 0,09% 3,4% MOTHER 94,16% 3,12% 2,72% 100,00%

Marriage in the data MOTHER M_BAS M_SEC M_HIG FATHER F_BAS 91,42% 1,01% 0,74% F_SEC 1,74% 1,28% 0,41% F_HIG 1,00% 0,82% 1,57%


Table II. Parents’ educational achievement

N. %

M_BAS/F_BAS 9,538 91.42

M_BAS/F_SEC 182 1.74

M_BAS/F_HIG 104 1.00

M_SEC/F_BAS 105 1.01

M_SEC/F_SEC 134 1.28

M_SEC/F_HIG 86 0.82

M_HIG/F_BAS 77 0.74

M_HIG/F_SEC 43 0.41

M_HIG/F_HIG 164 1.57

Total 10,433 100.00


Table III. Parents’ labor market situation

N. %

M_NOT/F_NOT 116 1.11

M_NOT/F_UNE 29 0.28

M_NOT/F_EMP 5,172 49.57

M_UNE/F_NOT 3 0.03

M_UNE/F_UNE 6 0.06

M_UNE/F_EMP 29 0.28

M_EMP/F_NOT 93 0.89

M_EMP/F_UNE 12 0.12

M_EMP/F_EMP 4,973 47.67

Total 10,433 100.00


Individuals’ schooling versus parents


NONE BAS SEC HIGH Total

Schooling of parents

M_BAS/F_BAS 513 6973 1318 737 9541

% 5,38 73,08 13,81 7,72 100M_BAS/F_SEC 0 44 77 61 182

% 0 24,18 42,31 33,52 100M_BAS/F_HIG 1 18 40 45 104

% 0,96 17,31 38,46 43,27 100M_SEC/F_BAS 0 17 53 35 105

% 0 16,19 50,48 33,33 100M_SEC/F_SEC 0 17 56 61 134

% 0 12,69 41,79 45,52 100M_SEC/F_HIG 0 9 27 50 86

% 0 10,47 31,4 58,14 100M_HIG/F_BAS 0 15 35 27 77

% 0 19,48 45,45 35,06 100M_HIG/F_SEC 0 1 16 26 43

% 0 2,33 37,21 60,47 100M_HIG/F_HIG 0 7 53 104 164

% 0 4,27 32,32 63,41 100


Results from Ordered Probit –marginal effects for Higher Education

Table VII. Marginal effects on higher education completion

variable dy/dx Std. Err. z P>|z|M_BAS_F_SEC .2997595 .04272 7.02 0.000

M_BAS_F_HIG .4164844 .06094 6.83 0.000

M_SEC_F_BAS .4031556 .06458 6.24 0.000

M_SEC_F_SEC .4032619 .05392 7.48 0.000

M_SEC_F_HIG .4861511 .06872 7.07 0.000

M_HIG_F_BAS .4122408 .06973 5.91 0.000

M_HIG_F_SEC .5987253 .08863 6.76 0.000

M_HIG_F_HIG .5595771 .05066 11.05 0.000

M_NOT/F_UNE -.0748998 .00366 -20.47 0.000

M_NOT/F_EMP .0283184 .02671 1.06 0.289

M_UNE/F_EMP .2178198 .13513 1.61 0.107

M_EMP/F_NOT .0031802 .04033 0.08 0.937

M_EMP/F_UNE -.052403 .02757 -1.90 0.057

M_EMP/F_EMP .0255261 .02694 0.95 0.343

AGEII .0242619 .00995 2.44 0.015

AGEIII -.0235694 .00737 -3.20 0.001

AGEIV -.0296682 .00712 -4.17 0.000

AGEV -.040434 .00674 -6.00 0.000


M_BAS_F_SEC*FEM .0231177 .02928 0.79 0.430

M_BAS_F_HIG*FEM .0014126 .0323 0.04 0.965

M_SEC_F_BAS*FEM -.0426145 .01677 -2.54 0.011

M_SEC_F_SEC*FEM .0232 .0349 0.66 0.506

M_SEC_F_HIG*FEM .0257958 .04591 0.56 0.574

M_HIG_F_BAS*FEM -.0387563 .02139 -1.81 0.070

M_HIG_F_SEC*FEM -.0032356 .05095 -0.06 0.949

M_HIG_F_HIG*FEM .0326183 .03624 0.90 0.368

M_NOT/F_UNE*FEM -.0678814 .01254 -5.41 0.000

M_NOT/F_EMP*FEM -.0207577 .03016 -0.69 0.491

M_UNE/F_EMP*FEM -.0708181 .00875 -8.09 0.000

M_EMP/F_NOT*FEM -.0447669 .02508 -1.78 0.074

M_EMP/F_UNE*FEM .0405425 .14939 0.27 0.786

M_EMP/F_EMP*FEM -.0443322 .02638 -1.68 0.093

AGEII*FEM .0052481 .01266 0.41 0.679

AGEIII*FEM -.0195432 .01003 -1.95 0.051

AGEIV*FEM -.0418633 .00798 -5.25 0.000

AGEV*FEM -.0726491 .00541 -13.43 0.000

FEM .0927274 .03446 2.69 0.007

Predicted probability for the reference group (young male with both parents with BAS education and not in the labor market) = .07644406


We did independent regressions for each gender


Total effect from parents’ education

Table VII – Total effects on higher education completion

fbas fsec fsup

Female Male Difference Female Male Difference Female Male Differencembas

9,15% 6,10% 3,04% 45,59% 34,83% 10,76% 51,94% 46,73% 5,21%msec

35,37% 45,31% -9,95% 56,07% 45,32% 10,76% 64,56% 53,78% 10,78%msup

37,80% 46,18% -8,37% 68,44% 65,49% 2,94% 72,44% 61,34% 11,10%


For the cohort 25 to 34

Total effects on higher education completion, age 25 to 34

fbas fsec fsup

Female Male Difference Female Male Difference Female Male Differencembas

24,68% 12,51% 12,18% 75,18% 34,74% 40,44% 78,30% 41,80% 36,49%msec

78,30% 62,73% 15,57% 76,75% 56,27% 20,47% 73,54% 68,00% 5,54%msup

59,93% 63,46% -3,53% 54,94% 71,70% -16,76% 97,68% 75,86% 21,82%


Main reason to leave school

For individuals born after 1977 (included) leaving school at BAS or less it was asked the main reason to leave school

From these 1046 individuals, we have data on 944 parents´ schooling


Three main reasons for leaving school

Reasons to abandon schooling

M_BAS/F_BAS

M_BAS/F_SEC

M_BAS/F_HIG

M_SEC/F_BAS

M_SEC/F_SEC

M_SEC/F_HIG

M_HIG/F_BAS

Total

Didn’t like to study 305 3 1 4 1 0 2 316% 33,44 23,08 50 57,14 16,67 0 66,67 33,47

Wanted to earn its own money

205 3 0 2 0 0 0 210

% 22,48 23,08 0 28,57 0 0 0 22,25

Had economic difficulties

116 4 0 1 0 0 0 121

% 12,72 30,77 0 14,29 0 0 0 12,82Other 286 3 1 0 5 1 1 297

% 31,36 23,07 50 0 83,33 100 33,33 31,46Total 912 13 2 7 6 1 3 944

% 100 100 100 100 100 100 100 100


For females


M_BAS/F_BAS

M_BAS/F_SEC

M_BAS/F_HIG

M_SEC/F_BAS

M_SEC/F_SEC

M_SEC/F_HIG

M_HIG/F_BAS

Total

Didn’t like to study 100 1 0 0 0 0 1 102% 29,24% 16,67% 0,00% 0,00% 0,00% 0,00% 100,00% 28,57%Wanted to earn its own money

59 0 0 2 0 0 0 61

% 17,25% 0,00% 0,00% 66,67% 0,00% 0,00% 0,00% 17,09%

Had economic difficulties 56 3 0 1 0 0 0 60

% 16,37% 50,00% 0,00% 33,33% 0,00% 0,00% 0,00% 16,81%Other 127 2 1 0 3 1 0 134% 37,13% 33,33% 100,00% 0,00% 100,00% 100,00% 0,00% 37,54%Total 342 6 1 3 3 1 1 357% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00

%


For males


M_BAS/F_BAS

M_BAS/F_SEC

M_BAS/F_HIG

M_SEC/F_BAS

M_SEC/F_SEC

M_SEC/F_HIG

M_HIG/F_BAS

Total

Didn’t like to study 205 2 1 4 1 0 1 214

% 35,96% 28,57% 100,00% 100,00% 33,33% 50,00% 36,46%Wanted to earn its own money

146 3 0 0 0 0 0 149

% 25,61% 42,86% 0,00% 0,00% 0,00% 0,00% 25,38%Had economic difficulties

60 1 0 0 0 0 0 61

% 10,53% 14,29% 0,00% 0,00% 0,00% 0,00% 10,39%Other 159 1 0 0 2 0 1 163% 27,89% 14,29% 0,00% 0,00% 66,67% 50,00% 27,77%Total 570 7 1 4 3 0 2 587

% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00%


Evolution of higher education attainment

Higher Education

sample %

Males 18-24 25-34 35-44 45-54 55-64 Total

M_BAS/F_BAS 2,23% 10,25% 4,71% 6,29% 4,75% 5,68%

M_BAS/F_SEC 6,90% 21,43% 41,67% 33,33% 42,86% 24,21%

M_BAS/F_HIG 0,00% 28,57% 30,00% 64,29% 42,86% 37,74%

M_SEC/F_BAS 17,65% 50,00% 62,50% 16,67% 50,00% 36,17%

M_SEC/F_SEC 13,64% 44,44% 50,00% 40,00% 44,44% 34,33%

M_SEC/F_HIG 0,00% 58,33% 83,33% 80,00% 83,33% 48,84%

M_HIG/F_BAS 15,38% 52,94% 50,00% 75,00% 0,00%* 41,86%

M_HIG/F_SEC 22,22% 60,00% 85,71% 100,00% 100,00% 56,52%

M_HIG/F_HIG 20,00% 69,57% 81,25% 63,64% 63,64% 56,41%

Total 4,17% 15,60% 8,66% 8,84% 6,70% 8,77%•- only one case• less than 30%


sample %

Females 18-24 25-34 35-44 45-54 55-64 Total

M_BAS/F_BAS 8,51% 19,84% 9,66% 8,12% 5,41% 9,56%

M_BAS/F_SEC 21,74% 66,67% 40,00% 47,06% 50,00% 43,68%

M_BAS/F_HIG 0,00% 62,50% 58,33% 63,64% 66,67% 49,02%

M_SEC/F_BAS 3,70% 72,22% 42,86% 0,00% 33,33% 31,03%

M_SEC/F_SEC 35,00% 70,00% 64,71% 80,00% 40,00% 56,72%

M_SEC/F_HIG 40,00% 61,54% 83,33% 80,00% 100,00% 67,44%

M_HIG/F_BAS 0,00% 50,00% 33,33% 37,50% 0,00%* 26,47%

M_HIG/F_SEC 42,86% 33,33% 100,00% 66,67% 100,00% 65,00%

M_HIG/F_HIG 10,53% 95,00% 87,10% 69,23% 100,00% 69,77%

Total 10,23% 26,21% 14,55% 10,41% 7,02% 12,98%

•- only one case• less than 30%


Conclusions

The probability of achieving a higher education degree is more than eight times higher for an individual both of whose parents have a higher education degree than for one whose parents both have at most 9 years of education. Therefore low level of education is going to perpetuate from generation to generation, creating a lasting problem.


Females have an advantage in terms of educational attainment – an average increase of around 10% in the probability of attaining a higher education degree. The average disguises situations that are unfavorable for females, such as the case of having the mother with more education than the low educated father.

The time trend seems to be steeper for females than for males.

Given the findings, it is very important to intervene in the educational process to see if the children of parents with low levels of education obtain support, in order that they do not leave their studies early. This should also be done with children whose parents are unemployed, especially the father. Female children whose father has low education should also have extra support.


Revista Brasileira de Política e Administração da Educação

http://www.anpae.org.br/website/publicacoes/revista-da-anpae


… o estrato alto/médio alto encontra-se fortemente representado entre os estudantes do ensino superior, considerando que o estrato social alto/médio alto representava, apenas, 9.9% da população portuguesa de acordo com o Censo de 2001…


Nature or Nurture in Higher Education?Inter-generational Implications of theVietnam-Era Lottery, IZA DP No. 9046´May 2015Louis N. ChristofidesMichael HoyJoniada MillaThanasis Stengos

Is it a genetic inter-generational transmission of innate ability from parents to their children (i.e. nature) or is it the environment that the better educated parents provide for their children (i.e. nurture) that explains this positive relationship? Understanding the relative contributions of nature versus nurture is critical to the development of any social policy designed to increase social and economic mobility between generations.


NON-TECHNICAL SUMMARY Earlier studies show that the Vietnam draft lottery provided extra incentives for men to attend university and that their attendance increased. Men who (for nature reasons) might not have gone to university during “normal times” appear to have gone to university to avoid the draft. We examine the propensity of their children to go to university relative to those of a control group. Did those children behave as nature would suggest, or did the nurture provided by their university-educated fathers lead them to be as at least as likely to go to university? Consistent with nurture, we find the latter.


We use the Vietnam Era Draft Lottery as a natural experiment to address causation in the context of the nature-nurture question and to identify whether there is a causal elect of parental education on children's education. Card and Lemieux (2001) showed that the college enrolment rates for men increased and fell abruptly between 1965 and 1975. Therefore, the strategy of attending university in order to avoid the draft creates a cohort of men who would not normally have attended post-secondary education (PSE) institutions. We will refer to this cohort as the PSE draft “avoiders cohort." Comparing the educational attainment of the children of this cohort to that of cohorts who attended university in “normal times" creates a natural experiment to test the relative importance of the nature and nurture explanations. If the transmission of post-secondary education from parents to children for the normal cohorts" exceeds that for the PSE draft “avoiders cohort", then we conclude that individuals who would not normally have obtained PSE do not pass on that achievement to as great an extent as “normal" PSE attendees. Such a result would be consistent with at least some extent of nature being the reason for the inter-generational transmission of PSE. This follows since such a finding would imply that those who would not normally have attended PSE would, under the nature explanation, have lower innate ability and so pass on lower innate ability to their children which would in turn reduce the chances of them attending PSE. However, a finding that there is the same degree of inter-generational transmission of PSE for the two cohorts points in the direction of a nurture explanation. This follows since such a finding would imply that those who would not normally have attended PSE but do so for ulterior motives pass on to their children the ability and aspiration for PSE to the same extent of “normal PSE attendees." Such a result, which is what we find, is consistent with the nurture explanation; that is, the act of attaining some PSE in itself appears to create a different sort of parent and a different sort of environment for the children and this leads these children to also be more likely to obtain some PSE. In other words, it appears that the education level of one generation has a causal effect on the education level of the subsequent generation.


In this paper we track whether the PSE education transmission rate from these men to their children and compare to that for men who faced normal incentives to attend PSE. The treatment is having a father who was born during the years 1945-1950. We find evidence, contrary to expectations of the nature hypothesis, that the transmission rate of fathers' PSE educational attainment is not less than for those fathers born outside this period (i.e., not in the treatment group). In fact, we find a modest increase in the transmission rate for the treatment group. Therefore, the evidence is more consistent with the nurture hypothesis. Hence, we conclude that the source of the correlation between the parental education and the educational attainment of their children is in fact due to the educational attainment per se. From a policy perspective, the inter-generational multiplier effects that this may generate are of interest in poverty alleviation and inequality reduction initiatives.

Transmissão Intergeracional

Documents

Transcript of Transmissão Intergeracional