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The geography of mobility T Evidence of intergenerational educational persistence and the F Great Gatsby Curve in Brazil A R Tharcisio Leone D Free University of Berlin School of Business and Economics Institute for Latin American

  1. The geography of mobility T Evidence of intergenerational educational persistence and the F ”Great Gatsby Curve” in Brazil A R Tharcisio Leone D Free University of Berlin School of Business and Economics Institute for Latin American Studies June 11, 2018 Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 1 / 35

  2. Outline 1 Introduction 2 Data 3 Estimating intergenerational mobility 4 The Great Gatsby Curve 5 Linking Inequality and school dropouts 6 Conclusion Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 2 / 35

  3. Outline 1 Introduction 2 Data 3 Estimating intergenerational mobility 4 The Great Gatsby Curve 5 Linking Inequality and school dropouts 6 Conclusion Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 3 / 35

  4. Motivation “Great Gatsby Curve” Source: Corak (2012) Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 4 / 35

  5. Motivation (a) Income distribution Distrito Federal .577 Acre .543 Amazonas .529 Maranhão .527 Bahia .526 Rio de Janeiro .523 Tocantins .512 Paraíba .510 Pernambuco .505 Ceará .503 Roraima .501 Piauí .501 Alagoas .497 Gini States Rio Grande do Norte .495 São Paulo .489 Espírito Santo .488 Pará .487 Sergipe .483 Minas Gerais .482 Mato Grosso do Sul .480 Rio Grande do Sul .475 Amapá .470 Rondônia .469 Mato Grosso .457 Paraná .449 Goiás .444 Santa Catarina .416 Brazil .515 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 Outcome share (Proportion) Bottom 50% Middle 40% Top 10% Note: Estimations based on per capita household income. Source: PNAD-2014, own estimates. Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 5 / 35

  6. Research questions 1 There is a variation in intergenerational educational mobility across Brazilian states? 2 What socioeconomic indicators are correlated with the mobility at state level? 3 Does the “Great Gatsby Curve” also hold true within a single country? 4 How higher income inequality leads to lower rate of mobility? Investigation of one specific mechanism behind the correlation between inequality and mobility: School dropout rate. Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 6 / 35

  7. Outline 1 Introduction 2 Data 3 Estimating intergenerational mobility 4 The Great Gatsby Curve 5 Linking Inequality and school dropouts 6 Conclusion Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 7 / 35

  8. Data 1 Brazilian National Household Sample Survey (PNAD) Mobility supplement 2014 (46 , 051 individuals) 2 Main variables for the investigation Number of years of schooling Level of education School Dropout rate Income inequality 3 Variable construction Only individuals born between 1940 and 1989 The most educated parent 25/10 Ratio for income inequality Economic Marginalization 4 Further variables Individual characteristics (gender, birth cohort, race, locality of residence and living with both parents at age 15) Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 8 / 35

  9. Data (a) Average years of schooling North, Acre North, Amapá North, Amazonas North, Pará North, Rondônia North, Roraima North, Tocantins 12 10 8 6 4 2 0 Northeast, Alagoas Northeast, Bahia Northeast, Ceará Northeast, Maranhão Northeast, Paraíba Northeast, Pernambuco Northeast, Piauí 12 10 Years of Schooling 8 6 4 2 0 Northeast, Rio Grande do Norte Northeast, Sergipe South, Paraná South, Rio Grande do Sul South, Santa Catarina Southeast, Espírito Santo Southeast, Minas Gerais 12 10 8 6 4 2 0 Southeast, Rio de Janeiro Southeast, São Paulo West, Distrito Federal West, Goiás West, Mato Grosso West, Mato Grosso do Sul Brazil 12 10 8 6 4 2 0 1940-1944 1950-1954 1960-1964 1970-1974 1980-1984 1940-1944 1950-1954 1960-1964 1970-1974 1980-1984 1940-1944 1950-1954 1960-1964 1970-1974 1980-1984 1940-1944 1950-1954 1960-1964 1970-1974 1980-1984 1940-1944 1950-1954 1960-1964 1970-1974 1980-1984 1940-1944 1950-1954 1960-1964 1970-1974 1980-1984 1940-1944 1950-1954 1960-1964 1970-1974 1980-1984 1945-1949 1955-1959 1965-1969 1975-1979 1985-1989 1945-1949 1955-1959 1965-1969 1975-1979 1985-1989 1945-1949 1955-1959 1965-1969 1975-1979 1985-1989 1945-1949 1955-1959 1965-1969 1975-1979 1985-1989 1945-1949 1955-1959 1965-1969 1975-1979 1985-1989 1945-1949 1955-1959 1965-1969 1975-1979 1985-1989 1945-1949 1955-1959 1965-1969 1975-1979 1985-1989 Birth cohorts Children Parents Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 9 / 35

  10. Data Average Education by region and states in Brazil Mean Acre Amapá Amazonas h Pará t r o Rondônia N Roraima Tocantins Alagoas Bahia Ceará Maranhão t Paraíba s a e Pernambuco h t r Piauí o N Rio Grande do Norte Sergipe Espírito Santo Minas Gerais t s Rio de Janeiro a e h São Paulo t u o S Paraná Rio Grande do Sul h u t o Santa Catarina S Distrito Federal Goiás t s Mato Grosso e w d Mato Grosso do Sul M i 0 1 2 3 4 5 6 7 8 9 10 11 Years of schooling Source: PNAD-2014, own estimates. Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 10 / 35

  11. Outline 1 Introduction 2 Data 3 Estimating intergenerational mobility 4 The Great Gatsby Curve 5 Linking Inequality and school dropouts 6 Conclusion Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 11 / 35

  12. Estimating intergenerational mobility 1. Transition matrix Probability of children from parents with the educational attainment j to achieve the education level i . Provide a overview about the direction of the mobility. 2. Linear regression model Summarize the grade of persistence between parents’ and children’s educational attainment. Take into account the changes over time in the education inequality. Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 12 / 35

  13. Transition matrices 1 Classification of educational outcomes Education of children (generation t ) and parents (generation t + 1) into four categories: no school certificate, primary, secondary and tertiary education. 2 Estimation of matrices A trasition matrix is a process { X 0 , X 1 , X 2 , ... } with number of states S , where S has size R (possibly infinite) such that: p ij = P ( X t +1 = j | X t = i ) for i, j ∈ S, t = 0 , 1 , 2 , ... (1) with two important properties: ∀ i, j ∈ R , P ( i, j ) ≥ 0 , and N N N � � � p ij = P ( X t +1 = j | X t = i ) = P { X t = i } ( X t +1 = j ) = 1 j =1 j =1 j =1 Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 13 / 35

  14. Transition matrices 3 Measure of intergenerational mobility Immobility Ratio: � N ImR = Tr ( P ) i =1 ρ ij = S S Upward and Downward Mobility: UpM = Pr ( X t > l | X t +1 = l ) and DoM = Pr ( X t < l | X t +1 = l ) Prais–Shorrocks-Indicator: M P S ( P ) = S − Tr ( P ) with M P S ∈ [0 , 1] S − 1 Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 14 / 35

  15. Transition matrices Descendants predicted propabilities of education attainment Parents with no school certificate Parents with primary education 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 Year of Birth Year of Birth Parents with secondary education Parents with tertiary education 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 Year of Birth Year of Birth Source: PNAD-2014, own estimates. Tertiary Secondary Primary No school Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 15 / 35

  16. Transition matrices Intergenerational Education Mobility by regions and states in Brazil Brazil l z i a r B Acre Amapá Amazonas Pará h t r Rondônia o N Roraima Tocantins Piauí Alagoas Bahia Ceará Maranhão s t a Paraíba e h Pernambuco t r o Rio Grande do Norte N Sergipe Paraná Rio Grande do Sul h t u Santa Catarina o S Espírito Santo Minas Gerais t s Rio de Janeiro a e São Paulo h t u o S Mato Grosso Distrito Federal t s Goiás e w Mato Grosso do Sul d M i 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1 Probability Downward Immobility Upward Source: PNAD-2014, own estimates. Tharcisio Leone (FU-Berlin) The geography of mobility June 11, 2018 16 / 35

  17. Transition matrices Tharcisio Leone Probability 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 Source: PNAD-2014, own estimates. Paraíba (FU-Berlin) M. G. do Sul Alagoas Prais-Shorrocks Index Maranhão Sergipe Rio de Janeiro Intergenerational Mobility Indexes Pernambuco Mato Grosso The geography of mobility R. G. do Sul Pará Brazil Botton to Top Minas Gerais Ceará Bahia São Paulo Paraná Bottom Persistence Santa Catarina Acre Distrito Federal Espírito Santo Roraima Goiás Amazonas Top Persistence June 11, 2018 Rondônia Amapá Piauí Tocantins R. G. do Norte 17 / 35

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