Decomposing Intergenerational Income Elasticity

The gender-differentiated contribution ofcapital transmission in rural Philippines

Leah Bevis & Christopher B. Barrett, Cornell UniversityCalvin College Summer Seminar

on the Economics of Global PovertyAugust 2013

Background• Equality of socio-economic opportunity

o Often proxied by intergenerational income elasticity (IGE) estimates:

• Multiple possible pathways behind IGE and the pathways matter to policy design:o Intergenerational transmission of educationo Intergenerational transmission of healtho Intergenerational land transfers o Assortative marriageo Migrationo Productivity due to correlated unobservables

• Yet there has been very limited exploration of multiple possible pathways, esp. in developing countries

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• How high is IGE/socio-economic mobility in rural Philippines?

• Which pathways account for estimated IGE?

• Do these pathways vary by child or parent gender?

• Does migration affect capital transmission or income transmission?

Core questions

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Conceptual ModelPer Becker-Tomes model, child adult income results from parental investment in child capital stocks and productivity.

Parental capital stocks may affect child capital stocks in 3 ways:

1) PC directly transmits to child capital (e.g., health, land)

2) PC affects parental income, which constrains investment in child capital (e.g., education) given borrowing constraints

3) PC affects parental preferences and expectations, which affect investment in child capital (e.g., marriage, education)

Also may be intergenerational productivity correlation due to genetics, natural/social environment, unobserved skills, etc.

Parent Land

Parent Education

Parent Productivity

Parent Health

Parent Income

Child Land Child /Spouse Education

Child Productivity

Child Health

Child Income

Conceptual ModelNaïve regression vs. pathway decomposition

Capital transmission pathways

Income transmission pathways

1) Estimate naïve IGE, w/ and w/o correction for measurement error in and transitory shocks to parent income (instrument w/initial period parent expenditure). Strategy resolves downward bias due to using short-term income.

2) Estimate intergenerational capital transmission

where E=education, H=health, L=land, S=spouse education, X=other covariates, ij is child, j is parent. Use OLS-IV.

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Estimation Strategy

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3) Estimate IGE via OLS-IV using different specifications to isolate pathways of transmission: i)Here π captures productivity transmission independent of child capital accumulation. λi estimates are returns to child capital. ii)where μ captures both direct productivity and indirect liquidity effects of parental income. λ are returns to parent capital.iii)allows testing of the exclusionary restriction (λp2 = 0) that parental capital has no direct effect beyond that on child capital accumulation and productivity transmission.

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Estimation Strategy

• Bukidnon: a rural, landlocked province of southern Philippines

• Gathered over two decades:o 1984: 448 families relying primarily on

agricultural income, largely sugar, corn or rice

o 2003/2004: revisited original families, tracked children to new homes in local, peri-urban & urban locations

• “Split” vs “migrant” children o As children, not significantly different

except by gender and birth order.o By adulthood migrants better

educated, wealthier

Data

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Data

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Mean Values Daughters

Mean Values Sons

Mean Values Migrants

Mean Values Non-Migrants

Child Age (years) ‘84 9.6 10.4 9.5 10.3

Father Age (years) ‘84 40 40 40 40

Mother’s Education (years) ‘84 5.9 5.6 5.9 5.6

Father’s Height (years) ’84 161 161 161 161

Parent Landholdings (hectares) ‘84 2.3 2.6 2.6 2.3

Parent Weekly Income (Philippine Peso) ‘84 270 301 288 279

Child Age (years) ‘03 29 30 29 29

Child Household Size (persons) ‘03 ` 7.2 4.6 5.3

Child Education (years) ‘03 9.7 8.6 9.8 8.8

Spouse Education (years) ‘03 9.3 10.1 10.2 9.1

Child Height (cm) ‘03 150 163 155 156

Child Landholdings (hectares) ‘03 0.1 0.3 0.2 0.2

Child Weekly Income (Philippine Peso) ‘03 1830 1805 2439 1326

Naïve IGE Estimates

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Once control for permanent income and life cycle effects, IGE much higher than w/o controls and higher than OECD countries. No stat. sig. difference b/n daughters/sons, migrants/non-migrants

Table A4: IGE across Various Estimation Approaches Estimator:

(3) OLS

(4) IV

Dependent Variable: Log Child Inc Log Child Inc Independent Variable: Avg Parent Inc Parent Inc ‘84 Instrument: NA Parent Expen ‘84 IGE All Children: 0.262*** 0.500*** (0.0538) (0.120) IGE Daughters: 0.248*** 0.537*** (0.0633) (0.163) IGE Sons: 0.269*** 0.434*** (0.0877) (0.146) IGE Splits: 0.280*** 0.474*** (0.0571) (0.103) IGE Migrants: 0.238*** 0.574*** (0.0739) (0.197)

Robust standard errors in parentheses Father’s age and child’s age are controlled for quadratically in all regressions

*** p<0.01, ** p<0.05, * p<0.1

Capital Transmission Pathways

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Key results:- Liquidity effects limited. Parental income exerts a significant positive effect only on daughters’ (and sons-in-law) education.

- Direct intergenerational human capital transmission is key. Esp. mothers’ human capital on both sons and daughters: children’s education and height, and their spouse’s education.

- Parent land affects no child capital stocks, perhaps due to 1988 land reform and mass exits from agriculture 1984-2004.

- Mother’s education negatively related to daughters’ height, seemingly through effect on maternal labor supply and thus on child feeding practices.

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Capital Transmission PathwaysTable 2: Intergenerational Capital Transmissions for Daughters (OLS-IV)

(1) (2) (3) (4) Daughter

Education Daughter Height

Daughter Landholdings

Daughter Spouse Education

Log Parent Income ‘84 1.642** 0.763 0.231 1.949** (0.702) (2.882) (0.169) (0.909) Parent Land ‘84 0.0727 -0.121 -0.00330 -0.0398 (0.0604) (0.408) (0.0192) (0.0995) Mother’s Education ‘84 0.348*** -0.578* -0.00206 0.159* (0.0807) (0.351) (0.0131) (0.0833) Father’s Education ‘84 0.149* 0.559 0.00871 0.258*** (0.0846) (0.359) (0.0143) (0.0860) Mother’s Height ‘84 -0.0837** 0.438*** -0.0102 -0.0158 (0.0352) (0.107) (0.00652) (0.0410) Father’s Height ‘84 0.0353 0.0460 -0.00635 0.00308 (0.0346) (0.195) (0.00626) (0.0421)

Son

Education Son

Height Son

Landholdings Son

Spouse Education Log Parent Income ‘84 1.311 -0.330 -0.132 -1.162 (1.211) (1.850) (0.389) (1.325) Parent Land ‘84 0.194 0.236 0.0752 0.224 (0.148) (0.241) (0.0674) (0.174) Mother’s Education ‘84 0.268** -0.190 0.0650** 0.321*** (0.120) (0.234) (0.0326) (0.121) Father’s Education ‘84 0.147 0.264 -0.0436 0.0505 (0.115) (0.206) (0.0462) (0.115) Mother’s Height ‘84 -0.00627 0.362*** 0.00531 0.0202 (0.0509) (0.0963) (0.0127) (0.0447) Father’s Height ‘84 -0.00461 0.296*** -0.0224 -0.00566 (0.0469) (0.0746) (0.0139) (0.0436)

Robust standard errors in parentheses Controls include household size, gender-specific birth order dummies,

location (barrio) & ethnic groups dummies

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Income Transmission Pathways

- Naïve IGE estimates statistically insignificantly different between daughters and sons, migrants and splits (0.43-0.57).

- But once we control for capital transmission, very different pathways appear by child gender.

- In both cases, landholdings and spouse education strongly affect children’s adult income – and is each strongly associated with parent land and maternal education, respectively. But the estimated marginal effects of landholdings (spouse education) are far higher for daughters (sons).

- For daughters, IGE runs primarily through intergenerational productivity correlation, while for sons no such effect exists.

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Daughters’ Income Transmission Pathways

Very strong intergenerational productivity/unobserved capital transmission effect.

Daughters’ landholdings and (own and spouse) education also play a role.

Some residual effect of maternal human capital and parental landholdings.

Table 5: Decomposing Intergenerational Income Elasticity for Daughters (OLS-IV) (1) (5) Income Income Parent Income ‘84 0.537*** 0.779** (0.163) (0.344) Parent Land ‘84 -0.0558** (0.0267) Mother’s Education 0.0614* (0.0357) Father’s Education -0.0325 (0.0275) Mother’s Height 0.0359*** (0.0114) Father’s Height -0.00619 (0.0117) Own Education 0.0632* (0.0346) Spouse Education 0.0356* (0.0193) Own Height -0.00605 (0.00730) Landholdings 0.307*** (0.112) Age Controls: Yes Yes Additional Controls: No Yes Observations 240 220 R-squared 0.114 0.433

Robust standard errors in parentheses Age controls include quadratic terms for child and father age

Additional controls include parent household size, gender-specific birth order dummies, location (barrio) & ethnic groups dummies

*** p<0.01, ** p<0.05, * p<0.1

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Sons’ Income Transmission Pathways

By contrast, no intergenerational productivity transmission effect.

Sons’ landholdings and (own and spouse) education key income determinants.

Some residual (negative?) effect of parental human capital.

(1) (5) Income Income Parent Income ‘84 0.434*** -0.00884 (0.146) (0.385) Parent Land ‘84 -0.0285 (0.0459) Mother’s Education 0.0511 (0.0382) Father’s Education -0.00327 (0.0312) Mother’s Height -0.0598*** (0.0186) Father’s Height -0.0245* (0.0132) Own Education 0.0367* (0.0223) Spouse Education 0.131*** (0.0229) Own Height 0.0217 (0.0140) Landholdings 0.161*** (0.0605) Age Controls: Yes Yes Additional Controls: No Yes Observations 182 157 R-squared 0.050 0.594

Robust standard errors in parentheses Age controls include quadratic terms for child and father age

Additional controls include parent household size, gender-specific birth order dummies, location (barrio) & ethnic groups dummies

*** p<0.01, ** p<0.05, * p<0.1

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Which Pathways Explain Most IGE?

Use change in r2 from adding variable to naïve specification as upper bound estimate and from dropping variable from full specification as lower bound in establishing relative importance of different paternal capital/income pathways in explaining adult child income. Punch line: maternal education biggest factor, but much variation.

Table 9: Pathway Explanatory Power Model Sub-Sample Proportion of 𝑅2Explained by Each Parent Capital Level

Productivity Parent Land Maternal Education

Paternal Education

Maternal Height

Paternal Height

Naïve IGE Regression

Daughters 0.011 0.448 0.407 0.128 0.006 Sons 0.101 0.366 0.383 0.147 0.003

Migrants 0.104 0.631 0.265 0.000 0.000 Splits 0.001 0.438 0.535 0.007 0.020

IGE Decomposition

Daughters 0.780 0.001 0.149 0.001 0.067 0.002 Sons 0.117 0.179 0.222 0.064 0.309 0.101

Migrants 0.028 0.008 0.679 0.007 0.035 0.244 Splits 0.508 0.069 0.127 0.060 0.015 0.221

1. IGE is high (~0.5) in rural Philippines2. But there are sharp gender differences in the pathways

behind these IGE estimates.3. For sons, IGE operates through land and spouse education

capital transmission, with some residual (negative!?) association with parental human capital.

4. For daughters, IGE also operates through human capital transmission, but with some residual association with maternal human capital and very strong intergenerational productivity transmission.

5. Parent income does not affect most child capital levels, which are driven primarily by direct transmission of parent human capital stocks. But education is a normal good.

Conclusions

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6. Parental landholdings play a surprisingly negligible role in intergenerational income transmission, perhaps due to major land reform episode.

7. Marriage markets are crucial institutions limiting equality of opportunity.

8. Patterns also differ for migrants and non-migrants (not shown due to time).

9. Mothers’ human capital is important and transmits relatively equally to sons and daughters. Fathers’ human capital much less important and rarely equal to both sons and daughters.

Conclusions

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Thank you for your time,attention and comments