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How family size affects children’s schooling and work in Mexico

This research study aims to examine how family size affects the educational attainment and work participation of children in Mexico. The quantity-quality model suggests that larger families may reduce investment in education. The study uses instrumental variables, such as twin births and same-sex siblings, to identify the causal effect. The analysis is based on a large sample of households and children aged 11-17 from the Mexican ENCASEH survey. The results will contribute to the existing literature on the effects of family size on education in developing countries.

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How family size affects children’s schooling and work in Mexico

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  1. How family size affects children’s schooling and work in Mexico Emla Fitzsimons Bansi Malde 27 Feb 08

  2. Introduction • Question of Interest • Does family size affect children’s school and/or work participation? • Theory • Quantity-Quality model: bigger families (quantity) reduce investment in schooling (quality) • Empirical Issues • To test how well the quantity-quality model fits reality requires exogenous changes in fertility that are uncorrelated with preferences or budget constraints • We use Instrumental Variables to identify the causal effect

  3. Instrumental Variables We use the following instruments • Twin births: increases family size by definition • First n children are of the same sex: increases family size if parents have preferences for having children of both sexes • Note, the literature that considers the causal effects of family size basically always uses these instruments

  4. A glance at the literature! • Most of these studies consider developed countries and outcomes different to ours (female labour supply) • Literature most comparable to what we do (effects of family size on education in developing countries): • India: Rosenzweig & Wolpin (1980) • China: Qian (2006), Rosenzweig & Zhang (2006) • Korea: Lee (2004) • Brazil: Ponczek & Souza (2007) • Colombia: Baez (2007) • We will hopefully improve on them thanks to extremely large samples

  5. Methodology • Basic model • IV first stage • Using same-sex instrument • Using twins instrument

  6. Data • The main source we use is the Mexican ENCASEH survey: cross-sectional census data collected across marginalised rural areas b/w 1996 and 1999 • Info on individual, household and locality characteristics • Restrict sample to children aged 11-17 • Drop households with • both parents not living together/not married • eldest child>18 • >1 household head So we’re left with a sample of ~600,000 households and ~1.1million children aged 11-17 • Note, average # of children per family in our sample is 4.3 • We’re also going to merge these data with the PROGRESA surveys, as there’s v useful info for our purposes in these - we’ll come back to this later

  7. Randomisation check - same-sex of first 2 births

  8. Randomisation check - twins at second birth

  9. First stage results – Boys and Girls

  10. First Stage Results - Girls

  11. First Stage Results - Boys

  12. TSLS estimates for First Born Boys and Girls

  13. TSLS estimates for First Born Girls

  14. TSLS estimates for First Born Boys

  15. Issues/Next Steps Validity of Instruments Economies of scale? (Rosenzweig and Wolpin (2000))

  16. Issues/Next Steps Robustness Checks • Compare results across different instruments (what we have just shown) • Use an instrument that should suffer much less from this issue: twins at second birth that are of different sex from first-born sensitivity first stage.doc; sensitivity second stage.doc • Use PROGRESA consumption data to see if there is any evidence of economies of scale • we observe expenditure on children’s clothes and shoes, separately by sex: we are going to use these data to see if sex-sameness affects these expenditures • we also observe value of assets, may be useful • Assess sensitivity of parameter estimates to different correlations b/w the IV and the error term using method of Ashley (2008); (note refine correlations using info from PROGRESA data)

  17. Issues/Next Steps • Results obtained from the IV are all LATE and affect only particular types of households • How do we reconcile all these different LATEs?

  18. Any Comments/Questions?

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