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Can’t buy mommy’s love? Universal childcare and children’s long-term cognitive development


What happens to children’s long-run cognitive development when introducing universal high-quality childcare for 3-year-olds mainly crowds out family care? To answer this question, we take advantage of a sizeable expansion of publicly subsidized full-time high-quality childcare for 3-year-olds in Spain in the early 1990s. Identification relies on variation in the initial speed of the expansion of childcare slots across states. Using a difference-in-difference approach, we find strong evidence for sizeable improvements in children’s reading skills at age 15 (0.15 standard deviation) and weak evidence for a reduction in grade retentions during primary school (2.5 percentage points). The effects are driven by girls and disadvantaged children.

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  1. In this aspect, our paper contrasts with that of Black et al. (2012) in which the authors are able to isolate the effects of childcare subsidies on both parental and student outcomes.

  2. Please refer to Appendix Table A.1 for an overview of the research on the impact of public childcare on children’s development. In addition, several recent studies evaluate the other side of the coin: the impact of maternal care on children’s development. Exploiting parental leave expansions, most studies do not find any significant effect on children’s long-run development (Baker and Milligan 2011; Dustmann and Schöenberg 2012; Liu and Oskar 2010; Rasmussen 2010). The exception is Carneiro et al. (2011) who find improvements in children’s long-run educational outcomes following a parental leave expansion in Norway. Likewise, a recent paper by Bettinger et al. (2013) exploits the introduction of an allowance paid to parents who do not utilize public care as an exogenous shock to maternal time devoted to their children in Norway. They also find positive effects on elderly siblings’ long-run educational outcomes.

  3. About one third of children in primary school in Spain are enrolled in private schools. In this paper, private schools refer to escuelas concertadas for which the government subsidizes the staff costs (including teachers).

  4. See Felgueroso et al. (2014) for an analysis of the effects of the primary and secondary school component of the reform on high school dropout rates.

  5. Unfortunately, we only have information on enrollment rates and not on actual supply rates. In the context of rationed supply, enrollment rates should, however, resemble coverage rates quite closely.

  6. Unfortunately, data disaggregated at the preschool level or at a lower regional level is not available.

  7. While the pedagogical movements behind the LOGSE are close to those in Scandinavian countries, they have been viewed as an alternative to the test-oriented instruction legislated by the No Child Left Behind educational funding act in the USA or the reception class in the UK.

  8. For our binary outcomes, we replicate our analysis using logit models, which yield similar results.

  9. Due to perfect collinearity between the constant and the Post t dummy on the one hand and the PISA cohorts on the other hand, we omit two cohort dummies (2000 and 2009). Alternatively, we could omit the Post t dummy and include dummies for both “post reform” cohorts (see Section 7).

  10. While we have administrative data on preschool enrollment at the lower level, we lack that information in PISA (in fact, gaining access to PISA data disaggregated at the state level is already quite hard). As such, our analysis relies on variation between states but ignores potential variation within states.

  11. Following Berlinski and Galiani (2007), we estimate the proportion of public preschool seats offered in each state as the number of public preschool units available for 3- to 5-year-olds in each region times the average size of the classroom divided by the population of 3- to 5-year-olds in each state.

  12. To account for the fact that there is a time- and state-varying trend in maternal employment that is positively correlated with the implementation of the reform but negatively correlated with maternal employment (or vice versa)—as shown by Nollenberger and Rodríguez-Planas (2011)—we add state-specific trends when the LHS variable is maternal employment. We abstain from doing so in our baseline estimates, as we only possess of PISA data at 4 points in time (every third year and not on an annual basis as it is the case for maternal employment data). Nevertheless, results for child outcomes including state-specific time trends are comparable in magnitude but less precise and are available upon request.

  13. See

  14. As the Ministry did not publish the enrollment rates at state level in the yearbooks, they were calculated by the authors as the ratio between the number of children enrolled in public and private schools (available at state level in the Education Statistics yearbooks) and the population of the corresponding age group and state from the Spanish Statistics Institute. ( We check the consistency of our calculations comparing overlapping data for the school years 1992/1993 and 1993/1994.

  15. Again, we do not observe children’s day care enrollment, thus precluding us from analyzing a “first-stage” model, as in Cascio (2009) and Berlinski and Galiani (2007) with a dummy for public day care enrollment of the mother’s youngest child as dependent variable.

  16. Potentially, one could use PISA 2000 and 2003 and analyze whether we find evidence of a differential effect on cognitive development between youths in Basque Country and Navarra and the rest of Spain. However, because of the greater fiscal and political autonomy in these two regions, it is likely that other policies may have occurred at the same time, confounding the effect of the universal childcare policy.

  17. As explained at the end of Section 3, we adjust the identification strategy to be comparable to the baseline strategy of the current paper.

  18. We estimate the separate effect on the 1993/1994 and 1996/1997 cohorts and find similar coefficients (0.261 versus 0.256). As a consequence, we decided to pool both post-reform cohorts into one. Results when estimating our specification using the two cohorts separately are shown in Table 8 panel C and are discussed in Section 7.

  19. Prior to the reform, the average employment rate of mothers of 3-year-olds was 35.7 % in fast-implementing states.

  20. In addition, the migration flow by skill level is similar to the ones presented in the table and does not indicate any migration flows that would threaten our identification strategy.

  21. Appendix Table A.2 explores additionally the sensitivity of our results to sequentially adding other (potentially endogenous) regional characteristics, individual characteristics, such as family characteristics (parents’ level of education and home possessions), type of school, and population density of the area of residence. While the effect on reading is robust across all specifications, the estimate on falling behind a grade becomes practically zero when regional characteristics are included. In this specification (column 2), the reform has a significant and beneficial effect on grade retention during secondary school. Yet, it is important to keep in mind that these additional control variables are likely to be affected by the reform and thus the estimated coefficients represent only net (off potential channels) effects of the reform on children’s cognitive long-run development.

  22. While additional analysis adding a second-order polynomial of the number of available seats does not indicate any nonlinear impact of public childcare slots on children’s long-run cognitive development, using a step function instead does indicate that the effect is the effect of adding slots when the supply is still low (e.g., below the median and even in the lower tercile) is stronger than when the supply is rising. This evidence goes in line with the subgroup analysis by cohort which indicates stronger effects for the cohort 1990 when the supply of slots was still low than for the cohort 1993 when the supply of slots had already risen.


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We would like to thank the editor, Erdal Tekin, and three anonymous referees for helpful comments that greatly improved the paper. The authors are also grateful to Manuel Bagues, Paul Devereux, Susan Dinarsky, Maria Fitzpatrick, Libertad González, Lídia Farré, Michael Lechner, Oskar Nordström Skans, Björn Öckert, Xavi Ramos, Antonio Cabrales, Ismael Sanz Labrador, Uta Schönberg, Anna Sjögren, Anna Vignoles, Conny Wunsch, Natalia Zinovyeva, as well as participants from the V INSIDE-MOVE, NORFACE, and CReAM Workshop on Migration and Labor Economics, the III Workshop on Economics of Education “Improving Quality in Education,” the CESifo Area Conference on the Economics of Education, the RES Annual Meeting, the SOLE Annual Meeting, the ESPE Annual Meeting the EALE Annual Meeting as well as seminars at DIW, IFAU, University College Dublin, Ludwigs-Maximilians Universität, and University of St Gallen. The authors also would like to thank the Spanish Instituto Nacional de Evaluación Educativa (INEE) del Ministerio de Educación, Cultura y Deporte for facilitating access to the geo-codes for PISA 2000 and Brindusa Anghel from FEDEA for her support with the Spanish Labor Force Survey.

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Correspondence to Christina Felfe.

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Responsible Editor: Erdal Tekin



Table A.1 Literature overview
Table A.2 Sensitivity analysis of covariates included
Table A.3 Difference-in-difference estimates for regional features

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Felfe, C., Nollenberger, N. & Rodríguez-Planas, N. Can’t buy mommy’s love? Universal childcare and children’s long-term cognitive development. J Popul Econ 28, 393–422 (2015).

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  • Universal high-quality childcare
  • Long-term consequences
  • Cognitive skills

JEL Classification

  • J13
  • I28