The Effects of Child Care Quality and Attendance in a Developing Country

The improved quality condition is based on an improvement package that was applied to some of the early childhood centers in Panama, and includes teacher training sessions and monitoring and supervision from the central level. It also includes additional resources and important improvements in infrastructure for some of the centers. The improvement package was randomly assigned across centers.

The children in our baseline survey are two or three years old, and the centers take children up to the age of four, so they will be able to stay for one or two years, which will be the treatment exposure time. Children not receiving slots at the centers can find preschool education or child care in any outside option or can get one of the slots if the families getting the original offers reject them.

2019-03-11

2020-12-30

• Child development, as measured by ASQ-III. Other instruments could be applied in the future, depending on budget constraints.
• Quality of home environment, as measured by HOME
• Parental and family labor market outcomes, as labor participation, type of occupation, having a formal job, wages and income

We will measure child development using the composite ASQ score and all of its dimensions. ASQ measures communication, gross motor, fine motor, problem solving, and personal-social. The literature shows that the most usual dimensions where we can have an impact are in the important communication and personal-social scales.

The HOME will be used primarily as the simple sum of the items. The dimensions will have to be constructed from scratch, as we selected a subset of the items to be applied. There is previous work on forming dimensions by Jeanne Brooks-Gunn and coauthors that we will use as the basis for our work.

The most important and obvious labor market outcome of interest are the mother’s labor force participation and labor income. However, we are also interested on whether other members of the family (e.g. grandmothers) were able to work thanks to having child care available.

• Body weight, height and BMI
• Types, quality and intensity of care. There are several intermediate outcomes of interest in this category: who takes care of the child at each moment in time; what are the characteristics of the care and the caregiver, including educational level, alternative wage; and how the time of the child is allocated during the day.
• Fees paid for formal and informal care by the parents

To have the possibility of evaluating the three treatment conditions, we chose preschool centers that were located at a walkable distance from each other, in which one had been assigned to the improvement package and the other was part of a control group. Then, we recruited families in the same geographical area, that had a child of the proper age, and that were interested in applying to a preschool center. A total of 1900 children were surveyed. All of the families were included on the application lists for the centers. For each center, each applicant child received a random priority and slots were offered in that order. That way, each child received a random priority in each of the two centers. We plan to use those random priorities as sources of exogenous variation in our analyses.

The experiment will allow us to identify the impact of the three different treatment conditions on the children, including pairwise comparisons of the counterfactual scenarios. Our main variables of interest are related to (i) child development, (ii) labor force participation of the members of the family, and (iii) quality of time at home.

The random priority numbers were constructed in an excel file, and then the slot offers and the waitlist priority were informed to the central administration offices. The child care center supervisors then called the families asking them if they wanted to matriculate. When a family rejected the slot, they continued to the next child in the wait list.

Children

No

41 centers

1900 children

For the child-level evaluation 486 children were offered slots in higher-quality preschools and 524 were offered slots in regular-quality preschool. The rest (around 890 children) are our control group.

Our randomization is at the individual level, so we do not take clusters into account in our power calculations. For inference on outcomes at the individual level, and considering individual-level randomization, assuming power 0.8, significance 0.05, an R-squared of 30% when predicting the outcome with baseline measurements, and an attrition of 20%. We first discuss testing the effect of participating in high-quality centers. For the following analysis, we consider the comparison between participating in a high-quality center and not participating in one. We consider a one-sided test. Initial pieces of information coming from administrative data show that our compliance will be relatively low, with many families not taking the offer of slots, or not being able to be re-contacted by the ministry. We estimate the difference in take-up of the group offered the high-quality centers compared with the rest of the children to be close to 29%. Then, our assumptions give us a MDE of 0.45. Then, we study the differences between attending centers and not attending. The assumptions are the same. The test is two-sided this time, as some of the literature shows negative impacts from child care in some population groups. With 1008 children offered treatment, and an average difference in take-up rate of 24%, our assumptions give us a MDE of 0.47. These calculations are too conservative, given that we also have the waitlist and the distance to the centers as additional instruments, and their help in determining the take-up is not considered in these calculations. We expect them to be very relevant in increasing our statistical power.