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Effects of a Large-Scale Program for the Construction of Daycare and Preschool Centers on Cognitive Skills and Female Employment

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Title: Effects of a Large-Scale Program for the Construction of Daycare and Preschool Centers on Cognitive Skills and Female Employment
Language: English
Authors: Marcelo Castro, Breno da Cruz
Source: Education Economics. 2024 32(6):786-811.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 26
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Early Childhood Education
Descriptors: Foreign Countries, Early Childhood Education, Educational Facilities, Labor Force, Employed Women, Construction Programs, Academic Achievement, Program Evaluation
Geographic Terms: Brazil
DOI: 10.1080/09645292.2023.2254516
ISSN: 0964-5292
1469-5782
Abstract: This paper assesses the impacts of a large-scale program aimed at constructing daycare and preschool centers in Brazil named Proinfância, which funded new buildings in nearly 45% of the municipalities between 2008 and 2017. We find a significant increase in early education care in the jurisdictions that participated in the program more than a decade after it had started: 4 percentage points in the attendance rate for infants aged up to three and six percentage points for children aged 4 to 5. However, the improvements in public schools' scores in 'Prova Brasil', which is a national exam for elementary school children, are small (at most 1%). Despite this, the program significantly helped increase female labor force participation, especially considering low-educated workers, but also with a small magnitude (1 percentage point). The results suggest that a faster increase in the coverage of public infant education would lead to more pronounced effects on children's development and female participation in the workforce.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1448103
Database: ERIC
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  Value: <anid>AN0180801952;ede01dec.24;2024Nov13.04:49;v2.2.500</anid> <title id="AN0180801952-1">Effects of a large-scale program for the construction of daycare and preschool centers on cognitive skills and female employment </title> <p>This paper assesses the impacts of a large-scale program aimed at constructing daycare and preschool centers in Brazil named Proinfância, which funded new buildings in nearly 45% of the municipalities between 2008 and 2017. We find a significant increase in early education care in the jurisdictions that participated in the program more than a decade after it had started: 4 percentage points in the attendance rate for infants aged up to three and six percentage points for children aged 4 to 5. However, the improvements in public schools' scores in 'Prova Brasil', which is a national exam for elementary school children, are small (at most 1%). Despite this, the program significantly helped increase female labor force participation, especially considering low-educated workers, but also with a small magnitude (1 percentage point). The results suggest that a faster increase in the coverage of public infant education would lead to more pronounced effects on children's development and female participation in the workforce.</p> <p>Keywords: Early childhood care; children's cognitive achievement; female labor force participation; large-scale program evaluation</p> <hd id="AN0180801952-2">1. Introduction</hd> <p>For decades, international studies have highlighted the importance of educational policies in early childhood (children aged up to 5), given this is a critical period in cognitive and non-cognitive achievement. Moreover, investments in early childhood education tend to be more cost-effective since development in this phase has larger impacts than interventions to reduce learning problems or re-qualify workers in other stages of life. In addition, access to early education by children in vulnerable conditions reduces inequalities of opportunities and contributes to increasing economic productivity (Barnett and Escobar [<reflink idref="bib6" id="ref1">6</reflink>]; J. J. Heckman [<reflink idref="bib52" id="ref2">52</reflink>]; Magnuson, Ruhm, and Waldfogel [<reflink idref="bib67" id="ref3">67</reflink>]; Masterov and Heckman [<reflink idref="bib68" id="ref4">68</reflink>]; Temple and Reynolds [<reflink idref="bib78" id="ref5">78</reflink>]; Waldfogel [<reflink idref="bib79" id="ref6">79</reflink>]).</p> <p>Nonetheless, the literature on the impacts of preschool–for children aged 4 to 5–and especially daycare centers–focused on children younger than 3–on future personal outcomes is not conclusive. Whereas some papers have found positive impacts on cognitive and non-cognitive skills (Brilli, Del Boca, and Pronzato [<reflink idref="bib24" id="ref7">24</reflink>]; Nores, Bernal, and Barnett [<reflink idref="bib72" id="ref8">72</reflink>]) and educational attainment (Krafft [<reflink idref="bib64" id="ref9">64</reflink>]), others have estimated no significant effects (Carta and Rizzica [<reflink idref="bib28" id="ref10">28</reflink>]). There is even a branch of literature that has estimated adverse effects of daycare centers on future cognitive (Bernal et al. [<reflink idref="bib12" id="ref11">12</reflink>]; Fort, Ichino, and Zanella [<reflink idref="bib45" id="ref12">45</reflink>]) and non-cognitive (Baker, Gruber, and Milligan [<reflink idref="bib4" id="ref13">4</reflink>]; Noboa-Hidalgo and Urzua [<reflink idref="bib71" id="ref14">71</reflink>]) attainment. Overall, the magnitude and direction of effects have been associated with the quality of school attendance compared to that of early care given to infants and toddlers by their families (Engle et al. [<reflink idref="bib39" id="ref15">39</reflink>]).</p> <p>Another argument for offering public early childhood care is that this kind of public policy allows access of less privileged mothers to the labor market, thus increasing household income and reducing inequality. Indeed, children's care is more commonly associated with women than men. Thus, the literature reports that access to daycare centers and preschools plays an essential role in enabling mothers to be productive outside their homes (Blau and Currie [<reflink idref="bib14" id="ref16">14</reflink>]; Olivetti and Petrongolo [<reflink idref="bib74" id="ref17">74</reflink>]).[<reflink idref="bib1" id="ref18">1</reflink>] Even so, recent studies investigating this relationship and using experimental or quasi-experimental designs have estimated minor or null effects on female employment (Havnes and Mogstad [<reflink idref="bib51" id="ref19">51</reflink>]) and household income (Barros et al. [<reflink idref="bib8" id="ref20">8</reflink>]).</p> <p>In this context, our objective is to evaluate the impacts of a large-scale program for the construction of daycare and preschool centers in Brazil–the National Program for Restructuring and Acquiring Equipment for the Public Early Childhood Education System[<reflink idref="bib2" id="ref21">2</reflink>] (Proinfância from now on)–on children's cognitive development and female labor supply. Proinfância is a Brazilian program coordinated and funded by the federal government but implemented by local jurisdictions. It aims to build new daycare centers and preschools throughout the country to increase the attendance rate in early childhood education. While municipalities must apply to the program, provide the construction site, and supervise the construction works, the federal government must fund the buildings and provide technical support.</p> <p>The empirical literature investigating the effects of early childhood care has focused on programs for the age of three or above and on high-income countries (Havnes and Mogstad [<reflink idref="bib51" id="ref22">51</reflink>]; J. Heckman, Pinto, and Savelyev [<reflink idref="bib55" id="ref23">55</reflink>]). Only in a few exceptions (Barros et al. [<reflink idref="bib8" id="ref24">8</reflink>]; Berlinski, Galiani, and Gertler [<reflink idref="bib11" id="ref25">11</reflink>]; Noboa-Hidalgo and Urzua [<reflink idref="bib71" id="ref26">71</reflink>]; Nores, Bernal, and Barnett [<reflink idref="bib72" id="ref27">72</reflink>]) is there evidence of the impact of childhood care for toddlers and infants in low- and middle-income countries with precarious children's access to early childhood education (Black et al. [<reflink idref="bib13" id="ref28">13</reflink>]). Thus, Proinfância provides an opportunity for evaluating a nationwide program seeking to increase access to daycare and preschool in a large middle-income country.</p> <p>To estimate the causal effects of Proinfância, we collect data from Brazilian municipalities for all years between 2007 and 2021 regarding the participation in the program and the final year of the buildings' construction, the scores in 'Prova Brasil'–a national exam applied in all public elementary schools–, and the share of formal jobs filled by women. Then, using the Difference-in-differences strategy and controlling for information on local demography, we compare the trends in the outcomes of such municipalities that received a building financed by Proinfância and the ones that did not conclude a facility funded by the program.</p> <p>We find an increase of nearly four percentage points (p.p.) in the attendance rate for children aged 0 to 3 and six p.p. for children aged 4 to 5 more than a decade after the beginning of the program. In addition, our results show that the average score in Portuguese and Mathematics improved in municipalities that participated in the program. Yet, the magnitude is small (roughly 1%). Finally, we find positive impacts of Proinfância on the share of formal jobs occupied by women, especially considering low-educated workers. Even though the effects are also small (around 1%), they go in line with a branch of literature that has evaluated the large-scale expansion of early childhood care in developed countries (Cascio [<reflink idref="bib29" id="ref29">29</reflink>]; Havnes and Mogstad [<reflink idref="bib51" id="ref30">51</reflink>]). However, they are opposed to the estimates in Hojman and Boo ([<reflink idref="bib57" id="ref31">57</reflink>]), with data from Nicaragua.</p> <p>Our results suggest that Proinfância helped increase access to public daycare and preschool institutions but was insufficient to produce a significant change in cognitive tests and female employment in the municipalities that implemented it. It is noteworthy that the program has faced many obstacles in its implementation. Not only was there a delay but also many construction works were canceled. The manner in which the built-up facilities operate was presumably very different all over the country. Hence, the provided care quality may vary a lot, given there is not a national standard or protocol that public childhood education institutions must comply with.</p> <p>In Section 2, we review the literature associating early childhood education with future school achievement and mothers' engagement in the labor force. In Section 3, we describe the institutional background of Proinfância implementation and the underlying features of early childhood education and the female labor force in Brazil. In Section 4, we describe data and methodology; whereas the results are shown in Section 5 and final remarks in Section 6.</p> <hd id="AN0180801952-3">2. Literature review</hd> <p></p> <hd id="AN0180801952-4">2.1. The relevance of early childhood education for school development at later stages</hd> <p>In the last decades, evidence regarding the importance of investments in early childhood education mounted up in many fields. Investing in the earlier stages of children's development might reverse adverse genetic, parental, or environmental conditions, enabling children to get the resources required for the adequate development of their cognitive and socio-emotional skills, which would increase their productivity and well-being in the future (J. J. Heckman [<reflink idref="bib52" id="ref32">52</reflink>]).[<reflink idref="bib3" id="ref33">3</reflink>]</p> <p>Despite the consensus on the importance of early childhood care, there are still questions about what kind of interventions are more appropriate, especially for infants and toddlers between 6 weeks and three years of age (J. Heckman, Pinto, and Savelyev [<reflink idref="bib55" id="ref34">55</reflink>]). A prominent observation from psychologists is that adult interaction is essential for a young child's development, mainly regarding child-directed speech (Weisleder and Fernald [<reflink idref="bib80" id="ref35">80</reflink>]). Therefore, the relative effects of daycare centers depend on the alternative supervision at home (or elsewhere) at an early age. Some studies evaluating the effects of daycare centers have found positive results on subsequent cognitive skills but negative ones on non-cognitive development, depending on the duration and specific childcare arrangement (Loeb et al. [<reflink idref="bib66" id="ref36">66</reflink>]).</p> <p>However, the empirical evidence relying on credible methods is usually focused on developed countries (Brilli, Del Boca, and Pronzato [<reflink idref="bib24" id="ref37">24</reflink>]; Fort, Ichino, and Zanella [<reflink idref="bib45" id="ref38">45</reflink>]; J. J. Heckman [<reflink idref="bib52" id="ref39">52</reflink>]), where many studies analyzed public programs to encourage children's development. In the United States, for instance, three early childhood intervention projects carried out appropriately randomized experimental and longitudinal designs that followed the participants until adulthood: the Perry Preschool, the Abecedarian Program, and the Star Project. These programs emphasized full-time and high-quality teaching and followed the participants to adulthood (Temple and Reynolds [<reflink idref="bib78" id="ref40">78</reflink>]).[<reflink idref="bib4" id="ref41">4</reflink>]</p> <p>Some evidence from Latin America has emerged in the last decade. Nores, Bernal, and Barnett ([<reflink idref="bib72" id="ref42">72</reflink>]) found positive effects of high-quality infant care on cognitive skills in Colombia, mainly for girls. Nonetheless, the current studies usually evaluate limited-scale one-off programs with specific arrangements. An exception is Noboa-Hidalgo and Urzua ([<reflink idref="bib71" id="ref43">71</reflink>]), who analyzed a significant expansion of a childhood care program targeting the poorest families in Chile. They found positive effects on emotional skills but reduced interactions with adults.</p> <p>Furthermore, Berlinski, Galiani, and Gertler ([<reflink idref="bib11" id="ref44">11</reflink>]) studied the significant expansion of preschools in Argentina, where the government started a large-scale program to build public facilities to increase access to preschool for children between 3 and 5 years old in the 1990s. The massive expansion in enrollments resulted in a positive effect on standardized third-grade Spanish and Mathematics scores and non-cognitive skills. On average, one more year of preschool attendance increased third-grade performance by 8%, and attention, effort, discipline, and participation measures were also positively affected by it.</p> <p>The evidence of early childhood care effects on future cognitive attainment is scarce in Brazil. Despite that, we can cite the paper of Curi and Menezes-Filho ([<reflink idref="bib38" id="ref45">38</reflink>]), in which they observed that primary school students, on average, who had access to early education, showed better cognitive results in elementary school.[<reflink idref="bib5" id="ref46">5</reflink>] Campos et al. ([<reflink idref="bib26" id="ref47">26</reflink>]) identified differences in children's school scores at the beginning of elementary school associated with attendance at a high-quality preschool. Silva and Gonçalves ([<reflink idref="bib77" id="ref48">77</reflink>]) estimated positive effects of preschool attendance on Prova Brasil scores, which increased by roughly 11 points for Portuguese and Mathematics compared to those who went directly to elementary school. Finally, Barros et al. ([<reflink idref="bib7" id="ref49">7</reflink>]) found a significant impact of high-quality daycare centers on children's development.</p> <hd id="AN0180801952-5">2.2. The importance of early childhood education in daycare and preschool centers for mothers...</hd> <p>Public policies aimed at early childhood education may have implications for female labor force participation and gender inequality. Usually, men and women's careers evolve in parallel until their first child's birth. After this event, their careers diverge and do not converge again. Thus, there is a 'penalty' for having children that affects women more than men (Kleven, Landais, and Søgaard [<reflink idref="bib63" id="ref50">63</reflink>]), which comes in three manners: difficulty in entering the labor market, fewer worked hours, and lower wages.</p> <p>Recent studies analyzing the impact of early childhood education on female labor force participation in developed countries show significant effects, but often with a small magnitude (Brilli, Del Boca, and Pronzato [<reflink idref="bib24" id="ref51">24</reflink>]; Carta and Rizzica [<reflink idref="bib28" id="ref52">28</reflink>]; Olivetti and Petrongolo [<reflink idref="bib74" id="ref53">74</reflink>]). Havnes and Mogstad ([<reflink idref="bib51" id="ref54">51</reflink>]) did not find any impacts regarding the significant expansion in Norway during the 1970s. They argue that the replacement of informal care–made by relatives, neighbors, friends, or in a community nursery, for example–may offset any relaxations in the biding conditions for female workforce.</p> <p>For illustrative purposes, in the event of childcare provision by the government, mothers might let their children in daycare and preschool centers and join the job market if they want to, or they might replace private/informal care with the public one (Blau and Currie [<reflink idref="bib14" id="ref55">14</reflink>]). In the latter situation, no variations in the supply of work by the mothers are expected to be seen. Therefore, ultimately, the program would not be cost-effective considering the dimension of additional income for mothers (Havnes and Mogstad [<reflink idref="bib51" id="ref56">51</reflink>]).</p> <p>Research evaluating the effects of early childhood care on female labor force participation in underdeveloped countries is scarce and often needs more robust methods for causal inference. Berlinski and Galiani ([<reflink idref="bib10" id="ref57">10</reflink>]) is the closest to us, as they analyzed a large-scale program to construct early education facilities in Argentina and found consistent increase in maternal employment.</p> <p>In Brazil, Barros et al. ([<reflink idref="bib8" id="ref58">8</reflink>]) estimated the impact of daycare centers in Rio de Janeiro state. In 2007, about 3800 families were selected and randomly assigned to municipal daycare centers funded by the federal government. They estimated an 8% increase in women's participation rate in the labor market. However, the additional income did not pay the costs <emph>per</emph> pupil participating in the program.</p> <p>In addition, in Brazil, Cirino and de Lima ([<reflink idref="bib32" id="ref59">32</reflink>]) found that the educational level, age, household position, race, and existence of young children have been associated with the probability of a Brazilian woman being economically active. Children's presence has a negative sign for women, but a positive one for men, reinforcing that women often hold the most responsibility for raising children. Female reservation wage is positively correlated with the per capita household income. Thus, mothers participate more actively in the labor market when their wages are needed to supplement the household income.</p> <p>Queiroz and Aragón ([<reflink idref="bib75" id="ref60">75</reflink>]) observed that marriage, motherhood, and family construction reduce the work supply of Brazilian women. Nevertheless, variables associated with education, being the family head, and access to daycare centers corroborate to increase female participation. In this line, Barbosa and Costa ([<reflink idref="bib5" id="ref61">5</reflink>]) estimated that the presence of children aged 0 to 5 years old is an inhibiting factor for female labor force participation. Access to daycare centers increases at least by 13% the probability of a mother with a 0 to 5-year-old child entering the labor market.</p> <hd id="AN0180801952-6">3. Institutional background</hd> <p></p> <hd id="AN0180801952-7">3.1. Proinfância description</hd> <p>The largest project carried out in Brazil to expand early childhood education in public facilities is the Proinfância, instituted in 2007 by Resolution No. 6, of April 24 (FNDE [<reflink idref="bib42" id="ref62">42</reflink>]). The program focuses on building daycare centers and preschools using the federal government's financial support and municipalities' management and accountability of the constructions. Proinfância also aimed to finance the acquisition of furniture and equipment to meet the minimum infrastructure demands required for providing early childhood care.[<reflink idref="bib6" id="ref63">6</reflink>]</p> <p>Figure 1 shows the evolution of signed contracts and works completed in the first ten years of the program. Proinfância started in 2007, but its effect on the care rates in early childhood education has depended on the conclusion of the buildings. There has been a period between the contract execution and the effective operation of the new facilities. The average time for delivering the facilities was 30 months.</p> <p>Graph: Figure 1. Number of signed contracts and concluded building constructions per year in Proinfância. Note: The height of the white bars represents the number of works signed and financed by Proinfância each year from 2008 to 2017. The height of the gray colored bars indicates the number of works concluded and delivered by Proinfância. Source: Authors' elaboration with data from FNDE/MEC.</p> <p>The program design has undergone several changes to mitigate its implementation problems. The first phase started in 2007 and lasted until mid-2012. During this period, the municipalities were responsible for bidding, contracting, executing, and inspecting the construction works. However, there were many technical difficulties due to delays in the bidding process and during construction (CGU [<reflink idref="bib31" id="ref64">31</reflink>]).[<reflink idref="bib7" id="ref65">7</reflink>] By 2011, only 282 projects out of 4217 signed contracts were delivered.</p> <p>Due to its low performance, the program has undergone some modifications. Its second phase (2013–2015) began when the federal government centralized the bidding process nationwide in order to reduce the time taken to complete the projects. Businesses had to comply with standard design and construction system methodologies to reduce costs and speed up the execution process. Yet, one construction firm became responsible for hundreds of works in many states. However, this company had no financial capacity to accomplish all the projects and was forced into bankruptcy, leading to the cancelation of many projects. Other deals were renegotiated and reformulated, returning to the conventional method. Many local administrations entered into judicial claims to finish the works using their own resources (Gaucha-ZH [<reflink idref="bib47" id="ref66">47</reflink>]). Between 2012 and 2015, there was the conclusion of numerous works initiated in phase one (CGU [<reflink idref="bib31" id="ref67">31</reflink>]; Mondo [<reflink idref="bib70" id="ref68">70</reflink>]).</p> <p>As the objectives were not once more achieved, the program returned to its former system in 2015 (the third phase), in which the conventional methodology and bidding procedures were under the responsibility of the municipalities. It was also during this period that new types of designs were created in addition to the existing ones.[<reflink idref="bib8" id="ref69">8</reflink>]</p> <p>We see in Figure 2 the geographical distribution of municipalities that had completed and delivered a Proinfância construction work in the national territory from 2007 to 2017. In the first five years of phase 1, only 791 jurisdictions had finished the construction works (Figure 2(a)). Even though it covers a small share of the 5570 Brazilian municipalities, the participation was well distributed regionally, except for the low one in the Central-West region. Over the next five years, between 2013 and 2017, the number of municipalities in the program was much higher, reaching approximately 2000 and covering all regions in the national territory (Figure 2(b)).</p> <p>Graph: Figure 2. Municipalities that constructed daycare or preschool buildings funded by Proinfância. Note: Colored unities represent municipalities with a school facility financed and delivered by Proinfância during the period 2008 to 2012 (a), 2013 to 2017 (b), and the whole period from 2007 to 2017 (c). Source: Authors' elaboration with data from FNDE/MEC and IBGE.</p> <p>The problems regarding the implementation of Proinfância shed some light on the difficulties for the federal government to coordinate the expansion of early childhood education in Brazil. Firstly, there is the issue of establishing a single standard for the nationwide projects of daycare and preschool centers. Likewise, the bidding process appears, secondly, as an obstacle, as well as monitoring the construction in conjunction with the schedule for releasing funds, all of which led to the postponement or even cancelation of the construction works (CGU [<reflink idref="bib31" id="ref70">31</reflink>]; M. D. C. M. T. Cruz [<reflink idref="bib34" id="ref71">34</reflink>]; Mondo [<reflink idref="bib70" id="ref72">70</reflink>]; Rezende [<reflink idref="bib76" id="ref73">76</reflink>]).</p> <p>Finally, completing the construction is the first step towards the expansion of early childhood education in a municipality. After that, employees and service providers have to be hired, and school meals and other inputs are required to operate the facilities.[<reflink idref="bib9" id="ref74">9</reflink>] The federal government created lines to finance the service in municipal daycare and preschool centers, but the accountability relies on the monitoring by local administrators. Hence, with no national standard indicator, the quality of care (of tutors' qualification, for example) for infants and toddlers can be very heterogeneous (Campos [<reflink idref="bib25" id="ref75">25</reflink>]). Despite these weaknesses, Proinfância delivered 3876 buildings between 2007 and 2017.[<reflink idref="bib10" id="ref76">10</reflink>]</p> <hd id="AN0180801952-8">3.2. Evolution of infants and toddlers' care in Brazil</hd> <p>Brazil has been substantially improving children's access to public education since the 1990s. The changes brought about by the 1988 Constitution triggered a swift in the coverage of elementary education for all children aged 7 to 14. However, not only was attendance in infant education relegated to the background, especially for infants aged 0 to 3 years old, but also the quality of provided services. For instance, attendance of children aged 4 to 5 years old in preschools has improved sharply since 2009, time when it became mandatory (BRASIL [<reflink idref="bib19" id="ref77">19</reflink>]), but that of children aged 0 to 3 years old in daycare centers is still increasing less than the required goals defined in law by the government (BRASIL [<reflink idref="bib22" id="ref78">22</reflink>]; INEP [<reflink idref="bib62" id="ref79">62</reflink>]).</p> <p>The Brazilian Federal Constitution of 1988 established education as a right for all children. It also set a decentralized system for the distribution of competencies, with the Union, the States, the Federal District, and the municipalities organizing their educational systems collaboratively (BRASIL [<reflink idref="bib15" id="ref80">15</reflink>]). Only when the Constitutional Amendment No. 14 of 1996 was enacted were the attributions clearly defined for each level of government in formulating and implementing educational policies. The municipalities were responsible for acting primarily in early childhood education, elementary and middle school, while the states and the Federal District were supposed to focus on middle and high schools.</p> <p>The federal government had to coordinate the national education system through funding and providing technical support to the states, the Federal District, and the municipalities (BRASIL [<reflink idref="bib16" id="ref81">16</reflink>]). Since then, several laws and measures have been taken to guarantee basic education financing to the local jurisdictions. In 1996, the National Fund for the Maintenance and Development of Elementary Education and Promotion of Teaching Education (FUNDEF, acronym in Portuguese)[<reflink idref="bib11" id="ref82">11</reflink>] passed in Congress and started distributing resources to states and municipalities based on the number of enrollments in public elementary schools.</p> <p>In addition, Article 212 of the Constitution determined that 25% of state and municipal revenues must be allocated to education, and FUNDEF established that at least 15% of it should be directed to elementary and middle education. Thus, there were no minimum requirements for spending on early childhood education. Despite being declared the first stage of basic education by the Law of Directives and Standards for National Education (Law No. 9394 of 1996), the development of this education stage was conditioned to the budget availability in the municipalities (G. Cruz and Rocha [<reflink idref="bib36" id="ref83">36</reflink>]; Gremaud, Fernandes, and Ulyssea [<reflink idref="bib50" id="ref84">50</reflink>]).</p> <p>At the beginning of the 2000s, the country had expanded elementary education to nearly all children.[<reflink idref="bib12" id="ref85">12</reflink>] Meanwhile, early childhood education gained more space in the Brazilian education scenario. It became part of several plans, programs, and actions under the objectives established by the National Education Plan (PNE, acronym in Portuguese) (BRASIL [<reflink idref="bib17" id="ref86">17</reflink>]),[<reflink idref="bib13" id="ref87">13</reflink>] which defined guidelines for managing and financing education, goals for each education stage and for training and valuing education professionals within ten years.</p> <p>As to early childhood education, the main goal was to reach 30% of the children aged 0 to 3 years old attending daycare centers and 60% of those aged 4 to 6 years old in preschools within five years.[<reflink idref="bib14" id="ref88">14</reflink>] By 2010, the goal was to create vacant spots for 50% of the children aged up to 3 years old and 80% for children from 4 to 5 years old.[<reflink idref="bib15" id="ref89">15</reflink>] In addition, it also established requirements for minimum infrastructure standards and professional qualifications of teachers (BRASIL [<reflink idref="bib17" id="ref90">17</reflink>]).</p> <p>The Brazilian Fund for Maintenance and Development of Basic Education and Promotion of Teaching Education (FUNDEB, acronym in Portuguese),[<reflink idref="bib16" id="ref91">16</reflink>] which replaced FUNDEF in 2007, filled the gap in early childhood education financing. This new fund considered all enrollments in primary education, including infant education, and required that state and municipal jurisdictions applied from 15 to 20% of their revenues in this education stage. The federal government would then transfer resourcers to the jurisdictions that did not reach the minimum value per student-year, which is defined nationally (BRASIL [<reflink idref="bib18" id="ref92">18</reflink>]).</p> <p>All the developments in legislation and growing importance given to early childhood education were not able to guarantee the accomplishment of the established PNE 2001 goals though. Then, a new PNE was instituted by Federal Law No. 13,005 (BRASIL [<reflink idref="bib22" id="ref93">22</reflink>]), updating the goal of serving 50% of the population from 0 to 3 years old by the end of its term in 2024. Furthermore, the new PNE intended to universalize preschool coverage within two years.</p> <p>Proinfância was launched to fill a lack of federal policies to promote the expansion of early education coverage.[<reflink idref="bib17" id="ref94">17</reflink>] The federal government helped coordinate, finance, and define parameters regarding the quality of the daycare and preschool building constructions, as well as the provided service (MEC [<reflink idref="bib69" id="ref95">69</reflink>]).</p> <p>We show in Figure 3 the increase in enrollment in municipal daycare and preschool centers in municipalities that participated and did not participate in Proinfância. For children aged 0 to 3 years old, the number of enrollments in daycare centers increased in both groups Figure 3(a), but the <emph>difference</emph> was more significant over time. Conversely, when we look at enrollments in preschool centers in Figure 3(b), there is a decrease in the difference between the two groups until 2012. Then, the number of enrollments in municipalities participating in the program started to increase, while the enrollments in non-participating jurisdictions remained flat.</p> <p>Graph: Figure 3. Evolution of enrollments in municipal institutions of early childhood education. Note: Graph (a) shows the evolution of enrollments in municipal daycare centers (a), and Graph (b) presents this trend in municipal preschool centers (b) over the period from 2007 to 2021. For each year, the line with circles indicates the total number of enrollments in the Brazilian municipalities that received a Proinfância building. The line with diamonds represents the total number of enrollments in the jurisdictions that did not receive a Proinfância construction work. Dash vertical lines indicate the years 2008–one year after the program was launched; 2012–when the number of concluded works ramped up (Figure 1); and 2017–when we expected to observe all the program effects. Source: Authors' elaboration using data from School Census/MEC.</p> <hd id="AN0180801952-9">3.3. Cognitive achievement of Brazilian children</hd> <p>Brazilian students are known to be in the worst positions of international rankings evaluating cognitive development, such as the PISA (Carnoy et al. [<reflink idref="bib27" id="ref96">27</reflink>]; Gomes, Hirata, and e Oliveira [<reflink idref="bib48" id="ref97">48</reflink>]). Historically, a large share of the population has had a low educational level–or even no education at all. Indeed, right after the re-introduction of democracy in 1990, 20% of the people aged 14 or older could not read–this rate dropped to 6.6% in 2019 (Ferraro [<reflink idref="bib41" id="ref98">41</reflink>]).</p> <p>Since the 1990s, the Brazilian federal government has developed a national system for monitoring and evaluating children's cognitive development–the National Basic Education Assessment System (SAEB, acronym in Portuguese). It was created in 1995 with national exams using a standard scale that follows Item Response Theory (IRT), making it possible to monitor the progress of scores over the years and to compare the results of schools or municipalities. The most important tool of the SAEB is 'Prova Brasil'–a national test applied every two years for all students from the fifth and ninth grades in all public elementary schools, who correspond to children aged 9 to 10 and 13 to 14 years old, respectively.[<reflink idref="bib18" id="ref99">18</reflink>]</p> <p>We show in Table 1 the expected age range of infants and toddlers that attended the Proinfância buildings delivered between 2011 and 2016. For each year of conclusion of a Proinfância building (I), we show the age range of children (II) who should attend the new daycare (A) and preschool (B) center. Then, we present the age range of these cohorts in 2017 (III), 2019 (IV), and 2021 (V), periods when Prova Brasil was applied to every student in the fifth grade (around ten years old). The cells corresponding to the cohorts that should be evaluated in these years are written in bold. We expected that preschools constructed from 2011 on would have had some impact on Prova Brasil scores since 2017, and daycare centers delivered in the period would have had some effect on Prova Brasil applied from 2019 on.</p> <p>Table 1. Age cohorts of infants and toddlers attending early education at Proinfância buildings and applying Prova Brasil (bold).</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Year of</td><td>Age cohort in</td><td>Age cohort in</td></tr><tr><td>conclusion (I)</td><td>inauguration (II)</td><td>2017 (III)</td><td>2019 (IV)</td><td>2021(V)</td></tr></thead><tbody><tr><td /><td>(A) Daycare centers</td></tr><tr><td>2011</td><td>0–3</td><td>6–9</td><td><bold>8–11</bold></td><td><bold>10–13</bold></td></tr><tr><td>2012</td><td>0–3</td><td>5–8</td><td><bold>7–10</bold></td><td><bold>9–12</bold></td></tr><tr><td>2013</td><td>0–3</td><td>4–7</td><td>6–9</td><td><bold>8–11</bold></td></tr><tr><td>2014</td><td>0–3</td><td>3–6</td><td>5–8</td><td><bold>7–10</bold></td></tr><tr><td>2015</td><td>0–3</td><td>2–5</td><td>4–7</td><td>6–9</td></tr><tr><td>2016</td><td>0–3</td><td>1–4</td><td>3–6</td><td>5–8</td></tr><tr><td /><td>(B) Preschool centers</td></tr><tr><td>2011</td><td>4–5</td><td><bold>10–11</bold></td><td>12–13</td><td>14-15</td></tr><tr><td>2012</td><td>4–5</td><td><bold>9–10</bold></td><td>11–12</td><td>13–14</td></tr><tr><td>2013</td><td>4–5</td><td>8–9</td><td><bold>10–11</bold></td><td>12–13</td></tr><tr><td>2014</td><td>4–5</td><td>7–8</td><td><bold>9–10</bold></td><td>11–12</td></tr><tr><td>2015</td><td>4–5</td><td>6–7</td><td>8–9</td><td><bold>10–11</bold></td></tr><tr><td>2016</td><td>4–5</td><td>5–6</td><td>7–8</td><td><bold>9–10</bold></td></tr></tbody></table> </ephtml> </p> <p>1 Note: For each year of conclusion of a Proinfância building (I), we show the presumable age cohorts of children attending (II) the new available daycare (A) and preschool (B) center. Then, we show the age range of these cohorts in 2017 (III), 2019 (IV), and 2021 (V), when Prova Brasil was applied to every student in the fifth grade (around ten years old). The cells corresponding to the cohorts that should be evaluated in these years are written in bold. Source: Authors' elaboration.</p> <p>Figure 4 presents the evolution of the average scores of public schools in Portuguese and Mathematics in Prova Brasil, which was taken by fifth-grade students, considering municipalities that participated or not in the program. The average score in Portuguese (Figure 4(a)) increased over the period until 2017, then it stagnated in 2019 and dropped in 2021–presumably due to the effects of the COVID-19 pandemic.[<reflink idref="bib19" id="ref100">19</reflink>] The average score in Mathematics (Figure 4(b)) increased until 2019, and then it declined in 2021. For both subjects, there has been no visual change over time in the difference in performances between the municipalities that participated or not at Proinfância.</p> <p>Graph: Figure 4. Evolution of public schools' scores in Prova Brasil. Note: Graph (a) shows the evolution of scores in Portuguese and graph (b) presents the evolution of scores in Mathematics over the period 2007–2021, considering the results for fifth-grade students from public elementary schools. For each year, the line with circles indicates the average scores in the Brazilian municipalities that received a Proinfância building. The line with diamonds represents the average scores in the jurisdictions that did not receive a Proinfância construction work. Dash vertical lines indicate the years 2008–one year after Proinfância was launched; 2012–when the number of concluded works ramped up (Figure 1); and 2017–when we expected to observe all the program effects. Source: Authors' elaboration using data from Prova Brasil/MEC.</p> <hd id="AN0180801952-10">3.4. Brazilian female labor force participation</hd> <p>In Brazil, the presence of women in the labor market has increased since the 1970s. In the 1980s, the living conditions of families worsened due to economic stagnation and hyperinflation, which encouraged the participation of women in paid work, given that their income became fundamental in complementing family income. As a result, in the last three decades, there has been substantial growth in the number of employed women (Hoffmann and Leone [<reflink idref="bib56" id="ref101">56</reflink>]).</p> <p>Nonetheless, female workers have been more present in underpaid activities, such as administrative and domestic jobs, especially in the informal market, and have often underused their labor force by working fewer hours than they could (Araújo and Lombardi [<reflink idref="bib3" id="ref102">3</reflink>]; IBGE [<reflink idref="bib60" id="ref103">60</reflink>]). As a result, the average wage of women was 76% lower than the average remuneration of men in 2012. Moreover, this difference in income increases with age, being 88% of male workers' wages for women between 25 and 30 years old and 71% for women between 40 and 49 years old (IBGE [<reflink idref="bib59" id="ref104">59</reflink>]), suggesting a possible penalty due to children's birth.</p> <p>The Brazilian labor market is segmented into formal, in which the workers are granted all the rights of the labor legislation, and informal, without any kind of legal guarantee.[<reflink idref="bib20" id="ref105">20</reflink>] Nearly 45% of Brazilian workers are in informal jobs, and this rate is even higher for women. Roughly 30% of these informal jobs are considered precarious (IBGE [<reflink idref="bib58" id="ref106">58</reflink>]). Therefore, the demand for infant care in public institutions is potentially higher for vulnerable women who cannot afford a particular daycare service.[<reflink idref="bib21" id="ref107">21</reflink>]</p> <p>In this context of informal jobs and children's care, families could replace private/informal care with the public one when available, which would result in minor changes on female employment (Blau and Currie [<reflink idref="bib14" id="ref108">14</reflink>]; Havnes and Mogstad [<reflink idref="bib51" id="ref109">51</reflink>]). Still, access to public infant care could impact the quality of the job that mothers might accept. Indeed, the provision of public and stable childcare might increase the possibility of making long-run agreements in the job market, which can lead to an increase in the rate of female workers in the formal labor market. Even mothers that have been, at least part-time, working in the informal market would seek to change to a formal job if they had access to public daycare and preschool centers. Formal jobs represent good-quality, predictable, and stable attainments, which indicate an improvement in terms of income and well-being compared to informal jobs.</p> <p>The rate of informal jobs is probably lower in many municipalities that participated in Proinfância, as formal attachments are concentrated in big cities.[<reflink idref="bib22" id="ref110">22</reflink>] Even so, our analysis is based on the formal market, as there are no credible data to evaluate the informal market size in every municipality. Moreover, the transition to the formal market is a signal of income stability for women, which is precisely the dimension of the program we want to capture. The higher rate of men in formal jobs explains to some extent the gender wage differentials in Brazil (IBGE [<reflink idref="bib58" id="ref111">58</reflink>]). Thus, reducing the informality rate for women should be a target of public policies aimed at shortening gender inequalities.[<reflink idref="bib23" id="ref112">23</reflink>]</p> <p>Figure 5(a) shows the evolution of the proportion of female workers in the formal occupations, comparing the municipalities that participated in Proinfância with jurisdictions that did not. An increase in the female participation rate in the labor market can be observed between 2007 and 2015, then it started to fall in 2016, when Brazil went through an economic crisis. There was even a larger drop in women's participation in 2020, showing that the COVID-19 pandemic had a more significant impact on women. However, there is no different visual trend in the municipalities participating in Proinfância, and there is even a reduction in the difference between participating and non-participating groups over time.</p> <p>Graph: Figure 5. Proportion of formal jobs filled by women. Note: Graph (a) shows the evolution in the proportion of formal jobs filled by women in the period 2007–2021, whereas Graph (b) presents the proportion of female workers in formal employment–considering low-educated workers who studied until high school. For each year, the line with circles indicates the overall proportion of women considering all the Brazilian municipalities that received a Proinfância building. The line with diamonds represents the proportion in the jurisdictions that did not receive a Proinfância construction work. Dash vertical lines indicate the years 2008–one year after Proinfância was launched; 2012–when the number of concluded works ramped up (Figure 1); and 2017–when we expected to observe all the program effects. Source: Authors' elaboration using data from RAIS/Ministry of Labor and Employment.</p> <p>As Proinfância intended to reach mainly the poorest families that depend on public daycare, we analyzed the participation rate among workers with medium or low educational level (formal schooling up to high school) in Figure 5(b). We see the same trend of the increase until 2016, but, considering the low-educated workers, the proportion of women started to fall even before the pandemic (in 2017) and then decreased even more in 2020, illustrating that the low-educated women were more affected than the male workers by the economic crises and the pandemic. For this group, the difference between participating and non-participating municipalities increased after 2016 (from 0.4 p.p. in 2012 to 1.3 p.p. in 2021), suggesting that Proinfância may have helped to preserve the jobs of low-educated women.</p> <hd id="AN0180801952-11">4. Data and methodology</hd> <p></p> <hd id="AN0180801952-12">4.1. Data</hd> <p>We use variables from different public databases to assess the impact of Proinfância on childhood care coverage, cognitive skills, and female labor force participation. All variables were collected for the years 2007–2021 and collapsed at the municipality level, such as the attendance rate in municipal daycare and preschool centers, the average scores of public schools in Prova Brasil, and the rate of formal jobs filled by women.</p> <p>We obtain data on all the contracts signed by Proinfância from the Brazilian Fund for Education Development (FNDE, acronym in Portuguese), an administrative organization under the Ministry of Education (MEC) responsible for implementing the basic education policies.[<reflink idref="bib24" id="ref113">24</reflink>] The FNDE database provides information about the stage (the conclusion percentage) and status of the construction works, including if they have been concluded, are in progress, or were canceled. There is also information regarding the last inspection/update date for each building. After data collection, we created a dummy indicating if the municipality had finished a Proinfância building between 2008 and 2017.</p> <p>The immediate objective of Proinfância was to increase care coverage in early childhood education. Thus, the primary outcome is the coverage of early childhood education separated by age ranges–0 to 3 and 4 to 5 years old. We calculate these percentages by dividing the total number of enrollments by the population in the age range in the municipality. The number of enrolled children per age group is available in the School Census, which is annually conducted by the Ministry of Education in all public schools. We consider in the main specification the enrollments in institutions administered by the municipalities, which are eligible for Proinfância.[<reflink idref="bib25" id="ref114">25</reflink>]</p> <p>We collect information on the local population stratified by age (0–3 and 4–5 years old) from the Brazilian Institute of Geography and Statistics (IBGE, acronym in Portuguese), which released the 2007 Population Counting and 2010 Census. For the other years, we use the estimates provided by the Ministry of Health.[<reflink idref="bib26" id="ref115">26</reflink>] We also consider the information regarding the female population aged 16 to 49 from DATASUS, as well as data on the number of births for each municipality and year.</p> <p>We obtain data on the number of women in formal jobs from the Annual List of Social Information (RAIS, acronym in Portuguese), a nationwide administrative register annually conducted by the Ministry of Labor and Employment. All private sector establishments must send information about the number of formal workers, such as age and gender.[<reflink idref="bib27" id="ref116">27</reflink>] We also collect data on the average wage and age of formal workers in each municipality from RAIS.</p> <hd id="AN0180801952-13">4.2. Difference-in-differences estimation</hd> <p>As Proinfância ran uninterruptedly throughout the analysis period, we first delimit the treatment and control groups. We consider the 2553 municipalities with at least one school facility financed and delivered by Proinfância between 2008 and 2017 as the treatment group. The control group includes the other 3012 municipalities that did not have construction works completed during such period, including those in which all the constructions were canceled or not concluded in this period, those that only completed projects after 2017, and those that never participated in the program.</p> <p>Identification of the Proinfância impact relies on the difference in trends between the municipalities that had or had not concluded a building financed by the program. The method named <emph>Difference-in-differences</emph> allows the elimination of any existing differences between the groups that may be associated with variables that are constant over time and influence both the chance of participation and outcomes. This method has long been applied in many fields and has become more prevalent in economics since the 1990s (Angrist and Krueger [<reflink idref="bib2" id="ref117">2</reflink>]; Imbens and Wooldridge [<reflink idref="bib61" id="ref118">61</reflink>]; Lechner [<reflink idref="bib65" id="ref119">65</reflink>]).</p> <p>We define the variable Proinfância = 1 when the municipality was treated and Proinfância = 0, otherwise. Then, following Imbens and Wooldridge ([<reflink idref="bib61" id="ref120">61</reflink>]), the Difference-in-differences estimator is the 'double difference of means' of the outcome variable Y:</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>DD</mi><mo>=</mo><mi>E</mi><mo stretchy="false">(</mo><msup><mi>Y</mi><mrow><mi>after</mi></mrow></msup><mo>−</mo><msup><mi>Y</mi><mrow><mi>before</mi></mrow></msup><mo fence="false" stretchy="false">|</mo><mi>Proinf</mi><mrow><mover><mi>a</mi><mo stretchy="false">^</mo></mover></mrow><mi>ncia</mi><mo>=</mo><mn>1</mn><mo stretchy="false">)</mo><mo>−</mo><mi>E</mi><mo stretchy="false">(</mo><msup><mi>Y</mi><mrow><mi>after</mi></mrow></msup><mo>−</mo><msup><mi>Y</mi><mrow><mi>before</mi></mrow></msup><mo fence="false" stretchy="false">|</mo><mi>Proinf</mi><mrow><mover><mi>a</mi><mo stretchy="false">^</mo></mover></mrow><mi>ncia</mi><mo>=</mo><mn>0</mn><mo stretchy="false">)</mo></math> </ephtml> , which is the same of comparing the effects of treated and untreated groups before and after the treatment.</p> <p>Assuming that potential effects follow a linear specification, this impact may be estimated as follows:</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>Y</mi><mrow><mi>it</mi></mrow></msub><mo>=</mo><msub><mi>β</mi><mn>0</mn></msub><mo>+</mo><msub><mi>β</mi><mn>1</mn></msub><mi>Proinf</mi><mrow><mover><mi>a</mi><mo stretchy="false">^</mo></mover></mrow><mi>nci</mi><msub><mi>a</mi><mrow><mi>i</mi></mrow></msub><mo>+</mo><msub><mi>β</mi><mn>2</mn></msub><mi>yea</mi><msub><mi>r</mi><mrow><mi>t</mi></mrow></msub><mo>+</mo><msub><mi>β</mi><mn>3</mn></msub><mi>Proinf</mi><mrow><mover><mi>a</mi><mo stretchy="false">^</mo></mover></mrow><mi>nci</mi><msub><mi>a</mi><mrow><mi>i</mi></mrow></msub><mspace width="thinmathspace" /><mo>∗</mo><mspace width="thinmathspace" /><mi>yea</mi><msub><mi>r</mi><mrow><mi>t</mi></mrow></msub><mo>+</mo><msubsup><mi>β</mi><mn>4</mn><mo>′</mo></msubsup><msub><mi>X</mi><mrow><mi>it</mi></mrow></msub><mo>+</mo><msub><mi>ϵ</mi><mrow><mi>it</mi></mrow></msub></math> </ephtml> (<reflink idref="bib1" id="ref121">1</reflink>)</p> <p>Where</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>Y</mi><mrow><mi>it</mi></mrow></msub></math> </ephtml> is one of the following outcomes in period t, which we calculate as the average for each municipality i: coverage of municipal daycare and preschool centers, public schools' scores in Portuguese and Mathematics in Prova Brasil, and the share of formal jobs occupied by women.</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>yea</mi><msub><mi>r</mi><mrow><mi>t</mi></mrow></msub></math> </ephtml> is set to zero if the year t is 2007 and 1 if data is related to an <emph>ex-post</emph> year. We can show that if the conditional expectation follows a linear specification as in Equation (<reflink idref="bib1" id="ref122">1</reflink>),</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>β</mi><mn>3</mn></msub></math> </ephtml> represents the impact of interest.[<reflink idref="bib28" id="ref123">28</reflink>]</p> <p>For each outcome, we estimate one regression for each <emph>ex-post</emph> year between 2008 and 2021. In other words, we consider <emph>ex-ante</emph> data from 2007, before the beginning of the program, and <emph>ex-post</emph> data from 2008 and the years afterward until 2021. If we identify the effects of Proinfância correctly, we might find significant impacts after 2012 only, when the bunch of facilities started to be delivered. Therefore, the lack of evidence before 2012 and significance after this year could suggest that we are estimating the causal impact of the program in the meaning of Granger ([<reflink idref="bib49" id="ref124">49</reflink>]).</p> <p>Furthermore, we control for variables potentially correlated with the demand for infant education enrollments (matrix</p> <p>Graph</p> <p> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>X</mi><mrow><mi>it</mi></mrow></msub></math> </ephtml> in Equation (<reflink idref="bib1" id="ref125">1</reflink>)). We want to ensure that we identify the causal effects of Proinfância correctly, not being associated with the population of young children and women and the fertility changes over time. Then, we control for the local age structure by adding information about the population size of young children aged 0 to 3 and 4 to 5 years old, as well as the population of women at a fertile age (16 to 49 years) and the number of births during the year. We also control for job market characteristics: the average age and income, as a multiple of the minimum wage, of formal workers in each municipality.</p> <p>We conduct several tests to check the robustness of our results. Firstly, we show graphs with the trends of the outcomes and covariates of treated and untreated municipalities over the years. Secondly, we conduct regressions for all the years from 2008 to 2021 to guarantee sufficient time to the effect span, especially on the scores in Prova Brasil, which is taken by students aged around ten years old.</p> <p>Appendix B provides the estimates using the municipalities that contracted but did not conclude a Proinfância building as an alternative (placebo) treatment. We also conduct t-tests on the difference of means before and after the program for all the variables. Additional regressions estimate the potential Proinfância spillovers on the private system of childhood education and the proportion of the female population employed in formal jobs, a further indicator of women's engagement in the labor market. Finally, following J. J. Heckman, Ichimura, and Todd ([<reflink idref="bib53" id="ref126">53</reflink>]), we implement in Appendix C the Difference-in-differences method with the propensity score matching based on <emph>ex-ante</emph> variables.</p> <hd id="AN0180801952-14">4.3. Validation and descriptive statistics</hd> <p>The Difference-in-differences method has the merit of eliminating any bias due to characteristics between the treatment and control groups that remain fixed over time, including unobservable variables correlated with participation in the program. Changes in the trends of outcome variables for the treated units after the beginning of the program may signal a causal impact. Nevertheless, threats to identification may arise due to bias from other omitted variables that are not constant. Hence, we investigate the trends of treated and control groups through time to show if the outcome variables differ over the years and to certify that the covariates evolve smoothly–a signal that omitted variables should do as well.</p> <p>Firstly, we present in Table 2 the average, standard deviation, and quartiles of the distributions of the outcome variables before and after the treatment (2007 and 2019).[<reflink idref="bib29" id="ref127">29</reflink>] Considering all Brazilian municipalities, the mean coverage of daycare in municipal institutions increased by almost 200%, increasing from 11.9% to 29.2% of children aged up to three years old (Column 1). Moreover, the rise was proportionally higher for municipalities with low attendance in 2007, as the coverage for percentile 25 increased from only 0.5 to 16.4% in 2019, while the one for percentile 75 doubled from 18 to 39.2%.</p> <p>Table 2. Descriptive statistics of outcome variables.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Early childhood care (%)</td><td>Scores–Prova Brasil</td><td>Proportion of jobs filled by women</td></tr><tr><td /><td>Daycare</td><td>Preschool</td><td>Portuguese</td><td>Mathematics</td><td>All</td><td>Low educational level</td></tr><tr><td /><td>(1)</td><td>(2)</td><td>(3)</td><td>(4)</td><td>(5)</td><td>(6)</td></tr><tr><td>Year</td><td>2007</td><td>2019</td><td>2007</td><td>2019</td><td>2007</td><td>2019</td><td>2007</td><td>2019</td><td>2007</td><td>2019</td><td>2007</td><td>2019</td></tr></thead><tbody><tr><td>Average</td><td char=".">11.9</td><td char=".">29.2</td><td char=".">70.6</td><td>83</td><td char=".">170.4</td><td char=".">209.4</td><td char=".">189.1</td><td char=".">223.7</td><td char=".">44.7</td><td char=".">45.9</td><td char=".">41.3</td><td char=".">39.6</td></tr><tr><td>S.d.</td><td char=".">12.4</td><td char=".">18.2</td><td char=".">32.1</td><td char=".">22.9</td><td char=".">16.7</td><td char=".">21.2</td><td char=".">19.3</td><td char=".">23.2</td><td char=".">12.8</td><td char=".">9.3</td><td char=".">13.3</td><td char=".">9.3</td></tr><tr><td /><td>Percentiles</td></tr><tr><td>25</td><td char=".">0.5</td><td char=".">16.4</td><td char=".">47.4</td><td char=".">69.1</td><td char=".">157.5</td><td char=".">193.6</td><td char=".">174.2</td><td char=".">206.1</td><td char=".">36.3</td><td char=".">40.5</td><td char=".">32.1</td><td char=".">33.6</td></tr><tr><td>50</td><td char=".">9.1</td><td char=".">26.9</td><td char=".">69.1</td><td char=".">80.7</td><td char=".">169.9</td><td char=".">211.5</td><td char=".">187.9</td><td char=".">224.4</td><td char=".">43.2</td><td char=".">45.8</td><td char=".">39.4</td><td char=".">39.5</td></tr><tr><td>75</td><td>18</td><td char=".">39.2</td><td char=".">91.3</td><td char=".">93.6</td><td char=".">182.6</td><td char=".">225.2</td><td>202</td><td char=".">240.5</td><td char=".">52.9</td><td char=".">51.8</td><td char=".">49.6</td><td char=".">45.2</td></tr></tbody></table> </ephtml> </p> <p>2 Note: Descriptive statistics for the <emph>ex-ante</emph> (2007) and <emph>ex-post</emph> (2019) data of outcome variables aggregated at the municipality level: (i) coverage of early childhood education–considering the number of enrollments in municipal daycare (column 1) and preschool centers (column 2) for the population between 0–3 and 4–5 years old, respectively; (ii) scores of public schools for Portuguese (column 3) and Mathematics (column 4) in Prova Brasil, and iii) proportion of formal jobs filled by women, considering all the workers (column 5) and the workers with formal educational level up to high school (column 6). Source: Authors' elaboration using data from School Census and Prova Brasil/Ministry of Education, RAIS/Ministry of Labor and Employment, and IBGE/Ministry of Economy.</p> <p>Preschool attendance in municipal institutions improved roughly 20% (Column 2), reaching 83% of children aged between 4 and 5 years old. Once more, the municipalities with low attendance in 2007 presented a more considerable improvement in 2019, as the coverage increased almost 50% for the percentile 25 and only 2.5% for the percentile 75.</p> <p>There was also an increase of nearly two standard deviations in the average scores of Prova Brasil in Portuguese (Column 3) and Mathematics (Column 4). Finally, the proportion of women in formal jobs remained unchanged in the period (Column 5), and there was even a drop in the average ratio when considering workers with educational level up to high school (Column 6). While the municipalities with low participation of women in 2007 (percentile 25) experienced an increase, it declined in jurisdictions with higher levels of female employment (percentile 75).</p> <p>We now turn to the trajectories of outcome and control variables from 2007 to 2021 in Figure 6, in which we present the average values for the treated (diamond lines) and control (circle lines) units. We see a continuous increase in the daycare center coverage, considering all the networks (Figure 6(a)) and in municipal centers only (Figure 6(b)), with a continuous rise in the difference between the two groups after 2012.</p> <p>Graph: Figure 6. Evolution of the outcome and control variables over the period from 2007 to 2021.. Note: The graphs present the mean evolution of outcome and control variables over 2007–2021, considering municipalities that concluded a Proinfância construction (circle lines) or that did not (diamond lines). Dash vertical lines indicate the years 2008–one year after Proinfância was launched; 2012–when the number of concluded works ramped up (Figure 1); and 2017–when we expect to observe all the program effects. We display in the graphs the rounded values for the years 2008, 2012, 2017, 2019, and 2021. Source: Authors' elaboration using data from MEC, IBGE, DATASUS, RAIS.</p> <p>Visual evidence for the impacts of Proinfância on the overall preschool coverage is more robust (Figure 6(c)), as it was smaller in the treated municipalities before the program and has improved since 2017. Furthermore, when we look at the attendance rate in the municipal preschool centers (Figure 6(d)),, there was an increase proportionally larger for municipalities participating in the program. This result suggests that Proinfância benefited the regions with the lowest levels of preschool coverage at the beginning of the program.[<reflink idref="bib30" id="ref128">30</reflink>]</p> <p>The coverage of private daycare and preschool centers has remained the same between 2007 and 2021 (Figures 6(e,f)), without any evidence that families replaced private caregiving with public one when available. Instead, there was a drastic change in the trend only in 2020 and 2021, arguably caused by the COVID-19 pandemic and the lockdowns, which affected hard childhood education institutions and even more private ones.</p> <p>We also show in Figures 6(g–l) that the control variables–female population in reproductive age, children population, total of births, and workers' average wages and ages–evolved smoothly throughout the period from 2007 to 2020. Moreover, demographic variables remained stable in 2021, while we see some changes in the labor market covariates in such year marked by the worldwide COVID-19 outbreak. Overall, there are no perceptible changes in the average distribution of covariates over the period that could be accounted for Proinfância.</p> <p>Combined with Figure 3, the visual evidence suggests that the attendance in early childhood education rose over time in treated municipalities due to Proinfância and the increase in the supply of slots. Therefore, there is no signal that this change was driven by the demand side as the population of young children and other demographic variables remained flat. The discrepancy in the national number and coverage of enrollments in municipal daycare centers had a slight increase. The visual evidence of the the impact on preschool enrollments and coverage is even more robust.</p> <hd id="AN0180801952-15">5. Results</hd> <p></p> <hd id="AN0180801952-16">5.1. Impact of Proinfância on early childhood education coverage</hd> <p>Table 3 presents the estimated impact of Proinfância (Equation (<reflink idref="bib1" id="ref129">1</reflink>)) on the attendance rate in municipal daycare and preschool centers. We estimate a single regression for each <emph>ex-post</emph> year in Columns 1 to 14. Table 3(A) shows that the estimated effect on the coverage of municipal daycare centers becomes significant at 10% in 2011, 5% in 2012, and 1% from 2013 on. We observe the same pattern when we look at the share of enrollments in municipal preschool centers in Table 3(B), which may be a suggestion that we are estimating the Proinfância effects correctly, considering we expect to find more significant impacts after the acceleration in the conclusion of building constructions since 2012.</p> <p>Table 3. The effects of Proinfância on the attendance rate in early childhood education.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td><italic>Ex-post</italic> year:</td><td>2008</td><td>2009</td><td>2010</td><td>2011</td><td>2012</td><td>2013</td><td>2014</td><td>2015</td><td>2016</td><td>2017</td><td>2018</td><td>2019</td><td>2020</td><td>2021</td></tr><tr><td /><td>(1)</td><td>(2)</td><td>(3)</td><td>(4)</td><td>(5)</td><td>(6)</td><td>(7)</td><td>(8)</td><td>(9)</td><td>(10)</td><td>(11)</td><td>(12)</td><td>(13)</td><td>(14)</td></tr></thead><tbody><tr><td /><td>(A) Daycare centers–municipal</td></tr><tr><td>Proinfância *year</td><td>−0.21</td><td char=".">0.025</td><td char=".">0.30</td><td char=".">0.93*</td><td char=".">1.26**</td><td char=".">1.80***</td><td char=".">2.68***</td><td char=".">3.20***</td><td char=".">3.82***</td><td char=".">4.24***</td><td char=".">4.16***</td><td char=".">4.43***</td><td char=".">4.105***</td><td char=".">2.76***</td></tr><tr><td>s.e.</td><td char=".">[0.475]</td><td char=".">[0.490]</td><td char=".">[0.497]</td><td char=".">[0.504]</td><td char=".">[0.515]</td><td char=".">[0.536]</td><td char=".">[0.544]</td><td char=".">[0.546]</td><td char=".">[0.552]</td><td char=".">[0.565]</td><td char=".">[0.569]</td><td char=".">[0.580]</td><td char=".">[0.570]</td><td char=".">[0.581]</td></tr><tr><td>R-squared</td><td char=".">0.03</td><td char=".">0.04</td><td char=".">0.05</td><td char=".">0.06</td><td char=".">0.08</td><td char=".">0.10</td><td char=".">0.13</td><td char=".">0.15</td><td char=".">0.18</td><td char=".">0.22</td><td char=".">0.25</td><td char=".">0.27</td><td char=".">0.28</td><td char=".">0.27</td></tr><tr><td /><td>(B) Preschool centers–municipal</td></tr><tr><td>Proinfância*year</td><td>−0.30</td><td char=".">0.61</td><td char=".">2.22**</td><td char=".">2.82***</td><td char=".">3.25***</td><td char=".">3.46***</td><td char=".">4.30***</td><td char=".">4.74***</td><td char=".">5.20***</td><td char=".">5.08***</td><td char=".">5.27***</td><td char=".">6.68***</td><td char=".">7.54***</td><td char=".">6.27***</td></tr><tr><td>s.e.</td><td char=".">[1.171]</td><td char=".">[1.122]</td><td char=".">[1.065]</td><td char=".">[1.044]</td><td char=".">[1.019]</td><td char=".">[1.016]</td><td char=".">[1.009]</td><td char=".">[1.015]</td><td char=".">[1.013]</td><td char=".">[1.024]</td><td char=".">[1.029]</td><td char=".">[1.045]</td><td char=".">[1.054]</td><td char=".">[1.060]</td></tr><tr><td>R-squared</td><td char=".">0.05</td><td char=".">0.05</td><td char=".">0.05</td><td char=".">0.04</td><td char=".">0.06</td><td char=".">0.06</td><td char=".">0.08</td><td char=".">0.07</td><td char=".">0.09</td><td char=".">0.10</td><td char=".">0.09</td><td char=".">0.08</td><td char=".">0.08</td><td char=".">0.09</td></tr><tr><td>Obs.</td><td>11,124</td><td>11,124</td><td>11,124</td><td>11,124</td><td>11,124</td><td>11,128</td><td>11,128</td><td>11,128</td><td>11,128</td><td>11,128</td><td>11,128</td><td>11,128</td><td>11,128</td><td>11,128</td></tr><tr><td>Controls</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table> </ephtml> </p> <p>3 Note: *Significant at 10% (<emph>p</emph>-value <10%); **Significant at 5% (<emph>p</emph>-value <5%); ***Significant at 1% (<emph>p</emph>-value <1%). This table presents the estimates of Equation (<reflink idref="bib1" id="ref130">1</reflink>) for each <emph>ex-post</emph> year (Columns 1 to 14). Proinfância is a dummy indicating program participation; the variable year was set to 1 for each <emph>ex-post</emph> year and 0 for 2007. We consider the effects on the outcomes: (A) coverage of municipal daycare centers (number of enrollments divided by the population of children aged 0 to 3 years old) and (B) coverage of municipal preschool centers (number of enrollments divided by the population of children aged 4 to 5 years old). The covariates added as control are the female population aged 16 to 49 years old, the infants aged 0 to 3 years old, children aged 4 to 5 years old, the number of births in the municipality, and the averages of formal workers' income and age. Standard errors are in brackets.</p> <p>The magnitude of the impacts also increases over time. Indeed, the rise in daycare centers' coverage reached 4.43 percentage points in 2019, then it slowed down in 2020 and shrank in 2021, probably because the COVID-19 lockdown hit educational institutions hard. They were surely one of the first places to close in 2020, and Brazil was one of the countries that closed schools longer during the pandemic (OECD [<reflink idref="bib73" id="ref131">73</reflink>]). Similarly, the impact on the attendance rate in the municipal preschool centers reached a maximum of 7.54 percentage points in 2020, and then it reduced to 6.27 p.p. in 2021.</p> <hd id="AN0180801952-17">5.2. Proinfância impacts on cognitive skills</hd> <p>We found evidence that Proinfância contributed to the increase of children's attendance in daycare and preschool centers; therefore, we want to test if the access to early education due to Proinfância indirectly impacted the future school performance. Then, we estimate whether the public schools in municipalities that participated in Proinfância had better average scores in Prova Brasil–a Brazilian exam administered every two years to all the students in the fifth grade of elementary school.</p> <p>The impacts on students' scores (in logarithms) in Portuguese and Mathematics are reported in Table 4. Once again, we make one regression for each <emph>ex-post</emph> year, now considering that Prova Brasil is applied every two years (Columns 1 to 7). According to Table 1, the effects may become more apparent in 2017 and mainly 2019, due to the timing of building constructions and the age that children are entitled to apply to Prova Brasil.[<reflink idref="bib31" id="ref132">31</reflink>]</p> <p>Table 4. Proinfância effects on the scores of public schools (log) in Prova Brasil.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td><italic>Ex-post</italic> year:</td><td>2009</td><td>2011</td><td>2013</td><td>2015</td><td>2017</td><td>2019</td><td>2021</td></tr><tr><td /><td>(1)</td><td>(2)</td><td>(3)</td><td>(4)</td><td>(5)</td><td>(6)</td><td>(7)</td></tr></thead><tbody><tr><td /><td>(A) Portuguese</td></tr><tr><td>Proinfância*year</td><td char=".">0.003</td><td char=".">0.005</td><td char=".">0.011***</td><td char=".">0.009**</td><td char=".">0.006*</td><td char=".">0.005</td><td char=".">0.003</td></tr><tr><td>s.e.</td><td char=".">[0.004]</td><td char=".">[0.004]</td><td char=".">[0.004]</td><td char=".">[0.004]</td><td char=".">[0.004]</td><td char=".">[0.003]</td><td char=".">[0.004]</td></tr><tr><td>R-squared</td><td char=".">0.25</td><td char=".">0.30</td><td char=".">0.34</td><td char=".">0.51</td><td char=".">0.59</td><td char=".">0.61</td><td char=".">0.53</td></tr><tr><td /><td>(B) Mathematics</td></tr><tr><td>Proinfância*year</td><td char=".">0.004</td><td char=".">0.008**</td><td char=".">0.012***</td><td char=".">0.008**</td><td char=".">0.005</td><td char=".">0.005</td><td>−0.0001</td></tr><tr><td>s.e.</td><td char=".">[0.004]</td><td char=".">[0.004]</td><td char=".">[0.004]</td><td char=".">[0.004]</td><td char=".">[0.004]</td><td char=".">[0.004]</td><td char=".">[0.004]</td></tr><tr><td>R-squared</td><td char=".">0.24</td><td char=".">0.27</td><td char=".">0.27</td><td char=".">0.41</td><td char=".">0.45</td><td char=".">0.50</td><td char=".">0.37</td></tr><tr><td>Observations</td><td>10,883</td><td>10,706</td><td>10,782</td><td>10,758</td><td>10,955</td><td>10,897</td><td>10,551</td></tr><tr><td>Controls</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table> </ephtml> </p> <p>4 Note: *Significant at 10% (<emph>p</emph>-value <10%); **Significant at 5% (<emph>p</emph>-value <5%); ***Significant at 1% (<emph>p</emph>-value <1%). This table presents the estimates of Equation (<reflink idref="bib1" id="ref133">1</reflink>) for each <emph>ex-post</emph> year when Prova Brasil was applied (Columns 1 to 7). Proinfância is a dummy indicating program participation; the variable year was set to 1 for each <emph>ex-post</emph> year and 0 for 2007. We consider the effects on the outcomes: (A) Scores of public schools in Portuguese in Prova Brasil (in logarithm), (B) Scores of public schools in Mathematics in Prova Brasil (in logarithm). The covariates added as control are the female population aged 16 to 49 years old, infants aged 0 to 3 years old, children aged 4 to 5 years old, the number of births in the municipality, and the averages of formal workers' income and age. Standard errors are in brackets.</p> <p>Table 4(A) shows a minimum positive increase in Portuguese scores near 1% in municipalities that received a Proinfância building in 2013, 2015, and 2017. In the other years, the effects are positive but insignificant. The pattern is similar for the impacts on scores in Mathematics (Table 4(B)), being low in magnitude and insignificant at most of the years, unless in 2011, 2013, and 2015.</p> <p>The fact that the outcomes seem significant far before sufficient time for the children attending Proinfância facilities to apply to Prova Brasil casts doubts on this theoretical mechanism and raises the assumption that Proinfância could impact scores in the short run. Therefore, we should bear in mind that the participation in the program may immediately impact the public educational infrastructure as a whole, as many public schools are dedicated to infant education and the first phases of elementary school altogether. Therefore, a new building providing early childhood care could relieve the overcrowding in elementary schools, enhancing children's cognitive achievement.[<reflink idref="bib32" id="ref134">32</reflink>]</p> <hd id="AN0180801952-18">5.3. Proinfância impact on female labor force participation</hd> <p>Once we confirmed that Proinfância had an impact on early childhood education coverage, we analyze whether the program influenced female labor supply. Although we could not observe the behavior of mothers who benefited from the program, we can test if the proportion of formal female workers increased in the municipalities that received daycare and preschool centers funded by Proinfância.</p> <p>Table 5 shows the estimation of Equation (<reflink idref="bib1" id="ref135">1</reflink>) for each <emph>ex-post</emph> year in Columns 1 to 14, considering two indicators of female labor force participation. Firstly, we present the effects on the proportion of women occupying formal positions. Table 5(A) shows that this rate increased in the participating municipalities from 2014 on. The magnitude and significance of the effects increased slightly over time and even more during the COVID-19 outbreaks (2020–2021). However, the impact is small and statistically equal to a one percentage point increase.</p> <p>Table 5. Proinfância effects on female participation in the formal market.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td><italic>Ex-post</italic> year:</td><td>2008</td><td>2009</td><td>2010</td><td>2011</td><td>2012</td><td>2013</td><td>2014</td><td>2015</td><td>2016</td><td>2017</td><td>2018</td><td>2019</td><td>2020</td><td>2021</td></tr><tr><td /><td>(1)</td><td>(2)</td><td>(3)</td><td>(4)</td><td>(5)</td><td>(6)</td><td>(7)</td><td>(8)</td><td>(9)</td><td>(10)</td><td>(11)</td><td>(12)</td><td>(13)</td><td>(14)</td></tr></thead><tbody><tr><td /><td>(A) Proportion of formal jobs filled by women</td></tr><tr><td>Proinfância*year</td><td char=".">0.180</td><td char=".">0.0623</td><td char=".">0.109</td><td char=".">0.0453</td><td char=".">0.596</td><td char=".">0.356</td><td char=".">0.748**</td><td char=".">0.754**</td><td char=".">0.923**</td><td char=".">0.718*</td><td char=".">0.709*</td><td char=".">0.792**</td><td char=".">0.925**</td><td char=".">0.972**</td></tr><tr><td>s.e.</td><td char=".">[0.413]</td><td char=".">[0.405]</td><td char=".">[0.396]</td><td char=".">[0.394]</td><td char=".">[0.392]</td><td char=".">[0.384]</td><td char=".">[0.381]</td><td char=".">[0.376]</td><td char=".">[0.384]</td><td char=".">[0.375]</td><td char=".">[0.371]</td><td char=".">[0.373]</td><td char=".">[0.401]</td><td char=".">[0.394]</td></tr><tr><td>R-squared</td><td char=".">0.27</td><td char=".">0.26</td><td char=".">0.26</td><td char=".">0.25</td><td char=".">0.26</td><td char=".">0.25</td><td char=".">0.24</td><td char=".">0.25</td><td char=".">0.24</td><td char=".">0.24</td><td char=".">0.25</td><td char=".">0.24</td><td char=".">0.14</td><td char=".">0.14</td></tr><tr><td /><td>(B) Proportion of low-education jobs filled by women</td></tr><tr><td>Proinfância*year</td><td char=".">0.202</td><td char=".">0.176</td><td char=".">0.257</td><td char=".">0.149</td><td char=".">0.665</td><td char=".">0.753*</td><td char=".">1.145***</td><td char=".">1.106***</td><td char=".">1.253***</td><td char=".">1.076***</td><td char=".">1.127***</td><td char=".">1.181***</td><td char=".">1.134***</td><td char=".">1.450***</td></tr><tr><td>s.e.</td><td char=".">[0.436]</td><td char=".">[0.428]</td><td char=".">[0.420]</td><td char=".">[0.418]</td><td char=".">[0.413]</td><td char=".">[0.405]</td><td char=".">[0.401]</td><td char=".">[0.396]</td><td char=".">[0.402]</td><td char=".">[0.395]</td><td char=".">[0.393]</td><td char=".">[0.393]</td><td char=".">[0.399]</td><td char=".">[0.398]</td></tr><tr><td>R-squared</td><td char=".">0.25</td><td char=".">0.24</td><td char=".">0.24</td><td char=".">0.23</td><td char=".">0.24</td><td char=".">0.22</td><td char=".">0.21</td><td char=".">0.21</td><td char=".">0.21</td><td char=".">0.21</td><td char=".">0.21</td><td char=".">0.21</td><td char=".">0.21</td><td char=".">0.17</td></tr><tr><td>Observations</td><td>11,118</td><td>11,122</td><td>11,121</td><td>11,123</td><td>11,123</td><td>11,127</td><td>11,126</td><td>11,126</td><td>11,127</td><td>11,127</td><td>11,127</td><td>11,127</td><td>11,127</td><td>11,127</td></tr><tr><td>Controls</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table> </ephtml> </p> <p>5 Note: *Significant at 10% (<emph>p</emph>-value <10%); **Significant at 5% (<emph>p</emph>-value <5%); ***Significant at 1% (<emph>p</emph>-value <1%). This table presents the estimates of Equation 1 for each <emph>ex-post</emph> year (Columns 1 to 14). Proinfância is a dummy indicating program participation; the variable year was set to 1 for each <emph>ex-post</emph> year and 0 for 2007. We consider the effects on the outcomes: (A) the rate of formal jobs filled by female employees, (B) the rate of formal jobs filled by female employees, considering workers with low educational level only (up to complete high school). The covariates added as control are the female population aged 16 to 49 years old, infants aged 0 to 3 years old, children aged 4 to 5 years old, the number of births in the municipality, and the averages of formal workers' income and age. Standard errors are in brackets.</p> <p>In Table 5(B), we concentrate on the workers with a low educational level. Again, we use the percentage of formal employment relations filled by women as the outcome variable in the regressions, but now encompassing only workers with formal educational level up to high school. Qualification correlates with positions and income, so low-educated women should benefit more from access to public infant education.</p> <p>As expected, Proinfância impacts the employment of low-educated women more significantly, with the same pattern as before: the effects have become significant at 10% since 2013 and at 1% from 2014 on. The magnitude also improved over time, reaching a 1.45-point increase in 2021, when the restrictions of the COVID-19 pandemic had not been completely lifted yet. This result suggests that Proinfância helped to protect the employment of low-educated women, especially during the pandemic. It also indicates that the recovery of female labor supply was more notable in municipalities that had received a Proinfância building.</p> <p>The labor force has struggled worldwide to get back on track since the COVID-19 pandemic receded by the end of 2022. One of the stated reasons was the lack of caregivers, as the closure of daycare centers left no options for mothers who wanted to work but lacked childcare (CEA [<reflink idref="bib30" id="ref136">30</reflink>]). Our results align partially with Furman, Kearney, and Powell ([<reflink idref="bib46" id="ref137">46</reflink>]), who found that mothers accounted for a negligible share of the increase in unemployment during the pandemic. Still, they observed more considerable job loss for women who did not complete their bachelor's degree studies.</p> <hd id="AN0180801952-19">6. Discussion</hd> <p>This study sought to empirically assess the effects of Proinfância, which is a large-scale Brazilian program aimed at increasing the coverage of early childhood education through the construction of daycare and preschool centers. Comparing data from before and after the beginning of Proinfância, we look at the effects in the short and middle run on infant education coverage, education outcomes, and female labor force participation.</p> <p>Results show that Proinfância helped to increase access to municipal daycare and preschool institutions–a raise of at most 4.43 and 7.54 percentage points, respectively, more than ten years after the program launch. Nonetheless, the effects are low given the program scale, which funded building constructions in nearly one in every two Brazilian municipalities, and the federal government's goals for expanding early childhood education.</p> <p>According to information from the FNDE, Proinfância financed almost R$6.3 billion for the construction of 4658 daycare and preschool buildings between 2008 and 2019. Therefore, the average nominal cost was roughly 1,3 million for each building. Furthermore, considering that each center serves 150 children this provides an increase of 700,000 vacant spots, corresponding to roughly 54% of the rise in the number of enrollments in such period (see Appendix A.1 and Figure 3).</p> <p>Evidence of positive externalities of Proinfância on future cognitive skills is meager. We found an increase in average scores in Portuguese and Mathematics in Prova Brasil, but too small in magnitude (1% increase at most) and often insignificant. The effects were more significant in 2013 and 2015, when a large share of constructions just finished, but lost significance from 2017 on.</p> <p>There are a number of potential reasons for the significant effects in the short run but the lack of significance in the long run. First, Proinfância may have reduced students' overpopulation in the existing schools and daycare centers by transferring students to the new built facilities (Falciano, Nunes, and dos Santos [<reflink idref="bib40" id="ref138">40</reflink>]). When analyzing summarized statistical data from the School Census, we observed that the student-per-teacher ratio in early childhood education dropped from 17.45 students per teacher in 2007 to 14.73 in 2017 in Brazil.</p> <p>Second, the expansion of vacant spots between 2008 and 2012 may not have been substantial enough to impact the average results of the municipalities. Third, the quality of early childhood care in the inaugurated institutions may not be good enough to improve students' performance afterward.</p> <p>Finally, we aimed to test the relationship between childcare in daycare centers and preschools and the productive engagement of mothers. The impacts on female labor force participation were significant, but their magnitude was tiny in the standard specification (an increase of around one percentage point). A few threats to the impact identification could get the estimates downward, helping to explain the small impact of Proinfância on female employment. First, we do not observe individual data. Therefore, we cannot state the behavior of mothers who get access to daycare centers, but only about the proportion of jobs filled by women in a given municipality. However, as it is a large-scale program, we believe it is appropriate to evaluate the program on a large scale to observe if it changed the municipal rates as expected.</p> <p>Second, there is no reliable data on informal jobs at the local level, which consists of a large share of occupations in Brazil. Also, as observed in the literature (Havnes and Mogstad [<reflink idref="bib51" id="ref139">51</reflink>]), mothers could replace children's informal care with the public daycare center when available. Nevertheless, in an underdeveloped country with a sizeable informal market, providing a public daycare center could increase the predictability of time by mothers, who can leave part-time jobs and search for a more stable position. As we cannot directly test it because there are no reliable data on informal care and informal job market in every Brazilian municipality, it is reasonable to suppose that all these changes may operate simultaneously when a jurisdiction receives a Proinfância building.</p> <p>Overall, the results confirm the theoretical links between early childhood education, future education achievement, and female labor force engagement. At first glance, our results go in line with a branch of the recent literature relying on robust empirical strategies that found small or null effects regarding the expansion of early childhood care (Baker, Gruber, and Milligan [<reflink idref="bib4" id="ref140">4</reflink>]; Brilli, Del Boca, and Pronzato [<reflink idref="bib24" id="ref141">24</reflink>]; Carta and Rizzica [<reflink idref="bib28" id="ref142">28</reflink>]; Havnes and Mogstad [<reflink idref="bib51" id="ref143">51</reflink>]). However, the fact that we found significant causal impacts–even in small magnitude–suggests we should observe more effects on female employment and children development with a more considerable expansion of attendance rates.</p> <p>Notably, Proinfância contributed to expanding access to early childhood care, but the implementation was very heterogeneous around the country. Thus, improving the bidding and construction processes, which depends on the federate relations between upper and lower levels of government in Brazil, is essential to accelerate the construction of daycare and preschool centers. Moreover, it is crucial to guarantee a minimum standard of quality and full-time care to ensure that the effects on education outcomes and female labor supply become more perceptible.</p> <hd id="AN0180801952-20">Acknowledgments</hd> <p>We would like to thank Carlos Saiani for his comments, Ana Maria Franco for helping us with the econometric methodology implementation, Allana Santos for help with data, and Rebeca Regatieri for her first suggestion on the evaluation of Proinfância. In addition, we appreciate the support given by João Cintra from ABRINQ Foundation for explaining the estimates regarding the young children population, two anonymous referees for their constructive comments, and Angélica Halcsik for the text review. In dedication to Francisco Carvalho Castro and the new generation of infants and toddlers.</p> <hd id="AN0180801952-21">Disclosure statement</hd> <p>No potential conflict of interest was reported by the author(s).</p> <p>Correction Statement</p> <p>This article has been corrected with minor changes. These changes do not impact the academic content of the article.</p> <ref id="AN0180801952-22"> <title> Notes </title> <blist> <bibl id="bib1" idref="ref18" type="bt">1</bibl> <bibtext> The question of how childcare affects the labor supply of parents has been recently raised in headlines from the USA and many other countries due to the labor shortage caused by the COVID-19 pandemic (Albanesi and Kim [1]; CEA [30]; CNN [33]; Furman, Kearney, and Powell [46]; WSJ [81]).</bibtext> </blist> <blist> <bibl id="bib2" idref="ref21" type="bt">2</bibl> <bibtext> In Portuguese: 'Programa Nacional de Reestruturação e Aquisição de Equipamentos da Rede Escolar Pública de Educação Infantil'</bibtext> </blist> <blist> <bibl id="bib3" idref="ref33" type="bt">3</bibl> <bibtext> Research conducted in Psychology, Neurology, and other fields also supported the effects of high-quality early childhood education on cognitive and non-cognitive skills and other welfare indicators, such as level of education, wages, crime participation, health, and success in numerous other areas of life (Yoshikawa et al.[82]). According to Cunha, Heckman, and Lochner ([37]), investing in early childhood education increases 'self-productivity', meaning that education in the early life cycle improves the ability to achieve new skills in later stages. Also, these investments are 'complementary' because they reduce the costs to increase productivity in the future. In sum, if the base for developing fundamental skills is weak, the return for later investments will be low. Early investments to reduce disparities in education avoid gaps in children's development and reduce the cost of fixing failures in human capital formation in the future (J. Heckman, Pinto, and Savelyev [55]).</bibtext> </blist> <blist> <bibl id="bib4" idref="ref13" type="bt">4</bibl> <bibtext> The Abecedarian Program resulted in a permanent increase in the participants' IQ, while the Star Project showed a positive difference in cognition and better behavior of the treated group in the classroom with greater salaries in the future. Perry Preschool participants registered consistent improvements in several aspects: higher test scores, improved educational level, less need for special education, greater likelihood of getting a job, and lower chances of committing crimes. Even when interventions in early childhood may not increase IQs, they might as well improve socio-emotional skills, which also have significant effects on education, labor market, and other behavioral aspects (J. J. Heckman and Karapakula [54]; Temple and Reynolds [78]).</bibtext> </blist> <blist> <bibl id="bib5" idref="ref46" type="bt">5</bibl> <bibtext> Likewise, they have also encountered a positive impact on the conclusion rates in elementary, high, and higher education schools.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref1" type="bt">6</bibl> <bibtext> It is based on some premises, such as diminishing disparities in access, guaranteeing minimum standards of teaching quality, and providing society with improvements in early childhood education facilities. See Appendix A.2.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref49" type="bt">7</bibl> <bibtext> More than 60% of the Brazilian municipalities have fewer than 20,000 inhabitants, with low structure to organize and conduct an executive project.</bibtext> </blist> <blist> <bibl id="bib8" idref="ref20" type="bt">8</bibl> <bibtext> See Appendix A.1 for more details on Proinfância implementation.</bibtext> </blist> <blist> <bibl id="bib9" idref="ref74" type="bt">9</bibl> <bibtext> There is anecdotal evidence that some delivered facilities did not start their operations due to these constraints (BBC [9]; CGU [31]).</bibtext> </blist> <blist> <bibtext> The program covered all Brazilian states, especially Minas Gerais (13% of supplied facilities), São Paulo (12%), and Paraná (11%), which were the greatest beneficiaries in the number of construction works, followed by Rio Grande do Sul (10%), Bahia (6%), and Santa Catarina (6%). Near half of the participating municipalities (51%) had concluded just one building financed by Proinfância and 85% had fewer than five.</bibtext> </blist> <blist> <bibtext> In Portuguese, 'Fundo de Manutenção e Desenvolvimento do Ensino Fundamental e de Valorização do Magistério'.</bibtext> </blist> <blist> <bibtext> In Portuguese, 'Ensino Fundamental'.</bibtext> </blist> <blist> <bibtext> In Portuguese, 'Plano Nacional de Educação'.</bibtext> </blist> <blist> <bibtext> Federal Law 11,274 of 2006 changed the initial age of elementary school to six years old. As a result, enrolling 6-year-old children became part of the scope of FUNDEF transfers. Then, early childhood education policies began to target children aged 0 to 5 years old.</bibtext> </blist> <blist> <bibtext> Table 2 shows that the goal for daycare coverage was not reached by 2019.</bibtext> </blist> <blist> <bibtext> In Portuguese, 'Fundo de Manutenção e Desenvolvimento da Educação Básica e de Valorização dos Profissionais da Educação'.</bibtext> </blist> <blist> <bibtext> As part of an effort to increase access to infant education, the federal government launched other procedures aimed at early childhood education. To finance the cost of services in the buildings funded by Proinfância, the federal government instituted a Program to Support New Early Childhood Education Establishments (BRASIL [20]) and 'Brasil Carinhoso' (BRASIL [21]), specifically to encourage the presence of children from the poorest families in daycare centers (M. D. C. M. T. Cruz, Farah, and Sugiyama [35]).</bibtext> </blist> <blist> <bibtext> Elementary school, or 'Ensino Fundamental (Fundamental Education)' in Brazil, corresponds to the first eight years of formal education–children aged 6 to 14 years old. Prova Brasil is applied at schools with at least 20 students enrolled in these grades.</bibtext> </blist> <blist> <bibtext> According to SAEB's Proficiency Scale, scores below 125 for both tests indicate lack of elementary skills (BRASIL [23]).</bibtext> </blist> <blist> <bibtext> Formal employment is every employment that has been duly registered in the national system of the Ministry of Labor and Employment and that, therefore, complies with labor legislation.</bibtext> </blist> <blist> <bibtext> Anecdotal evidence shows that the demand for daycare centers is higher in big cities, where the job market is more dynamic and the cost of opportunity for not-working is higher, as well as the overall living cost (Folha [43]). Historical evidence shows that families rely on informal caregivers for their children, and such trend has also increased during the COVID pandemic (Folha [44]).</bibtext> </blist> <blist> <bibtext> About 70% of the Brazilian municipalities had 20,000 inhabitants at most according to our data, while the biggest cities have typically more than 500,000 citizens.</bibtext> </blist> <blist> <bibtext> We do not have accurate data on informal workers, given this market is not regulated, and we do not have credible estimates at the municipality level. The same is true for data on informal caregivers.</bibtext> </blist> <blist> <bibtext> 'Fundo Nacional de Desenvolvimento da Educação', in Portuguese.</bibtext> </blist> <blist> <bibtext> Early childhood education is provided mostly by municipal institutions–roughly 65% of the enrollments in daycare centers and 75% of enrollments in preschool centers. Enrollments in private institutions correspond to roughly 35% of the enrollments in daycare centers and 24% of enrollments in preschool centers. The remaining enrollments are registered in institutions administered by the federal or state governments and do not reach 1% of the total.</bibtext> </blist> <blist> <bibtext> The methodology consists of applying the local population growth, which is annually estimated by the IBGE for each municipality, to the population cohorts per age provided by the previous Population Census. Only six jurisdictions in 2007 and 16 in 2017 had more enrollments in daycare centers than the population between 0 and 3 years old. However, 1308 had more registrations than the population at the preschool age in 2007, and this number dropped to 1,026 in 2017. Therefore, we remade the estimates replacing the attendance rate with 100% when the number of enrollments in a municipality was larger than the population size. The results remain qualitatively unchanged.</bibtext> </blist> <blist> <bibtext> Instituted by Decree No. 76,900 from December 23, 1975, RAIS covers 99% of the formal Brazilian labor market; however, it is not possible to analyze factors related to the family environment, i.e. to know whether employed women have children or not.</bibtext> </blist> <blist> <bibtext> The reason is straightforward: express the outcomes in the treatment group before the program implementation as</bibtext> </blist> <blist> <bibtext>Graph</bibtext> </blist> <blist> <bibtext> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi>Y</mi><mi>T</mi><mn>0</mn></msubsup><mo>=</mo><msub><mi>β</mi><mn>0</mn></msub><mo>+</mo><msub><mi>β</mi><mn>1</mn></msub><mo>+</mo><msub><mi>ϵ</mi><mrow><mi>it</mi></mrow></msub></math> </ephtml> and after the implementation as</bibtext> </blist> <blist> <bibtext>Graph</bibtext> </blist> <blist> <bibtext> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi>Y</mi><mi>T</mi><mn>1</mn></msubsup><mo>=</mo><msub><mi>β</mi><mn>0</mn></msub><mo>+</mo><msub><mi>β</mi><mn>1</mn></msub><mo>+</mo><msub><mi>β</mi><mn>2</mn></msub><mo>+</mo><msub><mi>β</mi><mn>3</mn></msub><mo>+</mo><msub><mi>ϵ</mi><mrow><mi>it</mi></mrow></msub></math> </ephtml> . For the control group, we have the potential outcome before the beginning of the program as</bibtext> </blist> <blist> <bibtext>Graph</bibtext> </blist> <blist> <bibtext> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi>Y</mi><mi>C</mi><mn>0</mn></msubsup><mo>=</mo><msub><mi>β</mi><mn>0</mn></msub><mo>+</mo><msub><mi>ϵ</mi><mrow><mi>it</mi></mrow></msub></math> </ephtml> and after as</bibtext> </blist> <blist> <bibtext>Graph</bibtext> </blist> <blist> <bibtext> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><msubsup><mi>Y</mi><mi>C</mi><mn>1</mn></msubsup><mo>=</mo><msub><mi>β</mi><mn>0</mn></msub><mo>+</mo><msub><mi>β</mi><mn>2</mn></msub><mo>+</mo><msub><mi>ϵ</mi><mrow><mi>it</mi></mrow></msub></math> </ephtml> . Then, the Proinfância effect is given by the coefficient associated with the interaction between time and program, as</bibtext> </blist> <blist> <bibtext>Graph</bibtext> </blist> <blist> <bibl id="bib10" idref="ref57" type="bt"></bibl> <bibtext> <ephtml> <math xmlns="http://www.w3.org/1998/Math/MathML"><mi>DD</mi><mo>=</mo><mi>E</mi><mo stretchy="false">(</mo><msubsup><mi>Y</mi><mi>T</mi><mn>1</mn></msubsup><mo>−</mo><msubsup><mi>Y</mi><mi>T</mi><mn>0</mn></msubsup><mo stretchy="false">)</mo><mo>−</mo><mi>E</mi><mo stretchy="false">(</mo><msubsup><mi>Y</mi><mi>C</mi><mn>1</mn></msubsup><mo>−</mo><msubsup><mi>Y</mi><mi>C</mi><mn>0</mn></msubsup><mo stretchy="false">)</mo><mo>=</mo><msub><mi>β</mi><mn>3</mn></msub></math> </ephtml> , which we estimate using the Ordinary Least Squares (OLS).</bibtext> </blist> <blist> <bibtext> We consider 2019 as our benchmark <emph>ex-post</emph> year, as it was the first one before the outbreak of the COVID-19 pandemic.</bibtext> </blist> <blist> <bibtext> There seems to be a 'tipping point' in preschool coverage in 2010, when it was shrinking and started to rise swiftly, which is explained by the mandatory law for preschool in 2009 (BRASIL [19]) and the new count of the population from 4 to 5 years old in 2010.</bibtext> </blist> <blist> <bibtext> We also run the regressions using only a sample of municipalities treated in the first phase of the program, between 2008 and 2012. 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An: EJ1448103
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PubType: Academic Journal
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Effects of a Large-Scale Program for the Construction of Daycare and Preschool Centers on Cognitive Skills and Female Employment
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Marcelo+Castro%22">Marcelo Castro</searchLink><br /><searchLink fieldCode="AR" term="%22Breno+da+Cruz%22">Breno da Cruz</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Education+Economics%22"><i>Education Economics</i></searchLink>. 2024 32(6):786-811.
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  Label: Availability
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 26
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2024
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Early+Childhood+Education%22">Early Childhood Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Early+Childhood+Education%22">Early Childhood Education</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Facilities%22">Educational Facilities</searchLink><br /><searchLink fieldCode="DE" term="%22Labor+Force%22">Labor Force</searchLink><br /><searchLink fieldCode="DE" term="%22Employed+Women%22">Employed Women</searchLink><br /><searchLink fieldCode="DE" term="%22Construction+Programs%22">Construction Programs</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Program+Evaluation%22">Program Evaluation</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Brazil%22">Brazil</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1080/09645292.2023.2254516
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0964-5292<br />1469-5782
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper assesses the impacts of a large-scale program aimed at constructing daycare and preschool centers in Brazil named Proinfância, which funded new buildings in nearly 45% of the municipalities between 2008 and 2017. We find a significant increase in early education care in the jurisdictions that participated in the program more than a decade after it had started: 4 percentage points in the attendance rate for infants aged up to three and six percentage points for children aged 4 to 5. However, the improvements in public schools' scores in 'Prova Brasil', which is a national exam for elementary school children, are small (at most 1%). Despite this, the program significantly helped increase female labor force participation, especially considering low-educated workers, but also with a small magnitude (1 percentage point). The results suggest that a faster increase in the coverage of public infant education would lead to more pronounced effects on children's development and female participation in the workforce.
– Name: AbstractInfo
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  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2024
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1448103
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  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/09645292.2023.2254516
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 26
        StartPage: 786
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Early Childhood Education
        Type: general
      – SubjectFull: Educational Facilities
        Type: general
      – SubjectFull: Labor Force
        Type: general
      – SubjectFull: Employed Women
        Type: general
      – SubjectFull: Construction Programs
        Type: general
      – SubjectFull: Academic Achievement
        Type: general
      – SubjectFull: Program Evaluation
        Type: general
      – SubjectFull: Brazil
        Type: general
    Titles:
      – TitleFull: Effects of a Large-Scale Program for the Construction of Daycare and Preschool Centers on Cognitive Skills and Female Employment
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Marcelo Castro
      – PersonEntity:
          Name:
            NameFull: Breno da Cruz
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 0964-5292
            – Type: issn-electronic
              Value: 1469-5782
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              Value: 32
            – Type: issue
              Value: 6
          Titles:
            – TitleFull: Education Economics
              Type: main
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