Elsevier

Economics of Education Review

Volume 64, June 2018, Pages 144-164
Economics of Education Review

The contribution of early childhood and schools to cognitive gaps: New evidence from Peru

https://doi.org/10.1016/j.econedurev.2018.03.009Get rights and content

Highlights

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    We measure the contribution of early childhood and school influences to the cognitive gap between urban and rural eight-year-old children in Peru.

  • •

    We argue and empirically illustrate how our decomposition strategy is less prone to biases than those employed before.

  • •

    We find that school influences occurring between ages 6 and 8 account for a significant share of urban/rural cognitive gap (around 35%).

  • •

    The share attributable to early childhood influences is important but no larger than 50%.

Abstract

Cognitive gaps between children of different socioeconomic backgrounds are particularly significant in the developing world. We propose and use a new decomposition strategy to measure the contribution of early childhood and school influences to the cognitive gap between urban and rural eight-year-old children in Peru. This strategy accounts for the relation between family choices and skill inputs and is less prone to biases than those employed before. We find that school influences occurring between ages 6 and 8, account for a significant share of urban/rural cognitive gap (around 35%). The share attributable to early childhood influences is important but no larger than 50%. Because skill depreciates, only a fraction of the gap (70–80%) is carried forward to the next period. Therefore, inequalities in school environments are sustaining a cognitive gap that would otherwise be smaller and this explains why differences that emerge during early childhood can remain unchanged after children start school.

Section snippets

Introduction and motivation

Differences in developmental outcomes between children of dissimilar socioeconomic backgrounds are particularly significant in the developing world (Grantham-McGregor et al., 2007, Walker et al., 2007). Peru is no exception to the presence of these early forms of inequality. In fact, national student evaluations reveal a significant and persistent gap between the proportion of urban and rural second grade students that attain satisfactory results in reading comprehension (see Fig. 1).1

The production function of skill and families’ choices

In this section, we describe the skill formation technology and present a simple model describing how families’ choices determine its inputs. For this, let us divide the relevant phase of child development into two time periods. The first begins when the child is born and finishes at age 5, that is, when the child is ready to start the basic education cycle. The second period corresponds to the time when the child remains within primary school age, which is usually between ages 6 and 11.

Assume

Empirical specifications and decomposition strategy

In this section, we use the insights provided by the model described above to propose a decomposition strategy. We explain the assumptions required for the identification of the contributions of early childhood and school influences and explain why this strategy is less prone to biases than those employed thus far in the literature. We also discuss its rationale under the lens of the Blinder-Oaxaca (henceforth BO) technique. The decomposition strategy proposed here is motivated by the empirical

Data sources and variables

This analysis will employ the information contained in the first three rounds of the child and household surveys, as well as the school survey, focusing on the Younger Cohort of the Young Lives Study in Peru.14 The basic structure of this data is summarized in Table 3.

The estimations will be based on two different samples. The first considers all

Concluding remarks

Children of dissimilar socioeconomic backgrounds demonstrate significant differences in cognitive outcomes across the developing world. Cognitive skill formation is a cumulative process and, therefore, influences that have taken place early in the life of these children but also later, at school, can both play in role in shaping these gaps.

This paper sought to contribute to the literature by using a new decomposition strategy to measure the contribution of early childhood and school influences

Acknowledgements

The authors are grateful to Sandra McNally, two anonymous reviewers, Paul Glewwe, Douglas Gollin, Imane Chaara, Andreas Georgiadis, Stefan Dercon and participants at the 2016 Meeting of the International Association for Applied Econometrics, the 2016 Meeting of Latin American and Caribbean Economic Association and the 12th Midwest International Economic Development Conference for their valuable comments. This research did not receive any specific grant from funding agencies in the public,

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