Essays on Early Childhood Development, Essays (university) of Childhood Development

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Essays on Early Childhood Development

Pamela Jervis Ortiz

A thesis submitted for the Degree of Doctor of Philosophy (P.hD) to the University College London

September 2016

Declaration

I, Pamela Jervis Ortiz confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis.

Acknowledgments

I would like to thank my supervisor, Professor Orazio Attanasio, for his guidance and support throughout the work of this thesis. Thanks for always being available, for teaching me and for your confidence in me. A special thanks to Italo Lop´ez and Fl´avio Cunha, my co-authors in chapter 3 and 4 respectively of this thesis. I am also grateful to colleagues, professors and sta↵ from the Department of Economics at UCL. I am deeply thankful to Nicol´as and my family in Chile for their unconditional support and love.

Funding acknowledgments

This thesis has been made possible through the scholarship “Programa de Formaci´on de Capital Humano Avanzado Becas Chile” from The National Commission for Science and Technology CONICYT, Government of Chile, the Institute Fiscal Studies Scholarship from ESRC, the WM Gorman Schol- arship from the Department of Economics at UCL and the “Early Child Development Programs: E↵ective Interventions for Human Development” from the Eunice Kennedy Shriver National Institute of Child Health and Human Development.

A.0.1Home Assessments: Proportion answering yes.......... 175 A.0.2Kernel densities of latent traits: One investment input, 7-23mths, Specification b............................ 202 A.0.3Kernel densities of latent traits: One investment input, 48- 58mths, Specification b....................... 203 A.0.4Maternal Investment: time and didactic materials........ 204 A.0.5Expected Value Functions for periods T to t = 1......... 205 A.0.6Solution for the optimal family decisions, x axis is the child’s cognitive skills............................ 206

List of Tables

Chapter 1

Introduction

Early Childhood Development has been in the centre of the debate in the liter- ature over the last years gave its implications for welfare society. An increasing body of studies in neuroscience, psychology and economics, shows that first years of life are critical for future development of children (Thompson, (2001); Van der Gaag, (2005); Noble et al. (2007); Crawford et al. (2010)). In partic- ular, Heckman et al. (2006) find that a low dimensional vector of cognitive and non-cognitive abilities explain a variety of labour market and behavioural out- comes. Hence, stimulation of these abilities plays a crucial role in the child’s future and the social development of future generations. Numerous studies es- tablish that measured cognitive ability is a strong predictor of economic success in life (summarised in Cawley et al., 2001) and those non-cognitive abilities are likely to be an essential determinant of social success in life (Bowles and Ginties, 1976) and for predicting wages, schooling, and participation in risky behaviours (Heckman and Rubinstein, 2001). As a result, there is a significant literature on how parental characteristics and household environment a↵ect in- vestment in children’s human capital, but there is little information about how parents’ investment decisions, behave: What are the channels, if any, through which these decisions a↵ect child outcomes? Do these decisions, respond to incentives/stimulation? Do public policies influence child outcomes via these decisions? This is why my research has been focused on the study of those parental

investment decisions on early child development, which is crucial information for both, parents and policy makers. Understanding these e↵ects in complex economic environments requires assessing the mechanisms through which they act using simulated counterfactual worlds, and most of the time, incorporating a dynamic point of view to determine long-term e↵ects. Reducing gaps in multiple dimensions at early life-cycle stages with policies that also promote productivity contributes to shrink social inequality, poverty and exclusion, and to foster economic development. To achieve this goal, the analysis should be twofold: i) identify the factors behind the surge of these gaps, and ii) provide feedback to policy-makers so better policies are implemented to narrow these gaps. There is wide consensus about the need in social sciences of using rig- orous methodologies to assess the impacts of social policies. Recent studies have moved away from more traditional empirical analysis based largely on associations in behavioural data towards the identification of causation and counterfactuals using Randomised Controlled Trials (RCTs). Randomised evaluations can be very powerful tools to obtaining convincing estimates of the average e↵ect of a program or project. There are some examples of well- targeted and well-designed interventions having long-term e↵ects on outcomes (Jamaican home-visiting program (Grantham-McGregor et al. 1991), Perry Preschool Program (Schweinhart et al. 2005) and Abecedarian (Campbell et al. 2002) among others). However, the sole use of RCTs has been crit- icised on the grounds of external validity and narrow focus of what works, a black-box approach that prevents further understanding why a program or project works and incapacity for examining counterfactuals (Heckman and Smith, 1995; Deaton, 2010). Structural economic models of individual behaviour, when properly identi- fied, can lead to estimated policy-invariant parameters that govern preferences or technologies, and can be used to learn about behaviours and therefore to evaluate the e↵ectiveness of a program even when that policy has not been implemented. Moreover, structural models provide the tools to understand the mechanisms behind observed decisions in a way that is consistent with accepted theories of economic behaviour. They also provide the flexibility to accommodate observed and unobserved heterogeneity explaining behaviours.

ponents of human capital? How do acquired skills generate new skills and how does this process di↵er by the developmental stage of the child? What are the determinants of parental investments in children and what are the constraints they face? Is the lack of knowledge (or awareness) of the potencial returns, the lack for time or monetary resources, or their beliefs the reason why par- ents behave in one or another way? And what is the relative importance of these constraints? Do public investments in human capital (for example, pre- schooling or child care services) compensate for or replace parental investments (money and time)? To address all these questions, it is indispensable to develop more com- plex economic analysis to simulate the e↵ects of alternative policies and to understand the mechanisms behind decision-making. To do so in the Chilean context, this thesis dissertation provides a better insight of the state-of-the- art of numerical methods and computer technology to develop new techniques posed by modern economic models. Some of these ex-ante policies to be simulate will be based on current social policies in Chile and associated with early childhood development as extensions of maternity leave, extending parental leave to fathers, parenting programs of- fered by Chile Grows with You as well as a cash transfer (Asignaci´on Familiar ) to the poorest families. I divide this thesis dissertation into five chapters, each related to my re- search questions. In chapter 2, I present a theoretical framework and empirical analysis to contribute to the debate about the determinants of early childhood development in a developing country from Latin America: Chile. The Eco- logical Environment theoretical model for childhood was proposed to define the determinants of early childhood. This chapter aims to disentangle the de- terminants behind early childhood development based on multiple empirical strategies through the use of the first and second wave of a recent longitu- dinal survey, which was designed to characterise the child development. The data contains information about demographics, family’s background, cogni- tive, socioemotional and physical measures for mothers and children under five years old and home assessment environment. The determinants of early childhood development, particularly, cognitive and non-cognitive skills, are studied through the estimation of contemporaneous and value-added cognitive

and non-cognitive production functions, as well as the use of factor analysis such as item response theory for reducing the number of inputs. Three main results arise: (1) there are significant socioeconomic gradients in all cognitive tests between poorest and richest quintiles, which lead to a liability among disadvantaged children. Once controlling by observables, the gradient starts to decrease and in some cases to lose significance; (2) there is a significant e↵ect of mother’s characteristics and family background at later stage devel- opment (above 24/30 months old) measured principally by mother’s education, age and cognitive skills, if the family is a two-parent family, the presence of younger/older children as well as home environment measures by parent-child activities, learning materials, parental involvement and verbal and emotional responsibility scores. The later stage development also adds a significant ef- fect on attending a preschool. The previous determinants drive the fall in the socioeconomic gradient in both stages; and (3) regarding the non-cognitive skills, for both waves, the results are similar, there are socioeconomic gradi- ents that are still significant after controlling for all the variables. If the child is male, have a negative and significant e↵ect as well if they attend to preschool. Mother’s education and age have positive and significant impact meanwhile having younger children in the household have an adverse and significant ef- fect. Having both parents have a positive impact as well as child’s weight at birth and the mother’s cognition level. For the first time, all the sub scales of the mother’s socioemotional test are (positively) correlated with the child’s so- cioemotional skills. The home environment continues presenting positive and significant e↵ect on child’s development. Chapter 3 is based in a co-authored paper with Italo Lop´ez (RAND). We characterise the process of human capital accumulation in early years. Genet- ics, environment and parental investment at di↵erent stages of early years of childhood a↵ect the formation of human capital skills. Only when these chan- nels are adequately incorporated in the study of the human capital formation will be possible to tackle early gaps in childhood and formulating ecient public policies. Despite these recent advances, there is still very little known about the return to cognitive and non-cognitive skills in developing countries. Recent studies have demonstrated how multiple factors relate in a complex way (Cuhna et. al. (2007, 2010)) through the use of technologies of skill

formation. We follow the methodology proposed by Cuhna et al. (2010) to estimate a multistage technology of skill formation for capturing di↵erent de- velopment phases in the early years of a child and dealing at the same time the problem of endogeneity of inputs (correlation with the unobserved shock) and the multiplicity of inputs relative to measures. One contribution to the literature is that we include multiple parental investments not only regarding material resources (monetary investment) and quality time investment but also regarding cognitive stimulation and emotional support. This model provides two critical parameters, the self-productivity of skills (if the child learn how to count, then he can use it to learn other skills which means that skills are self-reinforcing and persist into future periods) and dynamic complementarity (synergy of investments at di↵erent t), hence, a second contribution is to anal- yse if complementarities change with age stages. This chapter also contributes from previous research as include a rich Chilean data to apply the state-of-the- art methodology in the estimation of the production function. Exploiting the rich panel structure of the Encuesta Longitudinal de Primera Infancia (Early Childhood Longitudinal Survey (ELPI)) survey we find evidence about the im- portance of the stock of child’s skills as well as early investment in childhood development. Comparing the formation of cognitive and non-cognitive skills in children dealing or not with endogeneity, there is substantial evidence of the e↵ect of parental investment in early childhood development and also support the fact that parental investment is endogenous. Based on the estimation of the same production function but for di↵erent age stages, the principal result is how parental investment foster cognitive skills between 24-47 months concern- ing early and older stages instead for future non-cognitive skills the parental investment have the same e↵ect for all the age stages. There is evidence of cross-productivity for both skills which raises for older stages. Regarding the impact of separating the investment in material resources and quality time in child skills at age t the results show that material resources are essential for determining future child’s cognitive skills and quality time for deciding future child’s non-cognitive skills. Finally, splitting the investment in cognitive stim- ulation and emotional support in child skills at age t the results show that there is not much return regarding cognitive stimulation meanwhile the return of emotional support is higher on future child’s non-cognitive skills.

Chapter 4 is based on a co-authored paper with Orazio Attanasio (UCL and IFS) and Fl´avio Cunha (Rice University). We shed light on the importance of maternal subjective beliefs in explaining the heterogeneity in maternal choices of investments in the development of their children. Subjective beliefs about the production function of skills in early childhood development is crucial since parents may have biased beliefs about the returns to investments, which is cru- cial to pin down in designing policies aimed at remediating poor investments. To determinate the importance of maternal subjective beliefs, we first show how to convert the answers to a specific set of questions into estimates of ex- pected rates of returns on specific investment and then relate these estimates to actual maternal behaviour, then we formulate and estimate a model in which mothers have subjective beliefs about the technology governing the formula- tion of skills in early childhood development, drawing on detailed and unique data for the identification of the model from an early childhood intervention ran in Colombia, in which, home visitors paid weekly visits to randomly chosen households with the aim of promoting child cognitive and non-cognitive devel- opment and improving mother-child interactions. The intervention targeted poor households with children aged 12 to 24 months at baseline and lasted 18 months. We find that parents think that the productivity of investment is much higher for low initial conditions than higher initial conditions. Some findings are worth being discussed. We have elicited maternal beliefs about the production function. We have shown how to relate answers about devel- opmental age under di↵erent scenarios to beliefs about returns to investment and parameters of the production function. We find that parents think that the productivity of investment is much higher for low initial conditions than higher initial conditions. We want to extend this approach and estimate si- multaneously the production function, the perceived production function and the investment strategy. In the last chapter, I develop a dynamic structural model estimated with rich longitudinal data from Chile, in which I integrate a children’s human capital model with multiple stages of childhood into a dynamic framework to explain parental investment decisions, modeling quality parental investment time and children’s technology skill formation accounting for unobserved het- erogeneity (income shocks). Parents maximise a constrained model, choosing