Parental Time Investment and Children Outcomes (Parentime)

It is evident that high socioeconomic status parents consistently produce high socioeconomic status children - the question is how.

The objective of PARENTIME is to develop new socio-economic theories that unpack the detailed mechanisms driving the inter-generational transmission of inequality.

Because of data limitations and theoretical traditions, the literature has focused on:

• a narrow conceptualisation of parental time (limited to the quantity of time spent with children in different kinds of activities), and
• a reduced set of child outcomes (limited to educational outcomes and socio-behavioural outcomes during the early years).

PARENTIME will link large representative 24-hour diary survey data on how much time parents spend with their children with detailed information on child outcomes from administrative data.

The aims are twofold:

• First, to go beyond the quantity of parental time to explore the inter-connections between family members in the child’s acquisition of skills (i.e., the timing and sequence, co-presence, multi-tasking, and instantaneous parental enjoyment).
• Second, to establish long-term effects of parental time investments by looking at a comprehensive set of child human capital measures all the way into the child’s adult life.

To understand how parental time investments influence child outcomes, we will first separate the contribution of other confounders such as:

• prenatal factors
• parental income and wealth
• parental employment

In some cases, individuals are linked across families and in networks. This allows us to compare:

• contributions from parental time inputs net of other factors
• school and neighbourhood characteristics.

These issues will be addressed through many state-of-the-art techniques that take care of selection and causation such as:

• treatment effects models
• siblings' fixed effects models
• instrumental variables
• propensity score matching.

To understand the factors at play we will:

• move forward statistical estimations of structural models of the technology of skills formation
• take advantage of the multi-level and longitudinal nature of the linked data to run sub-group analysis and heterogeneous effects - particularly across gender and class.

Principal Investigator

• Professor Almudena Sevilla

Co-investigators

• Dr Francesca Folliano
• Erin Hengel
• Pilar Cuevas-Ruiz
• Dr Greta Morando
• Dr Sarah Sander
• Margaux Suteau

Visitors

• Dr Janaina Heloísa Telles de Lima
• Dr Marina Morales
• Professor Ismael Sanz
• Dr Anika Schenck-Fontaine
• Dr Valentina Tonei

Collaborators

• Dr Cristina Borra
• Professor Nacho Gimenez-Nadal
• Professor Mette Goertz
• Dr Afshin Zilanawala

I aimed to inform and influence policy changes that would enhance social mobility for disadvantaged children, addressing a critical global policy failure. in the EU 24.7% of children under 18 are at risk of poverty and social exclusion and despite increased education funding by 15% in OECD countries in the past decade, many students still finish school without essential literacy skills. Disparities in childhood can lead to differences in adulthood, with a risk of adults earning up to 20% less than those who grew up in wealthier families (EUROSTAT, 2022). My goal was to use my research findings to develop a public engagement strategy that could directly impact policies to reduce these educational disparities and their long-term economic effects. In light of these challenges, it was crucial to devise a public engagement strategy aimed at shaping real-world policies based on my research findings.

I designed the strategy around the outcomes of two distinct research projects aiming at closing widening gaps during childhood: Project 1, "Tackling Childhood Inequalities in the Wake of COVID-19: Public Outreach for Policy Change", used several waves of real-time survey data on parents and children during the COVID-19 pandemic in the UK. The findings documented widening inequalities during childhood around this period, and challenged conventional beliefs about the roots of emerging gaps. The research uncover that income-driven gaps in children's socio-emotional and educational gaps was not the only channel at play. A divergence in parental time devoted to children (with children from the wealthiest families spending 75 more minutes daily on educational activities than those from the poorest), as well as parental labor market uncertainty and well-being, were crucial drivers of childhood inequalities during the COVID crisis, even when household incomes did not change because of the Government’s furlough scheme. Project 2, "Overcoming Literacy Inequalities in Collaboration with Policymakers and NGO’s from the onset", leveraged the differential timing in the deployment of an AI-based Computer-Assisted Learning (CAL) program across 273 public primary schools in the Region of Madrid (Spain) in order to assess the causal impact on student achievement of the implementation. The CAL program was designed to improve writing and reading skills using artificial intelligence and machine learning with the ability to simulate students' cognitive processes in order to offer personalized educational content at their academic level and close widening literacy gaps and their long-time consequences. Our findings challenged the commonly held assumption that literacy teaching interventions are expensive and teachers’ time-intensive by demonstrating that a technology-based approach like DytectiveU can deliver personalized instruction autonomously, proving to be both scalable and cost-effective.

Recognizing that building trust with stakeholders to drive policy change is a process that requires time and adaptability, I shaped the public engagement strategy to be both flexible and proactive from the start, allowing it to grow and adjust alongside the ongoing research. I developed a public engagement strategy from the outset to be dynamic and responsive. This strategy was built to foster trust through ongoing interaction, allowing for real-time adjustments in line with evolving research insights. I designed the public engagement strategy to encompass three interrelated initiatives—public outreach, awareness, and policy change—that were interwoven to mutually reinforce and enhance each other, thereby methodically cultivating stakeholder trust, which is fundamental to achieving enduring policy change.

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