Matteo Rava*, Edem Egnikpo**

Internal seminars
phd seminar

Matteo Rava*, Edem Egnikpo**

AMSE
Parental Beliefs in Early Childhood Investments: data from Antipolo, Philippines*
The effect of natural disasters on economic growth in the short, medium and long term: a reappraisal**
Joint with
Gilles Dufrénot**
Venue

MEGA Salle Carine Nourry

MEGA - Salle Carine Nourry

Maison de l'économie et de la gestion d'Aix
424 chemin du viaduc
13080 Aix-en-Provence

Date(s)
Tuesday, April 2 2024| 11:00am to 12:30pm
Contact(s)

Lucie Giorgi: lucie.giorgi[at]univ-amu.fr
Ricardo Guzman: ricardo.guzman[at]univ-amu.fr
Natalia Labrador: natalia.labrador-bernate[at]univ-amu.fr
Nathan Vieira: nathan.vieira[at]univ-amu.fr

Abstract

*This paper investigates parental beliefs on the returns on investments made during different stages of childhood development, particularly focusing on the early childhood and later education phases. Using vignette methodologies pioneered by Cuhna et al. (2013) in the context of Early Childhood Development ECD, the study examines whether caregivers perceive varying returns on their time investments during these periods and whether these investments are seen as substitutes or complements. Drawing on a sample of caregivers from Manila's outskirts, the research aims to shed light on the role of belief in parental investment decisions, and the relation between socioeconomic characteristics and parental belief. Using long-form recordings of home environments, the research measures investments and examines how beliefs about parenting returns influence actual investments. Additionally, it evaluates the accuracy of parental self-perception regarding engagement with children and their assessment of children's development compared to the broader sample. Ultimately, the study assesses the impact of a light-touch intervention implemented at health facilities to enhance parental engagement with newborns, leveraging insights from behavioral science.

**We propose a new approach to measure the sensitivity of economic growth to natural disasters at different time horizons: short-, medium- and long-term. Specifically, our modeling approach is based on three novelties. First, we allow for nonlinear effects using quantile-on-quantile regression. Second, a wavelet decomposition is considered to investigate the effects in the short- to long-term. Thirdly, we exploit the mixed frequency of macroeconomic and natural disaster variables to capture the effects at an annual frequency of shocks occurring within the year (namely, quarterly natural disasters).