Child Care Provider Survival Analysis

TL;DR

This study uses machine learning survival trees to identify key features influencing the longevity of child care providers in Florida, aiding efforts to improve provider stability amid pandemic challenges.

Contribution

Introduces the application of optimal survival trees to analyze factors affecting child care provider longevity, revealing complex interactions that influence business survival.

Findings

Religious affiliation correlates with longer provider survival.

Providers serving children in Prekindergarten or with subsidies tend to survive longer.

Small providers are more likely to have extended operational periods.

Abstract

The aggregate ability of child care providers to meet local demand for child care is linked to employment rates in many sectors of the economy. Amid growing concern regarding child care provider sustainability due to the COVID-19 pandemic, state and local governments have received large amounts of new funding to better support provider stability. In response to this new funding aimed at bolstering the child care market in Florida, this study was devised as an exploratory investigation into features of child care providers that lead to business longevity. In this study we used optimal survival trees, a machine learning technique designed to better understand which providers are expected to remain operational for longer periods of time, supporting stabilization of the child care market. This tree-based survival analysis detects and describes complex interactions between provider characteristics that lead to differences in expected business survival rates. Results show that small providers who are religiously affiliated, and all providers who are serving children in Florida's universal Prekindergarten program and/or children using child care subsidy, are likely to have the longest expected survival rates.