Employee turnover poses a significant challenge to organizations, leading to increased costs and disruptions in workforce stability. In this study, we propose a novel hybrid model for employee turnover prediction that integrates Genetic Algorithms (GA) for feature selection with LightGBM for...

This paper uses a structural, two-sided model of the education system to study the interactions between parents' school choices and teachers' labour supply decisions in the context of secondary education in England. I find that more affluent households put more weight on school performance when...

Identifying sensitive periods in which the returns to investments into skills are especially high is challenging, but crucial for an effective and efficient timing of parental or public investments aimed at fostering children's skills. We can detect sensitive periods with a novel design by...

I study the efficient design of a queue to dynamically allocate a scarce resource to long‐lived agents. Agents can be served multiple times, and their valuations fluctuate over time with some persistence. Each agent privately learns whether his prevailing valuation is high or low only when...

Identifying sensitive periods in which the returns to investments into skills are especially high is challenging, but crucial for an effective and efficient timing of parental or public investments aimed at fostering children's skills. We can detect sensitive periods with a novel design by...

Background: Financial institutions face significant challenges in predicting loan defaults, which directly impact the non-performing loan (NPL) rate. Incorrect predictions can lead to misinformed decisions and substantial financial losses. Objectives: This study aims to enhance default...