This paper introduces a framework for selecting policies that maximize expected welfare under estimation uncertainty. The proposed method explicitly balances the size of the estimated welfare against the uncertainty inherent in its estimation, ensuring that chosen policies meet a reporting...

This study evaluates the impact of incorporating mixed reality-including both augmented and virtual reality-into auto-mechanics training for students enrolled in selected public technical technological institutes in Ecuador. The intervention aims to enhance students' understanding of automotive...

We develop a deep reinforcement learning (RL) framework for an optimal market-making (MM) trading problem, specifically focusing on price processes with semi-Markov and Hawkes Jump-Diffusion dynamics. We begin by discussing the basics of RL and the deep RL framework used; we deployed the...

People often form mental models based on incomplete information, revising them as new relevant data becomes available. In this paper, we experimentally investigate how individuals update their models when data on predictive variables are gradually revealed. We find that people's models tend to...

Machine learning and deep learning are increasingly applied in finance, yet few studies explore how they can enhance traditional econometric models. This study proposes an innovative KAN-GM model, integrating the Kolmogorov-Arnold network (KAN) with the GARCH-MIDAS model to extract nonlinear...

Despite progress in expanding access to education, many students in low- and middle-income countries struggle with foundational and advanced mathematics skills. Education technology is increasingly seen as a tool for improving learning outcomes, and a pilot was conducted in 149 public junior...

Many models of the CEO market build on the classic analyses of Lucas (1978) and Rosen (1982) characterized by full information, a limited role for firm-specific human capital, and efficient allocation of workers across jobs and firms. But empirical evidence is not consistent with this approach....