The history of AI in economics is long and winding, much the same as the evolving field of AI itself. Economists have engaged with AI since its beginnings, albeit in varying degrees and with changing focus across time and places. In this study, we have explored the diffusion of AI and different...

How is algorithmic model interpretability related to human acceptance of algorithmic recommendations and performance on decision-making tasks? We explored these questions in a multi-method field study of a large multinational fashion organization. We first conducted a quantitative field...

The ChatGPT model of OpenAI allows users to ask questions, which are answered through an artificial intelligence trained through supervised, reinforced machine-learning. The answers depend on the input which the algorithm receives from the users, as well as from the content it has been given....

Central bank intervention in the form of quantitative easing (QE) during times of low interest rates is a controversial topic. This paper introduces a novel approach to study the effectiveness of such unconventional measures. Using U.S. data on six key financial and macroeconomic variables...

This paper contributes a multivariate forecasting comparison between structural models and Machine-Learning-based tools. Specifically, a fully connected feed forward nonlinear autoregressive neural network (ANN) is contrasted to a well established dynamic stochastic general equilibrium (DSGE)...

We study how researchers can apply machine learning (ML) methods in finance. We first establish that the two major categories of ML (supervised and unsupervised learning) address fundamentally different problems than traditional econometric approaches. Then, we review the current state of...