This paper offers a comparative analysis of the effectiveness of eight popular forecasting methods: univariate, linear, discriminate and logit regression; recursive partitioning, rough sets, artificial neural networks, and DEA. Our goals are: clarify the complexity-effectiveness balance of each...

Advanced machine learning has achieved extraordinary success in recent years. 'Active' operational risk beyond ex post analysis of measured-data machine learning could provide help beyond the regime of traditional statistical analysis when it comes to the 'known unknown' or even the 'unknown...

We investigate heterogeneous effects of new digital technologies on the individual-level employment- and wage dynamics in the U.S. labor market in the period from 2011-2018. We employ three measures that reflect different aspects of impacts of new digital technologies on occupations. The first...

Digitization triggered a steep drop in the cost of information. The resulting data glut created a bottleneck because human cognitive capacity is unable to cope with large amounts of information. Artificial intelligence and machine learning (AI/ML) triggered a similar drop in the cost of...

In this study, we present a brief narrative review focused on ChatGPT, a state-of-the-art conversational agent developed using OpenAI's Generative Pretrained Transformer (GPT) framework. Distinctive for its ability to generate text of high quality in real-time, ChatGPT has emerged as a leader...

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)...

Artificial intelligence and machine learning have increasing influence on the financial sector, but also on economy as a whole. The impact of artificial intelligence and machine learning on banking risk management has become particularly interesting after the global financial crisis. The...

This paper introduces a socio-technical typology of bias in data-driven machine learning and artificial intelligence systems. The typology is linked to the conceptualisations of legal anti-discrimination regulations, so that the concept of structural inequality-and, therefore, of undesirable...

AI is transforming labor markets around the world. Existing research has focused on advanced economies but has neglected developing economies. Different impacts of AI on labor markets in different countries arise not only from heterogeneous occupational structures, but also from the fact that...