Deep learning is a type of machine learning that has attracted a lot of attention in recent years because to its incredible achievements in a variety of applications like pattern recognition, audio recognition, computer vision, and natural language processing. Deep learning approaches can also...

This study aims to understand why some incumbent firms adapt to technological change while others do not. Previous research is mostly based on empirical studies of single technological changes, making generalization difficult. We considered technological change from four perspectives:...

Output markets usually respond to input price changes asymmetrically, with prices rising faster than they fall, known as the rockets and feathers pattern. We expand the vector autoregressive quantile (VARQ) model by incorporating quantile cointegrating relationships to investigate such...

The development of automated decision-making technologies creates the threat of deiuridification: replacement of the legal acts’ provisions with automated, technological solutions. The article examines how selected provisions of the General Data Protection Regulation concerning, among other...

Should automation be regulated? This paper studies optimal tax of robot and regulation of automation. A job assignment model is embedded into a Mirrleesian tax problem. A task may either be assigned to the robot or one type of labors, which naturally determines the automation rate. The robot can...

In response to today’s rapidly changing global trade environment, countries have continued to make changes to their policy objectives and instruments to address new and emerging issues such as supply chain restructuring and reshoring, climate change, and currency undervaluation. To this end...

The matching efficiency of the standard matching function is known to follow a pro-cyclical pattern. An observed rightward shift in the UK’s Beveridge Curve after the Great Recession, suggests a decrease in the matching efficiency between vacancies and unemployed workers. This paper studies...

Machine learning algorithms are becoming ubiquitous in modern life. When used to help inform human decision making, they have been criticized by some for insufficient accuracy, an absence of transparency, and unfairness. Many of these concerns can be legitimate, although they are less convincing...

Over the past few years, interest has increased in models defined on positive and negative integers. Several application areas lead to data that are differences between positive integers. Some important examples are price changes measured discretely in financial applications, pre- and...

Researchers studying the evolution of viral pathogens and other organisms increasingly encounter and use large and complex data sets from multiple different sources. Statistical research in Bayesian phylogenetics has risen to this challenge. Researchers use phylogenetics not only to reconstruct...