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In this paper we investigate potential changes which may have occurred over the last two decades in the probability mass of the right tail of the wage distribution, through the analysis of the corresponding tail index. In specific, a…
Fair machine learning (ML) methods help identify and mitigate the risk that algorithms encode or automate social injustices. Algorithmic approaches alone cannot resolve structural inequalities, but they can support socio-technical decision…
We propose a framework for nonparametric identification and estimation of discrete choice models with unobserved choice sets. We recover the joint distribution of choice sets and preferences from a panel dataset on choices. We assume that…
Surveys are an indispensable source of data for applied economic research; however, their reliance on self-reported information can introduce bias, especially if core variables such as personal income are misreported. To assess the extent…
Unsupervised skill discovery aims to acquire behavior primitives that improve exploration and accelerate downstream task learning. However, existing approaches often ignore the geometric symmetries of physical environments, leading to…
Context: Voluntary turnover is common in the software industry, increasing recruitment and onboarding costs and the risk of losing organizational and tacit knowledge. Objective: This study investigates how job satisfaction, work-life…
Recent waves of technological transformation are reshaping work in uncertain and hard-to-predict ways. However, jobs at the forefront of the digitizing economy offer an early glimpse of these changes and leave rich activity traces. We…
Evolution of cooperation is a widely studied problem in biology, social science, economics, and artificial intelligence. Most of the existing approaches that explain cooperation rely on some notion of direct or indirect reciprocity. These…
Reinforcement learning (RL) is concerned with how intelligence agents take actions in a given environment to maximize the cumulative reward they receive. In healthcare, applying RL algorithms could assist patients in improving their health…
We present a stylized model with feedback loops for the evolution of a population's wealth over generations. Individuals have both talent and wealth: talent is a random variable distributed identically for everyone, but wealth is a random…
The era of technological change entails complex patterns of changes in wages and employment. We develop a unified framework to evaluate the effects of capital-embodied technological change on, as well as the contributions of factor inputs…
The average and median income dependence on work experience and time is analyzed and modeled for the USA. The original data set providing the mean and median income estimates in 10 year long intervals spans a long time period of almost 35…
The distribution of household income is a central concern of modern economic policy due to its strong influence on life quality. Yet, non-expert audiences are unaware of the relationship between these two factors. To effectively communicate…
This work re-examines the commonly held assumption that the frequency of rewards is a reliable measure of task difficulty in reinforcement learning. We identify and formalize a structural challenge that undermines the effectiveness of…
This study examines the relationship between automation and income inequality across different countries, taking into account the varying levels of technological adoption and labor market institutions. The research employs a panel data…
We study fairness in supervised few-shot meta-learning models that are sensitive to discrimination (or bias) in historical data. A machine learning model trained based on biased data tends to make unfair predictions for users from minority…
Machine learning has grown in popularity to help assign resources and make decisions about users, which can result in discrimination. This includes hiring markets, where employers have increasingly been interested in using automated tools…
This paper highlights the potential for negative dynamic consequences of recent trends towards the formation of "skill-hubs". I first show evidence that skill acquisition is biased towards skills which are in demand in local labor markets.…
Across income groups and countries, individual citizens perceive economic inequality spectacularly wrong. These misperceptions have far-reaching consequences, as it is perceived inequality, not actualinequality informing redistributive…
Intra-household inequality continues to remain a neglected corner despite renewed focus on income and wealth inequality. Using the LIS micro data, we present evidence that this neglect is equivalent to ignoring up to a third of total…