We study the importance of noncognitive skills in explaining differences in the labor market performance of individuals by means of machine learning techniques. Unlike previous em- pirical approaches centering around the within-sample explanatory power of noncognitive skills our approach focuses...

We develop the case of two-stage least squares estimation (2SLS) in the general framework of Athey et al. (Generalized Random Forests, Annals of Statistics, Vol. 47, 2019) and provide a software implementation for R and C++. We use the method to revisit the classic application of instrumental...

Extended Characteristic Surface Model (eCSM) is a theoretical tool of general application designed for computing coefficients in stochastic (Monte Carlo) simulations in particular in multi equation stochastic econometric models. Econometric models are most often used for economic analysis of...

The interest collected by the main borrowers is collected to pay back the principal borrowed from the depositary bank. In financial risk management, credit risk assessment is becoming a significant sector. For the credit risk assessment of client data sets, many credit risk analysis methods are...

This paper analyzes the inner workings of cartels. To understand how sanctioning institutions prevent cartel formation we study their effect on firms' communication in a laboratory experiment. Using machine learning to organize the chat communication into topics, we find that firms are less...

Empirical evaluations of national minimum wages, such as in Germany or the UK, rely on bite measures that capture treatment variation; measured from the incidence (or intensity) of employees paid below the threshold before the minimum wage was introduced or raised. Bite-dependent estimations...

The production and use of carbon nanotubes (CNTs) have become extremely wide within the last decade. Hence, the high interest in producing non-expensive and quality CNTs has motivated many research projects. This research considers the design and development of new technology for producing...

High rates of student attrition in tertiary education are a major concern for universities and public policy, as dropout is not only costly for the students but also wastes public funds. To successfully reduce student attrition, it is imperative to understand which students are at risk of...

The aim of this paper is comparison of multivariate statistical analysis and machine learning methods based on the model used for the measurement of current and forecasting of the future customer profitability. Modern customer profitability analysis shows that customer-company relationship is...

Text classification is an essential work in text mining and information retrieval. There are a lot of algorithms developed aiming to classify computational data and most of them are extended to classify textual data. We have used some of these algorithms to train the classifiers with part of our...