Contributing to the literature on the consequences of behavioral biases for market outcomes and institutional design, we contrast producer liability and minimum quality standard regulation as alternative means of social control of product-related torts when consumers are heterogeneously...

We examine whether a corruption scandal in which the incumbent is implicated undermines trust in local government. We use a novel dataset containing information on local corruption scandals reported in Spain during the period 1999 - 2009, and data on the level of trust expressed in local...

This paper studies the role of governments and its link to trust. We argue that the public's trust strongly depends on governments delivering on their core tasks in a market economy. In some economies, a neglect of core tasks can be observed and there seems to be some erosion, notably in terms...

We provide a new framework to identify demand elasticities in markets where managers rely on algorithmic recommendations for price setting, and apply it to a dataset containing bookings for a sample of mid-sized hotels in Europe. Using non-binding algorithmic price recommendations and observed...

Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised...

When using digital devices and services, individuals provide their personal data to organizations in exchange for gains in various domains of life. Organizations use these data to run technologies such as smart assistants, augmented reality, and robotics. Most often, these organizations seek to...

The vast majority of existing studies that estimate the average unexplained gender pay gap use unnecessarily restrictive linear versions of the Blinder-Oaxaca decomposition. Using a notably rich and large data set of 1.7 million employees in Switzerland, we investigate how the methodological...

In this paper we show, using a Machine Learning Framework and utilising a substantial corpus of media articles on Brexit, confirmed evidence of co-integration and causality between the ensuing media sentiments and British currency. The novel contribution of this paper is that along with...

Modern investors face a high-dimensional prediction problem: thousands of observable variables are potentially relevant for forecasting. We reassess the conventional wisdom on market efficiency in light of this fact. In our model economy, which resembles a typical machine learning setting, N...