Tracking is widespread in U.S. education. In post-secondary education alone, at least 71% of colleges use a test to track students. However, there are concerns that the most frequently used college placement exams lack validity and reliability, and unnecessarily place students from...

This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying...

We propose two novel methods to "bring ABMs to the data". First, we put forward a new Bayesian procedure to estimate the numerical values of ABM parameters that takes into account the time structure of simulated and observed time series. Second, we propose a method to forecast aggregate time...

We analyze the exchange rate forecasting performance under the assumption of selective attention. Although currency markets react to a variety of different information, we hypothesize that market participants process only a limited amount of information. Our analysis includes more than 100,000...

This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks over the forecast horizon, taking account of the size and duration of past breaks (if...

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...

The energy transition increases the demand for minerals from ethnically diverse, conflict-prone developing countries. We study whether and where mining is possible in such countries without raising the risk of civil conflict. We proceed in three steps: First, we propose a theoretical model to...

There is vast heterogeneity in the human willingness to weigh others’ interests in decision making. This heterogeneity concerns the motivational intricacies as well as the strength of other-regarding behaviors, and raises the question how one can parsimoniously model and characterize...

The aim of this paper is to develop a continuous time exchange rate model that allows for heterogeneity of the agents' beliefs, in order to explore non-linearities and possible chaotic behaviour. The theoretical model contains an intrinsic non-linearity that gives rise to a jerk differential...

We introduce the technique of band spectral panel regression (BSPR) to analyze global linkages across sectors and frequency bands. It relies on decomposing time series —allowably measured in mixed observation frequency— into "deviation cycle" dynamics by frequency band. We use it to compute...