We propose a novel Bayesian Graded Response Model (BGRM) for food security measurement. Our BGRM has several attractive features. It produces continuous food security estimates and measures of estimation uncertainty at the household level. Unlike the USDA's official measurement model, the BGRM...

Die heutige Arbeitswelt ist gekennzeichnet von verschiedenartigen demografischen, technologischen und wirtschaftlichen Veränderungen, geprägt durch beispielsweise eine zunehmende Digitalisierung und Tertiarisierung. Eine Reaktion auf die damit einhergehenden veränderten und sich verändernden...

Using data from a large survey of American households, we compare density forecasts elicited with bins- and scenarios-based questions. We show that inflation density forecasts are sensitive to the survey question designs used to elicit them. The within-person discrepancy is smaller, but still...

Machine learning algorithms can find predictive signals that researchers fail to notice; yet they are notoriously hard-to-interpret. How can we extract theoretical insights from these black boxes? History provides a clue. Facing a similar problem - how to extract theoretical insights from their...