We develop a regression decomposition technique for hazard rate models, where the difference in observed rates is decomposed into components attributable to group differences in characteristics and group differences in effects. The baseline hazard is specified using a piecewise constant...

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the...

We discuss and compare five measures of individual well-being, namely income, an objective composite well-being index, a measure of subjective well-being, equivalent income, and a well-being measure based on the von Neumann-Morgenstern utilities of the individuals. After examining the...

School systems regularly use student assessments for accountability purposes. But, as highlighted by our conceptual model, different configurations of assessment usage generate performance-conducive incentives of different strengths for different stakeholders in different school environments. We...

We study the interaction between competitive markets that produce large but unequally distributed welfare gains and elections through which the poor majority can redistribute income away from the rich minority. In our simple laboratory democracy, subjects first earn their income by trading in a...

In this note, we present a novel computerized real effort task based on moving sliders across a screen which overcomes many of the drawbacks of existing real effort tasks. The task was first developed and used by us in Gill and Prowse (American Economic Review, forthcoming). We outline the...

We challenge the recent claim that mispricing in the experimental asset markets introduced by Smith, Suchanek, and Williams (1988) is merely an artefact of confusion over declining fundamental value, and can be eliminated through appropriate training. We instead propose that when training is...