We study the interaction between an agent of uncertain type, whose project gives rise to both good and bad news, and an evaluator who must decide if and when to fire the agent. The agent can hide bad news from the evaluator at some cost, and will do so if this secures her a significant increase...

The existing literature on large dynamic factor models invariably assumes that the cross sectional covariance matrix is diagonal. This is due to the curse of dimensionality which means that many parameters need to be estimated for large data sets. This paper introduces a novel maximum likelihood...

Until recently literature on dynamic factor models invariably assumed that the cross sectional error covariance matrix is diagonal. This is due to the many parameters which need to be estimated for large data sets, which is known as the curse of dimensionality. Spencer (2024) introduced a novel...

This paper presents a dynamic model averaging approach for forecasting nominal exchange rates, which is a novel approach in exchange rate forecasting literature. This framework encompasses most of the approaches commonly used in the forecasting literature. We focus on nine major trading currency...

This paper addresses the poor performance of the Expectation-Maximization (EM) algorithm in the estimation of low-noise dynamic factor models, commonly used in macroeconomic forecasting and nowcasting. We show analytically and in Monte Carlo simulations how the EM algorithm stagnates in a...