While the traditional components of employer brand equity are applied in the context of an organization's employees, this study sought to assess a hitherto unexplored context - the extent to which employer brand equity impacts on consumers of an organization's service brand rather than the...

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 examines the role of pricing errors in linear factor pricing models, allowing for observed strong and semi-strong factors, and latent weak factors. It focusses on the estimation of ∅k = λk − μk which plays a pivotal role, not only in the estimation of risk premia but also in...

This paper studies how to incorporate observable factors in difference-in-differences and document their empirical relevance. We show that even under random assignment directly adding factors with unit-specific loadings into the difference-in-differences estimation results in biased estimates....

Through the lens of a nonlinear dynamic factor model, we study the role of exogenous shocks and internal propagation forces in driving the fluctuations of macroeconomic and financial data. The proposed model 1) allows for nonlinear dynamics in the state and measurement equations; 2) can generate...

This paper studies the Level, Slope, and Curve factor model in the Chinese stock market. Empirical asset pricing tests reveal that the slope factor in the model represents either a reversal or a momentum effect for the Chinese stocks, and further tests on individual stocks demonstrate that the...

Portfolio selection is often faced with large noisy data sets of strongly correlated asset returns, and so is prone to unstable portfolio weights and serious estimation error. To attenuate these problems, this paper proposes a new latent factor model equipped with both a suitable robust...