This paper presents an empirical approach that combines competing paradigms of mod-eling in empirical capital market research. The approach simultaneously estimates the explanatory power of fundamentals, expectations, and historic yield patterns, making it possible to test the extent to which...

We propose a new unified approach to identifying and estimating spatio-temporal dependence structures in large panels. The model accommodates global crosssectional dependence due to global dynamic factors as well as local cross-sectional dependence, which may arise from local network structures....

We propose a new test for structural changes in large dimensional factor models via a discrete Fourier transform (DFT) approach. If structural changes occur, the conventional principal component analysis fails to estimate common factors and factor loadings consistently. The estimated residuals...

We propose a new methodology to select a subset of assets for (partial) index replication, based on the latest research on factor models of large dimensions. Our method selects the set of leader stocks that can fully capture the systematic risk of the index to be replicated. Our selection...

Researchers are often interested in testing for measurement invariance with respect to an ordinal auxiliary variable such as age group, income class, or school grade. In a factor-analytic context, these tests are traditionally carried out via a likelihood ratio test statistic comparing a model...

The issue of measurement invariance commonly arises in factor-analytic contexts, with methods for assessment including likelihood ratio tests, Lagrange multiplier tests, and Wald tests. These tests all require advance definition of the number of groups, group membership, and offending model...

Researchers are often interested in testing for measurement invariance with respect to an ordinal auxiliary variable such as age group, income class, or school grade. In a factor-analytic context, these tests are traditionally carried out via a likelihood ratio test statistic comparing a model...

The issue of measurement invariance commonly arises in factor-analytic contexts, with methods for assessment including likelihood ratio tests, Lagrange multiplier tests, and Wald tests. These tests all require advance definition of the number of groups, group membership, and offending model...

This paper develops an adaptive group lasso estimator for factor models with both global and group-specific factors. The global factors can affect all variables, whereas the group-specific factors are only allowed to affect the variables within a certain group. We propose a new method to...

In this paper we develop asymptotics for tests of equal predictive ability between nested models when factor-augmented regression models are used to forecast. We provide conditions under which the estimation of the factors does not affect the asymptotic distributions developed in Clark and...