Structural Equation Modeling in Archival Capital Markets Research : An Empirical Application to Disclosure and Cost of Capital

Structural equation modeling (SEM), an empirical methodology underutilized in archival research, enables empirical researchers to examine paths linking constructs in complex models. Specifically, SEM consists of two components: an empirical measurement model that generates common factors from observed variables and an empirical path model that links the common factors together. We discuss the components, estimation, and best practices of SEM. We also discuss SEM's advantages over similar, more common empirical techniques and we illustrate its application to a financial disclosure topic. In our empirical application, we find that higher earnings and voluntary disclosure quality are negatively associated with cost of capital both directly and indirectly through information asymmetry. In contrast to the conclusions of some prior research, we find that the paths from voluntary disclosure quality to cost of capital are significant even after controlling for the paths from earnings quality to cost of capital. Overall, we believe SEM offers fruitful avenues for future empirical research