000			01961nam a22002177a 4500
005			20240426132002.0
008			240426b ph ||||| |||| 00| 0 eng d
040			_cOCT
100			_aHinson, Lisa
240			_aJournal of Financial Reporting / _hFall 2023
245			_aStructural equation modeling in archival capital markets research : _bAn empirical application to disclosure and cost of capital / _cLisa Hinson and Steven Luke
300			_aVol 8 (2) pages 87- 130 : _billustrations ; _c28 cm
500			_aABSTRACT: Structural equation modeling (SEM), an empirical methodology underutilized in archival research, enables researchers to examine paths linking constructs. SEM consists of two components: a measurement model that generates common factors from observed variables and a path model that links the factors. We discuss SEM'S components, estimation, advantages, best practices, and limitations. We illustrate SEM with an application to disclosure research. Unlike some prior research, we find voluntary disclosure quality is negatively associated With cost of capital, both directly and indirectly through information asymmetry, even after controlling for earnings quality's direct and indirect associations with cost of capital. We believe SEM offers fruitful avenues for future research because it allows flexibility in modeling relations guided by theory, enables tests of underlying theoretical mechanisms, provides tools to address measurement error and missing data, and estimates simultaneous equations. SEM may be useful in settings that currently use path analysis or principal component analysis. Data Availability: Data used in this study are available from public sources identified in the paper.
650			_astructural equation modeling
650			_avoluntary disclosure
650			_ainformation asymmetry
650			_aearnings quality
650			_acost of capital
700			_aLuke, Steven
942			_2ddc _cCR _n0
999			_c9571 _d9571