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Corporate finance data, such as cash holdings and dividend payments, are simultaneously determined. In this study, new endogeneity was introduced into a simultaneous equation model. The proposed model features a correlation between the explanatory variable in the first equation and the disturbance term in the second equation. The necessity of this endogeneity can be derived from a theoretical requirement and/or model identification requirement. Covariance structure analysis was performed to estimate this model using the maximum likelihood method. The efficacy of the proposed model is assessed by comparing it with conventional estimation methods, such as two-stage least squares. Finally, a Monte Carlo simulation was conducted to determine the bias conventional estimation methods produce in the case of this new endogeneity.

Introducing new endogeneity into a simultaneous equation model: an application to corporate finance