We present a model to test the null hypothesis that firms organize their corporate governancearrangements optimally given the constraints they face. Following the literature, the modelrejects the null if the conditional correlation between governance and performance issignificantly different...

This paper presents estimates from a latent variables model of the relation between corporate governance and financial performance. We use data on large US corporations to estimate the correlation, conditional on the firms' investment opportunity set, between governance and performance. We find...

We present a model to test the null hypothesis that firms organize their corporate governance arrangements optimally given the constraints they face. Following the literature, the model rejects the null if the conditional correlation between governance and performance is significantly different...

This paper presents estimates from a latent variables model of the relation between corporate governance and financial performance. We use data on large US corporations to estimate the correlation, conditional on the firms' investment opportunity set, between governance and performance. We find...

We present a model to test the null hypothesis that firms organize their corporate governance arrangements optimally given the constraints they face. Following the literature, the model rejects the null if the conditional correlation between governance and performance is significantly different...

This paper examines the ability of beta and size to explain cross-sectional variation in average returns in twelve European countries. We find that average stock returns are positively related to beta and negatively related to firm size. The beta premium is in part due to the fact that high beta...

Measurement error causes a downward bias when estimating a panel data linear regression model. The panel data context offers various opportunities to derive moment conditions that result in consistent GMM estimators. We consider three sources of moment conditions: (i) restrictions on the...

The paper introduces the appropriate within estimators for the most frequently used three-dimensional fixed effects panel data models. It analyzes the behavior of these estimators in the cases of no self-flow data, unbalanced data, and dynamic autoregressive models. The main results are then...

Measurement error causes a downward bias when estimating a panel data linear regression model. The panel data context offers various opportunities to derive moment conditions that result in consistent GMM estimators. We consider three sources of moment conditions: (i) restrictions on the...

The paper introduces the appropriate within estimators for the most frequently used three-dimensional fixed effects panel data models. It analyzes the behavior of these estimators in the cases of no self-flow data, unbalanced data, and dynamic autoregressive models. The main results are then...