Artificial intelligence (AI) has radically changed companies' vision of business development, based on its widespread assimilation in key organisational processes. However, in organisational practice, the implementation of AI has generated major challenges, such as those related to the high need...

The paper considers two estimators for the linear random effects panel data model with known heteroskedasticity. Examples where heteroskedasticity can be treated as given include panel regression with averaged data, meta regression and the linear probability model. While one estimator builds on...

In the presence of fixed threshold effects, the least squares (LS) estimator of the threshold parameter poses challenges for statistical inference due to its non-standard limiting distribution, which also presents challenges for bootstrap methods. To address this issue, we propose a novel...

We revisit the finite-sample behavior of just-identified instrumental variables (IV) estimators, arguing that in most microeconometric applications, just-identified IV bias is negligible and the usual inference strategies likely reliable. Three widely-cited applications are used to explain why...