In many applications of conditional logit models the choice set and the characteristics of that set are identical for groups of decision makers. In that case is possible to obtain a more computationally efficient estimation of the model by grouping the data and employing a new user-written...

In this presentation, I provide a detailed discussion of an alternative iterative approach for the estimation of linear regression models with two high-dimensional fixed-effects, such as large employer-employee datasets. I also show how to extend the approach to three high-dimensional fixed...

In this presentation, I describe an alternative iterative approach for the estimation of linear regression models with high-dimensional fixed-effects, such as large employer–employee datasets. This approach is computationally intensive but imposes minimum memory requirements. I also show that...