We develop the case of two-stage least squares estimation (2SLS) in the general framework of Athey et al. (Generalized Random Forests, Annals of Statistics, Vol. 47, 2019) and provide a software implementation for R and C++. We use the method to revisit the classic application of instrumental...

The least-squares Monte Carlo method has proved to be a suitable approximation technique for the calculation of a life insurer's solvency capital requirements. We suggest to enhance it by the use of a neural network based approach to construct the proxy function that models the insurer's loss...

Individuals may be poor even if their household is not poor, because the intra-household distribution of resources may be unequal. Dunbar, Lewbel and Pendakur (2013) develop a model wherein the resource share of each person in a collective household - defined as their share of total household...

An estimand of interest in empirical studies with observational data is the average treatment effect of a multi-valued treatment in the treated subpopulation. We demonstrate three estimation approaches: outcome regression, inverse probability weighting and inverse probability weighted...

The purpose of this study is to identify how open innovation variables influence the competitive capability of manufacturing small and medium enterprises (SMEs) in a regional territory in Southern Brazil. The research method is a survey of 67 SMEs in Southern Brazil that provided data for an...

We develop the case of two-stage least squares estimation (2SLS) in the general framework of Athey et al. (Generalized Random Forests, Annals of Statistics, Vol. 47, 2019) and provide a software implementation for R and C++. We use the method to revisit the classic application of instrumental...