Using firm-level data for Belgium, we study the validity of Hicks neutrality in several sectors that cover the spectrum of knowledge intensity. We find that Hicks neutrality is clearly not supported by the data in different sectors. The results are not sensitive to altering the specification of...

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...

This paper discusses pairing double/debiased machine learning (DDML) with stacking, a model averaging method for combining multiple candidate learners, to estimate structural parameters. We introduce two new stacking approaches for DDML: short-stacking exploits the cross-fitting step of DDML to...