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This article introduces lassopack, a suite of programs for regularized regression in Stata. lassopack implements lasso, square-root lasso, elastic net, ridge regression, adaptive lasso and post-estimation OLS. The methods are suitable for the high-dimensional setting where the number of...
Persistent link: https://www.econbiz.de/10011972491
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...
Persistent link: https://www.econbiz.de/10014454715
We introduce the package ddml for Double/Debiased Machine Learning (DDML) in Stata. Estimators of causal parameters for five different econometric models are supported, allowing for flexible estimation of causal effects of endogenous variables in settings with unknown functional forms and/or...
Persistent link: https://www.econbiz.de/10014227783
Social networks are a key factor of success in life, but they are also strongly segmented on gender, ethnicity, and other demographic characteristics (Jackson, 2010). We present novel evidence on an understudied source of homophily, namely behavioral traits. Behavioral traits are important...
Persistent link: https://www.econbiz.de/10013472041
Rank-rank regression is commonly employed in economic research as a way of capturing the relationship between two economic variables. It frequently features in studies of intergenerational mobility as the resulting coefficient, capturing the rank correlation between the variables, is easy to...
Persistent link: https://www.econbiz.de/10015163470