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...

Using a firm level dataset from four regions of Russia covering 1996/97, an investigation was carried out into how the surplus created within the firm is divided between profits and wages. An efficient bargaining framework based on the work of Svejnar (1986) is employed which takes into account...

This paper uses a "local average treatment effect" (LATE) framework in an attempt to disentangle the separate effects of criminal and noncriminal gun prevalence on violence rates. We first show that a number of previous studies have failed to properly address the problems of endogeneity, proxy...

We use a rich personnel data set from a Russian firm for the years 1997 to 2002 to analyze how the financial crisis in 1998 and the resulting change in external labor market conditions affect the wages and the welfare of workers inside a firm. We provide evidence that large shocks to external...

We use data from over 20,000 firms in 60 countries to identify constraints on the growth of firms. We interpret managers' answers to survey questions on the extent to which various aspects of their external environment inhibit the performance of their firm as measuring the shadow cost of...

This paper uses the BEEPS firm-level data to study the process of convergence of transition countries with developed market economies. The primary focus of the study is on competition and market structure, finance and the structure of lending to firms, and how firms respond to the economic...

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...

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...

Quantile crossing has been a challenge for quantile regression, leading to research in how to obtain monotonically increasing quantile estimates. While important contributions, these papers do not provide insight into how enforcing monotonicity influences the estimated coefficients. This paper...