世界银行-后双重选择拉索在田间试验中的应用（英）

Policy Research Working Paper10931Using Post-Double Selection Lasso in Field ExperimentsJacobus CilliersNour ElashmawyDavid McKenzieDevelopment Economics Development Research GroupSeptember 2024 Public Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedProduced by the Research Support TeamAbstractThe Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.Policy Research Working Paper 10931The post-double selection Lasso estimator has become a popular way of selecting control variables when analyzing randomized experiments. This is done to try to improve precision, and reduce bias from attrition or chance imbal-ances. This paper re-estimates 780 treatment effects from published papers to examine how much difference this approach makes in practice. PDS Lasso is found to reduce standard errors by less than one percent compared to stan-dard Ancova on average and does not select variables to model treatment in over half the cases. The authors dis-cuss and provide evidence on the key practical decisions researchers face in using this method.This paper is a product of the Development Research Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at dmckenzie@worldbank.org. Using Post-Double Selection Lasso in Field Experiments ∗Jacobus Cilliers, Georgetown UniversityNour Elashmawy, Development Research Group, World BankDavid McKenzie, Development Research Group, World BankKeywords: Treatment effect; Randomized Experiment; Post-Double Selection Lasso; Attrition; Statistical Power.JEL classification codes: C93; C21; O12.∗We thank authors of the different papers we replicated for answering queries on their code; Christian Hansen, KasparWuthrich, Carolina Lopez, Anja Sautmann, Greg Lane, Erin Kelley, and participants in the World Bank half-baked seminarfor useful comments. Elashmawy was funded by the Robert S. McNamara Fellowships Program.1IntroductionIn a simple randomized experiment, regressing the outcome of interest on an indicator for treatment willgive the difference-in-means estimator, which provides an unbiased estimate of t