3期

最新文章

• Estimating the Impacts of Program Benefits: Using Instrumental Variables with Underreported and Imputed Data AI翻译
  作者：Stephens, Melvin, Jr.; Unayama, Takashi
  作者单位：University of Michigan System; University of Michigan; National Bureau of Economic Research; Hitotsubashi University
  摘要：Survey nonresponse has risen in recent years, which has increased the share of imputed and underreported values found on commonly used data sets. While this trend has been well documented for earnings, the growth in nonresponse to government transfers questions has received far less attention. We demonstrate analytically that the underreporting and imputation of transfer benefits can lead to program impact estimates that are substantially overstated when using instrumental variables methods to...
• Regression Discontinuity Designs Using Covariates AI翻译
  作者：Calonico, Sebastian; Cattaneo, Matias D.; Farrell, Max H.; Titiunik, Rocio
  作者单位：Columbia University; Princeton University; University of Chicago
  摘要：We study regression discontinuity designs when covariates are included in the estimation. We examine local polynomial estimators that include discrete or continuous covariates in an additive separable way, but without imposing any parametric restrictions on the underlying population regression functions. We recommend a covariate-adjustment approach that retains consistency under intuitive conditions and characterize the potential for estimation and inference improvements. We also present new c...
• The Reverse Matthew Effect: Consequences of Retraction in Scientific Teams AI翻译
  作者：Jin, Ginger Zhe; Jones, Benjamin; Lu, Susan Feng; Uzzi, Brian
  作者单位：University System of Maryland; University of Maryland College Park; National Bureau of Economic Research; Northwestern University; Purdue University System; Purdue University
  摘要：Teamwork pervades modern production, yet teamwork can make individual roles difficult to ascertain. The Matthew effect suggests that communities reward eminent team members for great outcomes at the expense of less eminent team members. We study this phenomenon in reverse, investigating credit sharing after damaging events. Our context is article retractions in the sciences. We find that retractions impose little citation penalty on the prior work of eminent coauthors, but less eminent coautho...