Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects

By David S. Lee. 2005

1,464 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/c547273f73af7facb0ea7e5add69958a7eb6baeb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Statistics and Probability

Citations in the corpus

The Effect of Cash, Vouchers, and Food Transfers on Intimate Partner Violence: Evidence from a Randomized Experiment in Northern Ecuador (2016, positive): “To bound our estimates we follow Lee ( 2009 ) and construct worst-case scenarios by assuming that women who select into the sample because of treatment ( marginal women are at the very top or very bottom of the distribution.”
Seeing is Believing? Evidence from an Extension Network Experiment (2014, positive): “The second check bounds the treatment effect for selective attrition using a method proposed by Lee (2009).”
Learning Job Skills from Colleagues at Work: Evidence from a Field Experiment Using Teacher Performance Data (2016, methodology): “To assess the potential influence of this attrition, Columns 2 and 3 provide bounds for the treatment effect following the approach described by Lee (2011).(32) Bounds for the average treatment effect (school-level treatment effect) are 0.”
Estimating Gender Disparities in Federal Criminal Cases (2015, methodology): “In that case worst-case bounds can be more readily estimated; the trim that will raise the treatment effect estimate by the most is just the lower tail of the treated outcome distribution (see Lee 2009).”
Cultural proximity and loan outcomes (2017, neutral): “[50] Lee, David, 2008, “Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects,” Review of Economic Studies, 76(3) 1071-1102.”
Learning and Earning: Evidence from a Randomized Evaluation in India (2017, background): “Liu (2008) finds that more risk averse (or more loss averse) farmers in rural China delay adoption of Bt cotton, a relatively newer technological improvement.”
Improving Early-Grade Literacy in East Africa: Experimental Evidence from Kenya and Uganda * (2014, methodology): “the spirit of Lee (2009) in which the higher attrition rate in the control group is applied first to”
Private and Public Provision of Counseling to Job-Seekers: Evidence from a Large Controlled Experiment (2014, background): “30 placement market which was dominated by for profit employment agencies perpetrating abuse towards vulnerable individuals (Lee, 2009).”
Inputs, Incentives, and Complementarities in Education: Experimental Evidence from Tanzania* (2018, positive): “3), we estimate Lee (2009) bounds on the treatment effects and find that the treatment effect is still positive and significant for every subject as well as the composite measure of learning (Table A.”