[gov3009-l] Rubin on "Are Job-Training Programs Effective?"

Hi all, We hope you can join us at the Applied Statistics Workshop this Wednesday, March 9th, when we are excited to have Don Rubin, the John L. Loeb Professor of Statistics here at Harvard University, who will be presenting recent work on job-training programs. You will find an abstract below. As usual, we will begin with a light lunch at 12 noon, with the presentation starting at 12:15p and wrapping up by 1:30p. "Are Job-Training Programs Effective?" Don Rubin John L. Loeb Professor of Statistics, Harvard University Wednesday, March 9th 12:00pm - 1:30pm CGIS Knafel K354 (1737 Cambridge St) Abstract: In recent years, job-training programs have become more important in many developed countries with rising unemployment. It is widely accepted that the best way to evaluate such programs is to conduct randomized experiments. With these, among a group of people who indicate that they want job-training, some are randomly assigned to be offered the training and the others are denied such offers, at least initially. Then, according to a well-defined protocol, outcomes, such as employment statuses or wages for those who are employed, are measured for those who were offered the training and compared to the same outcomes for those who were not offered the training. Despite the high cost of these experiments, their results can be difficult to interpret because of inevitable complications when doing experiments with humans. In particular, some people do not comply with their assigned treatment, others drop out of the experiment before outcomes can be measured, and others who stay in the experiment are not employed, and thus their wages are not cleanly defined. Statistical analyses of such data can lead to important policy decisions, and yet the analyses typically deal with only one or two of these complications, which may obfuscate subtle effects. An analysis that simultaneously deals with all three complications generally provides more accurate conclusions, which may affect policy decisions. A specific example will be used to illustrate essential ideas that need to be considered when examining such data. Mathematical details will not be pursued. Gov3009 website: http://www.iq.harvard.edu/events/node/1208 Cheers, matt. ~~~~~~~~~~~ Matthew Blackwell PhD Candidate Institute for Quantitative Social Science Department of Government Harvard University url: http://people.fas.harvard.edu/~blackwel/