Impact estimates when propensity-score methods are used to determine dropout
Roberto Agodini and Mark Dynarski’s article “are experiments the only option? A look at dropout prevention programs†is published in The Review of Economics and Statistics 2004 volume 86, number 1 from page 180 to 194. Agodini and Dynarski determine the possibility of getting unbiased program impact estimates when propensity-score methods are used to determine dropout. This is done by comparing estimates derived using experimental methods with those derived from propensity-score methods. It is first recognized that experimental designs are valid enough in portraying the impacts of a program since the control and the treatment groups have similar observed and unobserved characteristics. However, conducting experimental studies in some settings such as when programs are not achieving the minimum capacity or in cases where treatment affects the entire population that would be qualified for program services. The propensity-score method is thus viewed as an alternative design that can evaluate programs and display similar impacts to those that would be attained if experimental methods are used. In this study, Agodini and Dynarski (p.180) seek to know the ability of propensity-score methods to duplicate experimental impacts of student absenteeism, dropout, self-esteem and educational aspirations. The authors also seek to know the extent to which propensity-score methods can replicate experimental impacts using less extensive data that is readily obtained for public use. Finally, the authors seek to determine the precision of propensity-score-based impacts estimates
