@techreport{Augurzky2001Propensity,
abstract = {Propensity score matching is a prominent strategy to reduce imbalance in observational studies.
However, if imbalance is considerable and the control reservoir is small, either one has to match
one control to several treated units or, alternatively, discard many treated persons. The first
strategy tends to increase standard errors of the estimated treatment effects while the second
might produce a matched sample that is not anymore representative of the original one. As an
alternative approach, this paper argues to carefully reconsider the selection equation upon which
the propensity score estimates are based. Often, all available variables that rule the selection
process are included into the selection equation. Yet, it would suffice to concentrate on only
those exhibiting a large impact on the outcome under scrutiny, as well. This would introduce
more stochastic noise making treatment and comparison group more similar. We assess the
advantages and disadvantages of the latter approach in a simulation study.},
author = {Boris Augurzky and Christoph M. Schmidt},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {C14; C15; 330; Estimation of the propensity score; balance of relevant covariates; simulation study; Stichprobenverfahren; Mikro\"{o}konometrie; Theorie},
language = {eng},
number = {271},
title = {The Propensity Score: A Means to An End},
type = {IZA Discussion paper series},
url = {http://hdl.handle.net/10419/21122},
year = {2001}
}
