Opportunities and Constraints ofUsing Quasiexperimental Inquiry Based Methods in Public PolicyAnalysis.

Many policies or programs surrounding us today, from highway safety policies, innovation or science and technology policies to privatization policies or child wellbeing programs are implemented or reiterated without a sufficiently thorough and systematic analysis of their impact. Understandably, using comprehensive public policy analysis methodologies is not always a welcome or affordable option. However, in those instances when the use of such methods is sought, as well as in many other instances, two extremely powerful and yet not so often used methodological tools can be of tremendous value: time series based analyses and pragmatic eliminative induction enhanced quasiexperimental inquiry (QEI). The Quasi-experimental tradition underscores the importance of identifying and eliminating threats to validity from our analysis based on quasiexperimental settings. A very new and not so well known development in this tradition is the addition of context validation (elimination of context based threats to validity) to the four already traditional types of validations, respectively statistical conclusion validity, internal validity, external validity, and construct validity (Dunn 1997). This is done through pragmatic eliminative induction (PEI). PEI suggests a way to determine and test “an approximately complete set of rival hypotheses” (Dunn 1997) and not solely some rival hypotheses chosen most often because they are readily known or easily testable. Employing the methodology in our study is (1) scientifically more complete, and (2) likely to yield interesting insights that may not have been uncovered so far. In this paper, we offer a systematic description of the use of the pragmatic combination of these methods, their advantages and practical challenges to their application. We exemplify by briefly applying the combined methods to various policy analytical settings, such as assessing success of innovation or science and technology policies, forecasting or assessing success of implemented privatization policies, and assessing success of some Public Health programs. We also propose and test a small modification to the original (Dunn 1997) PEI technique for enhancing QEI based methodologies, likely to make the process more affordable and less time and resources intensive This study thus offers one of the first practical applications of the extremely new and thus seldom used PEI enhanced quasi-experimental method in scientific policy analysis. Combining PEI with the use of other policy impact analytical tools should empower policy analysts with a new powerful, quasi-complete and now relatively affordable tool in their methodological toolbox. [ABSTRACT FROM AUTHOR]