By Jeremy Arkes
One instrument the Air strength is utilizing to enhance its logistical help to the warfighter is procuring and supply-chain administration (PSCM). Is PSCM doing what it was once meant to do? if that is so, how good? Are different elements influencing its meant results? The authors have constructed an econometric version that is helping research a lot of these issues. whereas facts availability and caliber could be a problem, the version can also be valuable in different contexts.
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Extra info for Estimating the Benefits of the Air Force Purchasing and Supply Chain Management Initiative
Sample text
This could cause the Air Force to underestimate the effects of PSCM and could affect future Air Force resource decisions. In addition, this could provide incorrect feedback on the efforts of personnel who are actually bringing benefit to the Air Force, because, in our notional example, without their efforts in implementing the initiatives, things would have been worse. If, on the other hand, fewer parts were removed at the same time the PSCM initiative was implemented, there could be fewer MICAP incidents from both the initiative and the decrease in removals.
Including NIIN-level fixed effects essentially adds a set of NIIN dummy variables so that the identification of the effect of the PSCM initiative will come from within-NIIN changes in Model Methodology and Data Requirements 19 the outcome between before and after the PSCM initiative is implemented for the given NIIN, holding constant other factors. 1) where Y kt " a measure of supply chain performance (number of MICAP incidents) k " NIIN t " time (quarter) Rk " NIIN-level fixed effect Rt " time-level fixed effect PSCM kt " indicator for whether NIIN k was on a PSCM contract at time t C kt " a vector of co-occurring factors J kt " error term L " the coefficient estimate representing the effects of PSCM Q " the coefficient estimate(s) on the vector of co-occurring factors.
In this situation, isolating the causal effects of one particular initiative would require controlling for all other initiatives as well. Unfortunately, many of these co-occurring factors are not readily available or are difficult to quantify for a regression model. Economists have developed well-established techniques for reducing what is known as omitted variables bias, which is the technical term for the problems associated with being unable to control for these cooccurring factors. One technique that could be applied in this situation is to use a difference-in-difference approach, which entails the inclusion of entitylevel and time-level fixed effects.