• Research Paper on:
    Power Analysis for the Assessment of a Correlation between Hedging and Airline Profitability

    Number of Pages: 5

     

    Summary of the research paper:

    This 5 page paper looks at why and how primary research projects using quantitative research benefit from the use of power analysis in order to determine sample size. This is applied to the subject of fuel hedging for airlines and the sample size needed to assess any link between hedging and profitability. The bibliography cites 6 sources.

    Name of Research Paper File: TS14_TEhedgepower.doc

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    Unformatted Sample Text from the Research Paper:
    of profitability and whether or not this is impacted by the practice of hedging, there is the need to undertake a statistical assessment. This paper is a demonstration using only  limited data due to the time consuming nature of gathering large amounts of data. Top consider the type of data needed and how much it is necessary for to look  at data requirements and then the number of data points needed for an analysis to be credible. The general approach is to  compare the profitability of the airlines that undertake hedging against those which do not undertake hedging. However, for the result to be meaningful it is necessary to ensure that the  data used is comparable. The airline industry is one that is highly sensitive to different environment factors, not only fuel which may vary between years, for example the SARs  and 9/11 all had impacts on the profitability of the industry (Ito and Lee, 2005). Furthermore, many airlines have changed there policies, it is notable when looking at  data following difficulties some airlines adjusted their hedging programs, many continued hedging but reduced the level of hedging where as some others simply stopped hedging, as seen with US  Air, others changed the way in which they undertook hedging, shifting from hedging for fuel costs of between 12 and 18 months, to a matching strategy hedging fuel against the  fuel which would be needed against tickets sold, which was effectively a sorter term hedging strategy. To create data that can be  seen as comparable and answer the question the data is segregated into the different years, in the way there is a greater ability to compare like with like, as in 

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