Geographical Variation in Cost of Air Travel: Analysis of the Domestic Airline Fares Consumer Report
Author(s) -
William Anderson,
Gang Gong,
T. R. Lakshmanan
Publication year - 2002
Publication title -
transportation research record journal of the transportation research board
Language(s) - English
Resource type - Journals
eISSN - 2169-4052
pISSN - 0361-1981
DOI - 10.3141/1788-02
Subject(s) - destinations , regression analysis , deregulation , competition (biology) , kilometer , trips architecture , mile , variable (mathematics) , air travel , variables , econometrics , descriptive statistics , air transport , low cost carrier , revealed preference , geography , transport engineering , business , statistics , economics , aviation , tourism , mathematics , marketing , ecology , mathematical analysis , archaeology , geodesy , aerospace engineering , biology , engineering , macroeconomics
There is significant geographical variability in the cost of American domestic air travel. This variability may be attributable to a number of factors, including scale economies, the average length of trips, airport congestion, and other factors that vary by region. Also, in the post-deregulation environment the cost of air travel may depend on the level of competition in specific spatial markets. Data from Domestic Airline Fares Consumer Report are used to conduct descriptive and statistical analyses of the spatial variability of air travel cost. The ratio of average fare to distance (fare per mile) is used as a general measure of relative cost, which is observed to vary significantly across cities. Two regression analyses seek to identify the factors that drive this variation. The first takes weighted average fares in the 50 largest cities as its dependent variable, whereas the second takes average fares in more than 6,500 origin-destination pairs as its dependent variable. Results of both analyses indicate that fare per mile declines with the length of trip. They both also indicate a large and statistically significant competitive effect, whereby single-carrier market share has a positive effect on the fare. Regional variations are indicated in the results of the first regression, with higher fares in the Northeast and Midwest than in the West and South. The second set of regression results also indicates that, other things being equal, fares with origins or destinations in large cities tend to be higher.
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