# Report of

# The Secretary of Transportation

###### ^Rural\ Air\ Fare\ Study^

# ^To^

# ^The\ Committee\ on\ Commerce,\ Science,^

# ^and\ Transportation^

# ^of\ the\ Senate^

# ^And^

# ^The\ Committee\ on\ Transportation^

# ^and\ Infrastructure^

# ^of\ the\ House\ of\ Representatives^

######## ^Pursuant\ to\ Section\ 1213\ of\ the\ Federal\ Aviation\ Administration^

# Reauthorization Act of 1996

### ^\ \ ^

# ^\ \ \ \ \ \ \ \ \ \ April\ 1998^

# ^RURAL\ AIR\ FARE\ STUDY^

# ^Executive\ Summary^

^This\ study\ is\ in\ response\ to\ the\ congressional\ request\ in\ Section\ 1213\ of\ the\ Federal\ Aviation\ Administration\ Reauthorization\ Act\ of\ 1996\ for\ information\ on\ air\ service\ and\ fares\ at\ small\ communities.\ It\ is\ a\ follow-up\ to\ the\ Initial\ Service\ Analysis\ report\ submitted\ in\ January\ 1997\ and\ covers\ available\ fare\ information\ and\ analysis.^

^This\ study\ examines\ the\ average\ fares\ reported\ in\ the\ Origin-Destination\ Passenger\ Survey\ (O&D\ Survey)\ submitted\ by\ large\ certificated\ air\ carriers,\ the\ only\ source\ of\ fare\ information\ currently\ available.\ As\ requested\ by\ Congress,\ we\ have\ compiled\ fare\ data\ for\ all\ of\ the\ non-hub\ communities\ and\ "large"\ hub\ communities.\ Using\ fare\ data\ for\ the\ twelve-month\ period\ ending\ June\ 30,\ 1996,\ we\ have\ compared\ the\ average\ fares\ at\ non-hub\ communities\ with\ average\ fares\ at\ large\ hub\ communities.\ Also\ as\ requested,\ we\ have\ examined\ the\ data\ for\ the\ category\ of\ rural\ small\ communities\ and\ the\ relationship\ between\ fares\ and\ jet\ competition\ at\ small\ communities.^

# ^[Data\ Considerations]{.underline}^

Because the O&D Survey is based on a 10% sample of tickets collected and
because small certificated air carriers and commuter carriers, many of
which are primary carriers at small communities, do not participate in
the Survey, there is a lack of complete and representative fare data for
small communities, especially for local passengers who do not connect to
large carrier services. The statistical sampling limitations of the O&D
are most troublesome when considering fares in individual city-pair
markets, as fares in some small markets (particularly those heavily
served by commuter carriers) are likely to have a greater margin of
error. By aggregating the data across many city-pair markets, however,
the distortions inherent in the O&D data at small communities are
sufficiently ameliorated to allow conclusions to be drawn concerning
fare trends across small communities. With this in mind, we advise
readers against drawing conclusions based on fare data for individual
small communities or city-pair markets involving a small community.

Because of the shortcomings of the current database for analyzing small
community fares, we have initiated a project to obtain a complete data
bank of traffic and fares for domestic air transportation, as discussed
later in this report. Although we are optimistic about the prospects for
the new data system, it is still too soon to know how complete a data
bank can be compiled or when sufficient data will be available for
analytical purposes due to the developmental requirements of the new
system and the need to obtain data for a prospective 12-month period
once the system is operational.

We anticipate undertaking a more comprehensive analysis of fares once we
have compiled a complete and accurate data bank. We would want to
examine not only the differences that might exist in fares between
communities and markets but also explore in more depth the reasons
behind those differences. We will keep Congress advised of our progress
on this project.

# ^[Small\ Community\ Fares\ vs.\ Large\ Hub\ Fares]{.underline}^

·
**^The\ available\ data\ show\ that\ travelers\ to\ and\ from\ small\ communities,\ as\ a\ group,\ pay\ higher\ fares\ than\ travelers\ between\ large\ hubs\ do\ when\ compared\ to\ all\ hub-to-hub\ fares.^**

·
**^When\ fares\ in\ city\ pair-markets\ involving\ small\ communities\ are\ compared\ to\ fares\ in\ large\ hub\ markets\ ^^[without]{.underline}^^\ low-fare\ service^**[^1]**^,\ they\ are\ comparable.^**

·
**^When\ fares\ in\ city\ pair\ markets\ involving\ small\ communities\ are\ compared\ to\ fares\ in\ large\ hub\ markets\ ^^[with]{.underline}^^\ low-fare\ service,\ the\ small\ communities^^'^^\ average\ fares\ are\ substantially\ higher.\ City-pair\ markets\ involving\ small\ communities\ do\ not\ receive\ any\ significant\ amount\ of\ low-fare\ competition.^**

^The\ available\ data\ suggest\ that\ travelers\ to\ and\ from\ small\ communities,\ as\ a\ group,\ pay\ higher\ fares\ than\ travelers\ between\ large\ hubs\ do.\ Although\ the\ magnitude\ of\ the\ premium\ cannot\ be\ accurately\ measured,\ particularly\ if\ examined\ on\ an\ individual\ market\ basis,\ the\ fact\ that,\ in\ the\ aggregate,\ there\ is\ a\ consistent\ pattern\ of\ higher\ average\ yields\ suggests\ that\ small\ communities\ do\ experience\ higher\ fares.\ It\ also\ suggests\ that\ the\ premium\ is\ higher\ in\ shorter\ haul\ markets.^

^As\ with\ data\ for\ individual\ small\ communities,\ fares\ for\ travelers\ to\ and\ from\ large\ hubs\ differ\ substantially\ from\ market\ to\ market.\ We\ know\ from\ other\ studies\ that\ one\ major\ reason\ for\ large\ differences\ in\ fares\ is\ the\ presence\ of\ low-fare\ service.\ Because\ of\ the\ significant\ difference\ in\ fares\ between\ markets\ with\ and\ without\ low\ fare\ competition,\ we\ have\ presented\ a\ breakdown\ of\ average\ yields\ for\ the\ large\ hub\ community\ markets\ with\ and\ without\ low-fare\ competition\ as\ well\ as\ aggregate\ data\ for\ all\ large\ hub\ markets.\ A\ comparison\ of\ small\ community\ city-pair\ yields\ with\ yields\ in\ large\ hub\ markets\ without\ low-fare\ competition\ shows\ that\ yields\ in\ the\ two\ types\ of\ markets\ are\ comparable.\ In\ two\ mileage\ categories,\ small\ community\ average\ yields\ are\ actually\ lower\ than\ yields\ at\ large\ hubs\ without\ low-fare\ competition;\ in\ the\ other\ four,\ the\ large\ hub\ average\ yields\ are\ slightly\ lower.^

^The\ following\ table\ summarizes\ the\ yield\ data\ for\ the\ various\ categories\ of\ markets:^

######### ^[Yield\ (dollars/mile)\ by\ Mileage\ Category]{.underline}^

<table>
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<td><p><sup>Market Category</sup></p></td>
<td><p><sup>1-250</sup></p></td>
<td><p><sup>251-500</sup></p></td>
<td><p><sup>501-750</sup></p></td>
<td><p><sup>751-1000</sup></p></td>
<td><p><sup>1001-1500</sup></p></td>
<td><p><sup>1501-2000</sup></p></td>
<td><p><sup>2000+</sup></p></td>
<td><p><sup>Total</sup></p></td>
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<td><h5><sup>Small Communities</sup></h5></td>
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<td><p><sup>Average Yield </sup></p></td>
<td><p><sup>.7073</sup></p></td>
<td><p><sup>.4044</sup></p></td>
<td><p><sup>.3028</sup></p></td>
<td><p><sup>.2267</sup></p></td>
<td><p><sup>.1761</sup></p></td>
<td><p><sup>.1532</sup></p></td>
<td><p><sup>.1271</sup></p></td>
<td><p><sup>.2161</sup></p></td>
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<td><p><sup>All Large Hubs</sup></p></td>
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<td><p><sup>Average Yield</sup></p></td>
<td><p><sup>.3832</sup></p></td>
<td><p><sup>.2453</sup></p></td>
<td><p><sup>.1970</sup></p></td>
<td><p><sup>.1725</sup></p></td>
<td><p><sup>.1386</sup></p></td>
<td><p><sup>.1246</sup></p></td>
<td><p><sup>.1109</sup></p></td>
<td><p><sup>.1546</sup></p></td>
<td><p><sup> Large hubs -</sup></p></td>
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<td><p><sup>w/low fare comp.</sup></p></td>
<td><p><sup>.2969</sup></p></td>
<td><p><sup>.1927</sup></p></td>
<td><p><sup>.1542</sup></p></td>
<td><p><sup>.1411</sup></p></td>
<td><p><sup>.1185</sup></p></td>
<td><p><sup>.1180</sup></p></td>
<td><p><sup>.0798</sup></p></td>
<td><p><sup>.1436</sup></p></td>
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<td><p><sup>w/o low fare comp.</sup></p></td>
<td><p><sup>.6107</sup></p></td>
<td><p><sup>.3877</sup></p></td>
<td><p><sup>.4436</sup></p></td>
<td><p><sup>.2091</sup></p></td>
<td><p><sup>.2772</sup></p></td>
<td><p><sup>.1347</sup></p></td>
<td><p><sup>.1145</sup></p></td>
<td><p><sup>.2055</sup></p></td>
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</table>

#### ^[Rural\ Communities]{.underline}^

·
**^The\ data\ show\ that\ the\ average\ yields\ for\ city-pair\ markets\ involving\ rural\ small\ communities\ are\ higher\ in\ every\ mileage\ category\ than\ those\ for\ city-pair\ markets\ involving\ non-rural\ small\ communities.\ The\ percentage\ differences,\ by\ mileage\ category,\ range\ from\ four\ percent\ to\ twenty-one\ percent.^**

^We\ have\ examined\ fare\ data\ for\ the\ category\ of\ rural\ small\ communities,\ as\ directed\ in\ the\ legislation.\ The\ data\ show\ that\ the\ average\ yields\ in\ city\ pairs\ involving\ rural\ small\ communities\ are\ higher\ than\ the\ average\ yields\ in\ city-pairs\ involving\ non-rural\ small\ communities\ in\ every\ mileage\ category,\ ranging\ from\ four\ percent\ to\ twenty-one\ percent.\ The\ travel\ options\ that\ exist\ for\ urban\ passengers,\ whether\ they\ consist\ of\ substitute\ airports\ or\ entirely\ different\ modes\ of\ transportation,\ are\ often\ not\ available\ in\ rural\ small\ communities.\ This\ lack\ of\ substitutes\ translates\ into\ an\ inelastic\ demand\ for\ air\ travel,\ which\ in\ turn\ allows\ the\ airlines,\ like\ any\ profit-maximizing\ firm,\ to\ charge\ higher\ prices.\ ^

^Additionally,\ smaller\ passenger\ bases\ at\ rural\ communities\ may\ result\ in\ load\ factors\ that\ are\ low\ relative\ to\ load\ factors\ at\ small\ urban\ and\ hub\ communities.\ Airlines\ are\ only\ able\ to\ match\ the\ supply\ of\ seats\ offered\ with\ passenger\ demand\ to\ a\ limited\ degree\ because\ the\ number\ of\ seats\ on\ an\ airplane\ is\ relatively\ fixed.\ The\ use\ of\ smaller\ aircraft\ is\ one\ way\ to\ moderate\ the\ possibility\ of\ low\ load\ factors.\ However,\ the\ unit\ cost\ of\ operating\ aircraft\ increases\ as\ the\ size\ of\ the\ plane\ decreases.\ Therefore\ the\ use\ of\ smaller\ aircraft\ to\ maximize\ load\ factors\ in\ rural\ communities\ may\ justify\ somewhat\ higher\ fares.^

# ^[Jet\ Competition\ at\ Small\ Communities]{.underline}^

·
**^Average\ fares\ for\ small\ communities\ receiving\ jet\ aircraft\ service\ do\ not\ differ\ significantly\ from\ average\ fares\ for\ small\ communities\ served\ exclusively\ by\ turboprop\ aircraft.^**

·
**^The\ data\ show\ that\ communities\ large\ enough\ for\ jets\ are\ also\ large\ enough\ to\ support\ competitive\ service.^**

^Of\ the\ 73\ small\ communities\ served\ with\ jet\ aircraft\ (for\ our\ purposes\ large\ aircraft\ having\ more\ than\ 60\ seats)\ all\ but\ three\ \--\ Aspen,\ CO;\ Macon,\ GA;\ and\ Greenbriar,\ WV\ \--\ have\ competitive\ jet\ service.\ Since\ so\ few\ communities\ are\ served\ with\ large\ aircraft\ by\ only\ one\ carrier,\ it\ is\ difficult\ to\ draw\ any\ meaningful\ conclusions\ based\ on\ a\ comparison\ of\ fares\ between\ communities\ with\ competitive\ jet\ service\ and\ communities\ with\ a\ single\ jet\ service\ provider.^**^\ ^**^Rather,\ the\ data\ show\ that\ communities\ large\ enough\ for\ jets\ are\ also\ large\ enough\ to\ support\ competitive\ service.^

^A\ comparison\ of\ average\ yields\ for\ the\ city\ pairs\ of\ small\ communities\ served\ with\ large\ aircraft\ vs.\ communities\ served\ exclusively\ with\ medium/small\ equipment\ (under\ 60\ seats)\ does\ not\ indicate\ any\ material\ difference\ in\ yields.\ Furthermore,\ the\ wide\ variance\ in\ average\ fares/yields\ for\ city\ pairs\ of\ large\ hub\ communities,\ which\ all\ receive\ competitive\ service\ with\ jet\ aircraft,\ is\ further\ proof\ that\ the\ size\ and\ type\ of\ aircraft\ is\ not\ an\ overriding\ determinant\ of\ fares.\ While\ aircraft\ costs,\ both\ acquisition\ and\ operating,\ may\ be\ a\ major\ decisional\ criterion\ affecting\ whether\ the\ community\ will\ be\ linked\ to\ a\ network\ and\ the\ equipment\ size\ used,\ it\ may\ not\ be\ so\ important\ in\ setting\ fares.^

# ^[Related\ Findings\ and\ Analytical\ Considerations]{.underline}^

A notable feature of the available fare data is the wide variance in
average fares and yields between communities as well as between
city-pair markets at the same community. Fares and fare structures
appear to be based on individual city-pair market circumstances, not
generic or universal community factors. This appears to be the case for
both small communities and hub communities. To demonstrate, for the hub
communities, the average yields in markets in the 501-750 mile category
ranged from 10.34 cents per mile to 40.83 cents per mile, a
significantly wide range. We know from other studies that the presence
of low fare competition is a major factor explaining some of this
variation. Even when we limited our comparison to markets without low
fare competition, however, there is still a significantly wide range of
average fares. For the 336 small communities with markets in the same
501-750 mileage category, the range was 12.73 cents per mile to 68.71
cents per mile. Here, however, low fare competition is not a major
factor, since there is extremely limited low fare competition at the
small communities.

Wide variances in average yields and fares occur in every mileage
category for both hub and non-hub communities. This suggests that high
average fares are not just a function of the size of the community or
market. Nor are high average fares just related to the level/type of
service being provided since, again, high fares occur in
communities/markets served exclusively with jets and by major carriers
as well as in communities served with small equipment and by commuter
carriers.

^Another\ interesting\ characteristic\ of\ the\ fare\ data\ is\ how\ widespread\ lower\ average\ fares\ are\ in\ leisure\ markets\ for\ all\ communities\ --\ small\ or\ hub\ --\ and\ how\ comparable\ leisure\ market\ fares\ are\ for\ both\ small\ communities\ and\ hub\ communities.\ A\ sample\ of\ city-pair\ markets\ for\ Orlando\ shows\ that\ fares\ in\ the\ small\ community-Orlando\ markets\ appear\ similar,\ for\ the\ same\ distance\ categories,\ to\ the\ fares\ for\ hub\ community-Orlando\ markets.\ We\ did\ not\ do\ a\ complete\ analysis\ of\ leisure\ market\ data.\ But\ this\ phenomenon\ with\ respect\ to\ leisure\ markets\ was\ observed\ repeatedly\ for\ both\ small\ and\ large\ hub\ markets\ to\ Florida,\ Las\ Vegas\ and\ Hawaii.\ In\ discretionary\ markets,\ the\ elasticity\ of\ demand\ as\ influenced\ by\ the\ willingness\ of\ travelers\ to\ substitute\ other\ products\ (other\ air\ destinations\ or\ vacations\ by\ car)\ may\ be\ the\ primary\ determinants\ of\ fares\ rather\ than\ distance,\ the\ level\ or\ type\ of\ air\ transportation,\ or\ even\ the\ availability\ of\ competitive\ services.^

The above observations demonstrate that there are many characteristic
differences between markets that may account for variations in fare and
passenger levels. These characteristics are not always reflected in
comparisons of average fares/yields. A more detailed analysis and
comparison could take into account, for example, differences in the type
of travel (e.g. discretionary vs. nondiscretionary), the types of
tickets purchased (restricted/nonrefundable vs. changeable/refundable),
the size of the market (density), the cost of providing service, and the
level and type of competition, among other things.

[^1]: ^\ Low-fare\ airlines\ in\ this\ analysis\ were\ identified\ using\ the\ same\ criteria\ applied\ in\ the\ Department's\ ^*^Low\ Cost\ Airline\ Service\ Revolution^*^,\ released\ in\ April\ 1996.\ ^*^The^*^\ ^*^Low\ Cost\ Airline\ Service\ Revolution\ ^*^employed^*^\ ^*^unit\ costs\ and\ pricing\ practices\ as\ the\ basis\ for\ defining\ low-fare\ service.\ To\ be\ considered\ low-fare,\ a\ carrier\ should\ maintain\ low\ fares\ relative\ to\ prices\ charged\ by\ other\ carriers\ before\ it\ entered\ a\ city-pair\ market.\ ^