east-west airlines' sydney-melbourne service: market expansion or demand diversion?

East-West Airlines’ Sydney-Melbourne Service: Market Expansion or Demand Diversion?

PETER HARTLEY CHRIS TRENGOVE Rice Universiry Centre of Policy Studies, MoMsh Universiry.

and CIayton, Victoria 3168 Centre of Policy Studies, and

hionash University, Clayton. Victoria 3168

Data on 1278jlights on the East-West Airlines Sydney-AllxuyMel- bourne services, beginning when the Sydney-Melbourne excursion fare was first offered, are used 10 estimate three demand curves for the jointly provided services. The elasticities of demand for the Sydncy-Mclbourne service suggest it expanded the market as much as it attractedpassengers from the trunk carriers. The econometric problem ofjoint estimation with censored dependent variables should be of general interest.

I Introduction This paper presents estimates of the demand for air

travel on an Australian domestic route operated by a non-trunk carrier. The service in question is that flown by East-West Airlines (EWA) between Sydney and Melbourne, via the intermediate stop of Albury. The demand estimation is of interest for two distinct reasons. First, the price elasticities and other determinants of demand an of interest inasmuch as they relate to certain assumptions which underlie Australia’s Two Airlines Policy (TAP), and to the way in which new competition may emerge when that policy is abandoned in 1990. Second, the estimation serves as an example of the sorts of benefits to be had (and difficulties arising) from estimating demand using highly disaggmgated data, as against the use of data sets aggregated over time periods and, often, across suppli- ers of a particular good or service.

The prime intmt of the TAP is to limit the right to offer air service on trunk rwtcs to two designated canicrs; namely, Ansca Airlints of Australia (Ansen) and Ausealian Airlines (AA). ”hi3 intent is achieved by defining ‘tnmk routes’ m terms of the connections between any of a list of specified aqotts. Two trunk route airports can be ‘connected’ indmtly, however,

by providing service into, and out of, an intermediate non-trunk destination. Thus, while the air journey between Sydney and Melbourne is not an espzcially long one, the existenct of a sizable provincial town, Albury, part way betwLm them. raises the possibility of competing on this particular trunk route by offering an indirect service.

In March 1983, EWA, which for many years had been he sole canier opcrating between Sydney and Albury. received pemussion to offer such an indirect service between Sydney and Melboumc. This permis- sion came in the form of approval, by the Independent Air Fares Committee (LWC), of an ‘excursion’ fare for travel between the two cities. At the time this fare amounted to a discount of mox than 5 0 per cent on the standard economy fares of Ansca and AA.

The background to the service, and the legislative provisions which g o v m indirca flights between eunk centres. are detailed in Apprndix 1. In summary, the new service attmxcd a degree of controversy, which

tinue approval of the excursion fare fimn June 1983, and EWA’s prepation of a legal challenge to the constitutional validity of the TAP (both of which were eventually dropped). F m the point of view of the

W ~ S IK) doubt fuelled by the IAFC’S decision to discon-

203

204 M E ECONOMIC RECORD S E P E M B ER

regulators. the issue of substance was the extent to which passengers flying on the Sydney-Melbourne via Albuq service were merely being "diverted' from the two trunk carriers, or whether they constituted a net addition to air traffic, either through diversion from other transport modes. or through the generation of additional trips.

In order to examine this question further. the former Bureau of Transport Economics ( B E ) (now the Bu- reau of Transport and Communications Economics) conducted a series of passenger surveys. These surveys (which are further discussed in Appendix I , and are reported in BTE, 1985) produced three types of result of relevance to the econometric estimation. First, they attempted to quantify the mix of EWA passengers in terms of those diverted from the trunk carriers, those diverted from other transport modes, and those who othemise would not have undertaken the journey at all. Second, they provided demographic and trippurpose information on EWA passengers, as against those flyingon Ansett-AA fullanddiscount fares. Inparticular, they found that EWA passengers possessed chancter- istics substantially similar to those of the trunk carriers' discount fare group. Finally. they estimated elasticities of air transport demand on the Sydney-Melbourne route as a whole, obtaining figures of - 1.3 for standard fare passengers. and 4.2 for discount passengers.

Standard welfare analysis would suggest that expansion of the market as a result of the introduction of the new service would be welfare increasing. Even in the case of traffic diversion from the incum- bent carriers, however, competition from the new service might improve resource allocation. Prior lack of competition might have helped sustain inefficient production techniques, prices in excess of marginal costs, or inefficient service characteristics. including inefficient flight schedules.' Successful cornpetition on the part of EWA would then apply pressure on the trunk carriers to eliminate sources of inefficiency. and/or lead to expansion in the market shares of more efficient airlines. The underlying policy rationale of the regulations, of course. was rather different, maintaining that provision of an efficient domestic air transport system relied upon

The efficiency of the Australian air ~ p o n system under~TwoAirtinesPolicyhasbemcwninedinanumkr of pepers including %vies (1977,1980). Forsyth and Hock- ing( 1980). Hocking( 1979),Kihy( 198 I)andGannon( 1979). An imponant issue in this literature. but one which is not relevant to our current sfudy. is the relative efficiency of public versus private operators.

I

reservation of tile entire trunk market to two camers, presumably for reasons based upon market size and economies of scale.2

In this paper we estimate the effect of relative prices on the demand for travel on the EWA service. In articular, we obtain estimates for the (cross) elasticity of demand with respect to the AA relative price, and with respect to the relative prices pertaining to other transport modes. These elasticities enable judgements to be made as to the extent to which the EWA service CM, or cannot, be considered a close substitute for the direct flights or for other tmsport modes. High elasticities with respect to the priceofdirect services would be suggestive of substantial tnffic diversion-a potential regulatory concern. Conversely, large elasticities with respect to, say. bus or train fares, suggest an expansion of total demand to fly from Sydney and Melbourne with the introduction of the EWA service. This would be indicative of an overall increase in consumer surplus and presumably would be of less concern to the regulatory authorities.

Our methodology differs from that employed in many other transport demand studies because of the highly disaggregated data used. We were p t e d con- fidential access by EWA to passenger loads on the Sydney-Al bury-Melbourne services for approximately five quarters from the date of their introduction. These data included deparmrc times and numbers of passengers carried on all flights on the routes, as well as the type of aircraft flown and the aircraft capacity. The

The airlines agreement attached to the Airlines Agreement Act of 198 I notes that ' . . . i t is expedient in the opinion of the Commonwealth to make provision for the purposes of ensuring:

a. the efficient and amomic operation of air passmger

only two operators of air parscnger services overthe entire

serviceswifhinAusaalia;and b.drconfinucd&stcnccincompetltionwith&ocherof

Dunk nmuOrtr witfiin Ausnalia' Similar words have been attached to previous airline agree- ments. although initially it is undoubtedly the case that the prime intention was to ~ S U R the survival of or /cast two competitors rather than prevent the entry of morc than two carriers. Over time. the thrrat of monopoly has greatly dimin- ished as the m d e t has p r m and technolog~d change has lowered costs. Whether or not there are scak ccmomies in providing trunk route air services in Australia is a hotly disputed issue. It is not a simple matter to calculafc returns to scale in airline service. Larger planes flying at less frequent intervals impose atirne cost on passengers. In addition. planes cannot be added to serve a single route without regard to passenger loads on the rest of the network.

1990 EAST-WEST AIRLlNES 205

econometric and modelling issues relate to the prob lems associated with jointly estimating separate demand curves (in our case, Sydney-Melbourne, Syd- ney-Albury. and Albury-Melbourne) in a situation where. for a number of observations in the sample, one or more of the actual demands is not directly observed due to capacity restrictions. In other words, we must estimafe a set of demands which is jointly supplied subject to a short-run supply curve which is (approximately) horizontal up to some fixed capacity limit Our study therefore may be of more general interest to applied ecollomists and econometricians, since the supply curve will take this form whenever some limited capacity is made available at a fixed price, as will often be the case with microeconomic data sampled at frequent intervals.

In Section I1 we discuss the econometric issues and develop the model to be estimated. The independent variables used in the analysis arc discussed in Section 111. Section IV presents the key parameter estimates. Finally. Section V relates these estimates to the policy questions mentioned above, both in the context of the TAP, and the move towards domestic airline deregulation, and concludes with some comments on the relative merits of this type of demand study as against approaches based on more highly aggregated data.

I I Econometric Issues For roughly onequarter of the observations in our

data set. the number of passengers is equal to the capacity of the plane. As long as the observed number of passengers is less than the available capacity, demand is assumed to equal the number of passengers observed flying. Otherwise. when the observed number of passengers equals the available capacity on the plane we do not know the exact demand to fly at that time. but instead observe a truncated dependent variable. Conse- quently, we have to estimate a Tobit-type regression?

To illusaate how one evaluates the likelihood function in such a case, assume thc true demand curve is given by:

with y, observed if y, < C, and C, observed otherwise. In the Tobit regression model, the likelihood function consists of two parts. For observations which arc not constrained by capacity, the log likelihood is just given by the usual log density evaluated at u, = yr - X r B . For

Useful references for discussions of similar problems includcTobm( l!X8).Heckman( 1976.1979). Maddala( 1983) and the survey article by Arnemiya (1984).

Yr =X ,B+u, (1)

observations where demand is constrained, since any outcome for the random variable ur 2 Cr - Xr/3 will be mapped to the observation zr = C,. the log likelihood is thelogoftheprobabilitythatu, 2 C , - X , / 3 .

A complication in our case is that capacity is provided jointly to two sets of demanders. Focusing on southbound traffic, the routes of interest can be repre- sented schematically as in figure I . The planes fly from Sydney (SYD) to A l b q (ABX) and Albury to Mel- bourne (MEL). On the plane between Sydney and Albury will be some passengers who want to fly 'locally' from Sydney to Albury and others who want to fly 'through' Albury ( i t . transit at Albury for Mel- bourne). Therefore, when the Sydney-Albury flight is full. the sum of the demand to fly Sydney-Melbourne and the demand to fly Sydney-Albury is greater than or

. SYD

\/ MEL

FIGURE 1

equal to the observed capacity of the plane. In terms of calculating the probability of observ-

ing a capacity constrained flight. we know that the sum of two demand shocks must exceed some value, and also that the limited available seats have been allocated to the two se~s of demanders in a particular ratio. Presumably. the observed ratio of seats allocated to local and through traffic reveals some information about the relative strength of demand from the two groups of passengers. In order to use this information to aid in estimating the effects of the independent variables on demand, we need to specify how excess demands are rationed to the observed

THE ECONOMIC RECORD SEPIEMBER 206

number of passengers of each type. Available seats on airrraft arc never allocated corn-

pletely at random, or simply on a k s t come first w e d basis. Rafher, airlines rtserve blocks of seats for passengers flying on different fm and on different routes.

the deparmrr time a p p m h e s , the mewed bids of seats arc tiud up to be sold to otha passengas, since virtually any revenue which can be obtained for the scat is preferable to flying it vacant4 Passmgen who are less sensitive to the exact time of dcparmn can also be encouraged to take a later flight if the plane is full at check-in time. In this way, seats previously allocated to a particular class of customer can. at the last moment, be reassigned to other customers.

The rationing mechanism typically used by airlines will therefore impart a systematic bias towards serving some categories of customers in preference to others, but it also contains a significant random component. We shall approximate this complicated rationing proc- ess by assuming limited seats are allocated on the basis of a deterministic rationing scheme which gives priority to the local traftic on the Sydney-Albury flights. We were informed by EWA that it sets aside a high proportion of seats on its Sydney-Albury flights for Sydney- Albury passengers, particularly in the moming and afternoon. These seats are only released to passengers travelling through Albury to Melbourne as the depar- ture time approaches. Furthermore. on many occasions in the period during which our data were collected, additional aircraft were flown when the demand to fly from Sydney to Albury was particularly high, such as the beginning and end of NSW school holidays. There are at least two reasons for EWA to structure

its booking system to favour Sydney-Albury passengers. First. in strictly commercial terms, the Sydney- Albury market is likely to q u i r e a 'higher quality' service than the Sydney-Melboume market, in terms of seat availability. As emphasized by the BTE surveys, the Sydney-Melboume passengers carried by EWA form a distinct subset of the Sydney-Melbourne mar- ke t It is probable that these passcngm are likely to be less concerned about actual travel time than passengers paying !ill economy fares. Thc Sydney-Albury market, on the other hand, is likely to contain within it a stmngerelemcnt of timc-sensitive business traffic. and

It may be pttferable to fly the scat vacant if expectations of passmgm arc takm into accoMt If passmgm Come to believe they can always. or even often. obrain a low priced seat by delaying their booking time, the airline might make more money by flying empty seats and not allowing sales at the last moment.

this type of passenger would demand (and be willing to pay for) greater seat availability.

The second reason for priority beiig given to the Sydney-Albury aa!?ic is that, even if it were not in EWA's commercial intmst to guarantee seats to these passengers, the legislative provisions surrounding indirect services under the TAP (see Appmdi I) would give it a noncommercial interest in max'mizing local traffic. The airline may also have wished to provide better m i c e to Sydney-Albury passengers if it felt that any degradation in service might have compm- m i d its standing with the NSW State government and thrcatcned its status as a monopoly carrier on the route.

Returning to the model, it can be repesented alge- braically as follows. Let

y,, = demand to fly Sydney-Melbourne on flight r. yt, = demand to fly Sydney-Albury on flight r, and yJ, = demand to fly Albury-Melbourne on flight r .

We assume that:

where the independent variables X/ , , X,,, X,, include relative prices, the industrial production index, and various dummy variables as discussed in the next section of thepaper. Also we suppose u,,, u ,~ . u3,, are normally distributed and contemporaneously correlated. The error terms represent influences on demand which are not captured by our independent variables or are poorly measured by them. The con- temporaneous cornlation between the errors allows these influences on demand to be comlated across the different markets.

Let the capacity of the Sydney-AIbury flight at t be C,, and of the Albury-Melbourne flight at r be C2,. Then if

we o b s m e yzr If we also have:

we also observe the actual y I , and yJ,. Ifeirhery,,+y2,2 C,,ory,,+yJ,lC2,thenyl,isnot

1990 EAST-WESTAIRLINES m less than the observed value Z,, but we do not know its exact value. Similarly if:

Y,, + yzr 2 c,r then 'true demand', yzf is no less than zzr, the observed value, while if:

To evaluate the log likelihood under a deterministic rationing scheme, we need to specify a funcriomI mapping from true demands (and thus error terms) to the observed outcomes. If a given triple of values for the uir maps into more than one set of observed values, we cannot evaluate the likelihood of obtaining any given outcome. For example, if we assume that whenever

true demands y,, and y2, can be any values y,, Z z,, and y2, 2 z2, then the probability mass associated with a given (>,,, yz,) cannot be mapped uniquely to an o b served ( z , , , zzr).

*I y3+ FK~URE 2

h Figure 2, the shadcd area COmsJWnds to the possible observed values of (z,, z2) when the capacities are C, and C,. To calculate the probability of obtaining any givm wtcome of demands, we netd to specify how excess demand is rationed, or, in terms of Figure 2, how points outside the shadcd region an mapped to points

on ttu: fmderoftheregion. Thus, faexampk, ifeach point to the rKmkast O f D can be to any point on the fiuntieroftheobsavatiori~mAC,.wecarmotolculate thc pobability of obsaving any given point on AC,.

ThCSimpkStWaytoincorpaahtZ%IlZWHpiUlthat priaity isgivcn t o l d traac is toas9lnE tfiatwtnrva aplantisfull,dmughtraffichasbccn~ . artsothat Y , , q , ~ ~ -di;,e4uals**Y* and obsaved z3, equals m e danand yjr nis ratiaring as- slllqxlmcanberrpsentcdasinW~3.Allpointstothc right ofAC, maphorizaually tothcaxFespadm . Ppointon AC, and similarfy for points to thc right of SC,.

If we denote by T, the subset of observations for which at least one plane is full. and by T2 the remaining

V

'lf

*h- I \+

observations, the log likelihood becomes (assuming the uif are normally distribited)

208 THE ECONOMIC RECORD SEPTEMBER

We shall refer to the maximum likelihood estimates &r this truncation assumption as estimates I. Oneprob~emwiththisrationingassumptimisthatin

thosc cases where zlr zZr = C,, and I,, = 0 we implicitly assume z2r measures true demand to travel from Sydney to Albury? In terms of the diagram, we assume pointA is obtained only when y,, = C,, andy,,10 and that the probability of observing points to the northeast of A is zero. This amounts to an implicit assumption that local demand to navel Sydney-Albury is never sufficiently large on its o w n to exhaust available capacity6

A more complicated rationing scheme is to assume that in those cases where either plane is full and :,, > 0,

measure true demand to travel locally whereas y,, Z I,,. while in those cases where z,, = 0 and z,, = C,, (that is. the Sydney-Albury plane is full and observed through M i c is zero), we assume y,, 1 z2, and no information is provided on the value of y,!. In other words, we still assume that priority is given to local over through traffic, but supplement this with the assumption that demand on the Sydney-Albury service might be so large that not only is through traffic constrained out, but the observed patronage on the Sydney-Albury route might be less than demand. In terms of the diagram, we assume that point A is observed whenever true demand is any point to the northeast of A. Other points along AC, are obtained whenever true demand is any point to the right of the point on the frontier under consideration.

If we now let T, be the set of observations for which :,, = 0 and zIr = C,,, T, be the set of observations for which I,, + = C,, but :,, > 0. and T3 be the remaining (non-truncated) observations, the log likelihood function becomes':

and

There arc no cases in our sample where :,, + iJr = C,, and either

The diagrams have been drawn as though capacities C, and C, arc constant. The argument is not altered by incorporating the fact that the available capacities vary from one flight to the next.

= 0 or zJr = 0.

assumption on the truncation of demand shall be re- f e d to as estimates II.

A problem with both huncatim modcls I and Il is rhat

and Albury-Metboume arc related deterministically when tkyimplicitlyassumetruedemandstofly Sydney-Albury

both planesarc full and:, >o. I n k latIe!rcase,bothmodels assume y , 2, =y2 and z3=y3. In other words. when

Y j = Y,+c,-c,

both plants arc full and :, > 0 we implicitly assume true Y, and y3 coincidentally take the related values:

For I9oftheobsmatim in the sample (roughly 1.5 per

Fmm 4 3

' that

From the computational point of view. it is useful to note

- lexp[@(ul ; U 2 : 2 3 r - X 3 r P ) )Idul

-0a

is a bivariatc normal density with inverse variance-covariance matrix given by:

v- - vlz 1 VI " v 3 - I V i 2 V I ) ) 1 VI I when

'I3 '23 '33

is the invcrsc of the variancecovariance mauix of the original mvariate nand density. n u s for r E we must evah~ate a truncated bivariate normal density.

1990 EAST-WESTARLINES 209

cent)weobservebothpbnesfullandz,>OThismayappear tobetoohighapoporrionofreWotmvatimunlcss~ and u., arc sufficiently positively correlated.

An alternative model which does not have this implication is to assume that while local MIC is given priority on the Sydney-Albury route, through traffic is given priority on the Albury-Melbourne leg. This rationing assumption, which is illustrated ill Figurc4, then amounts to the following. When local Sydney-Albury demand (y2) exceeds available Sydney-Albury capacity (C,), rhmugh demand (Y,) is conshained to zero and 1ocalSydney-Alburydernandisalsocons~ed.When Y2 does not exceed C, but the sum of y2 and y, exceeds C,. through traffic is rationed to z, = C , - y2. Given the through traffic detennined on the fint leg, local Al- bury-Melbourne traffic CV,) is then rationed if the sum of z, and y., exceeds the available capacity.*

The maximum likelihood estimates (III) obtained under this rationing assumption are obtained by divid- ing the sample space into five regions. As before, we let TI be the set of observations where observed through M i c is zero. yet the Sydney-Albury plane is full. That is. for I E .y2 > z2 and y,can have any value. We let Tz be the set of observations where only the first plane is full but z , > 0. Thus for t E T2. y, 2 z,,y,, = z2. andy3= iy For r E T, only the second plane is full, so that y, =

z, , y2 =j2 but y3 2 z3. Both planes are full for t E TI. In this case. y, 1 zI and y3 1 z., and only Sydney-Albury demand is observed (y, = z2). In the remaining set of observations (Ts) neither plane is full and observed passenger flows are assumed to equal me demands. The log likelihood function now becomes:

The relationships between the variables y,, z, and

L = zlog[ 7 ~ ~ x P [ O ( U I ; U ~ ; Z ) ~ -x3,&)lh2du,l rerl -- Z2r-X2r&12 -

+ Clog[ jW9(u,;zzr -X21&;z3, - X , , & ) l 4 1 rch f ~ r -x1r81 ..

+ clog[ IexP [ # ( Z l l -Xl rS1 ;ZZr -X2 ,&;Uj ) l~31

zYr-x3th

+ clog[ j jup[~(ui ;22r-~,ra;u,) jdujdul l

+ t €T , C#(ilf -XlrSIJ2r -X2rS2J3r-X3rS3) )* (8)

ref4 21, -xlrBI '3r-X3rf93

Ci under the three demand rationing assumptions discussed above are set out in Table I .

The maximum likelinood computations were done using the Berndt. Hall, Hall and Hausman (1974) modified Newton method of approximating the second derivative matrix by the outer product of the first derivative vector. Ali probability integrals were evaluated numerically using Simpson's method. Or- dinary least squares estimates. treating the observed passenger flows as tm: demands, were used to provide starting values for the f l parameters and the variances and covariances of the u,'s. The convergence criterion was thilt the maximum proportional change in any parameter be no greater than 0.05. We estimated 79 parameters using 1278 observations.

111 Explanatory Variables In order to both simplify the model to be estimated

and reduce the number of data observations, we (arbitrarily) decided to restrict attention to southbound traffic. That is, we jointly estimated three demand curves for flights from Sydney to Melbourne, Syd- ney to Albury and Albury to Melbourne. This should not affect our results 100 much since the predomi- nance of return journeys should imply that north and southbound traffic are closely related. Even restrict- ing attention to southbound traffic left us with 1278 flights on two routes (hut satisfying three demands).

Previous regression studies of air transport demand have used more aggregated data than we arc using, but in either case the independent variables of most importance are expected to be the relative prices of air travel and some measure of i n ~ o m e . ~ Other independent variables of potential interest to us are quality of service variables (trip time, passenger comfort and so on) inasmuch as they affect the demand to travel on indirect versus direct flights. or air transpon versus other modes of transport.1o Also,

our data set doa aatcontain any Observations w h I x both p h m an full pad citurz, = C,. cxz3 = C,. Thus n c i h r point B nor C, is obsmed. If e i h point had ban more cmnmm. this might have plovidtd evidencc in favour of one orothaof the fnurrtioa rmdeh norm.

SeeforuampleBritishAirporrsAumority(BAA1981). rppollto (1981).Taoeja (1WS)and J u g adFuji (196). The focus m the efkct of priccs aod inoaae (oroutplt) is a k t application of rkmaad theory for a qmenta t ive individual (or fum). Tmvel time as an imponant non-monetary price is routinely emphasized in vansport studies.

8

210 THE ECONOMIC RECORD SEPTEMBER

TAgLEI

Relarionhips Between D e e (y,) and Observed Passengers (4 ) under the Alternative Rationing Schemes

observed passengers and plane sizes’

z1 +z2 4,; z1 +z3cc2 z1+z2=C1; z1+rjcc2; Z1>O

:1+z2=c,; z1+z3<C2; Z I = 0 zI+z2<cI; z1+z3=C2 zl+:2c,; z1+z3=; :,>O

It1 Y I Y2 Y3

a Some of the logically possible values for z, , :*, zp C, and C2 do not occur in o u r data.

and in contrast to aggregate studies. we are in a posi- tion to estimate daily, weekly and Kasonal demand fluauations. Although these influences on demand arc of considerable interest to airlines, in the past they have tended to be estimated using crude averaging or time-

Om focus is on substitution between the EWA air service and related products, so the relative prices of most interest arc the EWA air fares relative to other fares. We obtaineddata on train and bus faresas well as

tution between the EWA services and driving we included the EWA fare relative to the ‘indicarive automo- tive gasoline retail price’ published in Major Energy Statistics by the Depamnent of Resources and Energy.

A difficulty with the transport price variables is that concessional and regular fares for any given operator typically changed on the same dates and the relationship

series techniques.

EWA and competitive air f-. TO f a substi-

l o lppolito (1981) also includes flight fnqucncy and load facron~qualityofsmiccvariabks.~lytbeupcrrcd value of mac variables hflumca demand, and it is not clear howthacexpatatioassbouldkmodckdinoursample.For example. ProSpbFtivc pruenga3 at me agirmino and end of school holiday periods m doubt expect to fiad it hnder to obtain ascat than inoff-palrpaiods. mdthisupectltion probrMy dccrrrses &maDd below wimt it might omawise have been. ’nu? interp#atiaa of Q CoeffiCLnu al our durmny variabk3 is afkled, kn Q set of- inde- pendent Variables is not nu, dK dummy for dditional demand in school holidays is to k intnprrted as demand wr of any decrrase resulting from an expected deterioration in service quality.

between the different fares remained almost constant. However, examination of the EWA data on passengers carried in different fare categories indicated that most EWA passengers flew on just one of the fares. For example, Sydney-Melboumetraffic predominantly flew on the special excursion fare, and Sydney-Albury aaf- fic on the full economy farc (or fares aconstant multiple of the fill economy fare). We also concentrated on the full economy fare as the most relevant EWA fare on the Albury-Melbourne d c e . While the excursion fare remained below the full economy fare over the entire period, it was restricted in availability so that most passengers flew on the full economy fare. with many of the rtmaining flying on fares such as ‘ClubZ’, ‘Golden Oldies’ and advance pchase which werc closely related to the full economy fare. Part way through our sample (on 4 May 1983). the

Ansett subsidiary, Airlines of NSW (Air NSw), began a Sydney-Melboume service which touched down at Albury but did not pick up or let down passengers at that pai The fares charged on this service wert similar, but not identical, to EWA’s excursion fare and changed at different times. The variable E W M is zero up to 4 May 1983andequaltorheEWA excursion farcdivided by the Air NSW fare thereafter. In effect, we have assumed the price of the Air NSW service is intinite up

‘1 East-west Airiines has a monopoly on the intrastate Sydney-Altnuy service as a result of NSW Srate government policy. Supposedly in ordcr to remain in compliance with the legislative provisions discussed in Appendix 1, the Air NSW flights landed at Albury so they could not be said to be adirect flight from Sydney to Melbourne.

1990 EAST-WEST AIRLINES 21 I

TABLE 2 Dwnmy Vambles Included in the Regressionf

Variables

FT I-n 3

MON-SAT

HOL I-HOL 3

PSBE. PSAF

Definition

Time of day of flights

Day of the week

Beginning, middle and end of school holidays

7 Days before and after April 1984 pilot strike

Omiued Category

special flights

Sunday

normal schedule

normal schedule

' Together these variables and thne constant terms accounted for 45 p a r i i t e r s in the regrrssions.

4 May 1983. As far as Ansett and AA arc concerned the major

change in fare relativities during the sample period was the incrcasc in the standby fare from 75 per cent of full economy to 80 per cent of full economy on 1 July 1983. We included a dummy in the Sydney-Melbourne regression which is 1 from I July 1983 to attempt to account for any incrcase in demand as a result of this change.

We included the EWA air fare nlative to the quar- terly all items collsumer price index for Sydney (on the Sydney-Melboume and Sydney-Albury routes) and Melbourne (on the Albury-Melbourne route) to measure substitution between the EWA services and all other goods and smices. In the aggregate studies of airline demand. it is typically only the lmer relative price variable which is included since the passenger loads on all airline competitors on a given route arc added together. Furthermm. this single 'own-price' of air transport is relied upon to capture substitution between air travel and other cran~port modes, as well as between non-transport goods and services.

To account for income effects on demands we in-

sion. We chose this variable rather than a broader measure of nal income since it is available on a monthly basis. While it might be a satisfanory m u r e of

Melbourne, the industrial production index is likely to be apoormeasun of income effects on the demand for local services to and from Albuy. We know of no

district, let alonc one available on a monthly basis.

cluded tk industrid production in&x in W h r e p -

income efftas on the demand to fly fiml Sydney to

satisfaaory measure of rural wtpu in the Albury

We constructed a dummy variable JET which takes

the value 1 if the plane flying (only Sydney-Albury) is the jet-engined Fokker F28 and 0 if it is the turbo prop Fokker F27. It is the only measure we have of the effect of shorter travel time on demand. However as we note below, the J f l variable might reflect other influences of jet aircraft on demand (such as more comfortable travel), or, more impcrtantly, a supply responsc of EWA to higher demand.

Two variables were calculated in a crude mempt to account for spillover of demand from earlier flights to later ones. The variable PFSD is the total number of passengers (on the given mute) who have flown on the previous flights on the same day as the cumnt flight. while P D is the total number of passengers flown on the same route on the previous day.

The tables presented in the text and Appendix 2 report estimates of the effects on demand of the above variables. In addition we included a set of dummy variables in the regressions to caprurt time of day, day of week, seasonal and other effects. These variables arc summarized in Table 2 Many of them were estimated to be statistically significantly different from zero at very high levels of significance. Estimates of the time of day, day of week and seasonal dummies arc important to the airlines for 1eVdinf3 the intertemporal paatm of ckmand. and also could be of aoromic interest inasmuch as they rcveal potential consbaints on demand due to timetabling. HOWWCT, they have not been re- p o d in order to protect the confidlcntiality of our data

lime im-t variables we would very much like to have included if they had been available arr the advance notice the individual had of his intention to undertake the trip, the purpose of his trip, and the number of individuals travelling in a group. The size

212 THE ECONOMIC RECORD SEPTFMBER

TABU 3 Estimates of Key Demand Parameters for Sydney-Melbourne Trafic

(key components of

Indep. Estimated Elasticity at Estimated Elasticity at Estimated Elasticity at Variable‘ Coefficient var means Coefficient var mean Coefficient var means

(Ub (1) (11) (11) (111) (111)

EWIB

EWIP

EWIAA

EWIWX

EWIBTS

C 251P

EWICPI

I P

ATSBY

JET

PFSD

PD

PI2

‘ 1 3

4.47 (2.08)

0.08 (0.13)

(52.78)

4.92 ( I .28)

- 1.00 (0.67)

-0. I7 (0.16)

I .05 (52.95)

I .05 (0.39)

0.66 (1.03)

6.57 (0.84)

-0.0 1 (0.02)

0.10 (0.02)

-0.3 1

-0.18

-13.06

-0.60 (0.39)

I .04 ( 1.54)

-0.53 (2.16)

-0. I8 (0.10)

-0.08 (0.10)

- I .62 ( 1.59)

0.04 (2.15)

3.% (2.12)

0.02 (0.03)

‘23 4 . 2 4

4.48 (2.08)

0.09 (0.13)

-13.34 (52.84)

4.93 ( I .28)

- 1.00 (0.67)

-0.17 (0.16)

1.21 (53.02)

I .05 (0.39)

0.65 ( I .03)

6.62 (0.84)

-0.0 I (0.02)

0.10 (0.02)

-0.3 1

-0.18

4 .24

-0.60 (0.39)

1.04 ( I 3)

-0.54 (2.16)

-0.18 (0.10)

-0.08 (0.10)

-1.63 ( I .59)

0.05 (2.16)

3.96 (2.12)

0.02 (0.03)

4.5 I ( 1.99)

0.08 (0.12)

- 17.00 (50.03)

4.94 ( 1.33)

- 1.03 (0.64)

-0.15 (0.15)

8.48 (50.16)

0.97 (0.38)

0.62 (0.99)

6.40 (0.8 1)

-0-0 I (0.02)

0.09 (0.02)

-0.3 1

-0.19

4.23

-0.6 I (0.39)

0.90 ( 1.47)

-0.69 (2.05)

-0.18 (0.10)

-0.09 (0.10)

- I .37 (1.51)

0.35 (2.05)

3.69 (2.01)

0.02 (0.03)

a Asymptotic uandud errors in parrnrhoes. Thc d m (I), (II) and (IE) refen to the different nuncation assumpions discussed m Secaon n. Definitions of variables:

Ry E W A e x d m f a r e B Busfare AA Aasetr/Ausaalianfulleconomyfare WX Airlines of NSW ex~union fare BIS BusmPinstandbyfare C25 EWA Club 25 fare P Iadcxofpetrolprices IP Index of industrial production CPI Sydney all items consumer pnce index ATSEY AnseWAA standby increase dummy J E 7 s e e t e x t PD passengers flown on previous day PFSD passengers on previous flights same day P,, comlation between u, and u;

1990

Truncation Method

1

I1

111

EAST-WEST AIRLINES

Value of maximized log likelihood Changc: in log likelihood on last iteration

o.Oo0 395 5

O.Oo0 238 5

0.002 498 0

-12 216.807 676 5

-12 201.688 148 0

-12 233.146 728 0

213

of the travelling group probably would have been significant in explaining the choice between flying and driving. particularly on the shorter Albury- Melbourne route and, to a lesser extent, the Sydney- Albury route since individual fares may not ad- equately reflect the relative cost of having a group travel by air rather than car.

Despite the quite large list of independent variables included in our demand curves, we have no doubt that our regressions have omitted some important explanatory variables. Furthermore, we expect the omitted variables could well be correlated across equations. Accordingly, the error terms in the regression equations are likely to be correlated making it imperative. if efficient estimates for the panm- etemare tobeobtained,that theequationsbeestimated as a seemingly unrelated set.

N Marimwn Likelihood Estimates The maximum likelihood estimates of the key Syd-

ney-Melboumc relative pticecocfficients are presented in Table 3 with details of the maximized log likelihoods in Table 4.12 TIE c m p o n d i n g parameter estimates forthe two local demand curves are presented in A w n -

'' It is of intcnSttompam thc estimam in TaMe 3 with OLSestimatcsofthesmcequatiaLAsamwitofthconcction f o r r m r r a t i o n o f & m f m d , b r ~ plnarmschmgema d i r e c t i o n c a p i s p c n t w i t h ~ u p c c c a i o n r o f m e ~ o f mmcation ca me OLS atimam. % &xdllre Vahr ofthe coefiic*namEWIB,EWlAT,EWIWX.EWlBlS.~Pand IP d i r n a s ~ 0 m e o L s c s l i m r a I b e ~ o f t h e J E T d l m l m y ~ ~ % ~ e s t i m a a d c o m l a - rionrbamcnaralamsbrsedoatheoLsrtsidualswacp,2= 0.43,pu421 andpu=+0.24.Aswwouldurpca.axrsnng f o r t h e ~ o f m e d e p a d m t v s M M a ~ b r n t g a t i v c C a r r L t i a r p ~ ~ S ~ b a n r r a r O r a n d t h e C d l C f two QIo1s. 'Ihc canlation bcov&n u2 and u3atinwcd using maximum likelihood is margurally hi* than drat calculated frwl the OLS residuals.

dix 2. Table 3 also gives -he elasticities calculated at the variable means with standard errors calculated using a linear expansion about the mean.l3 MostpassengersflyingSydney-Melbourneon EWA

during this period did so on the excursion fare. The only other fare we include is the concessional Club 25 fare (colinear with the Golden Oldies fare). This would be used by Passengers in the appropziate demographic categories who wished to travel in just one dmtion. For return journeys the excursion fare was cheapcr.

The relative price variables included in the regression areEWIB.EWIP,EWIAA,EWIWX.RYIBTS.~IPand EWICPI. All of the relative price variables except EWI P and EWICPI have negative estimated coefficients. The most consistent substitute scrviccs for EWA, in the sew that the coefficienrs on the corresponding relative pricesarcestimatcd with a~lativelylowstandardmr, appear to be the bus (EWIB) and Air NSW (EWIWX) services. Each of EWIB. EWIBTS and EWlWX have negative coefficients. two of them significantly different from zcm. The fact that the bus fare fell in nominal terms in the

middle of oursample period gives additional credibility to the hypothesis that the EWA Service may have btcn a substitute for tbe bus hl addition. both the bus and train services introduced standby and apcx f a m part way through our sample (1 October 1983). per-

l3 Thus. if we let q denme the depcndcnt variable. p, the lndcpendcntvariabkwithcafficient~l .and€, theelasticity of q with mpcct top,:

l4 ~t is dso inuresting to note rha~ deregulation of airlioes in the US appears to haw: dversely affected pammage of interstate bus services.

214 THE ECONOMIC RECORD SEFTEWBER

haps also as a result of competition from EWA. The EWA excursion fare relative to the bus and train standby fares (EWIBTS), is zero up to 1 October 1983 and equal to the relative fare thereafter. This relative price has a marginally statistically significant effect on demand (using a one-tailed test) of the right sign. Unfortunately, the regular train fare did not change during the sample ~ e r i 0 d . I ~

The relative price variable EWIP attempts to measure the cost of flying at the excursion fare on EWA relative to driving a car. The only cost of driving we have is an index of petrol prices. A more important component of variation in the cost of driving over this period might have been improvements in the quality of the Hume Highway. However, a convenient measure of this variable was not readily available. The fact thatEWIP might be a p r measure of the cost of the EWA service relative to driving a car might explain its unexpected positive sign. The EWA Club 25 fare relative to the petrol price index (C25IP) is an attempt to measure one margin of substitution for concessional one-way passengers. This variable has the expected negative sign but is not statistically significantly different from zero. Taking the coefficients of R Y I P and C25IP together. a 1 per cent b a s e in petrol prices holding all other variables constant is estimated to reduce demand to fly on EWA by approximately 0.58 per cent.

It would Seem that the sign on the EWA fare relative to the consumer price index (CPI) wght also to be negative, since it attempts to measure substitution be- twem flying on EWA and purchasing other goods and services. However, thecoefficient onEWICPf measures the effect of changes in this variable holding alf other independem variables constant. In particular, therefore, the EWA fare relative to the complex of Ansett-AA fares based on their standard economy fare (EWIAA) is held constant. A uniform percentage incrcase in all air fares on the Sydney-Melbourne mute relative to the CPI would be expected to decrtase the total demand to fly from Sydney to Melboumc. However, it would also tend to incrrase the s h e of traffic c a n i d by EWA. A given pemntage incrrasC in the mney fare on EWA would increase the total, or rime inclusive, cost of flying EWAbyasmaller~onthanthesamepemntage incrcaSe in money fare would incrmse thc total cost of flying on Ansett and AA. We conclude that the sign of the coefficient on EWICPI is ambiguous in theory, and

l5 AS noted in Appndix 1, the B E surveys found that EWA excursion passcngm acndtd to be time insensitive and therefore likely to travel by bus orrrain as an alternative to the EWA service.

could well be positive. In our sample, however, there appears to be considerable colinearity between EWICP I and EWIAA and this is causing some difficulty in obtaining a precise estimate of the coefficients of both variables.

The coefficient on EWIAA is large and of the anticipated negative sign, but it is estimated with a high standard e m r (so that it is not statistically significantly different from zero). It might be thought that the high standard e m r is due solely to colinearity between EWI CPIandEWIAit. However, the statistical insignificance of the coefficient on EWIAA remains if the regression is reestimated with EWICPI omitted from the regressors. This result is at least consistent with the findings from the BTE surveys (noted in Appendix I) that the extent of passenger diversion from Ansett-AA to EWA appeared to vary over the period.

The only major change in the values of Ansett-AA fares relative to each other over our sample period was the increase in the standby fare from 75 per cent of full economy to 80 per cent of full economy on 1 July 1983. The Ansett/AA standby dummy (ATSBY) is set at zero before 1 July and 1 thereafter to attempt to account for any shift in demand as a result of this change. The estimate of this coefficient is of the expected positive sign but is not statistically significantly different from zero.

The industrial production indcx ( I f 1 was included in our regressions as a proxy (available monthly) for the effect of real income on demand. The estimate of its coefficient is of the expected positive sign.

We expect the JET variable to positively affe-ct demand in an OLS regression for two ccasom. The jet aircraft have higher capacity, but also reduce flying time. The correction for truncation of demand in the maximumlikelihoodestimatcsshouldhavercduccdthe effect of higher capacity. The coefficient did fall when we moved from the OLS to the maximum likelihood estimates. We might then be tempted to conclude that the maximum likelihood estimate of the coefficient on JET primarily refleas thc lower time ccst ass0ciatcd with thc faster plane. A difficulty with this intcrprcta- tion is that the jet is chosen to fly the mute partly when mampncnt expects demand to be higher.16 The significance of the J€T variable might ~ICXI result from inverse d o n from drmandtocapgcity choice rather

l6 Noh. however. that anticipated demand is not the only fanor influencing the schedule. planes have to be flown on a circuitwhichbeginsandcndsatthesamelocation(andal1ows for maintenance) and thus cannot be routed solely in response to anticipated demand.

1990 EAST-WESTAIRLUI(ES 215

than the effect of s h o e flying time on demand. As one might have hoped, the Air NSW service

appears to be a consistent substitute for the EWA service. Note that the elasticity of demand with respect to EWlWX at non-zero values of E W M will be higher than the figure reported in thc table s inceEWM= 0 for an initial block of observations in our data set.

Our key elasticity estimates are broadly consistent with those obtained in previous studies. While they are generally less than the BTE estimates based on s w e y evidence discussed in Appudix 1, Ippolito ( 198 1) finds a fare elasticity of -0.525 and an income elasticity of 2.35. To make our estimates comparable to those reported in Ippolito (1 98 1) we should consider the effect on demand of a 1 per cent incrrase in all the air fares while holding a l l other prices (including the CPI) constant. This would duce demand to fly on the. EWA service by approximately 1.22 per cent. Our price elasticity could be expected to be higher than that reported by Ippolito because of the prtdormnanc ' e o n the EWA xrVice of passengers less smsitive to travel time. Our ' i n m e elasticity' of approximately 3.% may be higher than a true income elasticity because we have proxied income by industrial production.

Comparing the thm sets of maximum l i k e l i h d estimates in Table 3, it would seem then is not much information in the data which would enable us to distinguish between closely-related rationing schemes. Comparing the results presented here with the results in Appcndix 2, we sct that we have modelled thc demand to fly from Sydney to Melbourne much more satisfac- torily than the other two demands. As a consequence, alternative rationing schemes which primarily have diffexcnt implications for the two local demand c w e s will yield similar results. Once we have allowed for the eUnCation of Sydney-Melbourne demand, further marginal changes in the model do not appear to significantly affect the d t s .

V Discussion of Results and Concluswn Thedrmandestimationpmcntedaboveisofbroader

relevance than the regulato~~ status of the EWA Syd- ney-Melboume servirr under the OM Two Airlines Policy. The Sydney-MeIboume rwte. and otha major dlmlestic~mutes.arcrmdou~yhighlylucrative lmder the purely distance-rekued fare-setting formtila utilized by the IAFC, and arc likely to be the first to experience incl.cased competition with the OllSet of deregulation in 1990. In terms of its effect on air fares, such competition may succeed in obtaining a general loweringoffarelevels,and/orachangeinthemiroffarrs.

With respect to this second phenomencq overseas experience with airline deregulation is suggestive of marked increases in the use of discount fares accompa- nied by restrictions on the days of travel. time away from home and so forth. When they are given fretdom to set fares in a deregulated environment, the airlines attempt to aftraCt the most time-sensitive patrons from slower transport modes. These additional airline passengers nevertheless are less time sensitive than the previous typical airline passenger, and therefore are m m willing to vary their travel time or take i n d i i t flights. The use of restricted travel times and indirect flights makes the discount fares profitable by reducing their appeal to he-sensitive travellers.

The EWA Sydney-Melbourne service is quicker than travelling by nain of bus, but uses slower aimaft

involves an intermediate stop. Its price is also between the prices of these alternatives. The EWAservice therefore would only appeal to travellers less time sensitive than the typical passenger currently carried by Anseu- AA. or more time sensitive than the typical bus or tram passenger. On the basis of our econometric results, we conclude that the evidence of s ~ b s t i t u t i ~ l from other modes of transport to the EWA service. particularly fnrm the interstate bus and hain services. is stronger than the evidence for substitutabiility between the. EWA service and direct trunk iwte flights. This suggests that deregulation of airline fares and mutes in Australia is likely to result in an expansion of discount fares and indirect flights as has occurred overseas.

Our results an also relevant to thc &hate over the merits of airline f a n and mute regulation. The nason- ably high and consistent degree of substitutability between the EWA service and the train and bus services illustrates how innovative smices can increase consumer surplus by expanding the choice set for consum- ers. There is even some evidence that passengers con- tinuing to travel by bus and & may have benefited frwn the competition of EWA reducing bus fares and forcing the introduction of new apex and standby fares. Thc weak evidence of a reasonable degrte of substitut- abiiity between the EWA seMce and the Ansect-AA tnmkroutesmictsuggcststhatindirtaservicescwld provide significant competition for the tnrnlr mute

competition would be beneficial if it does more to encourage management to control costs and attcnd to consumer wishes than it does to prevent the anainment of possible economies of scale.

Wealsofoundthat the AirNSW serviceappearstobe

than Ansect-AA w fM their aunk flights and also

opaators. As we d i n the inhoduaion, increased

216 THE ECONOMIC RECORD SEPIEMBER

a close and consistent substitute for the EWA indirect Sydncy-h4elboumc m i c e . Since the Air NSW flights could not pick up or put down passengers at Albury, it seems doubtful they would have earned sufficient revenue to cover costs at m n t farts. The service may have been supported, at least initially, by cross-subsidization by Ansett M i n e s from duopoly profits on protected routes. This sort of cross-subsidization might present difficulties for potential or actual enhants to the airline business where deregulation is confined only to certain routes.

A somewhat distinct aspect of the EWA operation is its utilization of the principle of 'hubbing'. The ability to 'top up' its flights with through traffic at low cost may have allowed EWA to offer a better service to origin- destination traffic to and from Albury. In particular, it is doubtful whether the jet service to and from Sydney to Albury (which lowers aavel time for local as well as through traftic) could have been operated as frequently without the oppottunity to cany some Sydney-Mel- bourn passengers. Similarly, the upgraded service to and from Albury to Melbourne (a Fokker F27 in addition to the Swearingen Metro of Kendell Airlines) was probably only viable in the context of the joint provision of service to passengers travelling indirectly to and from Sydney to Melbourne.

Finally, it is worth noting some of the major advan- tages and disadvantages associated with the estimation methodology used in the paper. On the positive side, the large number of data observations facilitates the con- struction and estimation of farmore sophisticated models than is typically the case in studies performed on more aggregate data. In particular, estimates of time-ofday and day-of-week effects, which would not be possible in the case of data aggregated to the weekly, monthly or annual level. can be made. M m v e r , it would seem probable that to obtain unbiased estimates of such facton in the presence of the capacity con- straints imposed by aircraft size, truncation of the dependent variable would need to be taken into account as we have done."

Similarly, the availability of a large number of de- grtes of M o m enables the inclusion of a variety of relative price parameters. instead of the single 'own- price' parameter oftcn included in regressions performed on. say, annual data. U n f m a t c l y , however, the results obtained for these paramam is mixed

" Our imp~ementation ofthe daily. w ~ e l d y and seasonal factors is somewhat crude, especially in its failure to allow for interaction between the time-ofday and day-of-week dummy variables.

(though, for the most pan, in accordance with estimates obtained in a g p g a t e studies). pnsumably due to the limited amount of price variation over the sample period of 15 months. In effect the number of degrees of M o m is illusory whcn the data do not cover a period long enough to incorporate significant relative price movement. More satisfactory results could be anticipated were the sample period to be extended. though at the cost of an additional computational buden.'*

AppecDcc.1 Background to the Sfudy

ThernostrecentAirlinesAg~~~~~entAct( 198l)pmscribes direct flights between key 'trunk route' cenms by any f m s other than Ansett Airlines of Australia (Ansett) and Austral- ian Airlines (AA). Other operators are permitted to fly sew- ices over what an referred to s 'prescribed routes' (roughly speaking. non-trunk routes). Smion 6( I)(c) of the Schedule to the A i r l k s Agreement Act then applies in rtspcct of prescribed mute services which link two trunk route c e n m indirectly. The provision removes the gacnl authority of opcratm, other than Ansctt and AA. to operate over prescribed routes in cucumstums whcrc the Secretary to the Department of Transport is satisfied that:

. . . such scheduled passenger air services are not predominantly for use for the purpose of the carriage of passengers over separate prescribed routes and arc to a significant extent used or to be used for the ptrpose of carriage of passengers between two centres that are for the time being clunk route ccnm.

In addition, Seaion 17(4Xb) of thc Independent Air Fares Committee Act ( 198 1 ) rcq~imthat in -of any discount fate, the Committee should be satism that

. .the introduction of that propwed discount air f a n IS

scrvicesprovidedby anytrunkrwteopcratorovatrunk

These twin ngulatory conditions arc interrclatcd in their attempt to limit deviations from the main anticompetitive thrust of the TAP. Given that the i n d i services arc less convenient for the traveller than their direct counterparts, they will presumably only be atnactive at fares lower than those pertaining to dm flights. The gencnl approach of the

lish 'standard' a m o m y fiues on a distance bwd formula Such a fonnula does not allow prices to vary dcpeading on whetha a flight is dina or indirst. aud may even charge

indirat flight thmfm is likely to be a 'disunmt' f a n and subject to Section 17(4)(b) above.

unlikely to d t in economy air fares in rrspa of air

routts being increased.

Indcpnrdtnt A i r k Canmima(IAF0 h a s h toestab-

m v e h morr for indina flights. Aoy Iowa fare for an

'8 he maximum ~ i l r c l i estimation was performed on a microcomputer with convergence requiring anything up to 12 hours. Increases in the number of observations could be expected to affect this time in a roughly linear fashion.

1990 EAST--WESTAIRLINES 217

East-West Airiines (EWA) intmduccd its 'excursion' fare for travel between Melbatrne and Sydney. via Albury. in March 1983.Theinitialkvelofthefanwasmorethan50pcr cent below the ANctt and AA return economy fare. The B w a u of Tnnsport Eccmomics ( B E ~33.1985) notes that 'in the fint few months of 1983. me intmdwtion by EWA of excursion f a t s ... was a topic of &bate within the aviation indusay'. This &bate was no doubt fucUcd by the initial decision of tbe IAFC ILO( to allow the continuation of the fare beyond the end of June 1983 and the prrpantion. by EWA, of a legal challenge to the constitutional validity of the two airlines legislation. As things ev- however, both the legal challenge and the IAFC's denial of pmnission to con- tinue he service were abandoned A compecitivc threat to the EWA operation did emerge, however, in the form of the commencement of a similar service operated by the Ansett subsidiary. Airtines of New South Wales.

In an effon to: *...contribute to this debate by quanufying the divenion of passengers frwn AAA [Ansea] and AA to the EWA excursim fares inaoduced on h e Sydney-Mclboume

vcysofpasxngcn-inJulyandNovember 1983andkbnrary 1984. The yfond survey also included pasxngcrs flying on

Ansea and AA m an aacmpt to addrtss a number of othcr questions. such as the d t m o p p h ~ c characteristics of the various passenger groups.

In respect of the question of 'diversion' the BTE obtained sigmtkantty different rrsu1t.s over its three surveys. On the basis of thc July 1983 survey, it concluded that 30 per cent of excursion fare passcngcn would otherwise have purchased a full (dm) economy fare, but the later surveys revealed this proportion to be 52 pcr cent and thm 36 per cent. Of the r e d g passcngm. 47 per cent (32 per m t and 52 per cent in the xcond and third surveys) were judged to have been 'diverted' from odvr modcs of wllsport and 20 per cent (13 per cent and 12 per cmt) indicated that they would othenvisc not have navcllcd at all.

and Sydney-BriSbane routes' the BTE coaducted thrre SUT-

Rrhaps morc sltisfactoly in tams of coasistcncy were tbe results f o r m fornavel. incomegrwp, lengthofstay. etc. All surveys tcndcd to indicate that

... comparrd .with AAA and AA passmgm, EWA plurcngm welt l eu M i aimtai, came from households in Iowa imam pup, mde the decision to travel hrrrha in rdvprc a d stayed away loager. In addition. many m EWA pruengm purchased their ownrickctr and& was a 1:l male to female ratioon EWA €ligba. wherets tbm was a 4 1 male to female ~ t J 0 A A A m d M f l i g b f S

Giventkslowapcaacy. r r w d a a s a n e o f tbc Fesaictioas pleadaitkexcmsaoaf.rcgthsseresuluPetobeexpectcd

AA discamt fan2 pwalgcnhadvay simihrchpraaeristiu as well a tk dditiad fiDdingoftk BTEthl '...AAA and

to EWA passmngas'. Finally, BTE (1985) gives estimptes of the elasticity of

demand for air navel. dcrived on tbe basis of passenger

rrsponses when q u e s t i d whether they would still have flown had fares been higher. These estimatedelasticities were -0.6, -1.3 and 4.2 for firstclass. economy and discount fare passengers, respcctive~y."~ T I I~ implication of these elasticities is that discount services of the type offered by EWA a~ likely to dispmportiowely attract touris& aod tlavellen less sensitive to navel time, as was found by tbc B E As such, the 'demand expansion' effcct of the service is likely to outweigh the 'traffic diversion' effect.

While we have no partlculardisagrament with the conclu- sions drawn from the suwcys, it is useful to have more than one method of measuring variables of intcmt. In panicular, surveys suffer from the problem that respondents might not understandthequutionsbeingasked.mightnotbotherto~e time to give a good answer, or might mpond with an answer they think the researcher is looking for. While econometric evidence has the virtue of actually measuring the response in the market place, it suffen from the defect that it is often difficult to idmtify the causal effect of different variables.

APpEM)IX 2 Estimates of the Local Demand Curves

Table A1 presents the maximum likelihood estimates of the key economic parameters in the Sydney-Albury demand curve and Table A2 estimates of thc corresponding param-

The Sydney-Melbourne equation is much more satisfactory than the two equations for the pumcys to and from Albuy. Thc most successful relative price in explaining demands to travel between Sydney and Albury is the EWA fare relative to the consumer price index (EWICPI). The cstimatcd coefficient cornsponds to an elasticity of approximately -0.72. The coefficient of the EWA fare relative to peml prices is also of the hypothesued negative sign. but barely slatistically significantly different from zero using a one-sided test. TheEWA farerelative tothe aain and bus fares have cstimatcd coefficients of thc wnmg sign and. m the case of the bus fare, a large value relative to the &mated standa~I error. Thc significant autaomlation in the Sydney-Albury e m terms, as indicated by the statistically significant nti- matcs of the cocffiicnts on PFSD and PD, may also indicate

resulted in biased parametcrestimateS.

etcr~ in the A l b ~ - M e l b o ~ e de-d curve.

some specificatim p m b h with our model and may have

The key relative prices €W/KD aad RYIKSBY in the

19 AS the vducof time t o p u s c n g m i n a w s a the money price of navel will be a Iowa pcmtage of the 'total' (time inclusive) price. Thw, one reason the clasticitks of dcmand may be ranked as found by the BTE is tha~ agivcn w e c h a n g C i n ~ y p r i c c w i l l b C ~ s m r l l c r p n m t . g e ~ g C i n toall price for fua dus md ecollomy C k psueagm In addition. me demmd for air travel by f i rs lc t rupasMgns is prcdomiamtly a demand for a (tax ckdwtible but possibly partly consumption oriented) factor of produaim whaeas it is largely a consumption p o d for discwnt fare passengers. There is no o priori reason for expecting thest elasticities to be similar in magrutude.

218 THE ECONOMIC RECORD SEplEMBER

TABLE Al Estimates of Key Demand Parameters for Sydney-Albury Trafic

(key components of Y

Indcpmdcnt Estimated Estimated Estimated Variable' Coefficient (I)b Coefficient (II) Coefficient (XU)

EWITR 5.05 (5.38)

5.02 (5.40)

5.62 (5.34)

EWIB 10.27 (2.42)

10.23 (2.42)

10.26 (2.41)

EWIP -0.11 (0.08)

-0.1 I (0.08)

-0.1 I (0.08)

EWICPI -96.28 (39.38)

-95.8 1 (39.50)

-99.12 (39.23)

IP -0.33 (0.33)

-0.32 (0-33)

-0.28 (0.33)

JET 5.89 (0.88)

5.79 (0.88)

5.69 (0.88)

PFSD -0.17 (0.02)

-0.16 (0.02)

-0.17 (0.02)

PD 0.10 0.10 (0.02) (0.02)

0.10 (0.02)

a Standard errors in parentheses. nenotationo, (II)and(m)nfcrstothcdifimtmcationassumptionsdiscussed insection II of the paper. Dcfintions of variables:

EW EWA full economy fare TR Trainfare B Busfare P Index of petrol prices CPI Sydney all items c011surner price indcx IP Index of industrial production PFSD passengers on previous flights same day PD passmgen on the previous day JET seetext

Albur-Melbourne equation appear to k almost colinear so it is difficult to obtain a good atirmtc of heir effect (notelhutbenlativesizesofthesev~luisroughly 1:2 in invme proportion to the ratio of their utinrrted coefficients). The EWA fare relative to the CPI again hu a large negative coefficient (which implies an elasticity of approximately -1.75). but the smaller absolute value of the coefficient than the corresponding coefficient in the Syd-

ney-Albury equation, and similar estimued stnadard error, implies the coefficient is no longer statistically significantly different fnnn zero M reuoaable levels of signifi- CMCC. The coefficient of the EWA fare relative to pen01 prices is also of the hypothesized negative s i p , and statistically significantly different from zero using a one- sided test.

We suspect them was insufficient variation in most of the

1990 EAST-WEST AlRLlNES 219

TABLE A2 Estimates of Key Demand Parameters for Albury-Melbourne Trafic

(key components of )“

Independent Estimated Estimated Estimated Variable‘ Coefficient (I)b Coefficient (11) Coefficient (111)

EWITR 1.58 (2.09)

1.56 (2.10)

1.15 (2.10)

EWIP -0.08 (0.06)

-0.08 (0.06)

-0.08 (0.06)

EWIKD 54.57 (37.78)

54.15 (37.8 1 )

46.13 (38.30)

EWIKSBY -24.53 ( 16.39)

-24.38 (16.41)

-2 1.20 ( 16.63)

EWICPI -26.63 (38.99)

-26.28 (39.03)

-28.15 (39.5 1 )

IP -0.26 (0.19)

-0.26 (0.19)

-0.22 (0.19)

PFSD 0.001 (0.0 16)

0.001 (0.016)

-0.005 (0.016)

PD 0.04 (0.02)

0.04 (0.02)

0.05 (0.02)

’ Standard errors in parentheses. The notation (I), (m and (m) refers to the different truncation assumptions discussed m kt im II of the paper. Defhtions of variables:

EW EWA full economy fare TR Trainfare P Index of petrol prices KD Kendell Airlines hll economy fare KSBY Kendell Airlines stand-by fare CPI Melbourne all items consumer price index IP Index of industrial production P FSD passengers on previous flights same day PD passengers on the previous day

rrlat~ve pice vanabks rn the two local routes to enable a ~estirmtcofmcuImp.amdanaad’Ibcmukct arramayhavcbanmon:rppropnatc.unfommately,~ formnrport 6umSydney to Melboumc undawent farmore drarmeic changes than did either of the local markets m the pcnod over which OUT data werr collected. dummres (not Rponcd In mc tabks) a n staastlcally SIgnlIi-

I n d d pruduchm has m c m d y sigmdeffccts on both local demands. Industrial product~on IS p”sumab1y a poor proxy for rial lllcome on the local Albury routes Some

seasonally djusted urdex of nualproduchon mtbcl(lvcnna

know of no such d x avlulrblc m a d y bas=. Most of the MY of day, day of the week uad holiday

candy different from 2em and appcar to c x p h most of the vanat~ons rn demand on these flights

220

REFERENCES*

THE ECONOMIC RECORD SEPTEMBER

Amemiya. T. (1984). 'Tobit models: A survey'. Journal of Econometrics 24,3-6 I .

Bemdt. E.R.. Hall, B.H.,Hall. R.E.andHausrnan. J.A. (1974). 'Estimation and inference in non-limar structural models', Annals of Economic andSocial Measurement3(4), 653-65.

BAA ( 198 1 ). BAA Trafic Forecasts: Methodology. British Airports Authority, London.

Bureau of Transport Economics (1985). Marker Response to Discount Domesrlc Air Fares. Occasional Paper 66. AGPS. Canbern.

Davies, D.G. (1977). 'Property Rights and Economic Effi- ciency -The Australian Airlines Revisited',Journal of Low and Economics 20. 223-6.

- ( 1980). 'Property Rights and Efficiency in a Regulated Environment', Economic Record. 56. 186-9.

Fonyth. PJ . and Hocking. R.D. ( I 980). 'Property Rights and Efficiency in a Regulated Environment'. Economic Record 56. 182-5.

Gannon. C.A. ( 1979). 'Parallel Scheduling', Appendix A 12. I in Dcpamnent of Transport. Domestic Air Transporr Policy Review 2, Appendixes.

Heckman, J J. (1976). 'The common structure of statistical models of truncation. sample selection and limited dependent variables and a simple estimatw for such models'.Anruals ofEconomic andSociulMeasurernent 5.475- 92.

- ( 1979). 'Sample selection bias as a specification error', Econometrica 47, 153-6 I .

Hocking, R.D. (1979). 'Economic Efficiency of the Ausual- ian Airlines'. Appendix A6.2 in Department of Trans- port. Domestic Air Transpon Policy Review 2, Appen- dixes.

Ippolito. R.A. (198 1 ), 'Estimating airline demand with quality of service variables'. Journal of Transport Econom- ics and Policy IS , January 1981.7-15.

Jung. J.M.. and Fuji, E.T. ( 1976). 'The price elasticity of demand f a air travel', Journal ofTranrpon Economics

Kirby. M.G. (198 1). Domestic Airline Regulation; The Am- rralian Debore. Research Studies in Government Regu- lation 1. h u e for Lndepadcnt Studies. Sydney.

Maddala G.S. (1983). Limited-Depndem and Qualitative Variables in Ecommrm'cs, Cambridge. Cambridge Univmity h.

Taneja. N.K. (1978). Airline T r m c Forecasting, Lexingtm Books, Lexington, Massachusetrs.

Tobin. J. (1958). 'Estimation of relationships for limited dependent variables'. Economemca 26.24-36.

ond Policy 10. sepcmkr, 37-62.

* DataandfinancialassisrancefromEast-WestAirlines are gratefully acknowledgd The views expnssd in this paperreplrcscnt those of tht a u b m and in no way

or employees. The authors thank Diana Strassmann, joint editor of the Economic Record Alan Woodland. two anonymous referees and seminar participants at Monash University and the AGSM for very valuable comments on earlier versions of this paper.

reflect the opinions of East-west Airlines management

east-west airlines' sydney-melbourne service: market expansion or demand diversion?

Documents