ransportation: The Case of VASP Brazilian AirlinesIntroductionThe Viao Area So Paulo, known by the great public as VASP BrazilianAirlines, was created in November of 1933, in So Paulo. The company at first wasinvestor owned and its first planes were two Monospar, bought from an English airline.
Even though it had a good beginning, the company had constant losses and the onlysolution to solve the crisis was asking for government help. On March of 1935, the SoPaulo government agreed to help the company, not lending money but making it a publiccompany owned half by the state and half by the city of So Paulo. The VASP ownersagreed with that decision, because it was the only way to avoid bankruptcy. After decades under government control, in 1988, the So Paulo state told the pressthat it wished to privatize the company because it still had monthly losses. On October of1990, on a public auction, the VOE/CANHEDO group, represented by the Canhedo Groupand the VASP employers, bought the company for US$44 million dollars.
Until today, thecompany is owned by the VOE/CANHEDO group. After the reelection of Fernando Henrique Cardoso as President of Brazil, thebrazilian central bank decided to devaluate its currency and the airlines suffered a lotbecause its debts were in US dollars. One of the biggest problems that VASP faced was thatit had earnings on brazilian currency and had costs in US dollars. QUndergraduate Student of EPGE/FGV; E-mail: emailprotectedWhile VASP was facing all this trouble, in 2001, the low fare airlines boomarrived in Brazil. The GOL Linhas Areas was a mimic of Jet Blue 1. Its prices were at least40% less than the airlines operating in Brazil and it did attract costumers.
The meal servedinside the plane is quite simple, just cold sandwiches and cereal bars. VASP that could not compete with the brazilian biggest airlines, VARIG and TAM,now had a competitor: GOL. At the end of 2002, GOL passed VASP on the brazilianairline market, making VASP the 4th brazilian airline, after VARIG, TAM and GOL. Recently, one of VASP airplanes had problems while flying to Fortaleza airport,Pinto Martins.
A week later, another airplane flying from So Paulo to Curitiba hadproblems after landing. The land crew tried to fix the problem and after it took off tocontinue the flight, the planes remained and the plane had to go back to Curitiba2. One ofthe biggest brazilian newspapers said that the VASP fleet was from the 1970s. The VASPfrequent flyers were shocked.
Nowadays, VASP and GOL compete for the third place ofthe brazilian airline market. MethodologyAccording to the microeconomics theory, the demand for a certain object dependson the price, the price of other similar object and the budget constraint. To help the study,the quality of services offered by the airlines besides the ones discussed above, we caninclude the frequency delay3 and flight timeYoung(1972) and Anderson & Kraus(1981). Our aim will be to analyze how the quality of services can affect the demand for airtransportationDouglas & Miller(1974), Anderson & Kraus(1981) and Trapani &Olson(1982).
A possible doubt that can come one your mind is how a passenger could measurethe age of the airline that he is fixing to board. The answer it is simple. An older airplanelooks are not good. It looks like it had received a complete patchwork.
Indeed, an oldairplane with those kinds of looks could worry some of the passengers. The data analyzed will be about the Rio de Janeiro So Paulo flight, because its amajor airline route. Three hundred thousand people use this route monthly. As discussedearlier, VASP tries to get back the thir d place of the brazilian airline market, so our datawill just include GOL and VASP passengers.
For the Rio de Janeiro So Paulo route,time is very important because the major part is businessmen. We will assume that t is thecomplete flight time, including flight time, time needed to get to the airport and theschedule delay4. Assuming that t is a function of F, the number of flights offered by theairlines composes it. (1) ( ); <0=Ftt t F1 Chris Isidore(2002)2 Folha de So Paulo newspaper, may 2004.
3 The absolute difference between the most desired time to fly and the flight time. 4 Same as frequency delay; see Douglas & Miller(1974)The demand for flights of the Rio de Janeiro So Paulo route will be a function ofthe place ticket price p, the complete flight time t and an X variable that measures thequality of services offered. (2) Q = Q(p + t(F), X)Where Q is the number of plane seats demanded. Following Gronau5, the full price is q = p + t(F) and it follows:(3) <0==qqqQpQpQ(4)> 0==FQ tFQFQqqqAs can be seen, the impact of the price on the demand for air transportation isnegative and the impact of the number of flights offered is positive as we expected.
The flight time between Rio de Janeiro domestic airport and So Paulo domesticairport is about 45 minutes. The difference between the speed of the airplanes used on thisroute is minimal, so we assume as zero. The difference in time of the flights of GOL andVASP are also minimal, so we assume it to be zero as we ll. Both airlines have the sameschedule delay. After that we eliminate the variable t of our demand function and the newdemand is:(5) Q = Q(p, X)The new demand of the VASP and GOL passengers is function of the price and thequality of services. The offered prices of both airlines are also alike.
It does not havemileage programs and it just operate domestic flights. The services provided by these airlines are quite alike, so we now assume tha t thedemand will be just function of the price. (6) Q = Q(p)5 Gronau(1980)We cannot forget that the age of the fleet could affect the demand for airtransportation of these airlines. GOL uses on this route Boeings 737-7006 and its from the90s while VASP uses 737-200/300 from the 70s. We will assume on this model that as oldthe plane is more hours it had flight.
The budget constraint of the passenger will not beconsidered because we are going to use the Taaffe s passenger definitionTaaffe(1962)this reference may be old, but it had not changed much since now. The demand for GOLpassengers could include others aspects because it can compete with VARIG and TAM,however VASP can just compete with GOL and its demand would be:(7) QVASP = Q(pVASP, pGOL, J )The variable J represents the airplane age. We expect in our model that the airplane age affects negatively the demandfunction:(8) <0JVASP QThe econometric model needed to solve this puzzle is called linear probabilitymodel(LPM 7). We want to see the impact(dj ) on the probability of success when thedependent variable(xj) suffers some variation:(9) j j DP( y = 1 x) = d xMutatis mutandes , the variation on the probability of failure:(10) DP( y = 0 x) = 1- DP( y = 1x)After knowing what to use to solve this puzzle, we now can come up with aregression equation to measure the effects of the age of the plane on the demand for airtransportation.
(11) =y +y +y +y 2 + e0 1 2 3 flyvasp price planeage planeage6 For further information visit Boeing website. 7 Wooldridge(2002)Where flyvasp is a dummy variable that assumes 1 if the passenger flew VASP and0 if the passenger flew GOL. The dependent variable price represents the price paid by thepassenger to fly(R$). The variable planeage represents the age of the airplane that thepassenger used.
(years). 0 y is the intercept of the equation while the i y are the slopes of thedependent variables. The quadratic variable planeage2 was included because we want tostudy also the positives or negatives marginal effects of the variable planeage. Themarginal effect would be:(12) planeageplaneageflyvasp2 3 =y + 2yAfter these problems that VASP faced with its airplanes, I think it would beimportant to analyze if the age of the airplane does affect the demand for airtransportation.
In order to do this I would use cross sectional data. The econometric modelused, as discussed above, would be the linear probability model(LPM). The estimationmethod used would be generalized least squares(GLS). 8 The need of this method is why wehave the risk of facing heteroskedasticy. The Wald test is needed for the variables and theShapiro-Wilk searching for outliers.
ConclusionsUnfortunately this research could not be finished because VASP went bankrupt andlost its permission to fly in March of 2005. However the model discussed above could beused to study the relationship between the demand of two airlines, just some modificationsneeded to be done. But indeed I know that this model would be helpful for further works. 8 Wooldridge(2002)ReferencesAbouchar, A.
(1970) Air Transport Demand, Congestion Cost, and the Theory of OptimalAirport Use. Journal of American Statistical Association, v. 3, n. 3, p. 463-475. Anderson J.
E, Kraus, M. (1981) Quality of Service and the Demand for Air Travel TheReview of Economics and Statistics. v. 63.
De Vany, A. S (1975) The Effect of Price and Entry Regulation on Airline Output,Capacity and Efficiency The Bell Journal of Economics v. 6, p. 327-345. Departamento de Aviao Civil http://www. dac.
gov. brDouglas, G. W. , Miller III J.
C (1974) Quality Competition, Industry Equilibrium andEfficiency in the Price-Constrained Airline Market American Economic Review v. 64,p. 67-76. Infraero http://www.
infraero. gov. brGronau, R. (1980) The Value of Time in Passenger Transportation: The Demand for AirTravel Occasional paper 109 , National Bureau of Economic Research, New York.
Isidore, C. (2002) Attack of low fare airlines CNNmoney, December 9, 2002Morrison, S. , and Winston, C. (1995), The Evolution of the Airline Industry.
BrookingsInstitutionTaaffe, E. J. (1956) Air Transportation and United States Urban DistributionGeographical Review 46, 219-238. Trapani, J.
M. , Olson, C. V. (1982), An Analysis of the Impact of Open Entry on Priceand the Quality of Service in the Airline Industry The Review of Economics andStatistics, 1982, vol. 64, issue 1, pages 67-76Verleger Jr. P.
K. (1972) Models of the Demand for Air Transportation The BellJournal of Economics and Management Service v. 3, p. 437-457Wooldridge, J.
(2002) Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT PressYoung, K. H. (1972), Cross-Sectional Demand Models: Estimates and Tests,” Journalof Regional Science, 9
