M I T I n t e r n a t i o n a l C e n t e r f o r A i r T r a n s p o r t a t i o nM I T I n t e r n a t i o n a l C e n t e r f o r A i r T r a n s p o r t a t i o n

MIT MIT ICAT ICAT

Is air transportation financially sustainable?

John-Paul Clarke, Alex Lee, Bruno MillerDepartment of Aeronautics and Astronautics

Massachusetts Institute of Technology

MIT MIT ICAT ICAT Measuring Financial Health (1)

There are three common methods to measure the financial health (or bankruptcy risk) of a firm

Managerial Performance ModelsSubjective model based on analyst’s judgment of the overall managerial, financial and trading position of the firm

Best known model is the Argenti “A” score modelAnalysts assign scores under 3 major headings

DefectMajor mistakesSymptoms

Scores based on a point system

MIT MIT ICAT ICAT Measuring Financial Health (2)

Univariate Financial Ratio AnalysisAnalyzes firms’ financial ratios both on a cross-sectional basis and on a time-series basis

Ratios commonly used include: Profitability ratiosLeverage ratiosActivity ratiosInvestment ratios

Analyst examines each ratio separatelyRatios could be contradictoryRelies on analyst’s interpretation of the ratios

MIT MIT ICAT ICAT Measuring Financial Health (3)

Multiple Discriminant Analysis (MDA)Altman developed MDA in response to shortcomings of the univariate financial ratio analysis

Based on objective statistical data rather than on the subjective interpretation of a financial analystResearchers have developed industry-specific MDA models

MDA models developed in the following steps:Establish two mutually exclusive groups, namely those firms which have failed and those which are still continuing to trade successfullyCollect financial ratios for both of these groupsIdentify the financial ratios which best discriminate between groupsEstablish z-score based on these ratios

Sensitive to changes in accounting practices

MIT MIT ICAT ICAT Altman Z-score model

The most commonly used MDA model to predict bankruptcy is the Altman Z-score model

Gritta (1982) applied Altman’s model to the airline industry and correctly predicted Braniff’s bankruptcy

Chow, Gritta, and Leung (1991) developed the first industry specific bankruptcy prediction model for the airline industry, called the AIRSCORE model (based on Altman’s Z-score model)

Authors indicate that these models are good for predicting bankruptcies two years into the future, but are not good for longer term predictions

This is partly due to the static nature of the model, not taking into account cycles in demand

MIT MIT ICAT ICAT AIRSCORE Model

The AIRSCORE model by Chow, et.al. is:z-score = a * (interest expenses/total liabilities) +

b * (operating revenues/miles flown) + c * (shareholder’s equity/total liabilities)

The coefficients they estimated were:a = -0.34140 b = 0.00003 c = 0.36134

Z-score boundaries:Carriers above 0.03 are healthy

Carriers below -0.095 are in trouble

MIT MIT ICAT ICAT AIRSCORE for "Failed" Airlines

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PA - System Wide EA - System Wide Healthy In-Trouble

AIRSCORE for Failed Airlines

MIT MIT ICAT ICAT

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1978

AIRSCORE: 1978-2003 (1)

MIT MIT ICAT ICAT AIRSCORE: 1978-2003 (2)

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1978

MIT MIT ICAT ICAT AIRSCORE: 1998-2003 (1)

-0.1

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1998 1999 2000 2001 2002 2003

AAUADLNWCOHealthy

MIT MIT ICAT ICAT AIRSCORE: 1998-2003 (2)

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1998 1999 2000 2001 2002 2003

USWNHPASTWHealthy

MIT MIT ICAT ICAT AIRSCORE: Observations (1)

AlaskaSafely in the healthy range

America WestGot into trouble during the recession in the early 90s

Restructured and emerged from bankruptcy in the mid-90s (as seen by the significant improvement in their z-score) and continues to be healthy

AmericanCurrently below the healthy level for the first time since deregulation

MIT MIT ICAT ICAT AIRSCORE: Observations (2)

Continental Low z-scores (and 2 bankruptcies) in the 80s and early 90s

Z-score improving since 1995 (arrival of Gordon Bethune)

DeltaCurrently below the healthy level for the first time since deregulation

NorthwestIn the healthy range but consistently declining

SouthwestVery healthy and consistently has the highest score

MIT MIT ICAT ICAT AIRSCORE: Observations (3)

TWADid not improve their z-score to the healthy range when they emerged from their first bankruptcy

Forced to file for a second bankruptcy shortly thereafter and isnow dead

UnitedCurrently well below the healthy level

US AirwaysStill below the "safe" line even after recent bankruptcy

MIT MIT ICAT ICAT Key Questions

What are the factors that drive the economics and viability of airlines?

Crew costs

Fuel costs

What could happen to the these factors?Crew costs in regional carriers could become aligned with the crew costs of mainline carriers

Fuel costs could vary significantly given volatility in fuel prices

What would the impact of these changes be?

MIT MIT ICAT ICAT Crew Cost (Mainline v. Regional)

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50 100 150 200 250No. of Seats

MIT MIT ICAT ICAT Impact of Salary Scale on RJ DOC

MIT MIT ICAT ICAT Fuel Burn

MIT MIT ICAT ICAT Impact of Fuel Cost on DOC

MIT MIT ICAT ICAT

Sensitivity of Earnings Per Share (EPS) to Fuel Price

80%$0.07$0.60Southwest

40%$0.25$1.60LanChile

40%$0.08$0.90JetBlue

10%$1.05- $0.50Continental

5%$1.85$0.30AMR

28%$0.15$0.75AirTran

% of 2004 fuelthat was hedged

Sensitivity to 10% fuel price increase

2004 EPSAirline

Source: Merrill Lynch

MIT MIT ICAT ICAT History and Model of Fuel Prices

Long-term average: $0.71/gallonSpeed of reversion: 0.17/yearVolatility: $0.0591/year

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1986

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pric

e (c

ents

/gal

lon)

MIT MIT ICAT ICAT 2004 EPS (95% Confidence Limits)

$0.70$0.50$0.60Southwest

$1.98$1.22$1.60LanChile

$1.02$0.78$0.90JetBlue

$1.10- $2.10- $0.50Continental

$3.14- $2.54$0.30AMR

$0.97$0.53$0.75AirTran

Upper LimitLower Limit2004 EPSAirline

MIT MIT ICAT ICAT Conclusions

Most airlines are in bad shapeUnited is in very poor shape but have not yet emerged from bankruptcy so the future is unclear

US Airways is not in the healthy range even after bankruptcy

Significant potential impact on airline direct operating cost and on measures of airline financial performance

Future of economic drivers uncertain

Impact of changes could be significant